BIALLELIC MARKERS FOR USE IN CONSTRUCTING A HIGH DENSITY DISEQUILIBRIUM MAP OF THE HUMAN GENOME

Abstract: The present invention relates to genomic maps comprising biallelic markers, new biallelic markers, and methods of using biallelic markers.

Description: BIALLEUC MARKERS FOR USE IN CONSTRUCTING A HIGH DENSITY DISEQUILIBRIUM MAP OF THE HUMAN GENOME Background of the Invention Recent advances in genetic engineering and bioinformatics have enabled the manipulation and characterization of large portions of the human genome. Wftilc efforts to obtain the full sequence of the human genome arc rapidly progressing, there are many practical uses for genetic iπfomiation which can he implemented with pπrtial knowledge of tho sequence of the human genome. As the full sequence of the human genome is assembled, the partial sequence information available can be used to identify genes responsible for detectable human traits, such as genes associated with human diseases, and to develop diagnostic tests capable of identifying individuals who express a detectable trait as the result αf a specific genotype or individuals whose genotype places them at risk of developing a detectable trait at a subsequent time. Each uf these applications for partial genomic sequence information is based upon the assembly of genetic and physical maps which order the known genomic sequences along the human chromosomes. The present invention relates to human genomic sequences which can be used to construct a high resolution map of the human genome, methods for constructing such a map, methods of identifying genes associated with detectable human traits, and diagnostics for identifying individuals who carry a gene which causes them tu express a detectable trait or which places them βt risk of expressing a detectable trait in the future. Summary of the Invention A first embodiment of the present invention is a method of obtaining a set of biallelic markers comprising the steps of obtaining a nucleic acid library comprising a plurality of genomic DNA fragments comprising the full genome or a portion thereof, determining the order of said plurality of genomic DNA fragments in the genome, determining the sequence of selected regions of said plurality of genomic DNA fragments, and identifying nucleotides in said plurality of genomic DNA fragments which vary between individuals, thereby defining a set of biallelic markers. In one aspect of " this first embodiment, the identifying step compπses identifying about 20,000 biallelic markers, In another aspect of this first embodiment, the identifying step comprises identifying about 40,000 biallelic markers. In a further aspect of this embodiment, the identifying step comprises identifying about 60,000 biallelic markers. In still another aspect of this first embodiment, the identifying step comprises identifying about 80,000 biallelic markers. . In still another aspect of this first embodiment, the identifying step comprises identifying about 100.000 biallelic markers. . In still another aspect of this first embodimeπ the identifying step comprises identifying about 120,000 biallelic markers. In still another aspect of this first embodiment, the biallelic markers are separated from one another by an average distance of 10kb-2Q0 kb. . In still another aspect αf this first embodiment, the biallelic markers are separated from one another by an average distance of 15kb-150 kb. In still another aspect of this first embodiment the biallelic markers are separated from one another by an average distance of 20kb-100 kb- . In still another aspect of this first embodiment, the biallelic markers are separated from one another by an average distance of 100kb-T50 kb. In still another aspect of this first embodiment, the biallelic markers are separated from one another by an average distance αf 50-1 OOkb.. in still another aspect of this first embodiment, the biallelic markers are separated from one another by an average distance of 25 kb-50 kb. In still another aspoct of this first embodiment, the step of determining the sequence of selected regions of said plurality of genomic DNA fragments comprises inserting fragments of said plurality of genomic DNA fragments into a vector to generate a plurality of subclones and determining the sequence uf a region of the inserts in said plurality of subclonβs or a subsot thereof. For example, in this aspect of the first embodiment, the step of determining the sequence of a region of said inserts or a subset thereof may comprise determining the sequence uf one or both end regions of said inserts or a subset thereof, In this aspect of the first embodiment, the step of determining the sequence of one or both end regions of said plurality of subclones comprises determining the sequence of about 500 bases at each end of said subclones or a subset thereof. In still another aspect of this first embodiment, a set of about 10,000 to about 20.000 genomic DNA inserts with an average size between 1Q0kb and 300kb are ordered. In still another aspect of this first embodiment, a set of about 10,000 to about 30.000 genomic DNA inserts with an overage size between 100 b and 150 kb are ordered. In still another aspect of this first embodiment, a set of about 15,000 to abuut 25,000 genomic DNA inserts with an average size between lOOkb and 200 kb are ordered. In still another aspect of this first embodiment, the identifying step comprises identifying between 1 and 6 biallelic markers per genomic DNA fragment. In still another aspect αf this first embodiment, the identifying step comprises identifying an average of 3 biallelic markers per genomic DNA insert. In still another aspect of this first embodiment the geπαmic DNA fragments are in a Bacterial Artificial Chromosome. In still another aspect of this first embodiment, the genomic DNA fragments are in a Yeast Artificial Chromosome. In still another aspect of this first embodiment, the method further comprises determining the position of said biaflefic markers along the genome or a portion thereof. In this aspect of the first embodiment, the step of determining the position of said biallelic markers along the genome or portion thereof may comprise determining the position of said biallelic markers along a chromosome. In this aspect of the first embodiment, the step of determining the position of said biallelic markers along the genome or portion thereof comprises determining the position of said biallelic markers along a subchrσ osomal region. In still another aspect of this first embodiment, the method further comprises identifying biallelic markers which are in linkage disequilibrium with one another. In this aspect of the first embodiment, the method may further comprise optimizing the intermarker spacing between said biallelic markers such that each identified marker is in linkage disequilibrium with at least one other identified marker. In still another aspect of this first embodiment, the portion of the genome comprises at least 200 kb of contiguous genomic DNA. In still another aspect of this first embodiment, the portion of the genome comprises at least 300 kb of contiguous genomic DNA. In still another aspect of this first embodiment, the portion of the genome compπses at least 500 kb of contiguous genomic DNA. In still another aspect of this first embodiment, the portion of the genomε comprises at least 2 Mb of contiguous genomic DNA. In still another aspect of this first embodiment, the portion of the genome comprises at least 5 Mb of contiguous genomic DNA. In still another aspect of this first embodiment, the portion of the genome comprises at least 10 Mb of contiguous genomic DNΛ. In still another aspect of this first embodiment, the portion of the genome comprises at least 20 Mb of contiguous genomic DNA. In still another aspect of this first embodiment, the method further comprises the step uf identifying one or more groups of biallelic markers which are in proximity to one another in the genome. In this aspect of the first embodiment, the biallelic markers in each of these groups may be located within a genuinic region spanning less than 1kb. Alternatively, in this aspect of the first embodiment, the biallelic markers in each of these groups may be located within a geπϋmic region spanning from 1 to 5kb. Alternatively, in this aspect of the first embodiment, the biallelic markers in each of these groups may be located within a genomic region spanning from 5 to 10kb. Alternatively, in this aspect nf the first embodiment, the biallelic markers in each of these groups may be located within a gonomic region spanning from 10 to 25kb. Alternatively, in this aspect of the first embodiment, the biallelic markers in each of these groups may be located within a genomic region spanning from 25 to 50kb. Alternatively, in this aspect of the first embodiment, the biallelic markers in each of these groups may be located within a genomic region spanning from 50 to 150kb. Alternatively, in this aspect of the first embodiment the biallelic markers in each of these groups may be located within a genomic region spanning from 150 to 250lcb. Alternatively, in this aspect of the first embodiment, the biallelic markers in each of these groups may be located within a genomic region spanning from 250 to 500kb. Alternatively, in this aspect of the first embodiment, the biallelic markers in each of these groups may be located within a genomic region spanning from 500kb to 1Mb. Alternatively, in this aspect of the first embodiment, the biallelic markers in each of these groups may be located within a genomic region spanning more than 1 Mb. A second embodiment of the present invention is a method of obtaining a set of biallelic markers comprising the steps of obtaining a nucleic add library comprising geπαmic DNA fragments comprising the full genome or a portion thereof, determining the sequence of selected regions of said genomic DNA fragments, identifying nucleotides in said genomic DNA fragments which vary between individuals, thereby defining a set of biallelic markers, and determining the order of said biallelic markers along the genome or portion thereof. A third embodiment of the present invention is a set of biallelic markers obtained by the method of the first embodiment In one aspect of this third embodiment the markers in said set have a known genomic position. In another aspect of this third embodiment, the markers in said set have a known genomic relationship to one another. A fourth embodiment of the present invention is a set of biallelic markers having a known relationship to one another and a known genomic position, said set of biallelic markers being obtained by the method of the first embodiment. In one aspect of this fourth embodiment, the biallelic markers have heterozygosity rates of at least about 0.18. In another aspect of this fourth embodiment, the biallelic markers have heterozygosity rate of at least about 0.32. In still another aspect of this fourth embodiment, the biallelic markers have a heterozygosity rate of at least about 0.42. A fifth embodiment of the present invention is a map comprising an ordered array of at least 20,000 biallelic markers obtained by the method of the first embodiment. In one aspect tf this fifth embodiment, the map comprises an ordered array of Bt least 60,000 biallelic markers obtained by the method of the first embodiment. In another aspect of this fifth embodiment the map comprises an ordered aπay of at least 120,000 biallelic markers obtained by the method of the first embodiment. In enother aspect of this fifth embodiment, biallelic markers are distributed at an average marker density ol one marker every 150kb. In a further aspect of this fifth embodiment the biallelic markers are distributed at πn average marker density of one marker every 50 kb. In a further aspect of this fifth embodiment, the biallelic markers are distributed at an average marker density αf one marker every 25 kb. A sixth embodiment of the present invention is a method of identifying one or more biallelic markers associated with a detectable trait comprising the steps of determiπiπgthe frequencies of each ollelc of one or more biallelic markers obtained by the method of tho first embodiment in individuals who expross said detectable trait and individuals who do not express said detectable trait, and identifying one or more alleles of said one or more biallelic markers which are statistically associated with the expression of said detectable trait. In one aspect of this sixth embodiment, tho detectable trait is selected from the group consisting of disease, drug response, drug efficacy, and drug toxieity. In another aspect of this sixth embodiment, the phenotype of said individuals whu express said detectable trait anil the pheπotype of said individuals who do not express said detectable trait are readily distinguishable from one another. In still another aspect of this sixth embodiment the individuals who express said detectable trait and the individuals whu do not express said detectable trait are selected from a bimodal phenotype distribution. In still another aspect of this sixth embodiment, the individuals who express said detectable trait are at one phenotγpic extreme of the population and said individuals who do not expross said detectable trait are at the other phenotypic extreme of the population. A seventh embodiment of the present invention is a method of identifying a haplotype associated with a trait comprising the steps of obtaining nucleic acid samples from trait positive and trait negative individuals, determining the frequencies of the alleles of each member of a group of biallelic markers obtained by the method of the first embodiment which are known to be located proximity to one another in the genome in said nucleic acid samples, and identifying a plurality of alleles of biallelic markers having a statistically significant association with said trait In one aspect of this seventh embodiment the detectable trait is selected from the group consisting of disease, drug response, drug efficacy, and drug toxicity. In another aspect of this seventh embodiment, the biallelic markers in each of these groups are located within a genomic region spanning less than 1kh. In still another aspect of this seventh embodiment, the biallelic markers in each of these groups are located within a genomic region spanning from 1 to 5kb. In still another aspect of this seventh embodiment the biallelic markers in each of these groups are located within a genomic region spanning from 5 to 10kb.. In stϊl another aspect of this seventh embodiment, the biaπclic markers in each of these groups are located within a genomic region spanning from 10 to 25kb. . In still another aspect of this seventh embodiment, the biallelic markers in each of these groups are located within a genomic region spanning from 25 to 50kb. In still another aspect of this seventh embodiment, the biallelic markers in each of these groups are located within a genomic region spanning from 50 to 150kb. . In still another aspect of this seventh embodiment, the biallelic markers in each of these groups are located within a genomic region spanning from 150 to 250kb. In still another aspect of this seventh embodiment, the biallelic markers in each of these groups are located within a genomic region spanning from 250 to 500kb. In still another aspect αf this seventh embodiment, the biallelic markers in each of these groups are located within a genomic region spanning from 500kb to 1Mb. In still another aspect of this seventh embodiment, the biallelic markers in each of these groups are located within a genomic region spanning more than 1Mb, An eighth embodiment of the present invention is a method of identifying one or more biallelic markers associated with a detectable trait comprising the steps uf selecting a gene in which mutations result in a detectable trail or a gene suspected of being associated with a detectable trait and identifying one or more biallelic markers obtained by the method of Claim 1 within the genomic region harboring said gene which are associated with said detectable trait. In one aspect of this eighth embodiment, the detectable trait is selected from the gtoup consisting of disease, drug response, drug efficacy, and drug toxicity. In another aspect of this eighth embodiment, the identifying step comprises determining the frequencies of said one or more biallelic markers in individuals who express said detectable trait and individuals who dα not express said detectable trait and identifying one or more biallelic markers which are statistically associated with the expression of said detectable trait. A ninth embodiment of the present invention is an array of nucleic acids fixed to a support, said nucleic acids comprising at least β consecutive nucleotides, including the polymorphic nucleotide, of one or more biallelic markers obtained by the method of the first embodimen In one aspect of this ninth embodiment, the nucleic acids comprise at least 1 consecutive nucleotides, including the polymorphic nucleotide, of at least five biallelic markers obtained by the method of the first embodiment In another aspect of this ninth embodiment the nucleic acids comprise at least 8 consecutive nucleotides, including the polymorphic nucleotide, of at least ten biallelic markers obtained by the method of the first embodiment. A tenth embodiment of the present invention is an array of nucleic acids fixed to a support, said nucleic acids comprising at least 8 consecutive nucleotides, including the polymorphic nucleotide, of one or more groups of biallelic markers known to be located in proximity to one another in the genome. An eleventh embodiment of the present invention is an array of nucleic acids fixed to a support, said nucleic acids comprising amplification primers for generating an amplification product comprising at least 8 consecutive nucleotides, including the polymorphic nucleotide, of one or more biallelic markers obtained by the method of the first embodiment A twelfth embodiment of the present invnetion is an array of nucleic acids fixed to a support, said nucleic acids of comprising amplification primers for generating an amplification product comprising at least 15 consecutive nucleotides, including the polymorphic nucleotide, of one or more groups of biallelic markers known to be located in proximity tn one another in the genome. A thirteenth embodiment of the present invnetion is an array of nucleic acids fixed to a support, said nucleic acids comprising one or more microsequeπciπg primers for determining the identity of the polymorphic base of one or more nucleic acids comprising at least 15 consecutive nucleotides, including the polymorphic nucleotide, of one or more biallelic markers obtained by the method of the first embodiment. A fourteenth embodiment of the present invention is an array of nucleic acids fixed to a support said nucleic nucleic acids comprising one or more microsequencing primers for determining the identity of the polymorphic bases of one or more groups of biallelic markers known tα be located in proximity to one another in the genome. A fifteenth embodiment of the present invention is an array of nucleic acids fixed to a support, wherein said nucleic acids arc complementary to one or more microsequencing primers lor determining the identities ul the polymorphic bases of one or more biallefic markers obtained by tho method of the first embodiment. In one aspect of this fifteenth embodiment the nucleic acids arc complementary to at least five microsequencing primers for determining the identities of the polymorphic bases of at least five biallelic markers obtained by the method of the first embodiment. In another aspect of this fifteenth embodiment, the αu eic acids are complementary to at least ten microsequencing primers fur determining the identities of the polymoφhic bases of at least ten biallelic markers obtained by the method of the first embodiment. A sixteenth embodiment of the present invention is an array of nucleic acids fixed tα a support, said nucleic acids comprising one or more nucleic acids complementary to one or more microserμmncing primers for determining the identity of the polymorphic bases of one or more groups of biallelic markers known to be located in proximity to one another in the genome. Another aspect of the present invention is an array of any one of the tenth, twelfth, fourteenth or sixteenth embodiments, wherein the members of each of said one or more groups of biallelic markers are located in physical proximity to one another on said support . Another aspect of the present invention is an array of any one of Claims of the tenth, twelfth, fourteenth or sixteenth embodiments, wherein said biallelic markers in each of these groups are located within a genomic region spanning less than 1kb. Another aspect of the present invention is an array of any one of of the tenth, twelfth, fourteenth or sixteenth embodiments, wherein said biallelic markers in each of these groups are located within a genomic region .spanning from 1 to 5kb. Another aspect of the present invention is an aπay of any one of of the tenth, twelfth, fourteenth or sixteenth embodiments, wherein the biallelic markers in each of these groups are located within a genomic region spanning from 5 to lOkb. Another aspect of the present invention is an aπay of any one of of the tenth, twelfth, fourteenth or sixteenth embodiments, wherein the biallelic markers in each of these groups are located within a genomic region spanning from 10 to 25kb, Another aspect of the present invention is an aπay of any one of of the tenth, twelfth, fourteenth or sixteenth embodiments, wherein the biallelic markers in each of these groups 8re located within a genomic region spanning from 25 to 50kb. Another aspect of the present invention is an aπay of any one of of the tenth, twelfth, fourteenth or sixteenth embodiments, wherein the biallelic markers in each of these groups are located within a genomic region spanning from 50 to 150kb, Another aspect of the present invention is an array of any one of of tho tenth, twelfth, fourteenth or sixteenth embodiments, wherein the biallelic markers in each of these groups are located within a genomic region spanning from 150 to 250kb. Another aspect of the present invention is an array of any one of of the tenth, twelfth, fourteenth or sixteenth embodiments, wherein the biallelic markers in each ol these groups are located within a genomic region spanning from 250 to 500kb. Another aspect of the present invention is an array of any one uf uf the tenth, twelfth, fourteenth or sixteenth embodiments, wherein the biallelic markers in each of these groups are located within a genuinic region spanning from 500kb to 1Mb. Another aspect of the present invention is an array of any one of of the tenth, twelfth, fourteenth or sixteenth embodiments, wherein the biallelic markers in each of ' these groups are located within a genomic rcgiun spanning more than 1Mb. Another aspect of the present invention is an array of any one of αf the tenth, twelfth, fourteenth or sixteenth embodiments, wherein each group of biallelic markers comprises at least 3 biallelic markers. Another aspect of the present invention is an array of any one of of the tenth, twelfth, fourteenth or sixteenth embodiments, wherein each group of biallcfic markers comprises at least 6 biallelic markers. Another aspect of the present invention is an aπay of any one of of the tenth, twelfth, fourteenth or sixteenth embodiments, wherein each group of biallelic markers comprises at least 20 biallelic markers. A seventeenth embodiment of the present invention is a method for determining whether an individual is at risk of developing a detectable trait or suffers from a detectable trait associated with said trait comprising the steps of obtaining a nucleic acid sample from said individual, screening said nucleic acid sample with one or more biallelic markers obtained by the method of the first embodiment, and determining whether said nucleic a id sample contains one or more of biallelic markers statistically associated with said detectable trait. I one aspect of this seventeenth embodiment, the detectable trait is selected from the group consisting of disease, drug response, drug efficacy and drug toxicity. In another aspect of this seventeenth βmobi ent the biallelic markers were obtained by the method of the sixth embodiment. In another aspect of this seventeenth embodiment, the biallelic markers were obtained by the method of the eighth embodiment An eighteenth embodiment of the present invention is a method of using a drug comprising obtaining a nucleic acid sample from an individual, determining the identity of the polymoφhic baso of one or more biallelic markers obtained by the method of the first embodiment which is associated with a positive response to treatment with said drug or one or more biallelic markers obtained by the method of the first embodiment which is associated with a negative response to treatment with said drug, and administering said drug to said individual if said nucleic acid sample contains one or more biallelic markers associated with a positive response to treatment with said drug or if said nucleic acid sample lacks one or more biallelic markers associated with a negative response to said drug. In one aspect of this eighteenth embodiment, the determining step comprises determining the identity of the polymorphic base of one or more biallelic markers obtained by the method of the aspect of the sixth embodiment wherein the trait is drug response which is associated with a positive response to treatment with said drug or one or more biallelic markers obtained by the aspect of the sixth embodiment wherein the trait is drug response which is associated with a negative response to treatment with said drug. In another aspect of this eighteenth embodiment the determining step comprises determining the identity of the polymorphic base of one or more biallelic markers obtained by the aspect of the eighth embodiment wherein the trait is drug response which is associated with a positive response to treatment with said drug or one or more biallelic markers obtained by the method of the aspect of the eighth embodiment wherein the trait is drug response which is associated with a negative response to treatment with said drug. A nineteenth embodiment of the present invention is a method of selecting an individual for inclusion in a clinical trial of a drug comprising obtaining a nucleic acid sample from an individual, determining the identity of the polymorphic base of one or more biallelic markers obtained by the method of tho first embodiment which is associated with a positive response to treatment with said drug or one or more biallelic markers associated with a negative response to treatment with said drug in said nucleic acid sample, and including said individual in said clinical trial if said nucleic acid sample contains one or more biallelic markers obtained by the method of the first embodiment which is associated with a positive responso to treatment with said drug or if said nucleic acid sample lacks one or more biallelic markers associated with a negative response to said drug, In one aspect of this nineteenth embodiment, the determining step comprises determining the identity of the polymoφhic base of one or mere biallelic markers obtained by the aspect of the sixth embodiment wherein the trait is drug response which is associated with a positive response to treatment with said drug or one or more biallelic markers obtained by the aspect of the sixth embodiment wherein the trait is drug respons which is associated with a negative response to treatment with said drug. In another aspect of this nineteenth embodiment the determining step comprises determining the identity of the polymorphic base of one or more biallelic markers obtained by tha aspect of the.eighth embodiment wherein the trait is drug response which is associated with a positive response to treatment with said drug πr one or more biallelic markers obtained by the aspect o( the eighth embodiment wherein the trait is drug response which is associated with a negative response to treatment with said drug. A twentieth embodiment of the present invention is a method of identifying a gene associated with a detectable trait comprising the steps of determining the frequency of each allele of one or more biallelic markers obtained by the method of the first embodiment in individuals having said detectable trait and individuals lacking said detectable trait identifying one or more alleles of one or more biallelic markers having a statistically significant association with said detectable trait, and identifying a gene in linkage disequilibrium with said one or more alleles. In one aspect of this twentieth embodiment, the method further comprises identifying a mutation in the gene which is associated with said detectable trait. In another aspect of this twentieth embodiment, the detectable trait is selected from the group consisting of disease, drug response, drug efficacy, and drug toxicitγ. A twenty-first embodiment of the present invention is a method of identifying a gene associated with a detectable trait comprising selecting a gene suspected of being associated with a detectable trait and identifying one or more biallelic markers obtained by tha method of the first embodiment within the genomic region harboring said gene which are associated with said detectable trait. In one aspect of this twenty-first embodiment, the detectable trait is selected from the group consisting of disease, drug response, drug efficacy, and drug toxicity. In another aspect of this twenty-first embodiment, the identifying step comprises determining the frequencies of said one or more biallelic markers in individuals who express said detectable trait and individuals who do not eipress said detectable trait and identifying one or more biallelic markers which arc statistically associated with tha expression of said detectable trait. Λ twenty-second embodiment of the present inventiuπ is a mεthud of identifying a haplotype associated with a trait comprising the steps of obtaining nucleic acid samples from trait positive and trait negative individuals, conducting an amplification reaction on said nucleic acid samples using amplification primers capable of generating amplification products containing the polymorphic bases of a plurolity of biallelic markers, contacting one or more arrays according to the tenth embodiment with said amplification products, determining the identities of the polymorphic bases of said amplification products, and identifying a haplotype having a statistically significant association with said trait. A twenty-third embodiment of the present invention is α method of identifying a haplotype associated with a trait comprising the steps of obtaining nucleic acid samples from trait positive and trait negative individuals, conducting amplification reactions on said nucleic acid samples using amplification primers capable of generating amplification products containing the polymoφhic bases of a plurality of biallelic markers, contacting one or more arrays according tn the fourteenth embodiment with said amplification products, conducting microsequencing reactions on said amplification products using microsequencing primers on said aπays, thereby generating elongated microsequencing primers comprising the polymoφhic bases of said amplification products, determining the identities of said polymorphic bases, and identifying a haplotype having a statistically significant association with said trait. A twenty-fourth embodiment of tho present invention is a method of identifying a haplotype associated with α trait comprising the steps of obtaining nucleic acid samples from trait positive and trait negative individuals, conducting amplification reactions on said nucleic acid samples uisπg amplification primers which are capable of generating ampfification products containing the polymoφhic bases of a plurality of biallelic markers, conducting microsequencing reactions on said nucleic acid samples, thereby generating microsequencing products containing the polymorphic bases of one or more biallelic markers at their 3' ends, said polymoφhic bases being detεctably labeled, contacting one or more arrays according to the sixteenth embodiment w ' rth said microsequencing products such that said microsequencing products specifically hybridize to said nucleic acids complementary to said microsequencing primers, determining the identities of the polymoφhic bases of said microsequencing products, and identifying a haplotype having a statistically significant association with said trait. A twenty-fifth embodiment of the present invention is a method of identifying a haplotype associated with a trait comprising the steps of obtaining nucleic acid samples from trait positive and trait negative individuals, contacting one or more arrays according to the twelfth embodiment with said nucleic acid sample, conducting on amplification reaction on said nucleic acid samples using amplification primers on said aπay which are capable of generating amplification products containing the polymoφhic bases of a plurality of biallefic markers, determining the identities of thβ polymorphic bases of said amplification products, and identifying a haplotype having a statistically significant association with said trait. A twenty-sixth embodiment of the present invention is a method of detcπiiiniπg whether an individual is at risk of developing Alzheimer's disease or whether ihe individual suffers from Alzheimer ' s disease as α result of possessing the Apo E e4 Site A allele comprising obtaining a nucleic acid sample from said individual, and determining the identity of the polymoφhic base in one or more of the sequences selected from the group consisting of SEQ ID Nos. 301 -305 and SEQ ID Nos. 307-311 or the sequences complementary thereto in sπid nucleic acid sample. In one aspect of this twenty- sixth embodiment, the method further comprises determining whether said nucleic acid sample contains the sequence of SEQ ID No. 300 or the sequence complementary thereto. In another aspect of this twenty-sixth embodiment, the step of determining the identity of the polymorphic bases in one or more of the sequences selected from the group consisting of SEQ ID Nos. 301-305 and SEQ ID Nos. 307-311 or the sequences complementary thereto comprises determining whether said nucleic acid sample contains the sequence of SEQ ID NO. 311 (the T allele of marker G9-365/344) or the sequence complementary thereto. In another version of the preceding aspect, the further comprises determining whether said nucleic acid sample contains the sequence of SEQ ID No. 30G αr the sequence complementary thereto. A twenty-seventh embodiment of the present invention is an isolated nucleic acid comprising a sequence selected from the group consisting of SEQ ID No. 301, SEQ ID No. 307, the sequences complementary thereto, and fragments comprising at least 8 consecutive nucleotides, including the polymorphic nucleotide, thereof. A twenty-eighth embodiment of the present invention is an isolated nucleic acid comprising α sequence selected from the group consisting of SEQ ID No. 302 , SEQ ID No. 308, the sequences complementary thereto, and fragments comprising at least 8 consecutive nucleotides thereof. A twenty-ninth embodiment of the present invention is an isolated nucleic acid comprising a sequence selected from the group consisting of SEQ ID No. 303, SEQ ID No. 309, the sequences complementary thereto, and fragments comprising at least 8 consecutive nucleotides, including the polymorphic nucleotide, thereof. A thirtieth embodiment of the present invention is an isolated nucleic acid comprising a sequence selected from the group consisting of SEQ ID No. 304, SEQ 10 No. 310 , the sequences complementary thereto, and fragments comprising at least β consecutive nucleotides, including the polymorphic nucleotide, thereof. A thirty first embodiment of the present invention is an isolated nucleic acid comprising a sequence selected from the group consisting of SEQ ID No. 305, SEQ ID No. 311, the sequences complementary thereto, and fragments comprising at least 8 consecutive nucleotides, including the polymoφhic nucleotide, thereof. A thirty second embodiment of the present invention is an isolated nucleic acid comprising a sequence selected from the group consisting of SEQ ID Nos. 313-317, SEQ ID Nos, 319-323, and fragments comprising at least 8 consecutive nucleotides thereof. A thirty third embodiment of the present invention is isolated nucleic acid comprising a sequence selected from the group consisting of SEQ ID Nos. 325-329, SEQ ID Nos. 331-335, the sequence complementary thereto, and fragments comprising at least 8 consecutive nucleotides thereof. A thirty fourth embodiment of the present invention is set of nucleic acids comprising at least 8 consecutive nucleotides, including the polymorphic nucleotide, of one or more biallelic markers obtained by the method of the first embodiment. A thirty fifth embodiment of the present invention is a set of nucleic acids comprising amplification primers for generating an amplification product comprising at least θ consecutive nucleotides, including the polymorphic nυcleotido. of one or more biallelic markers obtained by the method of the first embodiment, A thirty sixth embodiment of the present invention is a set of nucleic acids comprising une or more microsequencing primers for determining the identity of the polymorphic base of one or more nucleic acids comprising at least 8 consecutive nucleotides, including the polymorphic nucleotide, of one or more biallelic markers obtained by the method of the first embodiment Brief Description nf the Drawings Figure 1 is a cytogeiietic map of chromosome 21. Figure 2a shows the results of a computer simulation of the distribution of inter-marker spacing on a randomly distributed set of biallelic markers indicating the percentage of biallelic markers which will be spaced a given distance apart for 1. 2, or 3 markers/BAC in a genomic map {assuming a set of 20,000 minimally overlapping BACs covering the genome are evaluated). Figure 2b shows the results of a computer simulation of the distribution of intcr-mαrker spacing on a randomly distributed set of biallelic markers indicating the percentage of biallelic markers which will be spaced a given distance apart for 1, 3, or 6 markers/BAC in a genomic map (assuming a set of 20,000 minimally overlapping BACs covering the genome are evaluated). Figure 3 shows, for a series of hypothetical sample sizes, the p-value significance obtained in association studies performed using individual markers from the high-density biallelic map, according to various hypotheses regarding the difference of allelic frequencies between the T+ andT- samples. Figure 4 is a hypothetical association analysis conducted with a map comprising about 3,000 biallelic markers. Figure 5 is a hypothetical association analysis conducted with a map comprising about 20,000 biallelic markers. Figure 6 is 8 hypothetical association analysis conducted with a map comprising about G0,0DQ biallelic markers. Figure 7 is a haplotype analysis using biallelic markers in the Apo E region. Figure 8 is a simulated haplotype analysis using the biallelic markers in the Apo E region included in the haplotype analysis of Figure 7. Figure 9 shows a minimal array of overlapping clones which was chosen for further studies of biallelic markers associated with prostate cancer, the positions of STS markers known to map in the candidate genomic region along the contig, and the locations of biallelic markers along the BAC contig harboring a genomic region harboring a candidate gene associated with prostate cancer which were identified using the methods of the present invention. Figure 10 is a rough localization of a candidate gene for prostate cancer which was obtained by determining the frequencies of the biallelic markers of Figure 9 in affocted and unaffected populations. Figure 11 is a further refinement of the localization of the candidate gene for prostate cancer using additional biallelic markers which were not included in the rough localization illustrated in Figure 10. Figure 12 is a haplotype analysis using the biallelic markers in the genomic region of the gene associated with prostate cancer. Figure 13 is a simulated haplotype using the six markers included in haplotype 5 of Figure 11 Detailed Description of the Preferred Fmhndimeπt The human haploid genome contains an estimated B0,O0D to 100,000 or more genes scattered on a 3 κ 10 9 base-long double stranded DNA shared among the 24 chromosomes. Each human being is diploid, Le. possesses two haploid genomes, one from paternal origin, the other from maternal origin. The sequence of the human genome varies among individuals in a population. About 10 7 sites scattered along the 3 x 10 base pairs nf DNA are polymorphic, existing in at least two variant forms called alleles. Most of these polymorphic sites are generated by single base substitution mutations and are biallelic. Less than 10 s polymorphic sites are ύuc to more complex changes and are very often multi-allεlic, i.e. exist in more than two allelic forms. At a given polymorphic site, any individual (diploid), can be either homozygous (twice the same allele) or heterozygous (two different alleles). A given polymorphism or rare mutation can be either neutral (no effect on trait), or functional, ic. responsible for a particular genetic trait. Genetic Maps The first step towards the identification of genes associated with a detectable trait, such as a disease or any other detectable trait, consists in the localization of genomic regions containing trait-causing genes using genetic mapping methods. The preferred traits contemplated within the present invention relate to fields of therapeutic interest; in particular embodiments, they will be disease traits and/or drug response traits, reflecting drug efficacy or toxicity. Traits can either be "binary", β.g. diabetic vs. non diabetic, or "quantitative " , e.g. elevated blood pressure. Individuals affected by a quantitative trait can be classified according to an appropriate scale of trait values, e.g. blood pressure ranges. Each trait value range can then be analyzed as a binary trait. Patients showing a trait value within one such range will be studied in comparison with patients showing a trait value outside of this range. In such a case, genetic analysis methods will be applied to suhpopulations of individuals showing trait values within defined ranges. Genetic mapping involves the analysis of the segregation of polymorphic loci in trait positive and trait negative populations. Polymorphic loci constitute a small fraction of the human genome (less than \%), compared to the vast majority of human genomic DNA which is identical in sequence among the chromosomes of different individuals. Among all existing human polymorphic loci, genetic markers can be defined as genome-derived polynucleotides which are sufficiently polymorphic to allow a reasonable probability that a randomly selected person will be heterozygous, and thus informative for genetic analysis by methods such as linkage analysis or association studies, A genetic map consists of a collection of polymorphic markers which have been positioned on the human chromosomes. Genetic maps may be combined with physical maps, collections of ordered overlapping fragments of genomic DNA whose arrangement along the human chromosomes is known. The optimal genetic ap should possess the following characteristics: - the density of the genetic markers scattered along the genome should be sufficient to allow the identification and localization of any trait-related polymorphism. • each marker should have an adequate level of hetεrozygusity, so as to be informative in a large percentage of different mcioses, - all markers should be easily typed on a routine basis, at a rcasoruble expense, and in a reasonable amount of time, • the entire set of markers per chromosome should bo ordered in a highly reliable f ashiun. However, while the above maps are optimal, it will be appreciated that the maps of the present invention may be used in the the individual marker and haplotype association analyses described below without the necessity of determining the order of biallelic markers derived from a single BAC with respect tn one another. Genetic Maps Based on RFLPs or VNTRs Tho analysis of DNA polymorphisms has relied on the following types of polymorphisms, The first generation of genetic markers were restriction fragment length polymorphisms (RFLPs), siπrjle nucleotide polymorphisms which occur at restriction sites, thereby modifying the cleavage pattern of the corresponding restriction enzyme. Though the original methods used to type RFLPs were material-, effort- and time-consuming, today these markers can easily be typed by PCR-based technologies. Since they are biallelic markers [they present only two alleles, the restriction site being either present or absent), their maximum heterozygosity is 0.5. The theoretical number of RflPs distributed along 5 the entire human genome is more than 10 , which leads to a potential average inter-marker distance of 30 kilobases, However, in reality the number of evenly distributed RFLPs which occur at a sufficient frequency m the population to make them useful for tracking of genetic polymorphisms is very limited. The second generation of genetic markers was VNTRs (Variable Number of Tandem Repeats), which can he categorized as either miπisateHites or microsatellites. Mmisatellites are taπdemly repeated DNA sequences present in units of 5-50 repeats which are distributed along regions of the human chromosomes ranging from Q.1 to 20 kilobases in length. Since they present many possible alleles, their polymorphic informative content is very high. Mini-satellites are scored by performing Southern blots to identify the number of tandem repeats present in a nucleic acid sample from the individual being tested. However, there are only 10 potential VNTRs that can be typed by Southern blotting. Microsatellites (also called simple tandem repeat polymorphisms, or simple sequence length polymorphisms) constitute the most developed category of genetic markers. They include small arrays of tandem repeats of simple sequences (di-trϊ-tetra- nucleotide repeats) which exhibit a high degree of length polymorphism and thus a high level of ' mformativeness. Slightly more than 5,000 microsatellites easily typed by PCR-derived technologies, have been ordered along the human genome (Dib et al., Nature 380:152 (1996), the disclosure of which is incorporated herein by reference). A numher of these available microsatellites were used to construct integrated physical and genetic maps containing less than 5,00D markers. For example, CEPH (Chumakov et al., Na e 377: 175-298 (1995) and Cohθn et al., Nature 366: 638-701 (1933) , the disclosures of which are incorporated herein by reference), and Whitchead Institute and Gέnόthoπ (Hudson et al., 1995), constructed genetic and physical maps covering 75% to 95% of the human genome, based on 2500 to 5000 microsatollite markers. However, the number of easily typed informative markers in these maps was too small for the aveiage distance between informative markers to fulfill the above-listed requirements for genetic maps. Biallelic Mπrkt-rs Biallelic markers are genome derived polyπucluutides which exhibit bwllelic polymorphism. As used herein, the term biallelic marker means a biallelic single nucleotide polymorphism. Λs used herein, the term polymorphism may include a single base substitution, insertion, or delotion. By definition, ihθ lowest allele frequency of a biallelic polymorphism is 1% (sequence vanants which show allele frequencies below 1% are celled rare mutatiuns). There are j potentially more than 10 biallelic markers which can easily be typed by mutiπe automated techniques, such as sequence- or hybridization based techniques, out of which 10 are sufficiently informative for mapping purposes However, a biallelic marker will show a sufficient degree of informativencss for use in genetic mapping only if the frequency of its loss frequent allele is not less than about 10% (i.e. a heterozygosity rate of at least 0.18) (the heterozygosity rate for a biaHefic marker is 2 P, (I P,) , where P, is the frequency of allele a). Preferably, the frequoncy of the less frequent allele of the biallelic markers in the present maps is at least 20% (i e. a heterozygosity rate of at least 0.32}. More preferably, the frequency of the less frequent allele of the biallelic markers in the present maps is at least 30% (i e. its heterozygosity rate is higher than about 042). Initial attempts to construct genetic maps based on non RFLP bullehc markers have focused on identifying biallelic markers lying within sequence tagged sites (STS), pieces of genomic DNΛ having a known sequence and averaging about 250 bases in length. More than 30,000 STSs havo been identified and ordered along the genome (Hudson et al.. Science 270:1945-1954 (1995); Schuter et al. Science 274.540-546 (1996), the disclosures of which are incorporated herein by reference). For example, the Whitahead Institute and Gέnόthon's integrated map contains 15,086 STSs. These sequence tagged sites can be screened to identify polymorphisms, preferably Single Nucleotide Polymorphisms (SNPs), more preferably non RFLP biallelic markers therein. Generally polymorphisms are identified by determining the sequence of the STSs in 5 to 10 individuals. Wang et al. (Cold Spring harbor laboratory: Abstracts of papers pressented on genome Mapping and sequencing Λ7 (May 14-18, 1997), the disclosure of which is incorporated herein by reference) recently announced the identification and mapping of 750 Single Nucleotide Polymorphisms issued from the sequencing of 12,000 STSs from the WhiteheadfMIT map, in eight unrelated individuals. The map was assembled using a high throughput system based on the utilization of DNA chip technology available from Affymetrix (Chee et al.. Science 274:610-614 (1996), the disclosure of which is incorporated herein by reference). However, according to experimental data and statistical calculations, less than one out of 10 of all STSs mapped today will contain an informative Single Nucleotide Polymorphism. This is primarily due to the short length nf existing STSs (usually less than 250 bp). If one assumes 10 β informative SNPs spread along the human genome, there would on average be one marker of interest every 3X10 9 /10 G , i.e. every 3,000 lip. The probabiπty that one such marker is present on a 250 bp stretch is thus less than 1/1 . While it could produce a high density map, the STS approach based on currently existing markers docs not put any systematic effort into making sure that the markers obtained are optimally distributed throughout the entire genome. Instead, polymorphisms are limited to those locations for which STSs are available. Tine even distribution of markers along the chromosomes is critical to the future success of genetic analyses. In particular, a high density map having appropriately spaced markers is essential for conducting association studies on sporadic cases, aiming at identifying genes responsible for detectable traits such as those which are described beluw. As will be furthor explained below, genetic studies have mostly relied in the past on a statistical approach called linkage analysis, which took advantage of microsatellite markers to study their inheritance pattern within families from which a sufficient number of individuals presented the studied trait. Because of intrinsic limitations αf linkage analysis, which will be further detailed below, and hεcause these studies necessitate the recruitment of adequate family pedigrees, they are not well suited to the genetic analysis of nil traits, particularly those for which only sporadic cases are available (eg. drug response traits), or those which have a low penetrance within the studied population. Association studies offer an alternative to linkage analysis. Combined with the use of a high density map of appropriately spaced, sufficiently informative markers, association studies, including linkage disequilibrium-based genome wide association studies,will enable the identification of most genes involved in complex traits. The present invention relates to a method for generating a high density linkage disequilibrium b3sed genetic map of the human genome which will allow the identification of sufficiently informative markers spaced at intervals which permit their use in identifying genes responsible for detectable traits using genome-wide association studies and linkage disequilibrium mapping. Construction of a Physical Map The first step in constructing a high density genetic map of biallelic markers is the construction of a physical map. Physical maps consist of ordered, overlapping cloned fragments of genomic DNA covering a portion of the genome, preferably covering one or all chromosomes. Obtaining a physical map of the genome entails constructing and ordering a genomic DNA library. Physical mapping in complex genomes such as the human genome (3,000 egabases) requires the construction of DNA libraries containing large inserts (on the order of 0.1 to 1 Megabase). It is crucial that such libraries be easy to construct, screen and manipulate, and that the DNA inserts be stable and relatively free αf chimerism. Yeast artificial chromosomes (YACs; Burke et al., Science 236:B06-812 (1907), the disclosure of which is incorporated herein by reference) have provided an invaluable tool in the analysis of complex genomes since their cloning capacity is extremely high (in the Mb range). YAC libraries containing large DNA inserts (up to 2 Mb) have been used to generate STS-cαntent maps of individual chromosomes or of the entire human genome (Chumakov et a!. (1995), supra; -IB- Hudson et al. (1995), supra; Cohen et al„ Nature 366: 698-701 (1993, Chumakov et al.. Nature 359:380-367 (1992); Gemm.ll et al , Nature 377:299 319 (1995), Doggctt et al., Nature 377.335 365 (1995): the disclosures of which are incorporated herein by reference). The present genetic maps may be constructed using currently available YAC genomic libraries such as the CEPH human YΛC bbrary as a starting material (Chumakov et aL (1995), supra) Alternatively, one y construct a YAC genuinic library as described in Chumakov et al , 1995, the disclosure of which is incorporated herein by reference, or as described below. Once a YAC genomic library has been obtained, the geπuuuc DNA fragments therein are ordered. Urdnππg may be porformed directly on the guiiuinic DNΛ in the YAC library. However, direct ordering uf YAC inserts is not pieferred because YΛC libraries often exhibit a high rate of chimβπsm (40 to 50% of YΛC clones contain fragments frtnn more than one genomic region), often suffer from clonal instability withm their genomic DNΛ inserts, and require tedious procedures to manipulate and isolate tho insert DNA. Instead, it is preferable to conduct the mapping and sequencing procedures required for ordering the genomic DNA in a system which enables the stable cloning of large inserts while being easy to manipulate using standard molecular biology techniques. Accordingly, it is preferable to clone tho genomic DNΛ πito bacterial single copy plasmids, for example BACs (Bacterial Artificial Chromosomes), rather than into YACs. Bacterial artificial chromosomes arc well suited for use in ordering genomic DNΛ fragments. BACs provide a low rate of chimeπs and fragment rearrangement, together with relative ease of insert isolation. Thus BΛC libraries are well suited to integrate genetic, STS and cytogeπetic information while providing direct access to stable, readily sequenceable genomic DNΛ. Λπ example of bacterial artificial chromosome is the BAC cloning system of Shizuya et al., which is capable of stably propagating and maintaining relatively large genomic DNA fragments (up to 300 kb long) as single copy plasmids in E coh (Shizuya et al , Proc. Natl Acad Sci. USA 89:8794-8797 (1S92), the disclosure of which is incorporated herein by relerence). Example 1 describes the construction of a BΛC library containing human genomic DNΛ It will be appreciated that the source of the genomic DNA, the enzymes used to digest the DNA, the vectors into which the genomic DNA is inserted, and the size of the DNA inserts which are cloned into said vectors need not be identical to those described ,n Example 1 below. Rather, the genomic DNA may be obtained from any appropriate source, may be digested with any appropriate enzyme, and may be cloned into any suitable vector. Insert size may vary within any range compatible with the cloning system chosen and with the intended purpose of the library being constructed Typically, using BAC vectors to construct DNA libraries covering the entire human genome, insert size may vary between 50kb and 300 kb, preferably 100kb and 200kb. Example 1 Construction of a BAC library Three different human genomic DNA libraries were produced by cloning partially digested DNA from a human lymphoblastoid cell line (derived from individual N° 8445, CEPH fa ines) into the pBeloBACl l vector (Ki et al., Geπomics 34:213-218 (198B), the disclosure of which is incorporated herein by reference). One library was produced using a BamHI partial digestion of the genomic DNA from the lymphoblastoid cell line and contains 110,000 clones having an average insert size of 150 kb (corresponding to 5 human haploid genome equivalents). Another library was prepβrcd from a Hindlll partial digest and corresponds to 3 human genome equivalents with an average insert size of 150kb. A third library was prepared from a Ndel partial digest and corresponds to 4 human genome equivalents with an average insert size of 1 0kb. Alternatively, the Qenomic DNΛ may be inserted into BΛC vectors which possess both a high copy number origin of replication, which facilitates the isolation of the vector DNΛ, and a low copy number origin of replication. Cloning of a genomic DNA insert into the high copy number urigin of replication inactivates the origin such that clones containing a genomic insert replicate at low copy number. The low copy number of clones having a genomic insert therein permits the inserts to be stably maintained. In addition, selection procedures may be designed which enable luw copy number plasmids (i.e. vectors having genomic inserts therein) to be selected. Such vectors and selection procadurcs are described in the U.S. Patent Application entitled "High Tlirαughput DNA Sequencing Vector' (GENSET.015A. Serial No. 09/058,746), the disclosure of which is incorporated herein by reference. It will be appreciated that the present methods may be practiced using BAC vectors other than those of Shizuya et al. (1992, supra), or derived from those, or vectors other than BAC vectors which possess the ohiive- described characteristics. To construct a physical map of the genome from genomic ONA libraries, the library clones have to be ordered along the human chromosomes. In a preferred embodiment, a minimal subset of the ordered clones will then be chosen that completely covers the entire genome. For example the genomic DNA in the inserts of the above described BAC vectors are ordered using STS markers whoso positions relative to one another and locations oloπg the genome are known using procedures such as those described herein. The STS markers used to order the BΛC inserts may be the STS markers contained in the integrated maps described above. Alternatively, the STSs may be STSs which are not contained in any of the physical maps described above. In another embodiment, the STSs may be a combination of STSs included in the physical maps described above and STSs which are not included in the integrated maps described above. The BAC vectors are screened with STSs until there is at least one positive BAC clone per STS. Preferably, a minimally overlapping set of 10,000 to 30,000 BACs having genomic inserts spanning the entire human genome are identified. More preferably, a minimally overlapping set of 10,000 to 30,000 BACs having genomic inserts of about 100- 300kb in length spanning the entire human genome are identified. In a preferred embodiment, a minimally overlapping set of 10,000 to 30,000 BACs having genomic inserts of about 100-150 kb ' m length spanning the entire human genome is identified. In a highly preferred embodiment, a minimally overlapping set of 15,000 to 25,000 BACs having genomic inserts of about 100-200 kb in length spanning the entire human genome is identified. Alternatively, a smaller number of BACs spanning a set of chromosomes, a single chromosome, a particular subchromosomal region, or any other desired portion of the genome may be ordered. The BACs may be screened for the presence of STSs as described in Example 2 below. Example 2 Orderiππ of a BΛC Library: Screening Clones with STSs The BAC library is screened with a set of PCB-typcable STSs tα identify clones containing the STSs. To facilitate PCR screening of several thousand clonus, for example 200,000 clones, pools of clones aro prepared. Three-dimensional pools of the BAC libraries aiβ prepared as described in Chumakov et al. and are screened for the ability to generate on amplification fragment in amplification reactions conducted using primers derived from the ordered STSs. (Chumakov et al. (1995), supra). A BAC library typically contains 200,000 BΛC dunes. Since the average size of each insert is 100-300 kb, the overall size of such a library is equivalent ' to the size of at least about 7 human genomes. This library is stored as an array of individual clones in 518 384-wcll plates. It can be divided into 74 primary pools (7 plates each). Each primary pool can thon be divided into 48 subpouls prepared by using a three-dimensional pooling system based on the plate, row and column address of each clone (more particularly, 7 subpools consisting of all clones residing in a given microtiter plate: 16 subpools consisting of all clones in a given row; 24 subpools consisting of all clones in a given column). Amplification reactions ore conducted on the pooled BAC clones using primers specific for the STSs. For example, the three dimensional pools may be screened with 45,000 STSs whose positions relative to one another and locations along the genome are known. Preferably, the three dimensional pools are screened with about 30,000 STSs whose positions relative to one another and locations along the genome are known. In a highly preferred embodiment, the three dimensional pools are screened with about 20,000 STSs whose positions relative to one another and locations along the genome are known. Amplification products resulting from the amplification reactiuπs are detected by conventional agarose gel electrophoresis combined with automatic image capturing and processing. PCH screoning for a STS involves three steps: (1) identifying the positive primary pools; (2) for each positive primary pool, identifying the positive plate, row and column 'subpools' to obtain the address of the positive clone; (3) directly confirming the PCR assay on the identified clone. PCR assays are performed with primers specifically defining the STS. Screening is conducted as follows. First BAC DNA containing the genomic inserts is prepared as follows. Bacteria containing the BACs are grown overnight at 37°C in 120 i of LB containing chlora phcnicol (12 μg/ml). DNΛ is extracted by the following protocol: Centrifuge 10 in at 4°C and 2000 rpm Eliminate supernatant and resuspβnd pellet in 120 μ\ TE 10-2 (Tris HC1 10 M, EDTA 2 mM) Centrifuge 10 in at 4°C and 2000 rpm Eliminate supernatant and incubate pellet with 20 μ\ lyzozyme 1 mglml during 15 min at room temperature Add 20 l proteinase lOOzzg/ml and incubate 15 min at 60°C Add 8 μ\ DNAsβ 2U///I and incubate 1 hr at room temperature Add 100 μ\ TE 10-2 and keep at -80°C PCH assays are performed using the following protocol: Final volume * 5//l BΛC DNA 1.7 ng(yl gCl j . 2 mM dNTP (each) 200 μU primer (each) 2.9 ng///l Λmpli Taq Gold DNΛ polymerasa 0.05 unitf/zl PCR buffer (10x - 0.1 M TrisllCl pHB-3 0.5M KCI 1 x Tim amplification is performed on a Genius II thermocycler. After heating at 95° C for 10 min, 40 cycles are performed. Each cycle comprises: 30 sec at 95°C, 54°C for 1 in, and 30 sec at 72°C. For final elongation, 10 min at 72°C end tha amplification. PCR products are analyzed on 1% agarose gel with 0.1 mg/ml ethidium bromide. Alternatively, a YAC (Yeast Artificial Chromosome) library can be used. The very large insert size, of the order of 1 egabase, is the main advantage of the YAC libraries. The library can typically include about 33,000 YAC clones as described in Chumakov et aL (1995, supra). The YAC screening protocol may be the same as the one used for BAC screening. The known order of the STSs is then used to align the BAC inserts in an ordered array (contig) spanning the whole human genome. If necessary new STSs to be tested can be generated by sequencing the ends of selected BΛC inserts. Subchromosomal localization of the BACs can be established and/or verified by fluorescence in situ hybridization (FISH), performed on metaphasic chromosπmεs as described by Cherif et al. 1990 and in Example B below. BAC insert size may be determined hy Pulsed Field Gel Electrophoresis after digastioπ with the restriction enzyme Notl. Finally, a minimally overlapping set of BAC clones, with known insert size and subchromosomal location, covering the entire genome, a set of chromosomes, a single chromosome, a particular subchromosomal region, or any other desired portion of the genome is selected from the DNΛ library. For example, the BAC ones may cover at least IQOkb of contiguous genomic DNA, at least 250kb of contiguous genomic DNΛ, at least 500kb of contiguous genomic DMA, at least 2Mb of contiguous genomic DNA, at least 5Mb of contiguous genomic DNA, at least 10Mb of contiguous genomic DNA, or at least 20Mb of contiguous genomic DNA. Identification of biallelic markers In order to generate polymorphisms having the adequate informative content to be used as biallelic markers for genetic mapping, the sequences of random genomic fragments from an appropriate number of unrelated individuals are compared. Genomic sequences to be screened for biallelic markers may be generated by partially sequencing BAC inserts, preferably by sequencing the ends of BAC subclones. Sequencing the ends of an adequate number of BAC subclones derived from a minimally overlapping array of BACs such as those described above will allow the generation of biallelic markers spanning the entire genome, a set of chromosomes, a single chromosome, a particular subchromosomal region, or any other desired portion of the genome with an optimized inter-marker spacing. Thus, portions of the BACs in the selected ordered array are then subcloned and sequenced using, for example, the procedures described below. Example i. Suhdnπinα of BΛCs The cells obtained from three liters overnight culture of each BAC clone are treated by alkaline lysis using conventional techniques to obtain the BΛC DNA containing the genomic DNΛ inserts. After centrifugation of the BAC DNA in a cesium chloride gradient, ca. 50 g of BAC DNΛ are purified. 5-1 Oμu uf BAC DNΛ arc sonicated using three distinct conditions, to obtain fragments within a desired size range. The obtained DNΛ fragments are end-repaired in a 50 μ\ vulu β with two units of Vent polymerase for 20 min at 70° C, in the presence of the four deoxytriphosphotes (100/vM). The resulting blunt-ended fragments ore separated by electrophoresis on preparative low-melting point 1 % agarose gels (60 Volts for 3 hours). The fragments lying within a desired size range, such as 600 to 6,000 bp, are excised from the gel and treated with agarase. After chloroform extraction and dialysis on Microcon 100 columns, DNA in solution is adjusted to a 100 ng/μl concentration. A ligation to a linearised, dephosphorylated, blunt ended plasmid cloning vector is performed overnight by adding 100 ng of BAC fragmented DNΛ to 20 ng of pBluescript II Sk (+) vector DNA linearized by enzymatic digestion, and treating with alkaline phosphatase. The ligation reaction is performed in a 10 μ\ final volume in the presence of 40 units/μl T4 DNA ligase (Epicentre). The ligated products arc electroporatod into the appropriate cells (ElectroMAX £cø/r ' DH10B cells). IPTG and X-gal ore added to the cell mixture, which is then spread on tho surface of an ampirilfin-containing agar plate. After overnight incubation at 37 P C, recombinant (white) colonies are randomly picked and arrayed in 96 well microplates (or storage and sequencing. Alternatively, BAC subcloπiπg may be performed using vectors which possess both a high copy number origin of replication, which facilitates the isolation of the vector DNA. and a low copy number origin of replication. Cloning of a genomic DNΛ fragment into the high copy number origin of replication inactivates the origin such that clones containing a genomic insert replicate at low copy number. The low copy number of clones having a genomic insert therein permits the inserts to be stably maintained. In addition, selection procedures may be designed which enable low copy number plasmids (Le. vectors having genomic inserts therein) to be selected. In a preferred embodiment, BAC subcloning will be performed in vectors having the above described features and moreover enabling high throughput sequencing of long fragments of genomic DNA. Such high throughput high quality sequencing may be obtained after generating successive deletions within the subcloned fragments to be sequenced, using transposition-based or enzymatic systems. Such vectors are described in the U.S. Patent Application entitled "High Throughput DNA Sequencing Vector" (GENSET.015Λ, Serial No. 09/058,746), the disclosure of which is incorporated herein by reference. It will be appreciated that other subcloning methods familiar to those skilled in the art may also be employed. The resulting subclones are then partially sequenced using, for example, the procedures described below. Exa ple 4 Partial sπηucncina of BAC subclones. The genomic DNA inserts in the subclones, such as the BAC subclones prepared above, are amplified by conducting PCR reactions on the overnight bacterial cultures, using primers complementary to vector sequences flanking the insertions. The sequences of the insert extremities (on average 500 bases at each end, obtained under routine sequencing conditions) are determined by fluorescent automated sequencing on ABI 377 sequencers, using ΛBI Fiism DNΛ Sequencing Analysis software. Following gel image analysis and DNA sequence extraction, sequence data are automatically processed with adequate software to assess sequence quality. A proprietary base-caller, automatically flags suspect peaks, taking into account the shape of the peaks, the intcr-peak resolution, and the nnise level. The proprietary base-caller also performs an automatic trimming. Any stretch of 25 or fewer bases having more than 4 suspect peaks is usually considered unreliable and is discarded. The sequenced regions of the subclones, such as the BAC subclones prepared above, are then analyzed in order to identify biallelic markers lying therein. The frequency at which biallolic mβrkers will be detected in the screening process varies with the average level αf heterozygosity desired. For example, if biallelic markers having an average heterozygosity rate of greater than 0.42 arc desired, they will occur every Z5 to 3 kb on average. Therefore, on average, six 500 bp-genomic fragments have to be screened in order to derive 1 biallelic marker having an adequate informative content As a preferred alternative to sequencing the ends of an adequate number of BAC subclones, the above mentioned high throughput deletion-based sequencing vectors, which allow tha generation of a high quality sequence information covering fragments of ca. Bkb, may be used. Having sequence fragments longer than 2-5 or 3kb enhances tho chances of identifying biallelic markers therein. Methods of constructing and sequencing a nested set of deletions are disclosed in the U.S. Patent Application entitled "High Throughput DNΛ Sequencing Vector" (GENSET.015Λ, Serial No.09J058J46), the disclosure of which is incorporated herein by reference. To identity biallelic markers using partial sequence information derived from subclone ends, such as the ends of the BAC subclones prepared above, pairs of primers, each one specifically defining a 500 bp amplification fragment, are designed using the above mentioned partial sequences. The primers used for the genomic amplification of fragments derived from the subclones, such as the BAC subclones prepared above, may be designed using the OSP software (Hillier L. and Green P., Methods Appl, 1:124-8 (1991), the disclosure of which is incorporated herein by reference). The GC content of the amplification primers preferably ranges between 10 and 75 , more preferably between 35 and 60 %, and most preferably between 40 and 55 %. The length of amplification primers can range from 10 to 100 nucleotides, preferably from 10 to 50, 10 to 30 or more preferably 10 to 20 nucleotides. Shorter primers tend to lack specificity for a target nucleic acid sequence and generally require cooler temperatures to form sufficiently stable hybrid complexes with the template. Longer primers are expensive to produce and can sometimes self-hybridize to form hairpin structures. Λll primers may contain, upstraam of the specific target buses, a common oli iiuclootide tail that serves as 3 sequencing primer. Those skilled in the art are familiar with primer extensions which can be used for these purposes. To identify biallelic markers, the sequences corresponding to the paitial sequences determined above arc determined and compared in a plurality of individuals. The population used to identify biallelic markers having an adequate informative content preferably cuπsists of ca. 100 unrelated individuals from a heterogeneous population. First, DNΛ is extracted from the peripheral venous blood of each donor using methods such as thoso described in Example 5. Example 5 Extraction of ONΛ 30 ml of blood are taken from the individuals in the presence of EDTΛ. Cells (pellet) are collected after centrifugation for 10 minutes at 2000 rpm. Red calls are lyscd by a lysis sulution (50 ml final volume : 10 mM Tris pK7.6; 5 mM MrjCI 2 ; 10 mM NaCI). The solution is centrifuged (10 minutes, 2000 rpm) as many times as necessary to eliminate the residual red cells present in the supernatant, after resuspension of the pellet in the lysis solution. The pellet of white cells is lysed overnight at 42°C with 3.7 ml of lysis solution composed of: • 3 ml TE 10-2 (Tris-HC1 10 M, EDTA 2 mM) / NaCI 0.4 M • 200 μ\ SDS 10% • 500 μl K-proteinase (2 mg K-protciπasc in TE 10-2 / NaCI 0.4 M). For tha extraction of proteins, 1 ml saturated NaCI (6M) (1/3.5 v/v) is added. After vigorous agitation, the solution is centrifuged for 20 minutes at 10000 rpm. For the precipitation of DNA, 2 to 3 volumes of 100% ethanol are added to the previous supernatant, and the solution is centrifuged for 30 minutes at 2000 rpm. The DNΛ solution is rinsed three times with 70% ethanol to eliminate salts, and centrifuged for 20 minutes at 2000 rpm. Tha pellet is dried at 37° C, and resuspended in 1 ml TE 10-1 αr 1 ml water. The 0NA concentration is evaluated by measuring the 0D at 260 nm (1 unit 0D - 50 / vg/ml DNA). To evaluate the presence of proteins in the DNA solution, the 0D 250 / OD 280 ratio is determined. Only DNA preparations having a 0D 260 ( 0D 280 ratio between 1.8 and 2 are used in the subsequent steps described below. Once genomic DNA -from every individual in the given population has been extracted, it is preferred that a fraction of each DNA sample is separated, after which a pool of DNA is constituted by assembling equivalent DNA amounts of the separated fractions into a single one. Second, the DNA obtained from peripheral blood as described above is amplified using the above mentioned amplification primers. Example 6 provides procedures that may be used in the amplification reactions, and tho detection of polymorphisms within the obtained amplicons. Example 6 Amplification of DNΛ from Peripheral Blood and Identification of Biallelic Markers The amplification of each sequence is performed on pooled DNΛ samples obtained as in Example 5 above, using PCR (Polymerase Chain Reaction) as follows: - final volume 25 i • genomic DNΛ 2 ngjμl • MgCl 2 2 mM - dNTP (cach) 200 μM - primer (each) n\ } lμ\ - Ampli Tag Gold DNA polymerase (Perkin) 0.05 uπlllμ - PCH buffer (1 OX -0.1 M Tris HCI pH 8.3. 0.5 M KCI) 1X. The syntliesis of primers is performed following the phosphoramidite method, on a GENSET UFPS 24.1 synthesizer. To reduce the expense of preparing amplification primers for use in the above procedures, short primers may be used. While primers and probes having between 15 and 20 (or more) nucleotides are usually highly specific to a given nucleic acid sequence, it may be inconvenient and expensive to synthesize a relatively long oligoπucleotide fur each analysis. In order to at least partially circumvent this problem, it is often possible to use smaller but still relatively specific oligonucleotides that are shorter in length to create a manageable library. For example, a library of oligonucleotides comprising about 8 to 10 nucleotides is conceivable and has already been used for sequencing ul a 40,000 bp cosmid DNA (Studior, Proc. Natl. Acad. Sci USA B6(18):6917-6921 (1989), the disclosure of which is incorporated herein by reference). Another potential way to obtain specific primers and probes with a small library of oligonucleotides is to generate longer, more specific primers and probes from combinations of shorter, less specific oligonucleotides. Libraries of shorter origonucieotides, each one being from about five to eight nucleotides in length, have already been used (Kieleczawa et al.. Science 258:1767-1791 (1992); Kotler et aL, Proc. Natl. Acad. Sci. USA 90:42414245 (1993); aczorowski and Szγbalski, Ana] Biαchem. 221:127-135 (1994), the disclosures of which are incorporated herein by reference). Suitable probes and primers of appropriate length can therefore be designed through the association of two or three shorter oligonucleotides to constitute modular primers. The association between primers can be either covalent resulting from the activity of DNA T4 ligase or non-covalent through base-stacking energy. Tha amplification is performed on a Perkin Elmer 9600 Thermocycler or MJ Research PTC200 with heating lid. After heating at 95°C for 10 minutes, 40 cycles are performed. Each cycle comprises: 30 sec at 95°C, 1 minute at 54° C. and 30 sec at 72°C. For final elongation, 10 minutes at 72° C ends the amplification. The quantities of the amplification products obtained are determined on 96-well microtτtεr plates, using a f luorimeter and Picogreεn as intercalating agent (Molecular Probes). The sequences of the amplification products are determined using automated did β oxy terminator sequencing reactions with a dyef rimer cycle sequencing protocol. The products of the sequencing reactions are run on sequencing gels and the sequences are determined using gel image analysis. The sequence data are evaluated using software designed to detect the presence of biallelic sites among the pooled amplified fragments. The polymorphism search is based on the presence of superimposed peaks in tho electrophoresis pattern resulting from different bases occurring nt the same position. Because each diduoxy terminator is labeled with a different fluorescent molecule, the two peaks corresponding to a biallelic site present distinct colors corresponding to two different nucleotides at the same position on the sequence. The software evaluates the intensity ratio between the two peaks and the intensity ratio between a given peak and surrounding peaks of the same color. However, the presence of two peaks can be an artifact due to background noise. Tu exclude such on artifact, the two DNA strands are sequenced and a comparison between the peaks is carried out. In order to be registered as a polymorphic sequence, the polymorphism has to be detected on both strands. The above procedure permits those amplification products which contain biallelic markers to be identified. The detection limit for the frequency of biallelic polymorpliisms detected by sequencing pools of 100 individuals is about 10% for the minor allele, as verified by sequencing pools of known all die frequencies. However, more than 90% of the biallelic polymorphisms detected by the pooling method have a frequency for the minor allele higher than 25%. Therefore, the biallelic markers selected by this method have a frequency of at least 10% for the minor allele and 90% or less for the major allele, preferably at least 20% for the minor allele and 60% or less for the major allele, more preferably at least 30% for the minor allele and 70% or less for the major allele, thus a heterozygosity rate higher than 0.18, preferably higher than 0.32, more preferably higher than 0.42. In an initial study to determine the frequency of biallelic markers in the human genome that can be obtained using the above methods the following results were obtained. 300 different amplicons derived from 100 individuals, and covering a total of 150 kb obtained from different geπαmic regions, were sequenced. Λ tot3l of 54 biallelic polymorphisms were identified, indicating that there is one biallelic polymorphism with a heterozygosity rate higher than 0.18 (frequency of the minor allele higher than 10%), preferably higher than 0.38 (frequency of the minor allele higher than 25%), every Z5 to 3 kb. Given that tha human genome is about 3.10 B kb long, this indicates that, out of the 10 7 biallelic markers present on the human genome, approximately 10 e have adequate heterozygosity rates for genetic mapping purposes, Using the procedures of Examples 1-6, sets containing increasing numbers of biallelic markers may be constructed. For example, the procedures of Examples 1-6 are used to identify 1 to about 50 biallelic markers. In some embodiments, the procedures of Examples 1-6 are used to identify about 50 to about 200 biallelic markers. In other embodiments, the procedures of Examples 1-6 are used to identify about 200 to about 500 biallelic markers. In some embodiments, the procedures of Examples 1-6 are used to identi y about 1,000 biallelic markers. In other embodiments, the procedures of Examples 1-6 are used to identify about 3.000 biallelic markers. In further embodiments, the procedures of Examples 1-6 are used to identify about 5,000 biallelic markers. In another embodiment, the procedures of Examples 1-6 are used to identify about 10,000 biallelic markers. In still another embodiment, the procedures of Examples 1-B are used to identify about 20,000 biallelic markers. In still another embodiment, the procedures of Examples 1-6 are used to identify about 40,000 biallelic markers. In still another embodiment, the procedures of Examples 1-6 are used to identify about 60,000 biallelic markers. In still another embodiment, the procedures of Examples 1-6 are used to identify about 80,000 biallelic markers. In a still another embodiment, the procedures of Examples 1-6 arc used to identify more than 100,000 biallelic markers. In a further embodiment, the procedures of Examples 1-6 arc used to identify more than 120,000 biallelic markers. As discussed above, the ordered nucleic acids, such as the inserts in BΛC dunes, which contain the biallelic markers of the present invention may span a portion of tha genome. For example, the ordered nucleic acids may span at least 100kb of contiguous genomic DNA, at least 250kb of contiguous genomic DNA, at least 500kb of contiguous genomic DNA, at least 2Mb of contiguous genomic DNA, at least 5Mb ol contiguous genomic DNΛ, at least 10Mb of contiguous genomic DNA, or at least 20Mb of contiguous genomic DNA. In addition, groups of biallelic markers located in proximity to one another along the genome may be identified within these portions of the genome for use in haplotyping analyses as described below. The biallelic markers included in each of these groups may be located within a genomic region spanning less than 1kb, from 1 to 5kb, from 5 to l ϋkb, from 10 to 25kb, from 25 to 50kb, from 50 to 150kb, from 150 to 250kb, from 250 tu 500kh, from 500kb to 1 Mb, or more than 1 b. it will be appreciated that the ordered DNA fragments containing these groups of biallelic markers need not completely cover the genomic regions of these lengths but may instead bθ incomplete contigs having one or more gaps therein. As discussed in further detail below, biallelic markers may be used in single maker and haplotype association analyses regardless of the completeness of the corresponding physical contig harboring them. Using the procedures above, 653 biallelic markers, each having two alleles, were identified using sequences obtained from BACs which had been localized on the genome. In some cases, markers were identified using pooled BΛCs and thereafter reassigned to individual BACs using STS screening procedures such as those described in Examples 2 and 7. The sequences of 50 of these 653 biaDclic markers are provided in the accompanying Sequence Listing as SEQ ID Nos. 1-50 and 51-100 (with SEQ ID Nos. 1-50 being one allele of these 50 biallelic markers and SEO ID Nos. 51-100 being the other allele of these 50 biallelic markers). Although tha sequences of SEQ ID Nos, 1-50 and 51-100 will be used as exemplary markers throughout the present application, it will bo appreciated that the biallelic markers used in the maps of the present invention are not limited to these particular markers, nor are they limited to having the exact flanking sequences surrounding the polymorphic bases which are enumerated in SEQ ID Nos. 1-50 and 51-100 Rather, it will be appreciated that the flanking sequences surrounding the polymorphic bases of SEQ ID Nos. 1-50 and 51-100 may be lengthened or shortened to any extent compatible with their intended use and the present invention specifically contemplates such sequences. The sequences of these 653 biallelic markers, including the sequences αf SEQ ID Nos. 1- 50 and 51-100 may be used to construct the maps of the present invention as well as in the gene identification and diagnostic techniques described herein. It will be appreciated that the biallelic markers referred to herein may be of any length compatible with their intended use provided that the markers include the polymorphic base, and the present invention specifically contemplates such sequences. -2B- Ordering of biallelic markers Biallelic markers can be ordered to determine their positions along chromosomes, preferably subchromosomal regions, most preferably along the above described minimally overlapping ordered BΛC arrays, as follows. The positions of the biallelic markers along chromosomes may be determined using a variety of methodologies. In one approach, radiation hybrid mapping is used. Radiation hybrid (mil mapping is a somatic cell genetic approach that can be used for high resolution mapping of the human genome. In this approach, cell lines containing one or mure human chromosomes 8rc lethaBy irradiated, breaking each chromusoma into fragments whose size depends on the radiation dose. Tlicse fragments are rescued by fusion with cultured rodent cells, yielding subclones containing different portions uf the human genome. This teclinique is described by Benh un et al. {Genomics 4:509-517. 1989) and Cui et al., [Science 250:245-250, 1990), the entire contents of which are hereby incorporated by reference. The random and independent nature of the sub onos permits efficient mapping of any human genome marker. Human DNA isulatod from a panel of 80- 100 cell lines provides a mapping reagent for ordering biallolic markers. In this approach, the frequency of breakage between markers is used to measure distance, allowing construction of fine resolution maps as has been done for ESTs {Schulβf et al., Science 274:540-545, 1996, hereby incorporated by reference). RH mapping has been used to generate a high-resolution whole genome radiation hybrid map of human chromosome 17q22-q25.3 across the genes for growth hormone (GH) and thymidine kinase (TK) (Foster et aL, Genomics 33:185-19Z 1995), the region surrounding tfxs Gorlin syndrome gene (Ober ayr et aL, Fur. J. Hum. Genet. 4:242-245, 1996}, GO loci covering the entire short arm of chromosome 12 (Raeymaekers et al., Genomics 29:170-178. 1995), the region of human chromosome 22 containing the nβurofibromatosis type 2 locus (Frazer et al., Genomics 14:574-504, 1992) and 13 loci on the long arm of chromosome 5 (Warrington et al., Genomics 11:701-708, 1991). Alternatively, PCR based techniques and human-rodent somatic cell hybrids may be used to determine the positions of the bialleGc markers on the chromosomes. In such approaches, oligoπuclcotide primer pairs which are capable of generating amplification products containing the polymorphic bases of the biallefic markers are designed. Preferably, the oligonucleotide primers are 1B-23 bp in length and ore designed for PCR amplification. The creation of PCR primers from known sequences is well known to those with skill in the art For a review of PCR teclinology see Ertich, HA, PCR Technology; Principles and Applications for DMA Amplification. 1991 W.H. Freeman and Co., New York. The primers ara used ' m polymerase chain reactions (PCR) to amplify templates from total human genomic DNA. PCR conditions are as follows: 60 ng of genomic DNA is used as a template for PCR with 80 ng of each uligonudeαtidB primer, 0.6 unit of Taq polymerase, and 1 μCu of a 3Z P-labeled deoiycytidine triphosphata. The PCR is performed in a microplate thermocyder (Techne) under the following conditions: 30 cycles of 94°C, 1.4 min; 55°C, 2 min: and 72°C, 2 min; with a final extension at 72°C for 10 min. The amplified products are analyzed on a 6% polyacrylomide sequencing gel and visuaized by autoradiography. H the length of the resulting PCR product is identical to the length expected for an amplification product containing the polymorphic base of the biallelic marker, than the PCR reaction is repeated whh DNA templates from two panels of human-rodent somatic cell hybrids, BIOS PCRable DNA (BIOS Corporation) and NIGMS Human-Rodent Somatic Cell Hybrid Mapping Panel Number 1 (NIGMS, Camdeπ, NJ). PCR is used to screen a series of somatic cell hybrid ceU lines containing defined sets of human chromosomes for the presence of a given biallelic marker. DNΛ is isolated from the somatic hybrids and used as starting templates for PCR reactions using the primer pairs from the biallelic marker. Only those somatic cell hybrids with chromosomes containing the human sequence corresponding to tlie biallelic marker w3l yield an amplified fragment. The biallelic maikors are assigned to a chromosome by analysis of the segregation pattern of PCR products from the somatic hybrid DNA templates. The single human chromosome presont in all cell hybrids that ≠c rise to an amplified fragment is the chromosome containing that biallelic marker. For a review of techniques and analysis of results from somatic cell gene mapping experiments. (See Ledbettcr et al., Genomics 6:475-481 (1990).) Example 7 describes a preferred method for positioning of biallelic maikors on clones, such as BAC clones, obtained from genomic DNA libraries. Example 7 Screening BAC libraries with biellelic markers Amplification primers enabling the specific amplification of DNA fragments carrying the biallelic markers (including the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos 1-50 and 51-100) may be used to screon clones in any genomic DNΛ library, preferably the BΛC libraries described above for the presence of the biallelic markers. Pairs of primers were designed which allowed the amplification of fragments carrying the 653 hiallcfic markers obtained above. The amplification primers may be used to screen clones in a genomic DNA library for the presence of the G53 biallelic markers. For example, pairs of amplification primers of SEQ ID Nos. 101-150 and 151-200 may be used to amplify fragments which include the polymorphic bases of the biallelic markers of SEQ ID Nos. 1-50 and 51-100. It will be appreciated that amplification primers for tho biallelic markers may be any sequences which allow the specific amplification of any DNA fragment carrying the markers and may be designed using techniques familiar to those skilled in the art. The amplification primers may be oligonucleotides of 8, 10, 15, 20 or more bases in length which enable the amplification of any fragment carrying the polymorphic site in the markers. The polymorphic base may be in the center of the amplification product ur, alternatively, it may be located off-center. For example, in some embodiments, the amplification product produced using these primers may be at least 100 bases in length (i-e. 50 nucleotides on each side of the polymorphic base in ampDficatiun products in which the polymorphic base is centrally located). In other embodiments, the amplification product produced using these primers may be at least 500 bases in length (i.e. 250 nucleotides on each side of the polymorphic base in amplification products in which the polymorphic base is centrally located). In still further embodiments, the amplification product produced using these primers may be at least 1000 bases in length r e.500 nucleotides on each side of the polymorphic base in amplification products in which the polymorphic base is centrally located). Amplification primers such as those described above are included within the scape of the present invention. The localization of hiallelic markers on BAC clones is performed essentially as described in Example 2. The BAC clones tα be screened are distributed in three dimensional pools as described in Example 2. Amplification reactions are conducted on the pooled BΛC clones using primers specific for the biallelic markers to identify BΛC clones which contain the biallolic markers, using procedures essentially similar to those described in Example 2. Amplification products resulting from the amplification reactions are detected by conventional agnrosc gel eluctrophorcsis combined with automatic image capturing and processing. PCH screening for a biallolic marker involves three steps: (1) identifying the positive primary pools; (2) for each positive primary pools, identifying the positive plate. row and column 'subpools' to obtain the address of the positive clone; (3) directly confirming the PCH assay on the identified clone. PCR assays are performed with primers defining the biallelic marker. Screening is conducted as follows. First BΛC DNA is isolated as follows. Bacteria containing tha genomic inserts are grown overnight at 37°C in 12D I of LB containing chloramphen ul (12 g/ml). DNΛ is extracted by the following protocol: Centrifugo 10 min at 4 C and 2000 rpm Eliminate supernatant and resuspend pellet in 120 //I TE 10 2 (Tris IIC1 10 mM, EDTA 2 mM) Centrifuge 10 min at 4°C and 2000 rpm Eliminate supernatant and incubate pellet with 20 l lyzozyme 1 mg/ l during 15 min at room temperature Add 20 μ proteinase K 100 / Vg/ml and incubate 15 min at BO°C Add 8 μ\ DNΛse 2U/μl and incubate 1 hr at room temperature Add 100 μ\ TE 10-2 and keep at -8Q°C PCR assays are performed using the following protocol: Final volume 15 μ\ MgCl 2 2 mM dNTP (each) 200 primer (each) 2.9 nglμl A pfi Taq Gold DNA polymrase 0.05 unit/ /! PCR buffer (10x - 0.1 HI TrisHCl ρ.18.3 0.5 KCI lx The amplification is performed on a Genius II thermocy er. After heating at 95°C for 10 min, 40 cycles are performed. Each cycle comprises: 30 sec at 95°C, 54°C for 1 min, and 3D sec at 72°C. For final elongation, 1 min at 72°C end the amplification. PCR products are analyzed on 1% agarose gel with 0.1 mg/ml eihidium bromide. Using such procedures, a number of BAC clones carrying selected biallelic markers can be isolated. The position of these BAC clones on the human genome can be defined by performing STS screening as described in Example 2. Preferably, to decrease the number of STSs to be tested, each BAC can be localized on chromosomal or subchromosomal regions by procedures such as those described in Examples 6 and 9 below. This localization will allow the selection of a subset of STSs corresponding to the identified chromosomal or suhchromosomal region. Testing each BAC with such a subset of STSs and taking account of the position and order of the STSs along the genome will allow a refined positioning of the corresponding biallelic marker along the genome. In other embodiments, if the DNA library used to isolate BAC inserts or any typo of genomic DNA fragments harboring the selected biallelic markers already constitute a physical map of the genome or any portion thereof, using the known order of the DNA fragments will allow the order of the biallelic markers to be established. As discussed above, ft will bo appreciated that markers carried by the same fragment of genomic DNA, such as the insert in a BΛC clono, need not necessarily be ordered with respect to one another within the genomic fragment to conduct single point or haplotype association analysis. However, in other embodiments of the present maps, the order of biallelic markers carried by the same fragment of genomic DNA may be determined. The positions of the biallelic markers used to construct the maps of the present invention, including the 653 biallelic markers obtained above, may be assigned to subchromosomal locations using Fluorescence In Situ Hybridization (FISH) (Cherif et aL, Proc. Natl. Acad. ScL U.SA, 87:6639-6643 (1990), the disclosure of which is incorporated herein by reference). FISH analysis is described in Example 8 below. Example 8 Assignment πf Biallelic Markers to Sub womnsomal Regions Mataphase chromosomes ore prepared from phytohemagglutinin (PllA)-stimulated blood ceil donors. PHA- stimulated lymphocytes from healthy males are cultured for 72 h in RPMI-1640 medium. For synchronization, mcthotrexate (10 μM) is added for 17 h, followed by addition of 5-bromodeoryuridine (5-BudR, 0.1 mM) for 6 h. Colcemid (1 μg/ml) is added for the last 15 min before harvesting the cells. Cells are collected, washed in RPMI, incubated with a hypotonic solution of KC1 (75 mM) at 37°C for 15 min and fixed in tliree changes of rnctnaπohacetic acid (3:1). Tho cell suspension is dropped onto a glass slide and air-dried. BAC clones carrying the biallelic markers used to construct the maps of the present invention (including the 653 biallelic markers obtained abσvetα) can be isolated as described above. Those BACs or portions thereof, including fragments carrying said biallelic markers, obtained for example from amplification reactions using pairs of amplification primers as described above, can be used as probes to be hybridized with metaphasic chromosomes. It will be appreciated that the hybridization probes to be used in the contemplated method may be generated using alternative methods well known to those skilled in the art Hybridization probes may have any length suitable for this intended purpose. Probes are then labeled with biotin-16 dUTP by nick translation according to the manufacturer's instructions (Bethesda Research Laboratories. Bβthεsda, MD), purified using a Sephadεx G-50 column (Pharmacia, Upssala, Sweden) and precipitated. Just prior to hybridization, tho DNA pellet is dissolved in hybridization buffer (50% formamide, 2 X SSC, 10% dextran sulfate, 1 mg/ l sonicated salmon sperm DNΛ, pH 7) and the probe is denatured at 7Q"C for 5-10 min. Slides kept at -20°C 3re treated for 1 h at 37°C with RNase A (100 μg/ml). rinsed three times in 2 X SSC and dehydrated in an ethanol series. Chromosome preparations are denatured in 70% formamide. 2 X SSC for 2 min at 70°C, then dehydrated at 4°C. The sDdes are treated with proteinase K (10 μg/100 ml in 20 M Tris-HCI, 2 mM CaCt 2 ) at 37°C for 8 min and dehydrated. The hybridization mixture containing the probe is placed on the slide, covered with a coverslip, sealed with rubber cemont and incubatod overnight in a humid chamber at 37°C. After hybridization and post-liybtidizatioπ washes, the biotinylatcd probe is detected by avidin-FITC and amplified with additional layers of biotinylatcd goat anti-avidm and avidin-FITC. For chromusumal localization, fluorescent B-bands are obtained as previously described (Cherif et al.,(1990) supra.). The slides are ohscrved under a LEICA fluorescence microscope (DMRXΛ). Chromosomes are couπtcrstaiiied with propidium iodide and the fluorescent signal of the probe appears as two symmetrical yellow-green spots on both clirnmatids of the fluorescent R-baπd chromosome (red). Thus, a particular biallelic marker may be localized to a particular cytogenetic R-band on a given chromosome. The above procedure was used to coπfimi the subchromosomal locatiuπ of 95% of the BΛC clones harboring the 653 markers obtained abovB. In particular, the 50 markers of SEQ ID Nos. 1-50 and 51-100 were assigned to subchromosomal regions of chromosome 21. Simple identification numbers were attributed to each BAC from which the markers are derived. Figure 1 is a cytogenetic map of chromosome 21 indicating the subchromosomal regions therein. Table 1 Dsts the internal identification number of the localized biallelic markers, the internal identification number of the BACs from which the markers were derived, the size of the BAC kisert, tho average rrttcπnarkcr distance in tho BAC insert and the subchromosomal locations of the biallelic markers. The sequences of the localized markers are provided as SEQ ID Nos. 1-50 and 51-100 in the accompanying sequence fisting. Amplification primers far generating amplification products containing the polymorphic bases of these markers arc also provided as SEQ ID Nos. 101-150 and 151-200 in tho accompanying sequence listing. Microsequencing primers for use in determining the identities of the polymorphic bases of these biallelic markers are provided in the accompanying Sequence Listing as SEQ ID Nos.201-250 and 251-300. The rate at which biallelic markers may be assigned to subdiromuso al regions may be enhanced through automation. For example, probe preparation may be performed in a microtiter plate format, using adequate robots. The rate at which biallefic markers may be assigned to subchromosomal regions may be enhanced using techniques which permit the in situ hybridization of multiple probes on a single microscope slide, such as those disclosed in Larin et a!., Nucleic Acids Research 22: 3689-3692 (1994), the disclosure of which is incorporated herein by reference. In the largest test format descried, different probes were hybridized simultaneously by applying them directly from a 96-well microtiter dish which was inverted on a glass plate. Software for image data acquisition and analysis that is adapted to each optical system, test format, and fluorescent probe used, can be derived from the system described in Lichtεr et al. Science 247: 64-69 (1990), the disclosure of which is incorporated herein by reference. Such software measures the relative distance between the center of the fluorescent spot corresponding to the hybridized probe and the telomeric end of the short arm of the corresponding chromosome, as compared to the total length of the chromosome. The rate at which biallelic markers are assigned to subchromosomal locations may be further enhanced by simultaneously applying probes labeled with different flouoresceπt tags to each well of the 96 well dish. A further benefit of conducting the analysis on one slide is that it facilitates automation, since a microscope having a moving stage and the capability of detecting fluorescent signals in different ataphase chromosomes could provide the coordeπates of each proba on the metaphasβ chromosomes distributed on the 96 well dish. Example 9 below describes an alternative method to position biallelic markers which allows their assignment to human chromosomes. Example 9 Assignment of Riallelic Markers to Human Chromosomes The biallelic markers used to construct the maps of the present invention, including the 653 biallelic markers obtainad above (which include tho sequences of SEfl ID Nos. 1-50 and 51-100), may be assigned to a human chromosome using monosorπal analysis as described below. The chromosomal localization of a biallelic marker can be performed through the use of somatic cell hybrid panels. For example 24 panels, each panel containing a different human chromosome, may bo used (Russell et al., So at Cell Mol. Genet 22:425-431 (1996); Drwinga et al., Genomics 16:311-314 (1993), the disclosures of which are incorporated herein by reference). The biallelic markers are localized as follows. The DNA of e3ch somatic cell hybrid is extracted and purified. Genomic DNA samples from a somatic cell hybrid panel are prepared as follows. Cells arc lysβd overnight at 42" C with 3.7 ml of lysis solution composed of: 3 ml TE 10-2 (Tris HC1 10 mM, EDTA 2 mM) / NaCI 0.4 M 500 μl K-proteinase (2 mg K-proteinase in TE 10-2 / NaCI 0.4 M) For the extraction of proteins, 1 ml saturated NaCI (6M) (1/3.5 v/v) is added. After vigorous agitation, the solution is centrifuged for 20 min at 10,000 rpm. For the precipitation of DNA, 2 to 3 volumes of 100 % ethanol are added to the previous supernatant, and the solution is centrifuged for 30 min at 2,000 rpm. Tho DNA solution is rinsed three times with 70 % ethanol to eliminate salts, and centrifuged for 20 min at 2,000 rpm. The pellet is dried at 37°C, and resuspended in 1 ml TE 10-1 or 1 ml water. The DNA concentration is evaluated by measuring the OD at 260 nm (1 unit OD - 50 g/ml DNA). To determine the presence of proteins in the DNΛ solution, the ODorø/ODoso ratio is determined. Only DNA preparations having a ODorjj/OD∑βo ratio between 1.8 and 2 are used in the PCR assay. Then, a PCR assay is performed on genomic DNA with primers defining the biallelic marker. The PCR assay is performed as described above for BAC screening. The PCR products are analyzed on a 1 % agarose gel containing 0.2 mg/ml ethidium bromide. The ordering analyses described above may be conducted to generate an integrated genome wide genetic map comprising about 20,000 biallelic markers (1 biallelic marker per BAC if 20,000 BAC inserts are screened). In some D embodiments, the map includes one or more of the 653 markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto). In another embodiment, the above procedures are conducted to generate a map comprising about 40,000 markers (an average of 2 biallelic markers per BAC if 20.000 BAC inserts are screened). In some embodiments, tha map includes one or more of the 653 markers obtained above (which include the sequences of SEO ID Nos. 1-50 and 51-100 5 or the sequences complementary thereto). In a further embodiment preferred embodiment, the above procedures are conducted to generate a map comprising about 60,000 markers ( an average of 3 biallelic markers per BAC if 20,000 BAC inserts are screened). In soma embodiments, the map includes one or more of the 653 markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto). In a further embodiment preferred embodiment, the above procedures are conducted to generate a map comprising about 80,000 markers (an average of 4 biallelic markers per BAC if 20,000 GAC inserts are screened). In some embodiments, the map includes one or more of the 653 markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or tho sequences complementary thereto). In yet another embodiment, the above procedures are conducted to generate a map comprising about 100.000 markers (an average of 5 biallelic markers per BAC if 20,000 BAC inserts are screened). In some embodiments, the map includes one or more of the 653 markers obtained above (which include the sequences of SEQ ID Nos. 1-50 ami 51 -100 or the sequences complementary thereto). In a further embodiment, the above procedures are conducted to generate a map comprising about 120,000 markers (an average of 6 bialleϋc markers per BAC if 20,000 BAC inserts are screened). In some embodiments, the map includes one or more of the C53 markers obtained above (which include tha sequences of SEQ ID Nos. 1 -50 and 51 -100 or the sequences complementary thereto. Alternatively, maps having the above-specified average numbers of biallelic markers per BAC which comprise smaller portions of the genome, such as a sat of chromosomes, a single chromosome, a particular subchromosomal region, or any other desired portion of the genome, may also be constructed using the procedures provided herein. In some embodiments, the biallelic markers in the map are separated from one another by an average distance of 10-200kb. In further embodiments, the biallelic markers in the map are separated from one another by an average distance of 15-150kb. In yet another embodiment, the biallelic markers in the map are separated from one another by an average distance of 20-1 OOkb. In other embodiments, the biallelic markers in the map are separated from one another by an average distance of 100-150kb. In further embodiments, the biallelic markers in the map are separated from one another by an average distance of 50-1 OOkb. In yet another embodiment, the biallelic markers in the map are separated from one another by an average distance of 2550 b. Maps having the above-specified iπtermarker distances which comprise smaller portions of the genome, such as a set of chromosomes, a single chromosome, a particular subchromosomal region, or any other desired portion of the genome, may also be constructed using the procedures provided herein. Figure 2, showing the results of computer simulations of the distribution of inter-marker spacing on a randomly distributed set of biallelic markers, indicates the percentage of biatlefic markers which will be spaced a given distance apart for a given number of markers/BAC in the genomic map (assuming 20,000 BACs constituting a minimally overlapping array covering the entire genome are evaluated). One hundred iterations were performed for each simulation (20,000 marker map, 40,000 marker map, 60,000 marker map. 120,000 marker map). As illustrated in Figure 2a, 98% of inter-marker distances will be lower than 150kb provided 60,000 evenly distributed markers are generated (3 per BAC); 90% of inter-marker distances wilt be lower than 150kb provided 40,000 evenly distributed markers are generated (2 per BAC); and 50% of inter-marker distances will be lower than 150kb provided 20,000 evenly distributed markers are generated (1 per BAC). As illustrated in Figure 2b, 98% of inter-marker distances will be lower than 80kb provided 120,000 evenly distributed markers are generated (6 per BAC); 8ϋ% of iπter-markcr distances will be lower than BOkb provided 60,000 evenly distributed markers are generated (3 per BAC); and 15% of inter-marker distances will be lower than 80kb provided 20,000 evenly distributed markers are generated (1 per BAC). As already mentioned, high density biallelic marker maps allow association studies to be performed to identify genes involved in complex traits. Association studies examine the frequency ol marker alleles in unrelated trait positive (T+) individuals compared with trait negative (T-) controls, and are generally employed in the detection of polygenic inheritance. Association studies as a method of mapping genetic traits rely on the phenomenon of linkage disequilibrium, which is described below. Linkage Disequilibrium If two genetic loci lie on the same chromosome, then sets of alleles on the same chromosomal segment (called haplotypes) tend to be transmitted as a block from generation to generation. When not broken up by recombination, haplotypes can be tracked not only through pedigrees but also through populations. The resulting phenomenon at the population level is that the occurrence of pairs of specific alleles at different loci on the same chromosome is not random, and the deviation from random is called linkage disequilibrium (LD). If a specific allele in a given gene is directly involved in causing a particular trait T, its frequency will be statistically increased in a T+ population when compared to the frequency in a T- population. As a consequence of the existence of LD, the frequency of all other alleles present in the haplotype carrying the trait-causing allele (TCA) will also be increased in T+ individuals compared to T- individuals. Therefore, association between the trait and any allele in linkage disequilibrium with the trait-causing allele will suffice to suggest the presence of a trait-related gene in that particular allele's region. Linkage disequilibrium allows the relative frequencies in T + and T- populations of a limited number of genatic polymorphisms (specifically biallelic markers) to be analyzed as an alternative to screening all possible functional polymorphisms in order to find trait-causing alleles. The present invention then also concerns biallelic markers in linkage disequilibrium with the specific biallelic markers described above and which are expected to present similar characteristics in terms of their respective association with a given trait. In a preferred embodiment, the present invention concerns the biallelic markers that are in linkage disequilibrium with the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto). LD among a set of biallelic markers having an adequate heterozygosity rate can be determined by genotγping between 50 end 1000 unrelated individuals, preferably between 75 and 200, more preferably around 100. Geπotyping a biallelic marker consists of determining the specific allele carried by an individual at the given polymorphic base of the biallelic marker. Genotyping can be performed using similar methods as those described above for the generation of the biallelic markers, or using other genotyping methods such as those further described below. LD between any pair of biallelic markers comprising at least one of the biallelic markers of the present invention (M M ( ) can bo calculated for every allele combination (M Mr Mj, . and M, 2 ,M i2 ), according to the Piazza formula : ΔM,c,M j λ/G4 - V (θ4 + 03) (04 +02) , where : Θ4 frequency of genotypes not having allele k at M ( and not having allele I at M, Θ3- - + - frequency of genotypes not having allele k at M ( and having allele I at Mj Θ2- + ■ - frequency of genotypes having allele k at M, and not having allele I at M, Linkage disequilibrium (LD) between pairs of biallelic markers (Mi. Mj) can also be calculated for every allele combination (Mi1,Mj1 ; Mi1.Mj2 ; Mi2,Mj1 ; Mi2,Mj2) according to the maximum likelihood estimate (MLE) for delta (the composite linkage disequilibrium coefficient), as described by Weir (B.S. Weir, Genetic Data Analysis, (199G), Sinauer Ass. Eds, the disclosure of which is incorporated herein by reference). This formula allows linkage disequilibrium between alleles to be estimated when only genotype, and not haplotype, data are available. This LD composite test makes no assumption for random mating in the sampled population, and thus seems to be more appropriate than other LD tests for genotypic data. The skilled person win readily appreciate that other LD calculation methods con be used without undue experimentation. Example 10 illustrates the measurement of LD between a publicly known biallelic marker, the "ApoE Site Λ", located w ' rthin the Alzheimer's related ApoE gene, and other biallelic markers randomly derived from the genomic region containing the ApoE gene. Example 10 Measurement of Liπkaoe Oiseπuflibrium As originally reported by Strittmattor et al. and by Saunders et al. in 1993, the Apo E ε4 allele is strongly associated with both late-onset familial and sporadic Alzheimer's disease (AD). (Saunders, A.M. Lancet 342: 710-711 (1993) and Strittmater, W.J. βt al.. Proc. Natl. Acad. Sci. U.S.A. 90: 1977-1981 (1993), the disclosures of which are incorporated herein by reference). The 3 major isoforms of human Apolipoprotβin E (apoE2, -E3, and -E4), as identified by isoelectric focusing, are coded for by 3 alleles (ε 2, 3, and 4). The E 2, ε 3, and ε 4 isoforms differ in amino acid sequence at 2 sites, residue 112 (called site A) and residue 158 (called site B). The ancestral isoform of the protein is Apo E3, which at sites A/B contains cysteine/arginiπe, while ApoE2 and -E4 contain cysteine/cysteine and arginine/arginine, respectively (Weisgraber. K.H. et al., J. Biol. Chem. 256: 9077-9083 (1981); Rail, S.C. et al., Proc. Natl. Acad. Sci. U.S.A. 79: 6964700 (1982), the disclosures of which are incorporated herein by reference). Apo E ε 4 is currently considered as a major susceptibility risk factor for AD development in individuals of different ethnic groups (specially in Caucasians and Japanese compared to Hispaπics or African Americans), across all ages between 40 and 90 years, and in both men and women, as reported recently in a study performed on 5930 AD patients and 8607 controls (Farrer et A., JAMA 278:1349-1356 (1997), the disclosure of which is incorporated herein by reference). More specifically, the frequency of a C base coding for argiπiπe 112 at site A is significantly increased in AD patients. Although the mechanistic link between Apo E c 4 and neuronal degeneration characteristic of ΛD remains to be established, current hypotheses suguest that tho Apo E genotype may influence neuronal vulnerability by increasing the deposition and/or aggregation of the amyloid beta peptide in the brain or by indirectly reducing energy availability to neurons by promoting atherosclerosis. Using the methods of the present invention, biallelic markers that are in tho vicinity of the Apo E site A were generated and the association of one of their alleles with Alzheimer's disease was analyzed. An Apo E public marker (stSG94) was used to screen a human genome BAC library as previously described. A BAC, which gave a unique FISH hybridization signal on chromosomal region 19q13.2.3, the chromosomal region harboring the Apo E gene, was selected for finding biallelic markers in linkage disequilibrium with the Apo E gene as follows. This BAC contained an insert of 205 kb that was subcloned as previously described, Fifty BAC subclones were randomly selected and sequenced. Twenty five subclone sequences were selected and used to design twenty five pairs of PCR primers allowing 500 bp-a plicoπs to be generated. These PCR primers were then used to amplify the corresponding genomic sequences in a pool of DNA from 100 unrelated individuals (blood donors of French origin) as already described. Amplification products from pooled DNA were sequenced and analyzed for the presence of biallelic polymorphisms, as already described. Five amplicoπs were shown to contain a polymorphic base in the pool of 100 unrelated individuals, and therefore these polymorphisms were selected as random biallelic markers in the vicinity of the Apo E gene. The sequences of both alleles of these biallelic markers (99-344/439 ; 99-3551219 ; 99-359/308 ; 99- 365/344 ; 99-366/274) correspond to SEQ 10 Nos: 301-305 and 307-311 (See the accompanying Sequence Listing and Table 10) . Corresponding pairs of amplification primers for generating amplicons containing these biallelic markers can be chosen from those listed as SEQ ID Nos: 313 317 and 319-323. An additional pair of primers (SEQ ID Nos: 318 and 324) was designed that allows amplification of the genomic fragment carrying the biallelic polymorphism corresponding to the ApoE marker (99-2452/54; C/T; The C allele is designated SEQ ID NQ: 306 in the accompanying sequence listing, while the T allele is designated SEQ ID NO: 312 in the accompanying Sequence Listing; (See also Table 10), publicly known βs Apo E site A (Weisgraber et al. (1981), supra Rail βt al. (1982), supra) to be amplified. The five random biallelic markers plus the Apo E site A marker were physically ordered by PCR screening of the corresponding amplicons using all available BACs originally selected from the genomic DNA libraries, as previously described, using the public Apo E marker stSG94. The amplicon's order derived from this BAC screening is as follows: (99-344/99-366) - (99-365/99-2452) - 99-359 • 99-355. where brackets indicate that the exact order of the respective amplicons couldn't be established. Linkage disequilibrium among the six biallelic markers (five random markers plus the Apo E site A) was determined by genotyping the same 100 unrelated individuals from whom the random biallelic markers were identified. DNA samples and amplification products from genomic PCR were obtained in similar conditions as those described above for the generation of biallelic markers, and subjected to automated microsequencing reactions using fluorescent ddNTPs (specific fluorescence for each ddNTP) and the appropriate microsequencing primers having a 3' end immediately upstream of the polymorphic base in the biallelic markers. The sequence of those microsoqucncing primers is indicated within the corresponding sequence listings of SEQ ID Nos: 325-330. Once specifically extended at tha 3' end by a DNA polymerase using the complementary fluorescent didcoxynuclaotide analog (thermal cycling), the microsequencing primer was precipitated to remove the unincorporated fluorescent ddNTPs. The reaction products were analyzed by electrophoresis on ABI 377 sequencing machines. Results were automatically analyzed by an appropriate software further described in Example 13. Linkage disequilibrium (LD) between all pairs of biallelic markers (Mi, Mj) was calculated for eveiy allele combination (Mϋ.Mjl ; Mi1,Mj2 ; Mi2,Mj1 ; MI2.MJ2) according to the maximum likelihood estimate (MLE) for delta (the composite linkage disequilibrium coefficient). The results of the LD analysis between the Apo E Site A markar and the five new biallelic markers (99-344/439 ; 99 355/219 ; 99-359/308 ; 99 3G5/344 ; 99-366/274) ore summarized in Table 2 below : Table 2 Markers d x 100 SEQ ID Nos of tho SEQ ID Nos of the biallolic Markers amplification Primers ApoE SitoA 306 318 99-2452/54 312 324 99-344/439 1 301 313 307 319 99-3GB/274 1 305 317 311 323 99-365/344 8 304 318 310 322 99-359/308 2 303 315 309 321 99-355(219 1 302 314 308 320 The above LD results indicate that among the five biallelic markers randomly selected in a region of about 200 kb containing the Apo E gene, marker 99-365/344T is in relatively strong linkage disequilibrium with the Apo E site A allele (93-2452/540. Therefore, since the Apo E site A allele is associated with Alzheimer's disease, one can predict that the T allele of marker 99-365/344 will probably be found associated with AD. In order to test this hypothesis, the biallelic markers of SEQ ID Nos : 301-306 and 307-312 were used in association studies as described below. 225 Alzheimer's disease patients were recruited according to clinical inclusion criteria based on the MMSE test. The 248 control cases included in thi3 study were both ethnically- and age-matched to the affected cases. Both affected and control individuals corresponded to unrelated cases. The identities of the polymorphic bases of each of the biallelic markers was determined in each of these individuals using the methods described above. Techniques (or conducting association studies are further described below. The results of this study are summarized in Table 3 below : Tatilo 3 MARKER ASSOCIATION DATA Difference in allele frequency Corresponding p-value between individuals with Alzheimer's and control individuals 99-344/439 3.3 % 9.54 E-02 99-366/274 1.6% 2.09 E-01 99-3G5/344 17.7% 6.9 E-10 99-2452/54 (ApoE Site A) 23.8% 3.95 E-21 99 359/308 0.4% 9.2 £-01 99-355/219 2.5% 2.54 E-01 The frequency of the Apo E site A allele in both AD cases and controls was found in agreement with that previously reported (ca. 10% in controls and ca. 34% in AD cases, leading to a 24% difference in allele frequency), thus validating the Apo E ε4 association in the populations used for this study. Moreover, as predicted from the LD analysis (Table 2), a significant association of tha T allele of marker 99- 365/344 with AD cases (18% increase in the T allele frequency in AD cases compared to controls, p value for this difference - 6.9 E-10) was observed. The above results indicate that any marker in LD with one given marker associated with a trait will be associated with the trait. It will be appreciated that, though in this case the ApoE Site A marker is the trait-causing allele (TCA) itself, the same conclusion could be drawn with any other non TCA marker associated with the studied trait. These results further indicate that conducting association studies with a set of biallelic markers randomly generated within a candidate region at a sufficient density (here about one biallelic marker every 40kb on average), allows the identification of at least one marker associated with the trait In addition, these results correlate with the physical order of the six biallelic markers contemplated within the present example (see above) : marker 99-365/344, which had been found to be the closest in terms of physical distance to tho ApoE Site A marker, also shows the strongest LD with the Apo E site A marker. In order to further refine the relationship between physical distance end linkage disequilibrium between biallolic markers, a ca. 450 kb fragment from a genomic region on chromosome 8 was fully sequenced. LD within ca. 230 pairs of biallelic markers derived therefrom was measured in a random French population and analyzed as a function of the known physical iπtcr-marker spacing. This analysis confirmed that, on average, LD between 2 biallelic markers correlates with the physical distance that separates them. It further indicated that LD between 2 biallelic markers tends to decrease when their spacing increases. More particularly, LD between 2 biallelic markers tends to decrease when their inter-marker distance is greater than 50kb, and is further decreased when the inter-marker distance is greater than 75kb. It was further observed that when 2 biallelic markers were further than 150kb apart, most often no significant LD between them could be evidenced. It will be appreciated that the size and history of the sample population used to measure LD between markers may influence the distance beyond which LD tends not to be detectable. Assuming that LD can be measured between markers spanning regions up to an average of 150kb long, biallelic marker maps will allow genome-wide LD mapping, provided they have an average inter-marker distance lower than 150kb. Genome-wide LD mapping aims at identifying, for any TCA being searched, at least one biallelic marker in LD with said TCA. Preferably, in order to enhance the power of LD maps, in some embodiments, the biallelic markers therein have average inter-marker distances of 150kb or less, 75 kb or less, or 50 kb or less, 30kb or less, or 25kb or less to accommodate the fact that, in some regions of the genome, the detection of LO requires lower inter-marker distances. The present invention provides methods to generate biallelic marker maps with average inter-marker distances of 150kb or less. In somB embodiments, the mean distance between biallelic markers constituting the high density map will be less than 75kb, preferably less than 50kb. Further preferred maps according to the present invention contain markers that are less than 37.5kb apart In highly preferred embodiments, the average inter-marker spacing for the biallelic markers constituting very high density maps is less than 30kb, most preferably less than 25kb. Genetic maps containing biallelic markers (including the 653 biallelic markers obtained above, which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto) may be used to identify and isolate genes associated with detectable traits. The use of the genetic maps of the present invention is described in more detail below. Use of the Hinh Density Biallelic Marker Map to Identify Genes Associated with a Detectable Trait One embodiment of the present invention comprises methods for identifying and isolating genes associated with a detectable trait using the biallelic marker maps of the present invention. In the past, the identification of genes linked with detectable traits has relied on a statistical approach called linkage analysis. Linkage analysis is based upon establishing a correlation between the transmission of genetic markers and that of a specific trait throughout generations within a family. In this approach, all members of a series of affected families are geπotyped with a few hundred markers, typically microsatellite markers, which are distributed at an average density of one every 10 Mb. By comparing genotypes in all family members, one can attribute sets of alleles to parental haploid genomes (haplotyping or phase determination) The origin of rccombiπed fragments is then determined in the offspring of all famibes. Those that co segregate with the trait are tracked. After pooling data from all families. statistical methods are used to determine the likelihood that the marker and the trait ara segregating independently in all families. As a result of the statistical analysis, one or several regions having a high probability of harboring a grnu linked to the trait arc selected as candidates for further analysis. The result of linkage analysis is considered as significant (i.e there is a high probability that the region contains a gene involved in a detectable trait) when the chance of independent segregation of the marker and the trait is lower than 1 in 1000 (expressed as a LOD score > 3) Generally, the length of the candidate region identified using linkage analysis ts between 2 and 20Mb. Once a candidate region is identified as described above, analysis of recombinant individuals using additional markers allows further delineation of the candidate linked region. Linkage analysis studies have generally relied on the use of a maximum of 5,000 microsatellite markers, thus limiting tlie maximum theoretical attainable resolution of linkage analysis to ca. 600 kb on average Linkage analysis has been successfully applied to map simple genetic traits that show clear Mcndchan inheritance patterns and which have a high penetrance (penetrance is the ratio between the number of trait positive earners of allele a and the total number of a carriers in the population). About 100 pathological trait-causing genes were discovered using linkage analysis over the last 10 years. In most ol these cases, the majority of affected individuals had affected relatives and the detectable trait was rare in the general population (frequencies less than 0.1 %). In about 10 cases, such as Alzheimer's Disease, breast cancer, and Type II diabetes, the detectable trait was more common but the aDele associated with tha detectable trait was rare in the affected population. Thus, the alleles associated with these traits were not responsible for the trait in all sporadic cases. Linkage analysis suffers from a variety of drawbacks. First, linkage analysis is limited by its reliance on the choice of a genetic model suitable for each studied trait. Furthermore, as already mentioned, the resolution attainable using linkage analysis is limited, and complementary studies are required to refine the analysis of the typical 2Mb to 20Mb regions initially identified through linkage analysis. In addition, linkage analysis approaches have proven difficult when applied to complex genetic traits, such as those due to the combined action of multiple genes and/or environmental factors. In such cases, too large an effort and cost are needed to recruit the adequate number of affected families required for applying linkage analysis to these situations, as recently discussed by Risch, N. and Merikangas, K. (Science 273:1516 1517 (1996), the disclosure of which is incorporated herein by reference). Finally, linkage analysis cannot be applied to the study of traits for which no large informative families are available. Typically, this will ba the case in any attempt to identify trait causing alleles involved in sporadic cases, such as alleles associated with positive or negative responses to drug treatment. The present genetic maps and biallelic markers (including the 653 biallelic markers obtained above, which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto) may be used to identify and isolate genes associated with detectable traits using association studies, an approach which does not require the use of affected families and which permits the identification of genes associated with sporadic traits. Association studies are described in more detail below. Association Studies As already mentioned, any gene responsible or partly responsible for a given trait will be in LD with some flanking markers. To map such a gene, specific alleles of these flanking markers which are associated with the gene or genes responsible for the trait are identified. Although the following discussion of techniques for finding the gene or genes associated with a particular trait using linkage disequilibrium mapping, refers to locating a single gene which is responsible for the trait, it will be appreciated that the same techniques may also be used to identify genes which are partially responsible for the trait. Association studies may be conducted within the general population (as opposed to the linkage analysis techniques discussed abovo which ere Emitεd to studies performed on related individuals in one or several affected families). Association between a biallelic marker A and a trait T may primarily occur as a result of three possible relationships between the biallelic marker and the trait. First allele a of biallelic marker A may be directly responsible for trait T (eg., Apo E e4 site A and Alzheimer's disease). However, since the majority of the biallelic markers used in genetic mapping studies are selected randomly, they mainly map outside of genes. Thus, the likelihood of allele a being a functional mutation directly related to trait T is very low. Second, an association between a biallelic marker A and a trait T may also occur when the biallelic marker is very closely finked to the trait lotus. In other words, an association occurs when allele a is in linkage disequilibrium with the trait-causing allele. When the biallelic marker is in close proximity to a gene responsible for the trait more extensive genetic mapping will ultimately allow a gene to be discovered near the marker locus which carries mutations in people with trait T (i.e. the gene responsible for the trait or one of the genes responsible for the trait). As will be further exemplified below, using a group of biallelic markers which are in close proximity to the gene responsible for the trait the location of the causal gene can be deduced from the profile of the association curve between the biallelic markers and the trait. The causal gene will usually be found in the vicinity of the marker showing the highest association with the trait. Finally, an association between a biallelic marker and a trait may occur when people with the trait and people without the trait correspond to genetically different subsets of the population who, coincideπtally, also differ in the frequency of allele a (population stratification). This phenomenon may be avoided by using ethnically matched large heterogeneous samples. Association studies are particularly suited to the efficient identification of genes that present common polymorphisms, and are involved in multifactorial traits whose frequency is relatively higher than that of diseases with monofactorial inheritance. Association studies mainly consist of four steps: recruitment of trait-positive (T + ) and trait-negative (T-) populations with well-defined phβnotypes, identification of a candidate region suspected of harboring a trait causing Oenc, identification of said gene among candidate genes in the region, and finally validation of mutation(s) responsible for the trait in said trait causing gene. In a first step, trait + and trait - phenolypcs have to be well-defined. In order to perform efficient and significant association studies such as those described herein, the trait under study should preferably follow a bimodal distribution in the population under study, presenting two clear non-overlapping phenotypes, trait + and trait -. Nevertheless, in the absence of such a bimodal distribution (as may in fact be the case for complex genetic traits), any genetic trait may still be analyzed using the association method proposed herein by carefully selecting the individuals to bo included in the trait + and trait - phenotypic groups. The selection procedure involves selecting individuals at opposite ends of the non-bimodal phenotype spectrum αf the trait under study, so as to include in these trait + and trait - populations individuals who clearly represent non-overlapping, preferably extreme phenotypes. The definition of the inclusion criteria for the trait + and trait - populations is an important aspect of the present invention. The selection of those drastically different but relatively uniform phenotypes enables efficient comparisons in association studies and the possible detection of marked differences at the genetic level, provided that the sample sizes of the populations under study are significant enough. Generally, trait + and trait - populations to be included in association studies such as those proposed in the present invention consist of phβnotypically homogeneous populations of individuals each representing 100% of the corresponding phenotype if the trait distribution is bimodal. If the trait distribution is non-bimodal, trait + and trait - populations consist of phenotypically uniform populations of individuals representing each between 1 and 98%, preferably between 1 and 80%, more preferably between 1 and 50%, and more preferably between 1 and 30%, most preferably between 1 and 20% of the total population under study, and selected among individuals exhibiting non- overlapping phenotypes. In some embodiments, the T + and T groups consist of individuals exhibiting the extreme phenotypes within the studied population. The clearer the difference between the two trait phenotypes, the greater the probability of detecting an association with biallelic markers. In preferred embodiments, a first group of between 50 and 300 trait + individuals, preferably about 100 individuals, are recruited according to their phenotypes. In each case, a similar number of trait negative individuals are included in such studies who are preferably both ethnically- and age-matched to the trait positive cases. Both trait + and trait ■ individuals should correspond to unrelated cases. Figure 3 shows, for a series of hypothetical sample sizes, the p-value significance obtained in association studies performed using individual markers from the high-density biallelic map, according to various hypotheses regarding the difference of allelic frequencies between the T+ and T- samples. It indicates that, in all cases, samples ranging from 150 to 500 individuals are numerous enough to achieve statistical significance. It will be appreciated that bigger or smaller groups can be used to perform association studies according to the methods of the presont invention. In a second step, a marker/trait association study is performed that compares the genotype frequency of each biallelic marker in the above described T+ and T- populations by means of a chi square statistical test (one degree of freedom). In addition to this single marker association analysis, a haplotype association analysis is performed to define the frequency and the type of the ancestral carrier haplotype. Haplotype analysis, by combining the informativenoss of a set of biallelic markers increases the power of the association analysis, allowing false positive and/or negative data that may result from the single marker studios to be eliminated. Genotyping can be performed using the microsequencing procedure described in Example 13, or any other g β notyping procedure suitable for this intended purpose. If a positive association with a trait is identified using an array of biallolic markers having a high enough density, the causal gene will be physically located in the vicinity of the associated markers, since the markers showing positive association with the trait are in linkage disequilibrium with the trait locus. Regions harboring a gene responsible for a particular trait which are identified through association studies using high density sots of biallelic markers will, on average, be 20 • 40 times shorter in length than those identified by linkage analysis. Once a positive association is confirmed as described above, a third step consists of completely sequencing the BAC inserts harboring the markers identified in the association analyzes. Theso BACs are obtained through screening human genomic libraries with the markers probes and/or primers, as described above. Once a candidate region has been sequenced and analyzed, the functional sequences within the candidate region (e.g. exons, splice sites, promoters, and other potential regulatory regions) are scanned for mutations which are responsible for the trait by comparing the sequences of the functional regions in a selected numher of T+ and T- individuals using appropriate software. Tools for sequence analysis are further described in Example 14. Finally, candidate mutations arc then validated by screening a larger population of T+ and T- individuals using genotyping techniques described below. Polymorphisms arc confirmed as candidate mutations when the validation population shows association results compatible with those found between the mutation and the trait in the test population. In practice, in order to define a region bearing a candidate gene, the trait + and trait • populations are gβnotγped using an appropriate number of biallelic markers. The markers may include one or more of the 653 markers obtained above (which include tha sequences of SEQ ID Nos: 1-50 and 51-100 or the sequences complementary thereto. The markers used to define a region bearing a candidate gene may be distributed at an average density of 1 marker per 10-200 kb. Preferably, the markers used to define a region bearing a candidate gene are distributed at an average density of 1 marker every 15-150 kb. In further preferred embodiments, the markers used to define a region bearing a candidate gene are distributed at an average density of 1 marker every 20-1 OOkb. In yet another preferred embodiment, the markers used to define a region bearing a candidate gene ara distributed at an average density of 1 marker every 100 to 150kb. In a further highly preferred embodiment, the markers used to define a region bearing a candidate gene are distributed at an average density of 1 marker every 50 to 100kb. In yet another embodiment, the biallelic markers used to define a region bearing a candidate gene are distributed at an average density of 1 marker every 25-50 kilobases. As mentioned above, in order to enhance the power of linkage disequilibrium basBd maps, in a preferred embodimeπt, the marker density of the map will be adapted to take the linkage disequilibrium distribution in the genomic region of interest into account. In some embodiments, the initial identification of a candidate genomic region harboring a gene associated with a detectable phenotype may be conducted using a preliminary map containing a few thousand biallelic markers. Thereafter, the genomic region harboring the gene responsible for the detectable trait may be better delineated using a map containing a larger number of biallafic markers. Furthermore, tha genomic region harboring tha gene responsible for the detectable trait may be further delineated using a high density map of biallelic markers. Finally, the gene associated with the detectable trait may be identified and isolated using a very high density biallelic marker map. Example 11 describes a hypothetical procedure for identifying a candidate region harboring a gene associated with a detectable trait. It will be appreciated that although Example 11 compares the results of analyzes using markers derived from maps having 3,000, 20,000, and 60,000 markers, the number of markers contained in the map is not restricted to these exemplary figures. Rather, Example 11 exemplifies the increasing refinement of tho candidate region with increasing marker density. Λs increasing numbers of markers are used in the analysis, points in the association analysis become broad peaks. The gene associated with the detectable trait under investigation will lie within or near the region under the peak. Example 11 Identification of a Candidate Ruπiuπ Harboring a Gene Associated with a Detectable Trait The initial identification of a candidate genomic region harboring a gene associated with a detectable trait may he conducted using a genome-wide map comprising about 20,000 biallelic markers. The candidate genomic region may be further defined using a map having a higher marker density, such as a map comprising about 40,000 markers, about 60,000 markers, about 80,000 markers, about 100,000 markers, or about 120,000 markers. The use of high density maps such as those described above allows the identification of genes which are truly associated with detectable traits, since tha coincidental associations will be randomly distributed along the genome while tho true associations will map within one or more discrete genomic regions. Accordingly, biallelic markers located in the vicinity of a gene associated with a detectable trait will give rise to broad peaks in graphs plotting the frequencies of the biallelic markers in T+ individuals versus T- individuals. In contrast, biallelic markers which are not in the vicinity of the gene associated with the detectable trait wiQ produce unique points in such a plot. By determining the association of several markers within the region containing the gene associated with the detectable trait, the gene associated with the detectable trait can be identified using an association curve which reflects the difference between the allelo frequencies within the T+ end T- populations for each studied marker. The gene associated with the detectable trait will ba found in the vicinity of the marker showing the highest association with the trait Figures 4, 5, and 6 illustrate the above principles. As illustrated in Figure 4, an association analysis conducted with a map comprising about 3,000 biallelic markers yields a group of points. However, when an association analysis is performed using a denser map which includes additional biallelic markers, the points become broad peaks indicative of the location of a gene associated with a detectable trait. For example, the biallelic markers used in the initial association aπalysis may be obtained from a map comprising about 20,000 biallelic markers, as illustrated in Figure 5, In some embodiments, one or more of the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1 50 and 51-100 or the sequences complementary thereto) are used in the association analysis. In the hypothetical eiomplβ of figure 4, the association analysis with 3,000 markers suggests peaks near markers 9 and 17. Next, a second analysis is performed using additional markers in the vicinity of markers 9 and 17, as illustrated in the hypothetical example of Figure 5, using a map of about 20.000 markers. This step again indicates an association in the close vicinity of marker 17, since more markers in this region show an association with the trait However, none of the additional markers around marker 9 shows a significant association with tho trait, which makes marker 9 a potential false positive. In some embodiments, one or more of the 653 biallelic maikcrs obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto) are used in the second analysis. In order to further test the validity of these two suspected associations, a third analysis may be obtained with a map comprising about 60,000 biallelic markers. In some embodiments, one or more of the 653 biallelic markers obtained above are used in the ttϋrd association analysis. In the hypothetical example of Figure C, more markers lying around marker 17 exhibit a high degree of association with the detectable trai Conversely, no association is confirmed in the vicinity of marker 9. The genomic region surrounding marker 17 can thus be considered a candidate region for tho hypothetical trait of this simulation. The statistical power of LD mapping using a high density marker map is also reinforced by complementing the single point association analysis described above with a multi-marker association analysis, called haplotype analysis. When a chromosome carrying a disease allele is first introduced into a population as a result of either mutation or migration, the mutant allele necessarily resides on a chromosome havino a unique set of linked markers: the ancestral haplotype. A3 already mentioned, a haplotype association analysis allows the frequency and the type of the ancestral carrier haplotype to be defined. A haplotype analysis is performed by estimating the frequencies ol all possible haplotypes for a given set of biallelic markers in the T+ and T- populations, and comparing these frequencies by means of a chi square statistical test (one degree of freedom). Haplotype estimations are usually performed by applying the Expectation-Maximization (EM) algorithm (Excαffier L and Slatkin M, Mol. Biol. Evol. 12:921-927 (1995), the disclosure of which is incorporated herein by reference), using the EM-HAP10 program (Hawley ME, Pakstis AJ & Kidd KK, Am. J. Phys. Anthrapol. 18:104 (1994), the disclosure of which is incorporated herein by reference). The EM algorithm is used to estimate haplotype frequencies in the case when only genotype data from unrelated individuals are available. The EM algorithm is a generalized iterative maximum likelihood approach to estimation that is useful when data are ambiguous and/or incomplete. To improve the statistical power of the individual marker association analyses conducted as described above using maps of increasing marker densities, haplotype studies can be performed using groups of markers located in proximity to one another within regions of the genome. For example, using the methods described above in which the association of an individual marker with a detectable phenotype was analyzed using maps of 3,000 markers, 20,000 markers, and 60,000 markers, a series of haplotype studies can be performed using groups of contiguous markers from such maps or from maps having higher marker densities. In a preferred embodiment a series of successive haplotype studies including groups of markers spanning regions of more than 1 Mb may be performed. In some embodiments, the biallelic markers included in each of these groups may be located within a genomic egion spanning less than Ikb, from 1 to 5kb, from 5 to IQkb, from 10 to 25kb, from 25 to 50kb, from 50 to 150kb, from 150 to 250kb, from 250 to 500kb, from 5Q0kb to 1Mb, or more than 1 b. Preferably, the genomic regions containing the groups of biallelic markers used in the succβssivα haplotype analyses are overlapping. It will be appreciated that the groups of biallelic markers need not completely cover the genomic regions of the above-specified lengths but may instead be obtained from incomplete contigs having one or more gaps therein. As discussed in further detail below, biaϋβfic markers may be used in single point and haplotype association analyses regardless of the completeness of the corresponding physical contig harboring them. Without wishing to be limited to any particular numerical value, it is believed that those haplotypes displaying a coefficient of relative risk above 1, preferably about 5 or more, preferably of about 7 or more are indicative of a 'significant risk " for the individuals carrying the identified haplotype to develop the given trait However, it is difficult to evaluate accurately quantified boundaries for the so-called "significant risk". Indeed, and as it has been demonstrated previously, several traits observed in a given population are ultifactorial in that they are not only the result of a single genetic predisposition but also of other factors such as environmental factors. Thus, the evaluation of a significant risk must take these parameters into consideration in order to, in a certain manner, weigh the potential importance of external parameters in the development of a given trait, Thus, tho relative risk which constitutes a "significant risk" to develop a given trait is evaluated differently depending on the trait under consideration and the populations tested. Genome wide mapping using association studies with dense enough arrays of markers permit a case by-case best estimate cf p-value significance thresholds. Given a test population comprising two ethnically matched trait positive and trait negative groups of about 50 to about 500 individuals or more, conducting the above described association studies will allow a p-value "cut-off" to be established by, for example, analyzing significant numbers of allele frequency differences or, in some cases where appropriate, running computer simulations or control studies as described in Examples 11, 20, and 31. For B p-valua above the threshold, a corresponding association between the trait and a studied marker will be deemed not significant, while for a p-value below such a threshold, said association will be deemed significant If the p- value is significant, the genomic region arround the marker will be further scrutinized for a trait-causing gene. It is preferred that p-value significance thresholds be assessed for each case/control population comparison. Both the genetic distance between sampled population-'stratificatiαn'-and the dispersion due to random selection of samples may indeed influence the p-value significance thresholds. It will be appreciated that the above approaches may be conducted on any scale (i.e. over the whola genome, a set of chromosomes, a single chromosome, a particular subchromosomal region, or any other desired portion of tfiB genome). As mentioned above, once significance thresholds have been assessed, population sample sizes may be adapted as exemplified in Figure 3. Exa ple 12 below illustrates the increase in statistical power brought to an association study by a haplotype analysis. Example 12 Haplotype Analysis: Identification of biallelic markers delineating a nnnomic region associated with Alzheimer's Disease (AD) Λs shown in Table 3 within Example 10, at an average map density of one marker per 40 kb only one marker (99-365/344 ) out of five random biallelic markers from a ca. 200 kb genomic region around the Apo E gene showed a clear association to AD (delta allelic frequency in cases and controls - 18% ; p value - 6.9 E-10). The allelic frequencies of the other four random markers were not significantly different between ΛD cases and controls (p-values ≥ E-01 ). However, since linkage disequilibrium can usually be detected between markers located further apart than an average 40 kb as previously discussed, one should expect that, performing an association study with a local excerpt of a biallelic marker map covering ca. 200kb with an average inter-marker distance of ca. 40kb should allow the identification of more than one biallelic marker associated with AD. A haplotype analysis was thus performed using tho biallelic markers 99-344/439; 99-355/219; 99-359/308 ; 99-365/344 ; and 99-366/274 (of SEQ ID Nos: 301-305 and 307 311). In a first step, marker 99-365/344 that was already found associated with AD was not included in the haplotype study. Only biallelic markers 99-344/439 ; 99-355/219 ; 99-359/308 ; and 99-366/274. which did not show any significant association with AD when taken individually, were used. This first haplotype analysis measured frequencies of all possible two-, three-, or four-marker haplotypes in the ΛD case and control populations. As shown in Figure 7, there was one haplotype among all the potential different haplotypes based on the four individually non significant markers ("haplotype 8", TAGG comprising SEQ ID No. 305 which is the T allele of marker 99-366/274, SEQ ID No. 301 which is the A allele of marker 99-344/439, SEQ ID No. 303 which is the G allele of marker 99-359/308 and SEQ ID No. 302 which is the G allele of marker 99-355/219), that was present at statistically significant different frequencies in the AD case and control populations (Δ- 12% ; p value - 2.05 E-06). Moreover, a significant difference was already observed for a three-marker haplotype included in the above mentioned "haplotype 8" ("haplotype 7", TGG. Δ- 10% ; p value - 4.76 E-05). Haplotype 7 comprises SEO ID No. 305 which is the T allele of marker 99-366/274, SEQ ID No. 303 which is tho G allele of marker 99-359/308 and SEQ ID No. 302 which is the G allele of marker 99- 355/219). The haplotype association analysis thus clearly increased the statistical power of the individual marker association studies by more than four orders of magnitude when compared to single-marker analysis (from p valuos ≥ E- 01 for the individual markers - see Table 3 • to p valua ≤ 2 E 06 for the four-marker "haplotype 8"). The significance of the values obtained for this haplotype association analysis was evaluated by the following computer simulation. The genotype data from the AD cases and the unaffected controls were pooled and randomly allocated to two groups which contained the same number of individuals as the case/control groups used to produce the data summarized in Figure 7. A four-marker haplotype analysis (99-344/439 ; 99-355/219 ; 99-359/308 ; and 99- 366/274) was run on these artificial groups. This experiment was reiterated 100 times and tho results aro shown in Figure 8. No haplotype among those generated was found for which the p-value of the frequency difference between both populations was more significant than 1 E-05. In addition, only 4% of the generated haplotypes showed p-values lower than 1 E-04. Since both these p-value thresholds are less significant th3π the 2 E-06 p-voluβ showed by "haplotype 8", this haplotype can be considered significantly associated with AD. In a second step, marker 99-365/344 was included in the haplotypo analyzes. The frequency differences botwecn the affected and non affected populations was calculated for all two-, three-, four- or five-marker haplotypes involving markers: 99-344/439 ; 99-355/219 ; 99-359/308 ; 99-366/274; and 99-365/344. The most significant p- values obtained in each category of haplotype (involving two, three, four or five markers) were examined depending on which markers were involved or not within the haplotype. This showed that all haplotypes which included marker 99- 365/344 showed a significant association with AD (μ-values in the range of E 04 to E-11). An additional way of evaluating the significance of the values obtained in the haplotype association analysis was to perform a similar AD case-control study on biallelic markers generated from BACs containing inserts corresponding to genomic regions derived from chromosomes 13 or 21 and not known to be involved in Alzheimer's disease. Performing similar haplotype and individual association analyzes as those described above and in Example 10 did not generate any significant association results (all p-values for haplotype analyzes were less significant than E-03; all p-values for single marker association studies were less significant than E-02). The results described in Examples 10 and 12, generated from individual and haplotype studies using a biallelic marker set of an average density equal to ca. 40kb in the region of an Alzheimer's disease trait causing gene, indicate that all biallelic markers of sufficient informative content located within a ca. 200 kb genomic region around a TCA can potentially be succesfully used to localize a trait causing gene with the methods provided by the present invention. This conclusion is further supported by the results obtained through measuring the linkage disequilibrium between markers 99-365/344 or 99-359/308 and ApoE 4 Site A marker within Alzheimer's patients: as one could predict since LD is the supporting basis for association studies, LD between these pairs of markers was enhanced in the diseased population vs. the control population. In a similar way as the haplotype analysis enhanced the significance of the corresponding association studies. Once a given polymorphic site has been found and characterized as a biallelic marker according to the methods of the present invention, several methods can be used in order to determine the specific allele carried by an individual at the given polymorphic base. In some embodiments, genotyping will be applied to one or more of the markers of SEQ ID Nos: 301-305 and 307-311 or the sequences complementary thereto. In additional embodiments, genotyping will be applied to the markers of SEQ ID Nos. 306 and 312 as well as one or more of the markers of SEQ ID Nos. 301-305 and 307-311. In some embodiments, genotyping will be applied to one or more of the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto). The present invention further contemplates the genotyping of any biallelic marker within the provided maps, including those that are in linkage disequilibrium with the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51- 100 or the sequences complementary thereto) or the markers of SEQ ID Nos. 301-312 or the sequences complementary thereto. Most genotyping methods require the previous amplification of a DNA region carrying the polymoφhic site of interest. The identification of biallolic markers described previously, allows tha design of appropriate oligunuclcotides, which can be used as primers to amplify a DNA fragment containing the μolymoφhic site of interest and for the detection uf such polymorphisms. In particularly preferred embodiments, pairs of primers of SEQ ID Nos: 313-318 and 319-324 may bo used to generate amplicons harboring the markers of SEQ ID Nos: 301 -306/307-312 or the sequences complementary thereto. In further embodiments, pairs of amplification primers may be used to generate amplicons harboring the 653 markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto. In highly preferred embodiments, pairs of the amplification primers ol SEQ ID Nos: 101-150 and 151-200 may lie used to generate amplicons harboring the markers of SEQ ID Nos: 1-50 and 51 -100 or the sequences complementary thereto. It will be appreciated that amplification primers may he designed having any length suitable for their intended purpose, in particular arty length allowing their hybridization with a region of the DNA fragment to be amplified. It will be further appreciated that the hybridization site of said amplification primers may be located at any distance from the polymoφhic basa to be genotyped, provided said amplification primers allow the proper amplification of a DNA fragment carrying said polymoφhic site. The amplification primers may be oligonucleotides of 10, 15, 20 or more bases in length which enable the amplification of tha polymorphic site in the markers. In some embodiments, the amplification product produced using these primers may be at least 100 ba es in length (LB. on average 50 nucleotides on each side of the polymorphic base). In other embodiments, the amplification product produced using these primers may be at least 500 bases in length (i.e. on average 250 nucleotides on each side of the polymorphic base). In still further embodiments, the amplification product produced using these primers may be at least 1000 bases in length (i.e. on average 500 nucleotides on each side of the polymorphic base). The amplification of polymorphic fragments can be carried as described in Example 6 on DNA samples extracted as described in Example 5. As already mentioned, allele frequencies of biallelic markers tested in association studies (individual or haplotype) may be determined using microsequencing procedures. A first step in microsequencing procedures consists in designing microsequencing primers adapted to each biallelic marker to be genotyped. Microsequencing primers hybridize upstream of the polymorphic base to be genotyped. either with the coding or with the non-coding strand. Microsequencing primers may be oligonucleotides of 8, 10, 15, 20 or more bases in length. Preferably, the 3' end of the microsequencing primer is immediately upstream of the polymorphic base of the biallelic marker being genotyped, such that upon extension of the primer, the polymorphic base is the first base incorporated. Such microsequencing primers are included within the scope of the present invention. In preferred embodiments, the microsequencing primers are those indicated as features within tha sequence listings corresponding to markers of SEQ ID Nos: 325-330/331-336. In some embodiments, the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 end 51-100 or the sequences complementary thereto) aro genotyped using appropriate microsequencing oligonucleotides such as those of SEQ ID Nos. 201-250 or 251 -300. It will be appreciated that the biaflelic markers of the present invention may be genotyped using microsequencing primers having any desirable length, and hybridizing to any of the strands of the marker to bo tested, provided their design is suitable for their intended purpose. In some embodiments, the amplification primers or microsequencing primers may be labeled. For example, in somo embodiments, the amplification primers or microsequencing primers may be biotinylated. Typical microsequencing procedures that can be used in the context of the present invention are dascribed in Example 13 below. Example 13 Genotyping of biallelic markers usiπ microsequcncinκ procedures Several microsequencing protocols conducted in liquid phase are well known to those skilled in the art. A first possible detection analysis allowing the allele characterization of the microsequencing reaction products relies on detecting fluorescent ddNTP- extended microsequencing primers after gel electrophoresis. A first alternative to this approach consists in performing a liquid phase microsequencing reaction, the analysis of which may be carried out in solid phase. For example, the microsequencing reaction may be performed using 5'-biotinylated oligonucleotide primers and fluorescciπ-dideoxynuclβotides. The biotinylated oligonucleotide is annealed to the target nucleic acid sequence immediately adjacent to the polymoφhic nucleotide position of interest. It is then specifically extended at its 3'-eπd following a PCR cycle, wherein the labeled dideoxynucleotidβ analog complementary to the polymorphic base is incorporated. The biotinylated primer is then captured on a microtiter plate coated with streptavidiπ. The analysis is thus entirely carried out in a microtiter plate format The incorporated ddNTP is detected by a fluoresccin antibody • alkaline phosphatase conjugate. In practice this microsequencing analysis is performed as follows. 20 μ\ of the microsequencing reaction is added to 80 μ\ of capture buffer (SSC 2X. 2.5% PEG 80Q0, 0.25 M Tris pH7.5, 1.8% BSA, 0.05% Tween 20) and incubated for 20 minutes on a microtiter plate coated with streptavidiπ (Boehringer). The plate is rinsed once with washing buffer (0.1 M Tris pH 7.5, 0.1 M NaCI, 0.1% Tweβn 20). 100 μl of anti-fiuorescein antibody conjugated with phosphatase alkaline, diluted 1/5000 in washing buffer containing 1.8% BSA is added to the microtiter plate. The antibody is incubated on the microtiter plate for 20 minutes. After washing the microtiter plate four times, 100 μ\ of 4- ethylumbelliferyl phosphate (Sigma) diluted to 0.4 mg/ml in 0.1 M diethaπola iπe pH 9.6, 10mM MgCI 2 are added. The detection of the microsequencing reaction is carried out on a fluori eter (Dynatech) after 20 minutes of incubation. As another alternative, solid phase microsequencing reactions have been developed, for which either the oligonucleotide microsequencing primers or the PCR-amph ' fied products derived from the DNA fragment of interest are immobilized. For example, immobilization can be carried out via an interaction between biotinylated DNA and streptavidin-coated microtftratton wells or avidiπ coated polystyrene particles. As a further alternative, the PCR reaction generating the amplicons to be genotyped can be performed directly in solid phase conditions, following procedures such as those described in WO 96/13609, the disclosure of which is incorporated herein by reference. In such solid phase microsequencing reactions, incorporated ddNTPs can either be radiolabeled (see Syvaπcn. Clin. C im. Acta. 226:225-236 (1994), the disclosure of which is incorporated herein by reference) or linked to fluorescein (see Livak and Haincr, Hum. Mβtat. 3:379-385 (1994), the disclosure of which is incorporated heroin hy reference). The detection of radiolabeled ddNTPs can be achieved through scintillation-based techniques. The detection of fluorescein-linked ddNTPs can be based on the binding of antifluorcscβin antibody conjugated with alkaline phosphatase, followed by incubation with a chromogenic substrate (such as p-nitropheπyl phosphate). Other possible reporter-detection couples for use in the above microsequencing procedures include : ddNTP linked to dinitrophenyl (DNP) and aπti-DNP alkaline phosphatase conjugate (see Harju et al., Clin t7Λc?/r.39(πPt 11:2282-2287 (19931, incorporated herein by reference) biotinylated ddNTP and horseradish peroxidaso-coπjugated strcptavidin with o-phenylenediarnine as a substrate (sec WQ 92J15712, incorporated herein by reference). A diagnosis kit based on fluorescein-linked ddNTP with aπtifluorescein antibody conjugated with alkaline phosphatase has been commercialized under the name PRONTO by GamidaGen Ltd. As yet another alternative microsequencing procedure, Nyren et al. [Anal. Bioclicm. 208:171-175 (1993), the disclosure of which is incorporated herein by reference) have described a solid-phase DNA sequencing procedure that relies on the detection of DNA polymerase activity by an enzymatic luminomctric inorganic pyrophosphate detection assay (EUDA). In this procedure, the PCR-amplified products arc biotinylated and immobilized on beads. The microsequencing primer is annealed and four aliquots of this mixture are separately incubated with DNA polymerase and one of tha four different ddNTPs. After the reaction, the resulting fragments are washed and used as substrates in a primer extension reaction with all four dNTPs present. The progress of the DNA-directed polymerization reactions is monitored with the EUDA. Incorporation of a ddNTP in the first reaction prevents the formation of pyrophosphate during the subsequent dNTP reaction, in contrast, no ddNTP incorporation in the first reaction gives extensive pyrophosphate release during the dNTP reaction and this leads to generation of light throughout the ELIDA reactions. From the ELIDA results, the identity of the first base after the primer is easily deduced. It will be appreciated that several parameters of the above-described microsequencing procedures may be successfully modified by those skilled in the art without undue experimentation. In particular, high throughput improvements to these procedures may be elaborated, following principles such as those described further below. It will be further appreciated that any other genotyping procedure may be applied to the genotyping of biallelic markers. •51- Once the candidate region has been delineated using the high density biallelic marker map, 3 sequence analysis process will allow the detection of all genes located within said region, together with a potential functional characteπzatioπ of said ganes. The identified functional features may allow preferred trait causing candidates to be chosen from among the identified genes. More biallelic markers may then be generated within said candidate genes, and used to perlorm refined association studies that will support the identification of the trait causing gene. Sequence analysis processes are described in Example 14 below. Example 14: Sequence Analysis DNA sequences, such as BAC inserts, containing the region carrying the candidate gene associated with the detectable trait are sequenced and their sequence is analyzed using automated software winch eliminates repeat sequences while retaining potential gene sequences. The potential gene sequences are compared to numerous databases to identify putential exons using a set of scoring algorithms such as trained Hidden Markov Models, statistical analysis models (including promoter prediction tools) and the GRAIL neural network. Preferred databases for use in this analysis, the construction and use of which are further detailed in Example 22 below, include the following NetGeπe database: This proprietary database contains sequences ol 5' cDNA tags, obtained from a number of tissues and cells Currently more than 50,000 different 5" clones representing more than 50.000 different genes are included in NetGπne The sequences in the NetGene database correspond specifically to the 5' regions of transcripts (first exons) and therefore allow mapping of the beginning of genes within raw genomic sequences. NRPU (Npn Redundant Protein-Unique) database, NRPU is a non redundant merge of the publicly available NBRF/PIR, Genpept, 3iid SwissProt databases Homologies found with NRPU allow the identification of regions potentially coding for already known proteins or related to known proteins (translated exons). NREST (Non-Redundant EST database): NREST is a merge of the EST subsection of the publicly available GcnBank database. Homologies found with NREST allow the location of potentially transcribed regions (translated or non-translated exons). NRN (Non-Redundant Nuclpic acid database): NRN is a merge of GenBank, EMBL and their daily updates. Any sequence giving a positive hit with NRPU, NREST or an "excellent " score using GRAIL or/and other scoring algorithms is considered a potential functional region, and is then considered a candidate for genomic analysis. While this first screening allows the detection of the "strongest" exons, a semi-automatic scan is further applied to the remaining saquencos in the context of the sequence assembly. That is, the sequences neighboring a 5' site or an exon are submitted to another round of bioiπformatics analysis with modified parameters. In this way, new exon candidates ere generated for genomic analysis. Using the above procedures, genes associated with detectable traits may be identified. Examples 15-23 illustrate the application of the above methods using biallelic markers to identify a gene associated with a complex disease, prostate cancer, within a ca. 450 kb candidate region. Additunal details of the identification of the gene associated with prostate cancer are provided in the U.S. Patent Application entitled "Prnstatc Cancer Gene" (GENSET.018A, Serial No. 08/996,306), the disclosure of which is incorporated herein by reference. Use of Biallelic Markers to Identify a Gene Associated with Prostate Cancer Substantial amounts of LOII data supported the hypothesis that genus associated with distinct cancer types are located within a particular region of the human genome. More specifically, this region was likely to harbor a gene associated with prostate cancer. Association studies were performed as described below in order to identify this prostate cancer gene, A YAC contig containing the genomic region suspected of harboring a gene associated with prostate cancer was constructed as described in Example 15 below. Example 15 YAC Contig Construction in the Candidate Genomic Ref;ion First, a YAC contig which contains the candidate genomic region was constructed as follows. The CEPH- Geπethon YAC map for the entire human genome (Chumakov et al. (19951. supra) was used for detailed contig building in the genomic region containing genetic markers known to map in the candidate genomic region. Screening data available for several publicly available genetic markers were used to select a set of CEPH YACs localized within the candidate region. This set of YACs was tested by PCR with the above mentioned genetic markers as well as with other publicly available markers supposedly located within the candidate region. As a result of these studies, a YAC STS contig map was gonerated around genetic markers known to map in this genomic region. Two CEPH YACs were found to constitute a minimal tiling path in this region, with an estimated size of ca. 2 Megabases. During this mapping effort several publicly known STS markers were precisely located within the contig. Example 16 below describes the identification of sets of biallelic markers within the candidate genomic region. Example 16 BAC contiπ construction and Biallelic Markers isolation within the candidate chromosomal region. Next, a BAC contig covering the candidate genomic region was constructed as follows. BAC libraries were obtained as described in Woo et al., Nucleic Acids Res. 22:49224931 (1994), the disclosure of which is incorporated herein by reference. Briefly, tho two whole human genome BamHI and Hindlll libraries already described in Example 1 were constructed using the pBcloBAC11 vector (Kim et al. (1996), supra). Tho BAC libraries were then screened with all of the above mentioned STSs, following the procedure described in Example 2 above. The ordered BACs selected by STS screening and verified by FISH, were assembled into contigs and new markers were generated by partial sequencing of insert ends from some of them. These markers were used to fill the gaps in the contig of BAC clones covering the candidate chromosomal region having an estimated size of 2 megabases. Figure 9 illustrates a minimal array uf overlapping clones which was chosen for further studies, and the positions of tho publicly known STS markers along said contig. Selected BAC clones from the contig were subcloned and sequenced, essentially following the procedures described in Examples 3 and 4. Biallelic markers lying along the contig were identified fallowing the processes described in Examples 5 and 6. Figure 9 shows the locations of the biallelic markers along the BAC contig. This first set of markers corresponds tα a medium density map of the candidate locus, with an inter-marker distance averaging 5Qkb-150kb. A second set of biallelic markers was then generated as described above in order to provide a very high-density map of the region identified using the first set of markers which can be used to conduct association studies, as explained below. This very high density map has markers spaced on average every 2-50kb. The biallelic markers were then used in association studies. DNΛ samples were obtained from individuals suffering from prostate cancer and unaffected individuals as described in Example 17. Example 17 Collection of DNA Samples from Affected and Non-affected Individuals Prostate cancer patients were recruited according to clinical inclusion criteria based on pathological or radical prostatectomy records. Control cases included in this study were both ethnically- and age-matched to the affected cases; they were checked for both the absence of all clinical and biological criteria defining the presence or the risk of prostate cancer, and for the absence of related familial prostate cancer cases. Both affected and control individuals were all unrelated. The two following groups of independent individuals were used in the association studies. The first group, comprising individuals suffering from prostate cancer, contained 185 individuals. Of these 185 cases of prostate cancer, 47 cases were sporadic and 138 cases were familial. The control group contained 104 non-diseased individuals. Haplotype analysis was conducted using additional diseased (total samples: 281) and control samples (total samples: 130), from individuals recruited according to similar criteria. DNA was extracted from peripheral venous blood of all individuals as described in Example 5. The frequencies of the biallelic markers in each population were determined as described in Example 16. Example 18 Genotyping Affected and Control Individuals Genotyping was performed using the following microsequencing procedure. Amplification was performed on each DNA sample using primers designed as previously explained. The pairs of primers were used to generate amplicons harboring the biallelic markers 99-123, 4-2G, 4-14, 4-77, 99-217, 4-67, 99-213, 99- 221, 99-135, 99-1482, 4-73, and 4-65 using the protocols described in Example 6 above. Microsequencing primers were designed for each of the biallelic markers, as previously described. After purification of the amplification products, the microsequencing reaction mixture was prepared by adding, in a 2Q//I final volume: 10 pmol microsequencing oligonucleotide, 1 U Thennoscquenase (Amersham E79000G), 1.25 μ\ Thermosequenase buffer (260 mM Tris IICI pH 9.5, 65 M MgCI 2 ), and the two appropriate fluorescent ddNTPs (Perkin Elmer, Dye Terminator Set 401095) complementary to tho nucleotides at the polymorphic site of each biallelic marker tested, following the manufacturer's recommendations. After 4 minutes at 94°C, 20 PCR cycles of 15 sec at 55°C, 5 sec at 72°C, and 10 sec at 94°C were carried out in a Tetrad PTC-225 thermocyclcr (MJ Research). The unincorporated dye terminators were thon removed by ethanol precipitation. Samples were finally resuspended in formamide-EDTA loading buffer and heated for 2 min at 95°C before being loaded on a polyacrylamide sequencing gel. The data were collected by an ABI PRISM 377 DNA sequencer and processed using the GENESCAN software (Perkin Elmer). Following gel analysis, data were automatically processed with software that allows the determination of the alleles of biallelic markers present in each amplified fragment. The software evaluates such factors as whether the intensities of the signals resulting from the above microsequencing procedures are weak, normal or saturated, or whether the signals are ambiguous. In addition, the software identifies significant peaks (according to shape and height criteria). Among the significant peaks, peaks corresponding to the targeted site are identified based on their position. When two significant peaks are detected for the same position, each sample is categorized as homozygous or heterozygous based on the height ratio. Association analyzes were then performed using the biallelic markers as described below. Example 19 Association Analysis Association studies were run in two successive steps. In a first step, a rough localization of the candidate gene was achieved by determining the frequencies of the biallelic markers of Figure 9 in the affected and unaffected populations. The results of this rough localization are shown in Figure 10. This analysis indicated that a gene responsible for prostate cancer was located near the biallelic marker designated 4-67. In a second phase of the analysis, the position of the gene responsible for prostate cancer was further refined using the very high density set of markers including the 99-123, 4-26, 4-14, 4-77, 99-217, 4-67, 99-213, 99-221, 99-135, 99- 1482, -73, and 4-65 markers. As shown in Figure 11, the second phase of the analysis confirmed that the gene responsible for prostate cancer was near the biallelic marker designated 4-67, most probably within a ca. 150kb region comprising the marker. A haplotype analysis was also performed as described in Example 20. •55- Exa ple 20 Haplotype analysis The allelic frequencies of each of the alleles of biallelic markers 99-123, 4-26, 4-14, -77, 99-217, 4 67, 99- 213, 99-221, and 99-135 were determined in the affected and unaffected populations. Table 4 lists the internal identification numbers of the markers used in the haplotype analysis, the alleles of each marker, the most frequent allele in both unaffected individuals and individuals suffering from prostate cancer, the least frequent allele in both unaffected individuals and individuals suffering from prostate cancer, and the frequencies of the least frequent alleles in each population. Table 4 Frequency of least frequent allυle * * Markers Polymorphic bβsβ * Cases Controls 99-123 C/T 0.35 0.3 4-26 A/G 0.39 0.45 4-14 C/T 0.35 0.41 4-77 C/G 0.33 0.24 99-217 C/T 0.31 0.23 4-67 C/T 0.26 0.16 99-213 T/C 0.45 0.38 99-221 C/A 0.43 0.43 99-135 A/G 0.25 0.3 most frequent allele/lcast frequent allele standard deviations • 0.023 to 0.031 for controls - 0.018 to 0.021 for cases Among all the theoretical potential different haplotypes based on 2 to 9 markers, 11 haplotypes showing a strong association with prostate cancer were selected. The results of these haplotype analyzes are shown in Figure 12. Figures 11, and 12 aggregate association analysis results with sequencing results - generated following the procedures further described in Example 21 - which permitted the physical order and/or the distance between markers to be estimated. The significance of the values obtained in Figure 12 are underscored by the following results of computer simulations. For the computer simulations, the data from the affected individuals and the unaffected controls were pooled and randomly allocated to two groups which contained the same number of individuals as the affected and unaffected groups used to compile the data summarized in Figure 12. A haplotype analysis was run on these artificial groups for the six markers included in haplotype 5 of Figure 12. This experiment was reiterated 100 times and the results are shown in Figure 13. Among 100 iterations, only 5% of the obtained haplotypes are present with a p-value less significant than E-04 as compared tα the p-value of 9 E -07 for haplotype 5 of Figure 12. Furthermore, for haplotype 5 of Figure 12, only 6% of the obtained haplotypes have a significance level bolow 5 £ -03, while none of them show a significance level below 5 E -03. Thus, using the data of Figure 13 and evaluating the associations for single marker alleles or for haplotypes will permit estimation of the risk a corresponding carrier has to develop prostate cancer. It will be appreciated that significance thresholds of relative risks will be more finely assessed according to the population tested. Diagnostic techniques for determining an individual's risk of developing prostate cancer may be implemented as described below for the markers in the maps of the present invention, including the 99-123, 4-26, 4-14, 4-77, 99-217, 4-87, 99-213, 99-221. and 99-135 markers. The above haplotype analysis indicated that 171 kb of genomic DNA between biallelic markers 4-14 and 99- 221 totally or partially contains a gene responsible for prostate cancor. Therefore, the protein coding sequences lying within this region were characterized to locate the gene associated with prostate cancer. This analysis, described in further detail below, revealed a single protein coding sequence in the 171 kb genomic region, which was designated as the PG1 gene. Example 21 Identification of the Genomic Sequence in the Candidate Region Template DNA for sequencing the PGl gene was obtained as follows. BACs E and F from Fig. 9 were subcloned as previously described. Plasmid inserts were first amplified by PCR on PE 9600 theπnocyders (Perkin-Elmer), using appropriate primers, AmpliTaqGold (Perkin-Elmer), dNTPs (Boehringer), buffer and cycling conditions as recommended by the Perkin-Elmer Coφoratioπ. PCR products were then sequenced using automatic ABI Prism 377 sequencers (Perkin Elmer, Applied Biosystems Division, Foster City, CΛ). Sequencing reactions were performed using PE 9600 thermocyclcrs (Perkin Elmer) with standard dye-primer chemistry and Ther oSequenase (Amβrsham Life Science). Ttie primers were labeled with the JOE, FΛM, ROX and TAMRA dyes. The dNTPs and ddNTPs usod in the sequencing reactions were purchased from Boehringer. Sequencing buffer, reagent rpOnceπtretioπs and cycling conditions were as recommended by Λmβrsham. Following the sequencing reaction, the samples were precipitated with EtOH, resuspended in formamide loading buffer, and loaded on a standard 4% acrylamidβ geL Electrophoresis was performed for 15 hours at 3000V on an ABI 377 sequencer, and the sequence data were collected and analyzed using the ABI Prism DNA Sequencing Analysis Software, version 2.1.2, The sequence data obtained as described above were transferred to a proprietary database, whore quality control and validation steps were performed. A proprietary base-caller flagged suspect peaks, taking into account the shapa of the peaks, the inter-peak resolution, and the noise level. The proprietary base-caller also performed an automatic trimming. Any stretch of 25 or fewer bases having more than 4 suspect peaks was considered unreliable and was discarded. The sequence fragments from BAC subclones isolated as described above were assembled using Gap4 software from R. Staden (Bonfield et al. 1995). This software allows the reconstruction oi a single sequence from sequence fragments. The sequence deduced from the alignment of different fragments is called the consensus sequence. Directed sequencing techniques (primer walking) were used to complete sequences and link contigs. Potentiaf functional sequences were then identified as described in Example 22. Example 22 Identification of Functional Sequences Potential exons in BAC-derivcd human genomic sequences were located by ho ulogy searches on protein, nucleic acid and EST (Expressed Sequence Tags) public databases. Main public databases were locally reconstructed as mentioned in Example 14. The protein database, NRPU (Non redundant Protein Unique) is formed by u non-redundant fusion of the Genpept (Benson et al., Nucleic Acids Res. 24:1-5 (1996), the disclosure of which is incorporated herein by rclcrencc), Swissprot (Bairoch, A. and Apweiler, R, Nuddc Acids Res. 24:21-25 (1996), the disclosure of which is incorporated herein by reference) and PIR/NBRF (George et al., Nuclek Acids Res. 24:17-20 (1996), the disclosure of which is incorporated herein by reference) databases. Redundant data were eliminated by using the NRDB software (Benson et al. (1996), supra) and internal repeats were masked with the XNU software (Benson et al., supra). Homologies found using the NRPU database allowed the identification of sequences corresponding to potential coding exons related to known proteins. The EST local database is composed by the gbest section (1-9) of GenBaπk (Benson et al. (1996), supra), and thus contains all publicly available transcript fragments. Homologies found with this database allowed the localization of potentially transcribed regions. The local nucleic acid database contained all sections of GenBank and EMBL (Rodriguez-Tome et at., Nucleic Acids Res. 24:6-12 (1996), the disclosure of which is hcoφorated herein by reference) except the EST sections. Redundant data were eliminated as previously described. Similarity searches in protein or nucleic acid databases were performed using the BLAST software (Altschul ct al., J. Mol. Biol. 215:403410 (1990), the disclosure of which is incorporated herein by reference). Alignments were refined using the Fastα software, and multiple alignments used Clustal W. Homology thresholds were adjusted for each analysis based on the length and the complexity of the tested region, as well as on the size of the reference database. Potential exon sequences identified as above were used as probes to screen cDNA libraries. Extremities of positive clones were sequenced and the sequence stretches were positioned on the genomic sequence determined above. Primers were then designed using the results from these alignments in order to enable the cloning of cDNAs derived from the gene associated with prostate cancer that was identified using the above procedures. The obtained cDNA molecules were then sequenced and results of Northern blot analysis of prostate mRNAs supported the existence of a major cDNA having a 5-6kb length. The structure of the gene associated with prostate cancer was evaluated as described in Example 23. Example 23 Analysis of Gene Structure The intron/exon structure of the gene was finally completely deduced by aligning the mRNA sequence from the cDNA obtained as described above and the genomic DNA sequence obtained as described above. This alignment permitted the determination of the positions of the introns and exons, the positions of the start and end nucleotides defining each of the at least 8 exons, the locations and phases of the 5' and 3' splice sites, the position of the stop codon, and the position of the polyadenylation site to be determined in the genomic sequence. This analysis also yielded the positions of tha coding region in the mRNA, and the locations of the polyadenylation signal and polyA stretch in the mRNA. The gene identified as described above comprises at least 8 exons and spans more than 52kb. A G/C rich putative promoter region was identified upstream of the coding sequence. A CCAAT in the putative promoter was also idontifiod. The promoter region was idontifiod os described in Prβstridge, D.S., Predicting Pol II Promoter Sequences Using Transcription Factor Binding Sites, J. Mol. Biol. 249:923-932 (1995), the disclosure uf which is incorporated herein by reference. Additional analysis using conventional techniques, such as a 5'RACE reaction using the Marathon-Ready human prostate cDNA kit from Clontech (Catalog. No. PT1156-1), may be performed to confirm that tha 5' of tho cDNA obtained above is the authentic 5' end in the mRNA. Alternatively, the 5'scquence of the transcript can be determined by conducting a PCR amplification with a series of primers extending from the 5'eπd of the identified coding region. The above methods were also used to identify biallelic markers in a gene which was an attractive candidate for a gene associated with asthma. Examples 24-31 show how the use of methods of the present invention allowed this gene to be identified as a gene responsible, at least partially, for asthma in the studied populations. Additional details of the identification of the gene associated with asthma are provided in U.S. Provisional Application Serial Nos. 60/081,893 (Gensβt.026PR) and U.S. Provisional Patent Application Genset.026PR2, the disclosures of which are incorporated herein by reference. Example 24 Detection of hinllelic markers in the candidate oene: DNA extraction Donors were unrelated and healthy. They presented a sufficient diversity for being representative of a French heterogeneous population. The DNA from 100 individuals was extracted and tested for the detection of the biallelic markers. 30 m! of peripheral venous blood were taken from each donor in the presence of EDTA. Cells (pellet) were collected after centrifugation for 10 minutes at 2000 φ . Red cells were lysed by a lysis solution (50 ml final volume : 10 mM Tris pH7.6; 5 mM MgCI2; 10 M NaCD. The solution was centrifuged (10 minutes, 2000 rpm) as many times as necessary to eliminate the residual red cells present in the supernatant, after rβsuspension of the pellet in the lysis solution. Tha pellet of white cells was lysad overnight at 42" C with 3.7 ml of lysis solution composed of: - 3 ml TE 10-2 (Tris-HCl 10 mM, EDTA 2 mM) / NaCI 0.4 M • 200 μ\ SDS 10% • 500 /i K-proteinase (2 mg K-proteinase " m TE 10-2 / NaCI 0.4 M). For the extraction of proteins, 1 ml saturated NaCI (6M) (113.5 v/v) was added. After vigorous agitation, the solution was centrifuged for 20 minutes at 10000 rpm. For the precipitation of DNA, 2 to 3 volumes of 100% ethanol were added to the previous supernatant, and the solution was centrifuged for 30 minutes at 2000 rpm. The DNA solution was rinsed three times with 70% ethanol to eliminate salts, and centrifuged for 20 minutes at 2000 rpm, The pellet was dried at 37°C, and resuspended in 1 ml TE 10-1 or 1 ml water. The DNA concentration was evaluated by measuring the OD at 260 nm (1 unit OD - 50 //g/ml DNA). To determine the presence of proteins in the DNΛ solution, the DD 260 / OD 280 ratio was determined. Only DNΛ preparations having a OD 260 / OD 280 ratio between 1.8 and 2 were used in the subsequent examples doscribcd below. Tho pool was constituted by mixing equivalent quantities of DNA from each individual. Example 25 Detection of the hiallelir, markers: amplification of πcnomic DNA by PCR The amplification of specific genomic sequences of the DNA samples of Example 24 was carried out on the pool of DNΛ obtained previously. In addition, 50 individual samples were similarly amplified. PCR assays were performed using the following protocol: Final volume 25 μ\ MgCI2 2 mM dNTP (each) 200 zzM primer (each) 2.9 ng/μl Ampli Taq Gold DNA pαlymarase 0.05 unit//; I PCR buffer (10x - 0.1 M TrisHCI pH8.3 0.5M KCI) 1x Pairs of first primers were designed to amplify the promoter region, exons, and 3' end of the candidate asthma- associated gene using the sequence information of the candidate gene and the OSP software (Hillior 8ι Green, 1991). These first primers were about 20 nucleotides in length and contained a common oligonucleotide tail upstream of the specific bases targeted for amplification which was useful for sequencing. The synthesis of these primørs was performed following the phosphoramidite method, on a GENSET UFPS 24.1 synthesizer. DNA amplification was performed on a Genius II thermocyclor. After heating at 94°C for 10 min, 40 cycles were performed. Each cycle comprised: 30 sec at 94°C, 55°C for 1 min, and 30 sec at 72° C. For final elongation, 7 min at 72°C ended the amplification. The quantities of the amplification products obtained were determined on 96-well microtiter plates, using a fluorometer and Picogrβen as intβrcalant agent (Molecular Probes). Example 26 Detection of the biallelic markers: sequencing of amplified genomic DNA and identification of polymorphisms The sequencing of the amplified DNA obtained in Example 25 was carried out on ABI 377 sequencers. The sequences of the amplification products were determined using automated dideoxy terminator sequencing reactions with a dye terminator cycle sequencing protocol. The products of the sequencing reactions were run on sequencing gels and the sequences were analyzed as formerly described. The sequence data were further evaluated using the above mentioned polymorphism analysis software designed to detect the presence of biallelic markers among the pooled amplified fragments. The polymorphism search was based on the presence of superimposed peaks in the electrophoresis pattern resulting from diffcrunt bases occurring at the same position as described previously. Six fragments of amplification were analyzed. In these segments, 6 biallolic markers were detected. The localization of the biallelic markers, the polymorphic bases of each allele, and the frequencies of the most frequent alleles was as shown in Table 5. Tnhlo 5 Amplicoπ MarkβrNa e Origin of DNA Localization In Polymorphism Frequency gene 1 204/326 Intl. Promoter A/G 96.2 (G) 2 32/357 Pool Intron 1 A/C 67J (C) 3 33/175 Ind. Exon 2 C/T 97.3 (C) 3 33/234 Pool Intron 2 A/C 56.7 (C) 3 33/327 ind. Intron 2 C/T 75.3 (T) 5 35/358 Pool Intron 4 C/G G7.9 |G) 5 35/390 Ind. Intron 4 C/T 82 (C) 6 36/164 Ind. Exon 5 A/G 99.5 (G) Allelic frequencies were determined in a population of random blood donors from French Caucasian origin. Their wide range is due to the fact that besides screening a pool of 100 individuals to generate biallolic markers as described above, polymorphism searches were also conducted in an individual testing format for 50 samples. This strategy was chosen here to provide a potential shortcut towards the identification of putative causal mutations in the association studies using them. As the 36/164 biallelic marker was found in only one individual, this marker was not considered in the association studies. Tha fourth fragment of amplification carrying exon 3 (not shown in the Table) wa3 not polymorphic in the tested samples (1 pool + 50 individuals). Example 27 Validation of the polymorphisms throuπh microsEπueπciππ The biallelic markers identified in Example 26 were further confirmed and their respective frequencies were determined through microsequencing. Microsequencing was carried out for each individual DNΛ sample described in Example 24. Amplification from gunoinic DNA of individuals was performed by PCR as described above fin the detection of the biallelic markers with the same set of PCR primers described above. The preferred primers used in microsequencing had about 19 nuclootidβs in length and hybridized just upstream of the considered polymorphic base. Five primers hybridized with the nαπ-coding strand of the gene. For the biallelic markers 204/326, 35/358 and 36/164. primers hybridized with tho coding strand of the gene. The microsequencing reaction was performed as described in Example 18. Example 28 Association study between asthma and the biallelic markers of the candidate πenc: collection of DNΛ samples from affected anil nππ-πflected individuals The asthmatic population used to perform association studies in order to establish whether the candidate gene was an asthma-causing gene consisted of 298 individuals. More than 90 % of these 298 asthmatic individuals had a Caucasian ethnic background. The control population consistod of 373 unaffected individuals, among which 279 French (at least 70 % were of Caucasian origin) and 94 American (at least 90 % wore of Caucasian origin). DNA samples were obtained from asthmatic and non-asthmatic individuals as described above. Example 29 Association study between asthma and the biallelic markers of the candidate gene: nβnotypinπ of af ferried anil introl individuals The general strategy to perform the association studies was to individually scan the DNA samples from all individuals in each of the populations described above in order to establish the allele frequencies of the above described biallelic markers in each of these populations. Allelic frequencies of the above-described biallelic markers in each population were determined by performing microsequencing reactions on amplified fragments obtained by genomic PCR performed on tho DNA samples from each individual. Genomic PCR and microsequencing were performed as detailed above in Examples 25 and 27 using the describod amplification and microsequencing primers. Example 30 Association study between asthma and the biallelic markers of the candidate πene Tabla 6 shows the results of the association study between five biallelic markers in the candidate gene and asthma. •62- Table 6 Allelic frequencies (%) Markers Asthmatics Controls Frequency diff. P value 298 individuals 373 individuals 32/357 Λ 38.6 A 2D.B 8.8 7.34x10 "4 33/234 A 49 A 44.3 4.7 8,86x10 2 33/327 T 78.5 T 74.6 3.9 1.0x10 " ' 35/358 G 72.3 G 66.9 5.4 3.59x1 ϋ "2 35/390 T 30.4 20.3 10.1 2.33x10 '5 As shown in Table 6, markers 32/357 and 35/390 presented a strong association with asthma, this association being highly significant ( pvalue - 7.34x104 for marker 32/357 and 2.33x10 5 for marker 35 390). Three markers showed moderate association when tested independently, namely 33/234, 33/327, 35/358. It is worth mentioning that allelic frequencies for each of the biallelic markers of Table 6 ware separately measured within the French control population (279 individuals) and the Ainεncaπ cuπtrul population (94 individuals). The differences in allele frequencies botween the two populations were between 1 % and 7%, with p-values above 10 '. These data confirmed that the combined French/American control population (373 individuals) was homogeneous enough to be used as a control population for the present association study. Example 31 Association Studies: Haπlotypπ frequency analysis As already shown, one way of increasing the statistical power of individual markers, is by performing haplotype association analysis. A haplotype analysis for association of markers in the candidate gone and asthma was performed by estimating the frequencies of all possible haplotypes for biallolic markers 32/357, 33/234. 33/327, 35/358 and 35/390 in the asthmatic and control populations described in Example 30 (Table 6), and comparing tfioso frequencies by means of a chi squaro statistical test (one degree of freedom). Haplotype estimations were performed by applying the Expectatioπ-Maxi izatioπ (EM) algorithm (Excoffier L & Slatkin M, 1995, Mol.Biol.Evol. 12 :921-927), using the EM- HAPLO program (Hawley ME, Pakstis AJ & Kidd KK, 1 94, Am.J.Phys.Anthropol. 18 : 104). The results of such haplotype analysis are shown in Table 7. Table 7 llaμlutype frequencies Markers 32(357 33/234 33/327 35/358 351391) Astlim. Controls Dddt ratio P value Froquoney drtf. 8.6 4.7 3.9 0.4 10.1 P value 7.3 xHr* 8.86X1D '2 1.0x10 ' 3.53x10 3 2.33x10 5 llaplαtypβ 1 A T 0.2 0.11 2.02 8.47x10 5 Itaplotypα 2 A T G 0.27 0.18 I.Gfi 2.81 ι10 '( Haplotype 3 A A T G T 0.18 0.09 2.22 3.'J5x 1 ϋ 5 Λ two-marker haplotype covering markers 32/357 and 35/390 (haplotype 1, ΛT alleles respectively) presented a p value of 8.47x10-6, an odds ratio of 102 and haplotype frequencies of 0.2 for asthmatic and 0.11 for cuntrul populations respectively. A three-marker haplotype covering markers 33/234, 33/327 and 35/358 (haplotype 2, ΛTG alleles respoctivoly) presented a p value of 2.81x104. an odds ratio of 1.68 and haplotype fiequeπcics of 0.27 for asthmatic and 0.10 (or control populations respectively. Λ five-marker haplotype covering markers 32/357, 33/234, 33/327, 35/358 and 35/390 (haplotype 3, AATGT alleles respectively) presented α p value of 3.95x10-5, an odds ratio of 122 and haplotype frequencies of 0.18 for asthmatic and 0.09 for control populations respectively. Haplotype association analysis thus increased tho statistical power of the individual marker association studies when compared to single-marker analysis (from p values between 10 '1 and 2X10 "5 for the individual markers to p values between 3X1 Q 4 and 8X10 '6 for the three-marker haplotype, haplotype 2). The significance αf the values obtained for the haplotype association analysis was evaluated by the following computer simulation test. The genotype data from tha asthmatic and control individuals were pooled and randomly allocated to two groups which contained the same number of individuals as the trait positive and trait negative groups used to produce the data summarized in Table 7. A haplotype analysis was then run on these artificial groups for the three haplotypes presented in Table 7. This experiment was reiterated 1000 times and the results are shown in Tablo 8. •64- Table S Permutation Test Haplotype Chi Square Average Chi-Squaro Maximal Chi-Squaro P value Haplotype 1 (A-TJ 19.70 1.2 11.6 1.0x10 ^ Haplotype Z ( ATG ) 13.49 1.2 10.5 1.0x10 ' Haplotype 3 (AATGT) 16.66 1.2 9.3 1.0x10 ' The results in Table 8 show that among 1000 iterations only 1% 0 of the obtained haplotypes has a pvoluc comparable to the one obtained in Tablo 7. These results clearly validate the statistical significance of tho haplotypes obtained (haplotypes 1, 2 anil 3, Table 7). While Examples 15-31 illustrate the use of the maps and markers of the present invention for identifying a nes gene associated with a complex disease whhin a 2Mb genomic region for establishing that a candidate gene is, at least partially, responsible for a disease, the maps and markers of the present invention may also be used to identify one or more biallelic markers or one or more genes associated with other detectable phenotypes, including drug response, drug toxicity, or drug efficacy. The biallelic markers used in such drug responso analyses or shown, using the methods of the present invention to be associated with such traits, may lie within or near genes responsible for or partly responsible for a particular disease, for example a disease against which the drug is meant to act. or may lie within genomic regions which are not responsible for or partly responsible for a disease. For example, the genomic region harboring markers associated with 3 particular drug response may carry a drug metabolism gene, or a gene encoding a protein with a role in the drug response mechanism. Thus, biallelic markers within or near genes known to be involved in drug response. toxicity, or efficacy Dr genes suspected of being involved in drug response, toxicity, or efficacy may be used to identify individuals likely to respond positively or negatively to drug treatment. In the context of the present invention, a "positive response " to a medicament can be defined as comprising a reduction of the symptoms related to the disease or condition to be treated. In the context of the present invention, a "negative response' to a medicament can be defined as comprising either a lack of positive response to the medicament which does not lead to a symptom reduction or to a side-effect observed following administration of the medicament. Drug efficacy, response and tolerance/toxicitγ can be considered as multifactorial traits involving a genetic component in the same way as complex diseases such as Alzheimer's disease, prostate cancer, hypertension or diabetes. As such, the identification of genes involved in drug efficacy and toxicity could be achieved following a positional cloning approach, e.g. performing linkage analysis within families in order to obtain the subchromosomal location of the gene(s). However, this type of analysis is actually impractical in the case of drug responsiveness, due to the lack of availability of familial cases. In fact, tha likelihood of having more than one individual in a particular family being exposed to the same drug at the same time is very low. Therefore, drug efficacy and toxicity can only be analyzed as sporadic traits. In order to conduct association studies to analyze the individual response tu π given drug in groups πf patients affected with a disease, up to four groups are screened to determine their patterns of biallolic markers usiππ the techniquBS described above. The four groups arc: ■ Non-diseasod or random controls, • Diseased patients/drug respnnders, - Diseased patients/drug non-rospoπders, ■ Diseased patients/drug side effects, In preferred embodiments, the above mentioned groups are recruited according to phenotypiπg criteria having the characteristics described above, so that the phenotypes defining the different groups are non-ovorlapping, preferably extreme phenotypes. In highly preferred embodiments, such phenotyping criteria havo the bimodal distribution doscribcd πliuve. The final number and composition of the groups for each drug association study is adapted to the distribution of the above described phenotypes within the studied population. After selecting a suitable population, association and haplotype analyses may be performed as described herein to identify one or more biallelic markers associated with drug response, preferably drug toxicity or drug efficacy. The identification of such one or more biallelic markers allows one to conduct diagnostic tests to determine whether the administration of a drug to an individual will result in drug response, preferably drug toxicity, or diug efficacy. Tho methods described above for identifying a gene associated with prostate cancer and biallelic markers indicative of a risk of suffering from asthma may bo utilized to identify genes associated with other detectable phenotypes. In particular, the above methods may be used with any marker or combination of maikers included in the maps of the present invention, including the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto), the PG1 markers, the asthma-associated markers, and tho Apo E markers of SEQ ID Nos. 301-305/307-311 or the sequences complementary thereto. As described above, the general strategy to perform the association studies using the maps and markers of the present invention is to scan two groups of individuals (trait positive individuals and trait negative controls) characterized by a well defined phonotypa in order to measure the allele frequencies of the biallelic markers in each of these groups, Preferably, the froquencios of markers with inter-marker spacing of about 150 kb are determined in each groups. Mora preferably, the frequencies of markers with inter-marker spacing of about 75 kb are determined in each group. Even more preferably, markers with inter-marker spacing of about 50 kb, about 37.5kb, about 30kb. or about 25 kb will be tested in each population. For genome-wide studies, it will he preferred to measure the frequencies of about 20,000, or about 40,000 biallelic markers in each group. In a highly preferred embodiment, the frequencies of about 60.00D, about 80,000, about 100,000, or about 120,000 biallelic markers are determined in each group. In some embodiments, haolotype analyses may be run usiπg groups of markers located within regions spanning less than Ikb, from 1 to 5kb, from 5 to IQkb, from 10 to 25kb, from 25 to 50kb, from 50 to 150kb, from 150 to 250kb, from 250 to 500kb, from 500kb to 1Mb, or more than 1 Mb. Allele frequency can be measured using microsequencing techniques described herein; preferred high throughput icrosoquoncing procedures are further exemplified below; it will be further appreciated that any othor largo scale genotyping method suitable with the intended purpose coπtβmplatod herein may also be used. In some embodiments of the present invention a computer-based system may support the on-line coordination between the identification of biallelic markers arid the corresponding analysis of their frequency in tho different groups. It will be appreciated that it is not nocessary tu use a full high density biallelic marker map in order lo start a genome-wide association study. It is sufficient to generate and use a first set of about 20,000 markers (one marker per BAC, average inter-marker spacing of about 150kb). Maps having higher densities of biallolic markers (two or moru markers per BΛC, average inter-markβr spacing of about 75kb or less) may then be generated by starting first on those BACs for which a candidate association has been established at t e first step. In cases when one or mαie candidate regions have previously been dolinoated, such as cases where a particular gene or genomic region is suspected of being associated with a trait, local excerpts of biallelic marker maps having densities above one marker per 150kb may be exploited using BΛCs harboring said genomic icgiαπs, αr genes, or portions thereof. In these cases also, successive association studies may be performed using sets of biallelic markers showing increasing densities, preferably from about one overy 150 kb to about one every 75kb; more preferably, sets of markers with inter-marker spacing below about 50kb, below about 37.5kb, below about 30kb. most proforably below about 25 kb, will be used. Haplotype analyses may also be conducted using groups of biallolic markers within the candidate region. The biallolic markors included in oach of these groups may be located within a genomic rogion spanning loss than I b, from 1 to 5kb, from 5 to lOkb, from 10 to 25kb, from 25 to 50kb, from 50 to 15ϋkb, from 150 to 250kb, from 250 to 500kb, from 500kb tα 1Mb, or more than 1 b. It will be appreciated that the ordered DNA fragments containing these groups rjf biallelic markers need not completely cover the genomic regions of thoso lengths but may instead be incomplete contigs having one or more gaps therein. As discussed in further detail below, biallelic markers may be used in association studies and haplotype analyses regardless of the completeness of the corresponding physical contig harboring them, provided linkage disequilibrium between the markers can be assessed. As described above, if a positive association with a trait, such as a disease, or a drug efficacy and/or toxicity, is identified using the biallelic markers and maps of the present invention, the maps will provide not only the confirmation of the association, but also a shortcut towards the identification of the gene involved in the trait under study. As described above, since the markers showing positive association to the trait arc in linkage disequilibrium with the trait loci, the causal gene will be physically located in the vicinity of these markers. Regions idontifiod through association studies using high density maps will on average have a 20 • 40 times shorter length than those identified by linkage analysis (2 to 20 Mb). As described above, once a positive association is confirmed with the high density biallelic marker maps of the present invention, BACs from which the ast highly associated markers were derived are completely seαuenced and the utatioπs in tho causal gene are searched by applying genomic analysis tools. As described above, once a region harboring a gene associated with a detectable trait has been sequenced and analyzed, the candidate functional regions (e.g. exons and splice sites, promoters and other regulatory regions) are scanned for mutations by comparing the sequences of a solected number of controls and cases, using adequate software. In some embodiments, trait positive samples boing compared to identify causal mutations arc selεctod among those carrying the ancestral haplotype; in these emhodimonts, control samplos are chosen from individuals not carrying said ancestral haplotype. In further embodiments, trait positive samples being compared to identify causal imitations are selected among those showing haplotypes that are as close as possible to tho ancestral haplotype; in these embodiments, control samples are chosen from individuals not carrying any of the haplotypes selected for the case population, The mutation detection procedure is essentially similar to that used for biallelic site identification. A pair of ohgonucleotide primers are designed in order to amplify the sequences to be tested. In preferred embodiments, priority is given to the testing of functional sequences; in such embodiments, sequences covering every βxon/promαtur predicted region, preferably including potential splice sites, are determined and compared between the T + and T- populations Amplification is carried out on DNΛ samples from T+ and T- individuals using the polymerase chain reaction undor the above described conditions. To be sequenced, amplification products from genomic PCR may be subjected to automated dideoxy terminator sequencing reactions and βlectrophoresed on ΛBI 377 sequencers. Following gel image analysis and DNA sequence extraction, ABI sequence data are automatically analyzed tα detect the presence of sequence variations among T+ and T- individuals. Sequences are preferably verified by comparing the sequences of both DNA strands of each individual. It is preferred that candidate polymorphisms be then verified by screening a larger population of cases and controls by means of any genotyping procedure such as those described herein, preferably using a microsequencing technique in an individual test format. Polymorphisms are considered as candidate mutations when present in cases and controls at frequencies compatible with the expected association results, The maps and biallelic markers of the present invention may also be used to identify patterns ol biallelic markers associated with detectable traits resulting from polygβnic interactions. The analysis of genetic interaction between alleles at unlinked loci requires individual genotyping using the techniques described herein. The analysis of allelic interaction among a selected set of biallelic markers with appropπate p-values can be considered as a haplotype analysis, similar to those described in further details within the present invention. Use of Biallelic Markers to Identify Individuals Likely to Exhibit a Detectable Trait Associated with a Particular Allele of a Known Gone In addition to their utility in searches for genes associated with detectable traits on a genome-wide, chromosome wide, or subchromosomal level, the maps and biallelic markers of the present invention may be used in more targeted approaches for identifying individuals ϋkely tα exhibit a particular detectable trait or individuals who exhibit a particular detectable trait as a consequence of possessing a particular allele of a gene associated with the detectable trait. For 66 example, the biallelic markers and maps of the present invention may be used to identify individuals who carry an allele of a known gene that is suspected of being assoαated with a particular detectable trait, In particular, the target genes may bθ genes having alleles which predispose an individual to suffer from a specific disease state. In other cases, the target gones may be genes having alleles that predispose an individual to exhibit a desired or undesired response to a drug or other pharmaceutical composition, a food, or any administorcd compound. The known gene may encode any of a variety of typos of biomolecules. For example, the known gonos targetud ui such analyzes may bo genes known to be involved in a paitn.ular step in a motaholic pathway in which disruptions may cause a detectable traiL Alternatively, the target genes may bϋ uenes encoding receptors or ligands which bind to rθcβptors in winch disruptions may cause a detectable trait, genes encoding transporters, genes encoding proteins with signaling activities, genes encoding proteins involved in the immune respiiiise, genes encoding proteins involved in hematopoesis, or genes encoding proteins involved in wound healing. It will be appreciated that the target genes are not limited to those specifically enumoratcd above, but may be any gone known to be or suspected of being associated with a detectable trait. As previously mentioned, the maps and markers of the present invention may be used tu identify genes associated with drug response. Accordingly, the presont invention compπses a method of using a drug comprising obtaining a nucleic acid sample from an individual, determining the identity of the polymorphic base of one or more biallelic markers obtained by tho methods doscribcd above which is or are associated with a positive response to treatment with the drug or one or more biallelic markers obtained by the methods described above which is or are associated with a negative response to treatment ith the drug, and administering the drug to the individual if the nucleic acid sample contains one or more alloles of biallelic markers associated with a positive response to treatment with the drug or if said nucleic acid sample lacks one or more alleles of biallelic markers associated with a negative response to the drug. In some embodiments of the method, the administering step comprises administering the drug to the individual if the nucleic acid sample contains one or more alleles of biallelic markers associated with a positive response to treatment with the drug and the nucleic acid sample lacks one or more alleles of biallelic markers associated with a negative response to the drug. The biallelic markers of the present invention may also be used to select individuals for inclusion in the clinical trials of a drug. By selecting individuals who are likely to respond favorably to a drug for inclusion in the trial, the effectiveness of the drug can be assessed without lowering the measured effectiveness as a result of including non-respondβrs or negative responders in the clinical trial. May be more importantly, using such selection may avoid including patients who may suffer from undesirable side effects if administered the drug under trial, thus increasing the safety of clinical trials. Accordingly, tha present invontion also includes a method αf selecting an individual for inclusion in a clinical trial of 3 drug comprising obtaining a nucleic acid sample from an individual, determining the identity of the polymorphic base of one or more biallelic markers obtained by the methods described abovo which is or are associated with a positive response to treatment with the drug or one or more biallelic markers associated with a negative response to treatment with tho drug in the nucleic acid sample, and including the individual in the clinical trial if the nucleic acid sample contains one or more alleles of biallelic markers obtained by the methods described above which is or are associated with a positive response to treatment with said drug or if the nucleic acid sample lacks one or more alleles of •69- biallelic markers associated with a negative response to the drug. In one embodiment of the method, tho inclusion step comprises including the individual in the clinical trial if the nucleic acid sample contains one or more alleles of biallelic markers associated with a positive response to troatment with the drug and the nucleic acid sample lacks one or more alleles of biallelic markers associated with a negative response to tho drug. In particular embodiments, one or several of the ApoE linked murkors of SEZtl ID Nos 301-305/307-311 or the scqu β ncos complementary thereto may be used in targeted approaches to identify individuals who are likely to develop Alzhoimor's disease, or to identify individuals who do suffer from Al-l imer's disβaso. In oilier ernbodinionts, one or more of the markers of SEQ ID Nos. 306 and 312 and one or more of the the ApoE linked markers of SEQ ID Nos 301-305/307-311 or the sequences complementary thereto are genotyped approaches to identify individuals whu are likely to develop Alzheimer's disease, or to identify individuals who do suffer from Ahhetmei's disease. In further embodiments, une or several of the PG1 linked markers may be tested in targeted approaches to identify individuals who aro likely to develop pmstate cancer, or to identify individuals who do suffer from prostate cancer. Finally individuals likely to be asthmatic, or asthmatic individuals, can be identified using one or more of the asthma-associated markers to conduct the procedures of the present invention. Given the high number of cancer types in which tho PGl chromosomal region is involved, it will be appreciated that the PGl markers may be employed to identify individuals at risk of developing cancers other than prostate cancer, or to identify individuals suffering from cancors other than prostate cancer. It will be further appreciated that tin * asthma associated markers may be tested to identify individuals likely to exhibit or exhibiting, inflammatory traits other than the asthmatic state (e.g. arthritis, or psoriasis, among others). The present invention provides adequate methods to αslablish associations between markers, such as those mentioned above and candidate traits expressly contemplated herein, thus legitimating the corresponding targeted approaches to identify individuals Dkely to exhibit, or exhibiting said candidate traits. In some embodiments, the 653 biallelic markers obtained above (which include the sequencos of SED ID Nos, 1-50 and 51-100 or the sequences complementary thereto) may be used in targeted approaches to identify individuals at risk of developing a detectable trait, for example a complex disease or desired/uπdesirod drug response, or to identify individuals exhibiting said trait. The present invention provides methods to establish putative associations between any of the biallelic markers described herein and any detectable traits, including those specifically described herein. To use the maps and markers of the present invention in further targeted approaches, biallelic markers which are in linkage disequilibrium with any of the above disclosed markers may be identified. In cases where one or more biallelic markers of the present invention have been shown tα be associated with a detectable trait, more biallelic markers in linkage disequilibrium with said associated biallelic markers may be generated and used to perform targeted approaches aiming at identifying individuals exhibiting, or likely to exhibit said detectable trait, according to the methods provided herein. Furthermore, in cases where a candidate gene is suspected of being associated with a particular detectable trait or suspected of causing the detectable trait, biallelic markers in linkage disequilibrium with said candidate gene may be identified and usei in targeted approaches, such as the approaches utilized above for the asthma-associatod gene and the Apo E gene. •70- Biallelic markers that are in linkage disequilibrium with markers associated with a detectable trait, or with genes associated with a detectable trait, or suspected of being so, are identified by performing single marker analyzes, haplotype association analyzes, or linkage disequilibrium measurements on samples from trait positive and trait negative individuals as described above using biallelic markers lying in tlie vicinity of the target marker or gene. In this manner, a single biallelic marker or a group of biallelic markers may bo identified which indicate that an individual is likely to possess the detectable trait or doos possess the detectable trait as a consequence of a particular allele of the target marker or guπe. Nucleic acid samples from individuals to be tested for predisposition to a detectable trait or possession of a detectable trait as a consequence of a particular allele of the target gene may bo examined using the diagnostic methods described below. Diagnostic Methods To use tho maps and biallelic markers of the present invention to diagnose wfiethor an individual is predisposed to express a detectable trait or whether the individual expresses a detoctablo trart as a result of a particular mutation, one or more biallelic markers indicative of such a predisposition or causative mutation are idoniified by performing association studies and haplotype analysis on affected and non-affected individuals as described above. Tlie diagnostic techniques of the present invention may employ a variety of methodologies to determine whethor a test subject has a biallelic marker pattern associated with an increased risk of developing a detectable trait or whether the individual suffers from a detectable trait as a result of a particular mutation, including methods which enable the analysis of individual chromosomes for haplotypiπg, such as family studies, single spemi UNA analysis or somatic hybrids. Tho trait analyzed using the presont diagnostics may be any detectable trait, including diseases, drug response, drug efficacy, or drug toxicity. A "positive" drug response may refer tα a response indicating either some drug efficacy or no drug toxicity. Diagnostics which analyze drug response, drug efficacy, or drug toxicity may be used to dotermine whether an individual should be treated with a particular drug. For example, if the diagnostic indicates a likelihood that an individual will respond positively to treatment with a particular drug, the drug may be administered to the individual. Conversely, if the diagnostic indicates that an individual is likely to respond negatively to treatment with a particular drug, an alternative course of treatment may be prescribed. A negative response may be defined as either the absence of an efficacious response or the presence of toxic side effects. Clinical drug trials represent another application for the maps and markers of tho present invention. One or more markers indicative of drug response, drug efficacy, or drug toxicity may be identified using tho techniques described above. Thereafter, potential participants in clinical trials of the drug may be scroened to identify those individuals most likely tα respond favorably to the drug and exclude those likely to experience side effects. In that way, the effectiveness of drug treatment may be measured in individuals who respond positively to the drug, without lowering the measurement as a result of the inclusion of individuals who are unlikely tα respond postively in the study and without risking undesirable safety problems. In each of the diagnostic methods, a nucleic acid sample is obtained from the test subject and the biallelic marker pattern for one or more of the biallelic markers included in the maps of the present invention, iπcludinq tha B53 99/0403 • 71- biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto), the asthma-associated biallelic markers, the PG1 biallolic markers, and the Apo E biallelic markers, including those of SEQ ID Nos. 301-305/307-311 or the sequences complementary thereto. In other embodiments, the biallolic marker pattern of one or more of the markers of SEQ ID Nos. 306 and 312 is determined in addition to determining the biallelic marker pattern of ono or more of the biallelic markers included in tl maps of the present invention, including the 653 biallelic markers obtained above (which include tin: sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto), the asthma associated biallelic markers, the PG l biallelic markers, and tha Apo E biallelic markers, including those uf SEO ID Nos. 301-305/307-311 or the si'qiii.'nccs complementary thereto. In some embodiments, the biallelic marker pattern is determined by conducting an amplification reaction to generate amplicons containing the polymorphic bases of the one or more biallelic markers tα be genotyped. The identies of the polymorphic bases of the one or more biallelic markers to be analyzed may be determined using a variety of methods, including hybridization assays which speciiically detect amplification products containing particular alleles of the one or more biallelic markers, and microsequencing reactions which identify the polymorphic bases of t e one or more biallelic markers tα be anlayzed. While the following discussion utiizes the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto), the asthma-associated biallelic markors, the PG1 biallelic markers, and the Apo E biallelic markers as examples of the diagnostics of the present invention, it will be appreciated that the same diagnostics may be used in conjunction with any marker or any group of markers included in the maps of the present invention, Examples of amplification primers enabling tho amplification, from subjects genomic DNA samples, of DNA fragments that carry each of the markers of SEQ ID Nos: 1 -50 and 51-100 or the sequences complementary thoroto, are oligonucleotides of SEQ ID NOs: 101-150 and 151-200; pairs of corresponding primers for a given biallelic marker may be reconstituted by choosing the adequate upstream oligonuπleπtide from SEQ ID Nos, 101-150 together with the corresponding downstream oligonucleotide from SEQ ID Nos: 151-200. SEQ ID Nos: 1-50 correspond to the sequence identification number for a first allele of the biallelic markers of SEQ ID Nos: 1-50 and 51-100 and SEQ ID Nos: 51-100 correspond to the sequence identification number for a second allele of the biallelic markers of SEQ ID Nos 1-50 and 51-100. SEQ ID Nos: 313-318 correspond to sequence identification numbers of upstream amplification primers that may be used to generate amplification products containing the polymorphic bases of the biallelic markers of respective SEQ ID Nos: 301-306/307-312. SEQ ID Nos: 319-324 correspond tD downstream amplification pri ors that may be used tα generate amplification products containing the polymorphic bases of the biallolic markers of rεspectivo SEQ ID Nos: 301-306/307-311 For all markers of SEQ ID Nos: 1-50151-100 and 301-306/307-312 or the sequences complementary thereto, the enclosed listings indicate the position and identity of the polymorphic base in each biallelic marker. Potential microsequencing primers are also included in the sequence listing. The sequences of SEQ ID Nos.201-250 may be used in microsequencing procedures such as those described herein to determine the sequence of the polymorphic bases of the biallelic markers of SEQ ID Nos. 1-50/51 -100. The sequences of SEQ ID Nos. 325-330 or 331-336 may be used in microsequencing procedures such as those described herein to determine the sequence of the polymorphic bases of the biallolic markers of SEQ ID Nos. 3D1 -30G/307-312. All listings indicate tiie internal identification number corresponding to the biallelic marker to which the listed sequence is related to. One aspect of the present invontion is a method for determining whether an individual is at risk uf developing Alzheimer ' s Disease or whether an individual suffers from Alzheimer's Disease as a consequence ol possessing the Apo E e4 site A allele. The method involves obtaining a nucleic acid sample from the individual and determining whether the nucleic acid sample contains one or more markers indicative of a risk of developing Alzheimer's Disease or one or moie markers indicative that tho individual suffers from Alzheimer's Disease as a result of possossing the Apn E e4 site Λ allele. In απe embodiment, the method comprises determining the identity of the polymorphic base of one or more biallelic markers selected from tlie group consisting of SEQ ID Nos. 301-305/307-312 or the sequences complementary thereto in the nucleic acid sample. In a further embodiment, the method involves determining whether the nucleic acid sample contains the sequence of SEQ ID No. 306 (the C allele of marker 99-2452/54 containing the Apo E e4 site A allele) or the sequence complementary thereto. In a further embodiment tho method comprises determining whether the nucloic acid sample contains SEQ ID No. 311 (the T allele of marker 99-365/344) or the soquence complementary thereto. In another embodiment, the method comprises determining whether the nucleic acid sample contains SEQ ID No. 311 (the T allolo of markor 99-365/344) and SEQ ID No. 30S (the C allele of marker 99-2452/54 containing tho Apo E site A allele) or the soquence complementary thereto. In still a further embodiment, the method comprises determining whether the nucloic acid sanplo contains SEQ ID No. 302, 301, 303, and 304 or the sequences complementary thereto. In still a further embodiment, the method comprises determining whether the nucleic acid sanple contains SEQ ID Nos. 302, 303, and 304 or the sequences complementary thereto. In a further embodiment the method comprises determining whether the nucleic acid sample contains SEQ ID No. 311 (the T allele of marker 99-365/344) or the sequence complementary thereto. In some embodiments, the step of determining the identity of tho polymorphic base of one or more biallelic markers sβlectod from tha group consisting of SEQ ID Nos. 301 -305 and SEQ ID Nos. 307-31 1 or the sequences complementary thereto in the nucleic acid sample comprises conducting an amplification reaction on said nucleic acid sample using απe or more of the amplification primers selected from the group consisting of SEQ ID Nos. 313-317 and SEQ ID Nos. 319-323 and determining the identity of the polymorphic base in said one or more biallelic markers. In some embodiments, tho identity of the polymorphic base may be determined using one or more of the microssquenciπg primers listed as SEQ ID Nos. 325-329 or 331-335. In embodiments comprising the step of determining whether the nucleic acid sample contains the sequence of SEQ ID No. 306, the method may comprise conducting an amplification reaction on the nucleic acid sample using the pair of amplification primers consiting of SEQ ID Nos. 318 and 324. In some embodiments, the step of determining whether the nucleic acid sample contains the sequence of SEQ ID 306 comprises conducting a microsequencing reaction using one of the microsequencing primers listed as SEQ ID Nos. 330 or 336. Another aspect of the present invention relates to a method of determining whether an individual is at risk of developing a trait or whether an individual expresses a trait as a consequence of possessing a particular trait causing allele. Alternatively, another aspect of the present invention relates to 3 method of dctrrminmg whether en individual is at risk of developing a plurality of traits or whether an individual expresses a plurality of traits as a result of possessing particular trait causing alleles Those methods involve obtaining a nucleic acid sample from the individual and determining whether the nucloic acid sample contains one or more markers indicative of a risk αf developing tho trait or one or more markers indicative that the individual expresses the trait as a result of pussussmg a particular trait causing allele. In one embodiment, tho methods comprise determining the identity of the polymorphic base of one or ure biallelic markers in the maps of the present invention, including any of tho 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto), the asthma associated biallelic markers, the PGl biallelic markers, and the new Apo E biallelic markers. In a further embodiment, the methods comprise determining the identities of tl polymorphic bases of at least two, at least three, at least five, at least Bight. at least 20. at least 100, at least 200, at least 30D, at least 400, between 400 and 2,00D, between 2,000 and 4,000, between 4,000 and 10,000, between 10,000 and 20,000 or more than 20,000 of the biallelic markers in the maps of the present invention, including any of the 653 biallelic markers obtained above (which include the soquonces of SCΩ 11) Nos. 1-50 and 51 100 or the sequences complementary thereto), the astluπa associated biallelic markers, the PG1 biallelic markers, and the new Apo E biallelic markers. In some embodiments, the step of determining the identity of the polymorphic base of one or more biallelic markers in the maps of the present invention, including any of the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos 1 50 and 51-100 or the sequences complementary thereto), the asthma associated biallolic markers, the PGl biallεBc markers, and the new Apo E biallolic markers, comprises conducting an amplification reaction on said nucleic acid sample using appropriate amplification primers and determining tho identity ol the polymorphic base in said one or more biallelic markers. In some embodiments, the identity of the polymorphic b3se may be determined using appropriate microsequencing primers. As described herein, the diagnostics may be based on a single biallelic marker or a group of biallelic markers. Without wishing to be limited to any particular value, it is preferred that the biallelic marker used in single marker diagnostics either as a positive basis for further diagnostic tests or as a preliminary starting point for early preventive therapy, exhibit a p value in preliminary screening association analyzes of about 1 x 10 or less. More preferably the p value is about 1 x 10 or less. Similarly, without wishing to be limited to any particular value for diagnostics based on more than one biallelic marker, it is preferred that the haplotype exhibit a p value of 1 x 10 3 or lass, still more preferably 1 10 or less and most preferably of about 1 x 10 β or less in a preliminary screening haplotype analysis. These values are believed tn be applicable to any association studies involving single or multiple marker combinations, Significance thresholds may be refined according to the methods previously described. Examplo 32 describes methods for determining the biallelic marker pattern in a nucleic acid sample. 99/04038 •74- Exa ple 32 A nucleic acid sample is obtained from an individual to be testEd for susceptibility to a detectable trait or for a detectable trait caused by a particular mutation. The nucleic acid sample may be a RNA sample or a DNA sample. Λ PCR amplification is conducted using primer pairs which generate amplification products containing the polymorphic nucleotides of one or more biallolic markers associated with such a predisposition or causative mutation. For example, the amplification products may contain tho pulymorphic bases of one or more of the biallelic maikcrs in the maps of the present invention, including any of the 653 biallelic nurkers obtaini'd above (which include the sequences uf SEQ ID Nos. 1 50 and 51-100 or the sequences complementary thereto), the nsthma-assuciπted bullelic maikcrs, the PG1 biallelic markers, and the Apo E biallelic markers or biallelic markers in linkage disequilibrium with any uf these biallelic markers. In some embodiments, the PCR ampliation is conducted using pnmor p.nrs which generate amplification products containing the polymorphic nucleotides of several biallelic markors. For example, in one embodiment, amplification products containing the polymorphic bases of one or more biallelic markers in the maps of the present invention, including any of the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1 50 and 51-100 or the sequences complementary thereto), the asthma associated biallelic markers, the PG1 biallelic markers, and the Apo E biallelic markors, biallelic markers which are in linkage disequilibrium therewith or with a causative mutation associated with a detectable phenotype may be generated In another embodiment, amplification products containing the polymorphic bases of five or more biallelic markers in the maps of the present invention, including any of the the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-5Q an 51- 100 or the sequeπcos complementary thereto), the asthma-associated biallelic markers, the PG1 biallelic markers, and the Apo E biallelic markers, biallolic markers which are in linkage disequilibrium therewith or With a causative mutation associated with a detectable phenotype m3y be generated In another embodiment, amplification products containing the polymorphic bases of 20 or more biallelic markers in the maps of the present invention, including any of the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51 100 or the sequences complementary thereto), the asthma-associated biallelic markers, the PGl biallelic markers, and tha Apo E biallelic markers, biallelic markers which are in linkage disequilibrium therewith or with the causative mutation may be generated. In another embodiment, amplification products containing the polymorphic bases of 100 or more biallelic markers in the maps of the present invention, including any of the the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto), the asthma associated biallelic markers, the PG1 biallelic markers, and the Apo E biallelic markers, biallelic markers which are in linkage disequilibrium therewith or with a causative mutation associated with a detectable phenotype may be generated. In another embodiment, amplification products containing the polymoφhic bases of 200 or more biallelic markors in the maps of the present iπvontion, including any of the the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51- 100 or the sequences complementary thereto), the asthma associatod biallelic markors, the PG1 biallelic markers, and the Apo E biallelic markers, biallelic markers which are in linkage disequilibrium therewith or with a causative mutation associated with a detectable phenotype may be generated. In another embodiment, amplification products containing the polymorphic bases of 300 or more biallelic markers in the maps of the present invention, includiπα anv of the 6 3 99/0 •75- biallelic markors obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto), the asthma-associated biallelic markers, the PG1 biallelic markers, and the Apo E biallelic markors, biallelic markers which are in linkage disequilibrium therewith or with the causative mutation may be generated. In another embodiment, amplification products containing tho polymorphic bases of 400 or more biallelic markers in tho maps of the presont invention, including any of the the G53 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto), the asthma-associated biallelic markors, the PGl biallelic markers, and the Arm E biallelic markers, biallelic markers which are in linkage disequilibrium therewith or with a causative mutation associated with a detectable phenotype may be generated. The primers used to generate the amplification products may be designed as described herein. Representative amplification primers for generating amplification products containing , the polymorphic bases of the biallelic markets of SEQ ID Nos. 1-50 and 51-100 are provided as SEQ ID Nαs. 101-150/151 200 in the accompanying Sequenco Listing. The PCR primers may be oligonucleotides of 10, 15, 20 or more bases in length which enable the amplification of the polymorphic site in the markers. In some embodiments, the amplification product produced usiπij these primers may be at least 100 bases in length (i.e. about 50 nucleotides on each side of the polymorphic base). In ot er embodiments, the amplification product produced using these primers may be at least 500 bases in length (i.e. about 250 nucleotides on each side of the polymorphic base). In still further embodiments, the amplification product produced using these primers may be at least 1000 bases in length (Le. about 500 nucleotides on each side of the polymorphic base). Table 9 lists the internal identification numbers of the 50 localized markers described herein and the Apo E markers described herein, the SEQ ID Nos. for each of the two alleles of these biallelic markers, the SEQ ID Nos. of representative upstream and downstream amplification pnmors which can bo used to generate amplification products including the polymoiphic bases of these biallelic markers, and the SEQ ID Nos uf microsequencing primers which can be used to determine the ideπtias of the polymorphic bases of these markers. Tahle lO Marker SEQ ID Nos SEQ ID Nos SEQ ID Nos (Guπset code! First Second Amplification primers Microsβquαπciπg primers allele allelα Upstream Downstream 1 2 99-2103 1 51 101 151 201 251 99-2228 2 52 102 152 202 252 99-2229 3 53 103 153 203 253 99-2240 4 54 104 154 204 254 99-2242 5 55 105 155 205 255 99-2244 6 56 106 156 206 256 99-2246 7 57 107 157 207 257 99-2248 6 58 100 158 208 258 99-2250 S 59 109 159 209 259 99-2251 to 60 11D 160 210 260 99-2269 11 61 111 161 211 261 99-2271 12 62 112 162 212 262 99-2272 13 63 113 1G3 213 263 99-2273 14 64 114 164 214 264 99-2275 15 65 115 165 215 265 99-2270 16 66 116 16E 218 2GG 99-2312 17 67 117 1G7 217 267 99-2315 18 68 118 168 218 268 99-2320 19 69 119 169 219 2G9 99-2321 20 70 120 170 220 270 99-2324 21 71 121 171 221 271 99-2333 22 72 122 172 222 272 99-2341 23 73 123 173 223 273 99-2342 24 74 124 174 224 274 99-2362 25 75 125 175 225 275 99-2364 2C 76 126 17G 226 276 99-2367 27 77 127 177 227 277 99-2371 28 78 128 178 228 278 99-2378 29 79 129 179 229 279 99-23Θ1 30 80 13D 180 230 280 99-2413 31 at 131 181 231 281 93-2419 32 82 132 182 232 282 99-2559 33 83 133 183 233 283 99-2566 34 84 134 184 234 284 99-2567 35 85 135 185 235 285 99-2570 36 66 136 186 236 286 99-2571 37 87 137 187 237 287 99-2610 3B 88 138 168 236 288 99-2615 39 89 139 189 239 289 99-262D 40 90 140 190 240 29G 99-2624 41 91 141 191 241 291 99-2625 42 92 142 192 242 292 99-2630 43 93 143 193 243 293 99-2633 44 84 144 194 244 294 99-2634 45 95 145 195 245 295 99-2637 46 96 146 196 246 296 99-2642 47 97 147 197 247 297 99-2645 48 98 148 198 248 298 99-2647 49 99 149 199 249 299 99-2649 50 100 150 200 250 300 It will be appreciated that the primers listed in Table 9 are merely oxemplary and that any other set of primers which produce amplification products containing the polymorphic nuclβotidos of one or more of the biallelic markers of SEQ ID Nos: 1 50 and 51-100 or biallelic markers in linkage disequilibrium therewith or with a causative mutation fur a detectable trait, or a combination thereof may ba used in the diagnostic methods. It will also be appreciated thdt these diagnostic methuds may be performed with any biallelic marker or combination of bidllelic a kers included in t e maps of the present invention. Following the PCH amplification, the identities of the polymorphic bases of one or more of the biallelic markei s in the nucleic acid sample are determinod. The identities of the polymorphic bases may be determined using the microsoquenciπg prucedures described in Example 13. It will be apprecutcd that the microsequencing primers listed as SEQ ID NOs. 201 -250 and 251-300 are merely exemplary and that any primer having a 3' end near the polymorphic nucleotide, and preferably immediately adjacent to the polymorphic nucleotide, may be used Similarly, it will be appreciated that microsequencing analysis may be performed for any marker or combination of markers in the m3ps of the present invention. Alternatively, the microsequencing analysis may be performed as described in Pastmon ct al., Genome Research 7.606-614 (1997), the disclosure of which is incorporated herein by reference, and which is described in more detail below Alternatively, the PCR product may be completely sequenced to determine the identities of the polymorphic bases in the biallelic markers. In another method, the identities of the polymorphic bases in the biallelic markers arc determined by hybridizing the amplification products to microarrays containing allele specific o gnoπucleotides specific for the polymorphic bases in the biallelic markers. The use of microarrays comprising allele specific oligonuclβotidos is described in more detail below. It will be appreciated that the identities of the polymorphic bases in the biallolic markers may be determined using techniques other than those listed above, such as conventional dot blot analyzes. Nucloic acids used in the above diagnostic procedures may comprise at least 10 consecutive nucleotides, including the polymorphic bases, of the biallelic markers in the maps of the present invention, including any of the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto), the asthma-associated biallelic markers, the PGl biallelic markers, and the new Apo E biallelic markers, including those of SEQ ID Nos. 301 305/307-31 1 or the sequences complementary thereto. Alternatively, the nucleic acids used in tha above diagnostic procedures may comprise at least 15 consecutive nuclootides, including the polymorphic bases, of the biallelic markers in the maps of the present invention, including any of the 653 biallolic markers obtained above (which include the sequences of SEQ ID Nos. 1 -50 and 51-100 or the sequences complementary thereto), the asthma-associated biallelic markers, the PG1 biallelic markers, and the new Apo E biallelic markers, including those of SEQ ID Nos. 301 3Q5/307-311 or the sequences complementary thereto. In some embodiments, the nucleic acids used in the above diagnostic procedures may comprise at least 20 consecutive nucleotides, including the poly orphic bases, of the biallelic markers in the maps of tho present invention, including any of the 653 biallelic markers obtained above (which include tha sequences of SEQ ID Nπs. 1 -50 and 51-100 or the sequences comploπiuntary thereto), the asthma-associatod biallelic markers, the PGl biallelic maikcrs, and the new Apo E biallelic markers, including those of SEQ ID Nos. 301-305/307-311 or the sequences complementary thereto. In still other embodiments, the nucleic acids used in the above diagnostic procedures may comprise at least 30 consecutive nucleotides, including the polymorphic bases, of the biallelic maikcrs in the maps αf the present invention, including any of the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51 -100 or the sequences complementary thereto), the asthma-associated biallelic markers, the PG1 biallelic markers, and the now Apo E biallolic markers, including those of SEQ ID Nos. 301-305/307-311 or tlie sequences complementary thereto. In further embodiments, the nucleic acids used in the above diagnostic procedures may compriso more than 30 consecutive nucleotides, including the polymorphic bases, of the biallelic markers in the maps of the present invention, including any of the the 053 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51 -100 or the sequences complementary thereto), the asthma-associated biallelic markers, the PGl biallelic markers, and the new Apo E biallelic markers, including those of SEO ID Nos. 301-305/307-311 or the sequences cumple ontary thereto. In still further embodiments, the nucleic acids used in the above diagnostic procedures may comprise the entire sequence of the biallelic markers in the maps of the present invention, including any of the the 653 biallelic markers obtained above (which include the sequences αf SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto), the asthma-associated biallelic markers, the PG1 biallolic markers, and the new Apo E biallelic markers, including those of SEQ ID Nus. 301 -305/307- 311 or the sequences complementary thereto. In some embodiments the nucleic acids used in the diagnostic procedures are longer than the sequences of SEQ ID Nos. 1-50, 51 -100, 301-305 and 307-11 because they contain nuclentides adjacent tπ these sequences. The diagnostics of the present invention may also employ nucleic acid arrays attached to DNA chips or any other suitable solid support, including beads. As usod herein, the term array means a one dimensional, two dimensional, or multidimensional arrangement of a plurality of nucleic acids of sufficient length tπ permit specific detection of nucleic acids capable of hybridizing thereto. DNA chips allow the integration of micro-biochemical processes (such as DNA hybridization), systems of signal detection (such as fluorescence) and data processing into a single system which can be usod to obtain information on polymorphism. The solid surface of the chip is often made of silicon or glass but it can be a polymeric membrane. Efficient access to polymorphism information is obtained through a basic structure comprising high-density arrays of oligonucleotide probes attached to a solid support (the chip) at selected positions. The immobilization of arrays of DNΛ probes on solid supports has been rβndored possible by the development of a technology generally identified as "Very Large Scale Immobilized Polymer Synthesis" (VLSIPS™) and in which, typically, probes are immobilized in a high density array on a solid surface of a chip. Examples of VLSIPS™ technologies are provided in US Patents 5,143,854 and 5,412,087 and in PCT Publications WO 90/15070, VYQ 92/10092 and WO 95/11995, the disclosures of which are incorporated herein by reference, which describe methods for forming oligonucleotide arrays through techniques such as iiπht-directed synthesis techniques. In designing strategies aimed at providing arrays of nucleotides immobilized on solid supports, further presentation strategies were developed to order and display the probo arrays on tho chips in an attempt to maximize hybridization pattorns and sequence information. Examples of such presentation strategies are disclosed in PCT Publications WO 94/12305. WO 04/11530, WO 97/20212 and WO 97/31250, the disclosures of which are incorporated herein by reference. Each DNA chip can contain thousands to millions of individual synthetic DNA probes arranged in a grid like pattorn and miniaturized to the size oi a dime. The chip technology has been successfully used to detect mutations in nurnuruus cases. Fur example, the screening of mutations has been undertaken in the DRCAl gene, in S cβrev/siae mutant strains, and in the protease geno of HIV-1 virus (see Hacia et al., Nat. Genet. 14:4 1-447(1996); Shoemaker et al , Nat. Genet. 14:450-450 (1990); Kozal et al., Nat. Med. 2:753-753 (1996), the disclosures of which aro incorporated herein by reference). At least three companies propose chips ablo to detect biallelic polymorphisms: Λffyrnθtπx (GeneChip), llysuq (HyChip and HyGiiostics), and Protogene Laboratories. In some embodiments, the efficiency of hybridization of nucleic acids in the sample with the probes attached to the chip may bo improved by using polyacrylamide gel pads isolated from one another by liydrophobic rogions in winch the DNA probes are covalently linked tα an acrylamide matrix. The polymorphic bases present in the biallelic marker or maikcrs of the sample nucleic acids are determined as follows. Probes which contain at least a portion of one or more πl the biallelic markers of the present invention are synthesized either in situ or by conventional synthesis and immobilized on an appropriate chip using methods known to the skilled technician. The nucleic acid sample which includes the candidate region tα be analyzed is isolated, amplified with primers capable of generating an amplification product containing the polymorphic bases of one or more biallolic markers, and labeled with a reporter group. The reporter group can be a fluorescent group such as phγcoerythrin. The labeled nucleic acid is then incubated with the probes immobilized on the chip using a fluidics station. For example, aπz et al. [A yd. in Chromatogr. 33:1 66 (1993), the disclosure of which is incorporated herein by roference) describe the fabrication of fluidics devices and particularly micrαcapillary devices, in silicon and glass substrates. After the reaction is completed, the chip is inserted into a scanner and patterns of hybridization are detected. The hybridization data is collocted as a signal emitted from the reporter groups already incorporated into the nucleic acids generated in the amplification of the sample DNA, which is now bound to the probes attached to the chip. Probes that perfectly match a sequence of the nucleic acid sample generally produce stronger signals than those that have mismatches. Since the sequence and position of each probe immobilized on the chip is known, the identity of tho nucleic acid hybridized to a given probe can be determined. For single-nucleotϊdo polymorphism analyzes, sets of four oligonucleotides are generally designed (one for each possibla base) that span each position of a portion of the candidate region found in the nucleic acid sample, differing only in the identity of the central base. The relative intensity of hybridization tα each series of probes at a particular location allows the identification of the base corresponding tα the central base of the probe. For example, to detect sincle nucleotide polymorphisms such as those in the present biallelic markers, oligonucleotides having each of the two allelic bases at their central position are affixed to tho chip. The amplification products resulting from amplification of the nucleic acids in the sample are hybridized to the chip under high striπoeπcy (at lower salt concontratiπii and higher temperature over shorter time periods) to facilitate specific detection of tho polymorphic sequences present in tho nucleic acid sample. The use of direct electric field control improves the determination of single base mutations (Wuiiiigeii). A positive fiold increases tlie transport rato of negatively charged nucleic acids ond results in a 10-fold increase of the hybridization rates. Using this technique, single base pair mismatches are detected in Ics3 than 15 sec (see Sosnowski et al., Proc. Natl. Acad. Sci. USA 94:11 19-1123 (1997), the disclosure of which is incorporated herein by reference). Another technique which can be used hi analyze polymorphisms includes multicompunent integrated systems which miniaturize and compartmentalize processes such as restriction enzyme digestion, PCR reactions, and capillary electrophoresis in a single functional device. An example of such technique is disclosed in US patent 5,589,136, the disclosure of which is incorporated herein by reference, which concerns the integration of PCR amplification and capillary electrophoresis in chips, lπterjrated systems are best applied with microftuidic systems. Those systems comprise a pattern of microchannels designed onto a glass, silicon, quartz, or plastic wafer included on a microchip, The movements of the samples are controlled by electric forces applied across different areas of tho microchip to create functional microscopic valves and pumps with no moving parts, Regulating or varying the voltage controls the liquid flow at intersections between the micro-machined channels and changes the liquid flow rote for pumping acruss different sections of the microchip. In the caso of biallelic marker analyzes, the micro-chip integrates nucleic acid amplification, a microsequencing reaction (such as the one described above), capillary electrophoresis and a detection method such as laser-induced fluorescence detection. In a first step, the DNA samples are amplified, preferably by PCR. Then, the amplification products are subjected to automated microsequencing reactions using ddNTPs (specific fluorescence for each ddNTP) and the appropriate oligonucleotide microsequencing primers which hybridize just upstream of the targeted polymorphic base. The microsequencing reactions may employ primers capable of being extended to the polymorphic bases of the biallelic markers. Preferably, the microsequencing primers comprise a sequence terminating at the base immediately preceding the polymorphic base of the biallelic markers. Once the extension at the 3' end is completed, tho primers are separated from the unincorporated fluorescent ddNTPs by capillary electrophoresis. The separation medium usod in capillary electrophoresis can for example be potyacrylamide, polyethylenoglycol or dextran. The iπcorporatod ddNTPs in the siπgle- nucleotide primer extension products are identified by fluorescence dotoction. Preferably, the micro-chip can be used to process at least 96 samples in parallel. More preferably, the micro-chip can be used to process at least 304 samples in parallel. Preferably, the microchip is designed for use with detection procedures using four color laser induced fluorescence detection of the ddNTPs. Any one or more alleles of the biallelic markers in the maps of the present invention, αr fragments thereof containing the polymoφhic bases, may be fixed to a solid support, such as a microchip or other immobilizing surface. The fragmonts of these nucleic acids may comprise at least 10, at least 15, at least 20, at least 25, or tire than 25 consecutive nucleotides of the biallelic markers described herein. Preferably, the fragments include the polymorphic bases of tlie biallelit; markers, A nucloic acid sample is applied to the immobilizing surface and analyzed to determine the iilontius of the polymorphic bases of one or more of the biallelic maikors. In some embodiments, the solid support may also include one or more of the amplification primers doscribod herein, or fragments comprising at least 10, at least 15, or at loast 20 consecutive nucleotides thereof, for generating an amplification product containing the polymorpliic base3 of the biallelic markers to be analyzed in the sample. Another embodiment of the present invention is a solid support which includes one or more of tho micrusequϋπcing primers listod as in the aecompying Sequence Listing, or fragments comprising at least 10, at least 15, or at least 20 consecutive nucleotides thereof and having a 3' terminus immediately upstream of the polymorphic base of the corresponding biallelic marker, for determining the identity of the polymorphic base of the one or more biallelic markers fixed to the solid support. For example, one embodiment of the present mvention is an array of nucleic acids fixed to a solid support, such as a microchip, bead, or other immobilizing surface, comprising one or more of the biallelic markers in the maps of the present invention or a fragment comprising at loast 10, at least 15, at least 20, at least 25, or more than 25 consecutive nucleotides thereof including the polymorphic base. For example, the array may comprise one or more αf any of the Θ53 biallelic markers obtainod above (which include the sequences of SEQ ID Nos. 1-50 and 51-100), the asthma-associated biallelic markers, the PGl biallelic markers, and the new Apo E biallelic markers (including SEQ ID Nos. 301-305/307-311) or the saquences complementary thereto, or a fragment comprising at least 10, at least 15, at least 20, at least 25, or more than 25 consecutive nucleotides thereof including tha polymorphic base. In a further embodiment, the array comprises at least five of the biallolic markers in the maps of the present invention or a fragment comprising at least 10, at least 15, at least 20, at least 25, or more than 25 consecutive nucleotides thereof including the polymorphic base. For example, the arrays may comprise at least five of any of the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100), the asthma-associated biallelic markers, the PGl biallelic markers, and the now Apo E biallelic markers (including the sequences of SEQ ID Nos. 301-305/307-311) or the sequences complementary thereto, or a fragment comprising at least 10, at least 15, at least 20, at least 25, or more than 25 consecutive nucleotides thereof including the polymorphic baso. In a further embodiment the array comprises at least 10 αf the biallelic markers in the maps of the present invention or a fragment comprising at least 10, at least 15, at least 20, at least 25, or more than 25 consecutive nucleotides thereof including the polymorphic base. For example, the array may comprise at least 10 of any of the 653 biallelic markers obtained above (which include tha sequences of SEQ ID Nos. 1-50 and 51-100), the asthma- associated biallelic markers, the PG1 biallelic markers, and the new Apo E biallelic markers (including the sequences of SEQ ID Nos.3D 1-305/307-311) or the sequences complementary thereto, or a fragment comprising at least 1D, at least 15, at least 20, at least 25, or more than 25 consecutive nucleotides thereof including the polymorphic base, In a further embodiment the array comprises at least 20 of the biallelic markers in the maps of the present invention or a frapment -82- comprising at least 15 consecutive nucleotides thereof including the polymorphic base. For example, the array may comprise at least 20 of any of the G53 biallelic markers obtained above (which include tho sequences of SEQ ID Nos. 1-50 and 51- 100), the asthma-associated biallelic markers, the PGl biallelic markers, and the new Apo E biallelic markers (including the sequencos of SEQ ID IMos. 301-305/307-311) or the sequences complementary thereto, or a fragment comprising at laast 10, at least T5, at least 20, at least 25, or more than 25 consecutive nucleotides lliereof including the polymorphic base. In a further embodiment the array comprises at least 100 αf tho biallelic markers in the maps of the present invention or a fragment comprising at least 10, at least 15, at least 20. at least 25, or more than 25 consecutive iiucloutides thereof including the polymorphic base. For exβmple, the array may comprise at loast 100 of any of the G53 biallolic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100), the asthma-associated biallelic markers, the PGl biallelic markers, and the new Apo E biallelic markers (including the sequences of SEQ ID Nus. 301- 305/307-311) or the sequonces complementary theroto, or a fragment comprising at least 10, at least 15, at least 20, at least 25, or more than 25 consecutive nucleotides thereof including the polymorphic base. In a further embodiment the array comprises at least 200 of tha biallelic markers in the maps of the present invention or a fragment thereof comprising at least 10, at least 15, at least 20, at loast 25, or more than 25 consecutive nucleotides thereof including the polymorphic base. For example, the array may comprise at least 200 of any of the G53 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100), the asthma-associated biallelic markers, the PG1 biallolic markers, and the new Apo E biallelic markers (including the sequences of SEQ ID Nos. 301-305/307-311) or the sequences complementary thereto, or a fragment comprising at least 10, at least 15, at loast 20, at loast 25, or more than 25 consecutive nucleotides thereof including the polymorphic base. In a further embodiment the array comprises at least 300 of the biallelic markers in the maps of the present invention or a fragment comprising at least 10, at least 15, at least 20, at least 25, or more than 25 consecutive nucleotides thereof including the polymorphic base. For example, the array may comprise at least 300 of any of the 653 biallelic markers obtained ahove (which include the sequences of SEQ ID Nos. 1- 50 and 51-100), the asthma-assαciated biallelic markers, the PGl biallelic markers, and the new Apo E biallelic markers (including tha sequences of SEQ ID Nos. 301-305/307-311) or the sequences complementary thereto, or a fragment comprising at least ID, at least 15, at loast 20, at least 25, or more than 25 consecutive nucleotides thereof including the polymorphic base. In a further embodiment the array comprises at least 400 of tha biallelic markers in the maps of the present invention or a fragment comprising at least 10, at least 15, at least 20, at least 25, or oro than 25 consecutive nucleotides thereof including the polymorphic base. For example, the array may comprise at least 400 of any of the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100), the asthma-3Ssociatβd biallelic markers, the PGl biallelic markers, and the new Apo E biallolic markers (including the sequences of SEQ ID Nos. 301-305/307-31 D or the sequences complementary thereto, or a fragment comprising at least 10, at least 15, at least 20, at least 25, or more than 25 consecutive nucleotides thereof including the polymorphic base. In a further embodiment the array comprises more than 400 of the biallelic markers in tha maps αf the present invention or a fragment comprising at least 10, at least 15, at least 20, at least 25, or more than 25 consecutive nucleotides thereof including the polymorphic base. For example, the array may comprise at least 400 of any of the 653 biallelic markers obtained above (which include the seαuencβs of SEQ ID Nos. 1-50 and 51-100), the asthma-associated biallelic markers, the PG1 biallelic markers, and the new Apo E biallGlic markers (including the sequences of SEO ID Nos. 301-305/307-31 1) or the sequences complementary thereto, or a fragment comprising at laast 10, at least 15, at least 20, at loast 25, or more than 25 consecutive nucleotides thereof including the polymorphic base. Each of tho embodiments listed above may also include one or more of the sequences αf SEO ID Nos.306 and 312 in addition to those enumerated abovo. Another embodiment of the present invention is an array comprising amplification primers far generating amplification products containing the μυlyiiiiirphic bases of one or inure, at least five, at least 10, at least 20, at least 100. at least 200, at least 300, at least 400, or more than 400 of the biallelic markers in the maps of the present invention. For example, the array may comprise amplification primers for generating amplification products containing the polymoipliic hasεs of one or more, at least five, at least 10, at least 20, at least 100, at least 200, at least 300, at loast 400, ur mure than 400 uf any of the 653 biallolic markers obtained abovo (which include the sequences of SEQ ID Nus. 1-50 and 51- 100 or the sequences complementary thereto), the asthma associated biallelic markers, the PGl biallulic markers, and the new Apo E biallelic markers (including the sequences of SEQ ID Nos. 301-305/307-311 or the sequences complementary thereto). In such arrays, the amplification primers included in the arr3y are capable of amplifying the biallelic marker sequences to bo detected in the nucleic acid sample applied to the aιτay (i.e. the amplification primers correspond to the biallelic markers affixed to the array). For example, if the array is designed to detect the biallelic marker of SEQ ID Nos. 1 and 51 it may also contain SEQ ID Nos. 101 and 151, the amplification primers capable of generating an amplicoπ which includes sequence ID Nos. 1 and 51. Thus, the arrays may include one or more of the amplification primers αf SED ID Nos. 101-200, 313-317, and 319-323 corresponding to the one or more biallelic markers of SEQ ID Nos. 1-50, 51-100. 301 -305, and 307-311 which are included in the array, In other embodiments, the arrnys may include amplification primers capable of generating an amplification product which includes the biallelic markers SEQ ID Nos. 306 and 312 in addition to amplification primers capable of generating an amplification product containing each of the markers enumerated above. Thus, in such embodiments, the arrays may further include the amplification primers of SEQ ID Nos. 31 B and 324. Another embodiment of the present invention is an array which includes microsequencing primers capable of determining the identity of the polymorphic bases one or more, at least five, at least 10. at least 20, at least 100, at least 200, at least 300, at least 400, or more than 400 of the biallelic markers in the maps of the present invention. For example, the array may comprise microsequencing primers capable of determining the identity of the polymorphic bases of one or more, at least five, at least 10, at least 20, at least 100, at least 200, at least 300, at least 400, or more than 400 of the 653 biallelic markers obtained above (which include the sequences of SEQ ID Nos. 1-50 and 51-100 or the sequences complementary thereto), the asthma-associated biallelic markers, the PG1 biallelic markers, and the new Apo E biallelic markers (including the sequences of SEQ ID Nos. 301-305/307-311 or the soqueπces complementary thoroto). The sequences of representative microsequencing primers which may be included in the array are listed in the sequence listing as SEQ ID Nos. 201-300, 325-329, and 331-335. In other embodiments, the arrays may further include microsequencing primers for determining the identity of the polymorphic bases of one or more of tho sequences of SEO ID Nos. 306 and 312, such as the microsequencing primers αf SEQ ID Nos. 330 and 336. Arrays containing any combination of the above nucleic acids which permits the specific detection or 99/04038 •84 identification of the polymorphic bases of the biallelic markers in the maps of the present invention, including any combination of the 653 biallelic markers obtained above (which include tho sequences of SEQ ID Nos. 1 50 and 51-100 or tho sequences complementary thereto), the asthma associated biallelic markers, the PG1 biallelic markers, an the new Apo E biallolic markers (including the sequences αf SEQ ID Nos. 301-305/307-311 or the sequences complementary thereto) are also within the scope of the present invention. Other embodiments of the arrays include nucleic acids which permit the specific detection or identification of the polymorphic bases of nπe or moru of SEQ ID Nns. 306 anil 312 in addition to the nucleic acids permitting the specific detection or identication of the polymorphic bases of the biallelic markers listed in the preceding sentence. For example, the array may comprise both the biallolic markers and amplification primers capable of generating amplification products containing the pulyiπorphic bases of the bullelic markers. Alternatively, the array may comprise both amplification primers capable of generating amplification products containing the polymorphic bases of the biallelic markers and microsequoncmg primers capable of deteminmg the idoπtiϋes αf the polymorphic bases of these markers. Although the above examples describe arrays comprising specific groups of biallelic markers and, in some embodiments, specific amplification primers and microsequencing primers, it will be appreciated that the present invention encompasses arrays including any biallelic marker, group of biallelic markers, amplification primer, group of amplification primers, microsequencing primer, or group of amplification pπmors described herein, as well as any combination of the preceding nucloic acids. Alternatively, the microsequencing procedures described above md be used to determine whether mi individual possesses a pattern of biallelic marker alleles associated with a detectable trait. In this approach, a PCR reaction is parformed on the ONΛ or RNA of the individual to be tested to amplify the desired biallelic markers or portions thereof. The amplification product is hybridized to one or moro oligonucleotides having their 3' end one base from the position of the polymorphic basos of the biallelic markers which are fixed to a surface. The oligonucleotides are extended one base using a detectably labeled dNTP and a polymerase. Incorporation of a pattern of detεctably labeled bases indicative of a biallelic marker pattern associated with a detectable trah indicates that the individual suffers from a detectable trait as the result of a particular mutation or that the individual is at risk for developing the detectable trait at a subsequent time. In addition to their use in diagnostic techniques such as those descπbed above, any of the arrays described above may also be used to identify a haplotype (i.β. a set of alleles of biallelic markers) which is associated with a particular trait. As described above, in such analyses nucleic acid samples are obtained from trait positive and trait negative individuals and the alleles of biallelic markers present in each population are determined to identify a haplotype which is statistically associated with the trait. The arrays may be employed in haplotype analyses as follows. Nucloic acid samples obtained from trait positive and trait negative individuals are amplified with pπmurs capable of gonorating ompiificatioπ products which include the polymorphic bases of tho biallelic markers. The amplification products are labeled with a reporter group and allowed to contact the biallelic marker probes which are attached to the support. As described above, the biallelic marker probes to which the labeled amplification products specifically hybridize are determined tα indicate which alleles of the biallelic markers are present in the samples, The patterns of alleles of biallelic markers in the trait positive and trait πegatϊve individuals are thon determined to identify a haplotype having a statistically significant association with tho trait. Alternatively, as described above, the nucleic acid samples from trait positive and trait negative individuals may be applied to an array comprising amplification primers capablo of generating amplification products which include the polymorphic bases of the biallelic markers. The identities of the polymorphic bases in the amplification products are then determined using techniques such as the microsoqueπciπg proceduros disclosed herein. Alternatively, amplification can ba conducted in liquid phase and microsequencing may be conducted on the array. Alternatively, both amplification and microsequencing reactions m3y be perfnππed in liquid phase. In such embodiments, tho labeled nucleotides incorporated in tlie microsoquencing primers during the microsoquencing reactions are d β tocted by hybridizing the extended microsequencing primers to sequences complementary to the microsequencing primers. The sequences complementary to the microsoquencing primers are immobilized on a support, such as those described above. The amplification and microsequencing reactions performed in liquid phase may be multiplexed, allowing the samples to be tested simultaneously for tens, hundreds, thousands or more biallelic markers. Preferably, the array used in tho haplotype analysis comprises one or more groups αf biallelic markers known to be located in proximity to one another in the genome. For example, the biallelic markers in the groups may be derived from a single YAC insert, a single BAC insert or a BΛC subclone. Alternatively, the biallelic markers in the groups may be derived from adjacent ordered clones. Tho biallolic markers in the groups may be located within a genomic region spanning less than 1 kb, from 1 to 5kb, from 5 to 10kb, from 10 to 25kb, from 25 to 50kb, from 50 to 150kb, f om 150 to 250kb. from 250 to 500kb, from 500kb to 1Mb, or more than 1Mb. In some embodiments, the biallelic markers in the groups comprise biallelic markers which have been localized to the same chromosome, subchromosomal region, or gene. It will be appreciated that the ordered DNΛ containing the biallelic markers need not completely cover tlie genomic regions of these lengths but may instead be incomplete contigs having one or more gaps therein. In some embodiments, the biallolic markers known to be locatod in proximity to one anotner in the genome may bs located in physical proximity on the array. For example, the array may comprise one or more groups of at least 3 biallelic markers known to be located in proximity to one another in the genome. In some embodiments, the array may comprise one or mare groups of at least 6 biailetjc markers known to be located in proximity to one another in the genome. In older embodiments, the array may comprise one or more groups of at least 20 biallelic markers known to be located in proximity to one another in the genome. The array may comprise one or more groups of biallelic markers known to be locatod on the same subchromosomal region. For example, the array could comprise two or more biallelic markers located at 21q11.2 ( selected from the group consisting of SEQ ID Nos. 29, 79, 30 and 80 ), two or more markers located at 21q21 (selected from the group consisting of SEQ ID Nos 1, 51, 2, 52. 3 and 53), two or αrβ markers located at 21q21.2 (selected from the group consisting of SEQ ID Nos 17, 67, 18, 68, 19, 69, 20, 70, 21, and 71) , two or more markers located at 2lq21.3-q22.l3 (selected from the group consisting of SEQ ID Nos 25, 75, 26, 76, 27, 77, 28, 78, 31, 81, 32, 82, 38, 86, 39, 89, 40, 90, 48, 98, 49, 99, 50. 100, 22, 7Z 23, 73, 24, 74, , 54, 5, 55, 6, 56. 7, 57, 8, 58, 9, 59, 10, 60. 11, 61, 12, 62, 13, 63, 14, 64, 15, 65, 16, and 66 ), two or more markers located at 2lq22.2 (selected from the group consisting of SEQ ID Nos 41, 91 , 42, 92, 43, 93. 44, 94. 45. 95, 46. 96, 47, and 97) , and two or more markers located at 21α22.3 (selected from the group coπsistinα of SEQ ID Nos 33, 83, 34, 84, 35, 85, 36, 86, 37, and 87). Alternatively, the array could compriso amplification primers capable of generating an amplification product containing the polymorphic bases of two or more biallelic markers located at 21 q1 1.2 ( for exampio, amplification primors capablo of generating an amplification product containing the polymoφhic bases of two or more biallelic maikcrs selected from the group consisting of SEQ ID Nos. 29, 70, 30 and 80 ), two or more markers locatod at 21q21 (fur example, amplification primers capable of generating an amplification product containing the polymorphic bases of two αr more biallelic markers selected from the group consisting uf SEQ ID Nos 1, 51, 2. 52, 3 and 53), two or more markors located at 21q21.2 (for example, amplification primers capable of generating an amplification product containing the polymorphic basos of two or more biallelic markers solocted from the group consisting of SEQ 10 Nos 17, 67, 18, 68, 19, 60, 20, 7D, 21, and 71) , two or more markers located at 21 q21.3 q22.13 (for example, amplification primors capable of generating an amplification product containing the polymorphic bases of two or more biallelic markers selected from the group consisting of SEQ ID Nos 25, 75, 26, 76. 27, 77, 28. 78. 31. 61, 32, 82, 38, 88, 39, 89, 40, 9D, 48, 98, 49, 99, 50, 100, 22, 72, 23, 73, 24, 74, 4, 54, 5, 55, 6, 56, 7, 57, 8, 58, 9, 59, 10, 60, 11, 61, 12, 62, 13, 63, 14. 64, 15, 65, 16, and 66 ), two or more markers located at 21q222 ( far example, 3inplilication primers capable of generating an amplification product containing the polymorphic bases of two or more biallelic markers solocted from the group consisting of SEQ ID Nos 41. 91, 2. 92, 43, 93, 4, 94, 45, 95. 4G. 95, 47, and 97) , and two or more markers located at 21 q2Z3 (for example, amplification primers capable of generating an amplification product containing the polymorphic bases of two or more biallolic markers selected from the group consisting of SEQ ID Nos 33, 03, 34, 04, 35, 85, 6, 86, 7, and 87), In some embodiments, the array may comprise αne or more groups of biallelic markers derived from tho same BAC insert. For example, the array could comprise two or more markers selected from the group consisting of SEQ ID Nus. 23, 79, 30, and 80 (derived from BAC 1), two or more markers selected from the group consisting of SEQ ID Nos. 1 and 51 (derived from BAC 2), two or more markers selected from the group consisting of SEQ ID Nos. 2 , 52, 3, and 53 (derived from BAC 3). two or more markers selected from the group consisting of SEQ ID Nos. 17, 67, 18, 68, 19, 69, 20, 70, 21, and 71 (derived frαm BAC 4), two or more markers selected from the group consisting of SEQ ID Nos. 25, 75, 26, 76, 27, and 77 (derived from BAC 5), two or more markers sleeted from tha group consisting of SEQ ID Nos. 28, 78, 31 , 81, 32, and 82 (derived from BAC 6), two or more markers selected from the group consisting of SEQ ID Nos. 38, 68, 39, 89, 40, and 90 (derived from BAC 7), two or more markers selected from the group consisting of SEQ ID Nos. 48, 98, 49, 99, 50, and 100 (derived from BAC 8), two or more markers selected from the group consisting of SEQ ID Nos. 22, 72, 23, 73, 24, and 74 (derived from BAC 9), two or more markers selected from tha group consisting of SEQ ID Nos.4, 54, 5, 55, 6, 56, 7, 57, 8. 58, 9, 59, 10, and 60 (derived from BAC 10), two or more markers selected from tho group consisting of SEQ ID Nos. 11, 61, 12. 62, 13, 63, 14, 64, 15, 65, 16, and 66 (derived from BAC 11], two or more markers selected from the group consisting of SEQ ID Nos.41, 91, 2, 92, 43, 93, 44, 94, 45. 95, 6, 96, 47, and 97 (dorivod from BAC 12). or two or more markers selected frαm the group consisting of SEQ ID Nαs. 33, 83, 34, 84, 35, 85, 36. 86, 37, and 87 (dorived from BAC 13). Arrays comprising biallelic markers known to be located in proximity to one another in the genome permit haplotyping analyses to be conducted even when the chromosomal locations of the biallolic markers has not been determined. For example, usinp the procedures described ahαve, the alleles of sets of biallelic markers which are present in -B7- nucleic acid samples from trait positive and trait negative individuals may be determined using a succession of arrays, with each array having one or more groups of nucleic acids known to be locatod in proximity to one another thoreαn. The succession of arrays may comprise biallelic markers spanning the entire genome having any of the average iπteππarker distances specified abovo. Alternatively, the succession ol arrays need not span the entire genome but may instead be derived from two or more contigated YAC, BAC, or BΛC subclone inserts. A stJtisticai πnπlysis is perfonnnd on tliu nlleles of biallolic maikcrs present in the trait positive and trait negative individuals to identify ,ι haplotype having a statistically significant association with tltu trait. Once a statistically significant haplotype is identified, the genomic locations uf the biallelic markers comprising the haplotype may be determined using the methods dcscnlmd herein, In addition, using the procedures described herein, the genuinic region harboring (he biallelic markers in the statistically significant li-φlntγ-ic may be evaluated tα identify the genes associated with the trait. Although this invention has boon doscribod in terms of certain preferred embodiments, other embodiments which will be apparent to those of ordinary skill in the art r view of the disclosure horom are also within the scope of this invention. Accordingly, the scope of tho invontion is intended to be defined only by reference to the appended claims. Table 1 Biallelic marker BAC Insert size average Intermarker subchromosomal (Gensβt code) (kb) distance (kb) localization 99-2378 1 150 75 21q112 99-2381 1 150 75 21q112 99-2103 110 110 21q2l 99-2228 105 525 21q21 99-2229 105 525 21q21 99-2362 5 100 333 21q213 q2213 99-2364 5 100 333 21q213 q2213 99-2367 5 100 333 21q213q2213 99-2371 6 135 45 21q2211-q2213 99-2413 6 135 45 21q2211-q2213 99-2419 6 135 45 21q2211-q2213 99-2610 7 185 617 21q2211-q2213 99-2615 7 185 617 21q2211-q2213 99-2620 7 185 617 21q2211-q2213 99-2645 8 250 833 21q2211 q2213 99-2647 8 250 833 21q2211 q2213 99-2649 8 250 833 21q2211-q2213 99-2333 9 140 467 21q2211 q2213 99-2341 9 140 467 21q2211-q2213 99-2342 9 140 467 21q2211 q2213 99-2240 10 95 136 21q2211-q2213 99-2242 10 95 136 21q2211-q2213 99-2244 10 95 136 21q2211-q2213 99-2246 10 95 136 21q2211-q2213 99-2248 10 95 136 21q2211-q2213 99-2250 10 95 136 21q2211-q2213 99-2251 10 95 136 21q2211-q2213 99-2269 11 40 67 2 q2211-q2213 99-2271 11 40 67 21q2211-q2213 99-2272 11 40 67 21q2211-q2213 99-2273 11 40 67 21q2211-q2213 99-2275 11 40 67 21q2211-q2213 99-2278 11 40 67 21q2211-q2213 99-2624 12 165 236 21q222 99-2625 12 165 236 21q222 99-2630 12 165 236 21q222 99-2633 12 165 236 21q222 99-2634 12 165 236 21q222 99-2637 12 165 236 21q222 99-2642 12 165 236 21q222

Claims: WHΛT IS CLAIMED IS: 1. A method of obtaining a set of biallelic markers comprising the steps of: oblniiiing a nucleic acid library comprising a plurality of genomic DNA fragments comprising tho full genuine or a portion thereof; doteimiiiiiirj the order of said plurality of genomic DNA fragments in the gonomo; determining the sequence of selected regions of said plurality of genomic DNA fragments; and identifying nucleotides in said plurality of genomic DNA fragments which vary between individuals, thereby defining a set of biallelic markers. 2. The method of Claim 1, wheroin said identifying step comprises identifying about 20.000 biallelic markers. 3. The method of Claim 1, wherein said identifying step comprises identifying about 40,000 biallelic markers. 4. Tlie method of Claim 1, wherein said identifying step comprises identifying about 60,000 biallelic markers. 5. Tlie method αf Claim 1, wherein said identifying step comprises identifying about 80,000 biallelic markers. 6. The method of Claim 1, whereiα said identifying step comprises identifying about 100,000 biallelic markers. 7. The method of Claim 1, wherein said identifying step comprises identifying about 120,000 biallelic markers. 8. The method of Claim 1, wherein said biallelic markors arc separated from one another by an average distance of lQ b-200 kb. 9. The method of Claim 1, wherein said biallelic markers aro separated from one another by an average distance of 15kb-l 50 kb. 10. The method of Claim 1, wherein said biallelic markers are separated from one another by an average distance of 20kb-l OO kb. 11. The method of Claim 1, wherein said biallelic markers are separated from one another by an avorage distance of 100kb-150 kb. 11 The method of Claim 1, wherein said biallelic markers are separated from one another by an averarje distance αf 50-1 OOkb. 13. The method of Claim 1, wherein said biallelic markers are separated from one another by an avoragø distance of 25 kb-50 kb. 14. The method of Claim 1, wherein the step of determining the sequence of selected regions of said plurality of genomic DNA fragments comprises inserting fragments of said plurality of genomic DNA fragments into a vector to generate a plurality αf subclones and determining the soquonce of a region of the inserts in said plurality of subclones or a subset thereof. 15. The method of Claim 14, wheroin said step ol determining the sequence of a rogion of said inserts or a subsot thereof comprises determining the sequence of one αr both c/id regions of said inserts or a subset thereof. IB. The method of Claim 14, wherein the step of determining the soquence ul one or both end regions of said plurality of subclones comprises determining the soquence of about 500 bases at each end of said subchmus or a subsot thereof. 17. The method of Claim 1, wherein a set of about 10,000 to about 20,000 genomic DNΛ inserts with an average si.e between 100kb and 300kb are ordered. 18. The method of Claim 1, wherein a set of about 10,000 to about 30,000 genomic DNA inserts with an average size between lOOkb and 150 kb are ordered. 19. The method of Claim 1, wherein a set ol about 15,000 to about 25,000 genomic DNΛ inserts with an average size between 100kb and 200 kb are ordered. 20. The method of Claim 1, wherein said identifying step comprises identifying between 1 and 6 biallelic markers per genomic DNA ragment. 21. The method of Claim 1, whoroin said identifying step comprises idoπtifying an average ol 3 biallelic markors per genomic DNA insert. 22. The method of Claim 1, wherein said genomic DNΛ fragments are in a Bacterial Artificial Chromosome. 23. Tlie method of Claim 1, wherein said genomic DNA fragments are in a Yeast Artificial Chromosome. 24. The method of Claim 1, further comprising determining the position of said biallelic markers along the genome or a portion thereof. 25. The method of Claim 24, wherein the step of determining the position of said biallelic markers along the genome or portion thereof comprises determining the position of said biallelic markers along a chromosome. 26. The method of Claim 24, wherein the step of determining the position of said biallolic markers along the genome or portion thereof comprises determining the position of said biallelic markers along a subchromosomal region. 27. The method of Claim 1, further comprising identifying biallelic markers which are in linkage disequilibrium with one another. 28. The method of Claim 27, furthor comprising obtaining pluralities of biallelic markers such that oach marker is in linkage disequilibrium with at loast ono identifie markers. 29. The method of Claim 1, wherein said portion of the genome comprises at least 200 kb of contiguous genomic DNA. 30. Tha method of Claim 1, wherein said portion of the genome comprises at least 300 kb of contiguous genomic DNA. 31. The method of Claim 1, whorein said portion of the genome comprisos at least 500 kb of cuntiguous genomic DIMΛ. 32. The method of Claim 1 , wherein said portion of the genome comprises at least 2 Mb of contiguous genomic DNA. 33. The method of Claim 1, wherein said portion of the genome comprises at least 5 Mh of contiguous genomic DNA. 34. The method of Claim 1, wherein said portion of the genome cimiprises at least 10 Mb of contiguous genomic DNA. 35. The method of Claim 1, wherein said portion of the genome comprises at least 20 Mb uf contiguous genomic DNA. 36. The method of Claim 1, further comprising the step of identifying one or more groups αf biallelic markers which are in proximity to one another in the genome. 37. The method of Claim 36, wherein the biallelic markers in each of those groups arc located within a genomic region spanning less than 1 kb. 38 The method of Claim 36, wherein the biallelic markers in each of these groups afe located within a genomic region spanning from 1 to 5kb. 39 The method of Claim 36, wherein the biallolic markers in each of these groups are located within a genomic region spanning from 5 to lOkb. 40 The method of Claim 36, wherein the biallelic markers in each of these groups are located within a genomic region spanning from 10 to 25kb. 41 The method of Claim 36, wherein the biallelic markers in each of these groups are located within a genomic region spanning from 25 to 50kb.. 42 The method of Claim 36. wherein the biallelic markers in each of these groups are located within a genomic region spanning from 50 to 150kb. 43 The method of Claim 36, wherein the biallelic markers in each of these groups are located within a genomic region spanning from 150 to 250kb. 44 The method of Claim 36, wherein the biallolic markers in each of these groups are located within a genomic region spanning from 250 to 500kb. 45 The method of Claim 36, wherein the biallelic markers in each of these groups are located within a genomic region spanning from 500kb to 1Mb. 46 The method of Claim 36, wherein the biallelic markers in each of these groups are located within o genomic region spanning more than 1Mb. 47. A method of obtaining a set of biallolic markers comprising the steps of: ohtaining a nucleic acid library comprising genomic DNA fragments comprising the full genome or a portion thereof; determining the sequence of selected regions αf said genomic DNA fraqments; identifying nucleotides in said genomic DfJΛ fragments which v3ry botween individuals, thereby defining a set of biallelic markers; ond determining the order of said biallelic markers along the genuine or portion thereof. 48 A set of biallelic markers obtained by tho method of Claim 1. 49 The set of biallelic markers of Claim 411, whorβin the markers in said sot have a known genuinic position. 50 Tho set of biallelic markers ol Claim 40, whoroin tlie arc απicied relativo to one another, 51. A set of biallelic markers having a known rclatiunship to one another and a knnwπ genomic position, said set of biallelic markers being obtained by the method of Claim 1. 52. The set of biallelic markers of Claim 48, whoroin said biallelic markers li3vo hotorozygosity rales of at least about 0.18. 53. The set of biallelic markers of Claim 48, wherein said biallelic markers have hoterozygosity rale of at least about 0.32. 54. The set of biallelic markers of Claim 48, wherein said biallolic markers have a heterozygosity rate of at least about 0.42. 55. A map comprising an ordered 3rray of at least 20,000 biallelic markers obtained by the method ol Claim 1. 56. The map of Claim 55, comp ising an ordered array of at least 60,000 biallelic markers obtained by the mothod of Claim 1. 57. The map of Claim 55 comprising an ordered arroy αf at least 100.000 biallelic markers obtained by the method of Claim 1. 58. The map ol Claim 55. wherein said biallelic aikeis are distributed at an average marker density of one marker every 150kb. 59. The map of Claim 56, whorein said biallelic markers are distributed at an average marker donsity of one marker evorγ 50 kb. 60. The map of Claim 57, wherein said biallelic markers are distributed at an average marker density of one marker every 25 kb. 61. Λ method of identifying one or more biallolic markers associated with a detectable trait comprising the steps of; determining tho frequencies of each allele of one or more bialolic markers obtained by the method of Claim 1 in individuals who express said detectable trait and individuals who do not express said detectablo trait; and identifying one or more alleles of said one αr more biallolic markers which aro statistically associatod with the expression of said detectable trait. 62. The method of Claim 61, wherein said detectable trait is selected from the group consisting of disease, drug response, drug efficacy, and drug toxicity. 63. The method of Claim 61, wherein the phenotypo of said individuals who express said detectable trait and the phenotypo of said individuals who do not express said detectable trait are icadily distinguishable from one another. 64. The method αl Claim 61, wherein the individuals who express said dotectable trait and the individuals who do not expross said dutcctablc trait are selected from a bimoiJal phenotypu distribution. 65. The method of Claim 61. wherein said individuals who express said detectable trait arc at one phcnotypic extreme of the population and said individuals who do not express said detectable trait are at the uther phcnotypic extreme of the population, 66. A method of identifying a haplotype associated with a trait comprising the steps of: obtaining nucleic acid samples from trait positive and trait negative individuals; determining the frcquoncios of the alleles αf each member of a group of biallelic markers obtained by the method of Claim 1 known to be located proximity to one another in the genome in said nucleic acid samples; and identifying a plurality of alleles of biallelic markers having a statistically significant association with said trait. 67. The method of Claim 66, wherein said dotectable tr3it is selected from the group consisting of disease, drug response, drug efficacy, and drug toxicity. 68. The method of Claim 66, wherein the biallelic markers in each of those groups ore located within a genomic region spanning less than Ikb. 69 The method of Claim 66, wherein the biallelic markers in oach of these groups arc located within a gonomic region spanning from 1 to 5kb. 70 The method of Claim 66, wherein the biallolic markers tn each of these groups aro located within a genomic region spanning from 5 to 10kb. 71 The method of Claim 66, wherein the biallelic markers in oach of these groups are located within a genomic region spanning from 10 to 25kb. 72 The method of Claim 66, wherein the biallelic markers in each of these groups arc located within a genomic region spanning from 25 to 50kb. 73 The method of Claim 66, wherein tho biallelic markers in each of theso groups are located within a genomic region spanning from 50 to 150kb. 74 The method of Claim 66, wherein the biallelic markers in each of these groups are located within a genomic region spanning from 150 to 250kb. 75 The method of Claim 66, wherein the biallelic markers in each of these groups are located within a gonomic region spanning from 250 to 500kb. 76 Tho method of Claim 66, wherein the biallelic markers in each of these groups are located within a genomic region spanning from 500kh to 1Mb. 77 The method of Claim 66, wherein the biallelic markers in each of these groups are located within a genomic region spanning more than 1 Mb. 78. A mothod of identifying one or more biallelic markers associated with a detectable trait comprising tho stops of : selecting a gene in which mutations result in a detectable tr it or a gono suspected of being associated with π detectable trait; and idontifying one or more biallelic markers obtained by the method ol Claim 1 walmi tin; gi-nomic region harboring said gene which are associated with said detectable trait. 79. The mothod of Claim 78, whoroin said detectable trait is selected horn tho group consisting uf disease, drug response, drug officacy, and drug toxicity. 80. The method of Claim 78, wherein sai identifying stop comprises: determining the frequencies αf said one or more biallelic maikors in individuals who express sai detectable trait and individuals who do not express said detectable trait; and identifying one or more biallolic markers which are statistically associated with the expression of said detectable trait. 81. An array of nucleic acids fixed to a support, said nucleic acids comprising at least 8 consecutive nucleotides, including the polymorphic nucleotide, of one or moro biallelic markers obtained by the method of Claim 1. 82. The array of Claim 81, wherein said nucleic acids comprise at least 8 consecutive nucleotides. including the polymorphic nucleotide. of at least five biallelic markers obtained by the method of Claim 1. 83. The array αf Claim 81, wherein said nucleic acids compπse at least 8 coπsccutivo nucleotides, including the polymorphic nucleotide, of at least ten biallelic markers obtained by the method ol Claim 1. 84. An a/ray of nucleic acids fixed to a support, said nucleic acids comprising at least 8 consecutive nucleotides, including the polymorphic nucleotide, of one or more groups of biallelic markers known to lie located in proximity to one another in the genome. 85. An array of nucleic acids fixed to a support, said nucleic acids comprising amplification primers for generating an amplification product comprising at least 8 consecutive nucleotides, including the polymorphic nucleotide, of one αr more biallelic markers obtained by the method of Claim 1. 86. An array of nucleic acids fixed to a support, said nucleic acids of comprising amplification primers for generating an amplification product comprising at least θ consecutive nucleotides, including the polymorphic nucleotide, of one or more groups of biaBehc markers known to be located in proximity to one another in the genome. 87. An array of nucleic acids fixed to a support, said nucleic acids comprising one or more microsequencing primers for determining tho identity of the polγmαrphic base of one or more nucleic acids comprising at least 8 consecutive nucleotides, including tho polymorphic nucleotide, of ono or more biallelic markers obtained by the method of Claim 1. 88. An array of nucleic acids fixed to a support, sairj nucleic nucleic acids comprising one or more microsequencing primers for determining the identity of the polymorphic bases of one or more groups αf biallelic markers known to be located in proximity to one another in the genome. 83. An array of nucleic acids fixed to a support, whoroin said nucleic acids are complementary to one or mαrc microsequencing primers for determining the identities of tho polymorphic bases of one or more biallelic markers obtained by the method αf Claim 1. 90. The array of Claim 09, wherein said nucleic acids are complementary to at least five microsequencing primers for dotermiπing (he identities of the polymorphic bases of at least five biallelic markers obtained by the mothod of Claim 1. 91. The array of Claim 89, wherein said nucleic acids aro complomontary to at least ten microsequencing primers for determining the identities of the polymorphic bases of at least ten biallolic markers obtained by the method uf Claim 1. 92. An array of nucloic acids fixed tu a support, S3 ' id nucleic acids comprising ono or more nucleic aci s complementary to one or more microsequencing primers for determining the identity of the polymorphic bases ol une or more groups of biallelic markers known to bo located in proximity to one another in tlie genome. 93. Tha array of any one of Claims 84. 86, 88, anil 92, wherein the members of each of said ono or more groups of biallelic markers arc located in physical proximity to one another on said suppurt . 94. The array of any one of Claims 84, 86, 88. and 92, wherein said biallelic maikcrs in each of those groups are located within a genomic rogion spanning less than I b. 95 The array of any one of Claims 84, 86. 88, and 92, wherein said biallelic markers in each of these groups are locatod within a genomic region spanning from 1 to 5kb. 96 The array αf any one of Claims 84, 86, 88, and 9Z, wheroin tho biallelic markers in each of these groups are locatod within a genomic region spanning from 5 to lOku. 97 The array of any one of Claims 84, 86, 88, and 92. wherein the biallelic markers in each of those groups are located within a genomic region spanning from 10 to 25kb. 98 The array of any one of Claims 84, 86, 88, and 92, wherein tho biallelic markers in each of these groups arc located within a genomic region spanning from 25 to 50kb. 99 The array of any one of Claims 84, 86, 88. and 92, wherein the biallelic markers in each of these groups are located within a genomic region spanning from 50 tα 150kb. 100 Tho array of any one of Claims 84, 66, 88, and 92, wherein the biallelic markors in each of these groups are located within a genomic region spanning from 150 to 250kb. 101 The array of any one of Claims 84, 86, 88, and 92, wherein tlie biallelic markers in oach of these groups are located within a genomic region spanning from 250 to 500kb. 102 The array of any ono of Claims 84, 86, BB, and 92, whorein the biallelic markers in each of these groups are located within a gonomic region spanning from 5Q0kb to 1Mb. 103 The array of any one of Claims 84, 86, 88, and 92, wherein the biallelic markers in oach of these groups are located within a genomic region spanning more than 1Mb. 104. The array of any one of Claims 84, 86, 88, and 92, wherein each group of biallelic markers comprises at least 3 biallelic markers. 105. The array of any απe of Claims 84, 86, 88, and 92, wherein each group of biallelic markers comprises at least 6 biallelic markers. 106. Tlie array of any one of Claims 84, BG, 111), and 92, whoroin each group of biallelic markers comprises at least 20 biallelic markers. 107. A method for determining whothαr an individual is at risk uf developing a detectable. Iiait or suffers from a detectable trait associated with said trait cnmprisiiig the stops of: obtaining a nucleic acid sample from said individual; screening said nucleic acid sample with one or more biallelic markers obtained by tho method of Claim 1; and determining whether said nucleic acid sample contains one nr more of biallelic markors statistically associated with said detectable trait. 108. The method of Claim 107, wherein said delectable trait is seloctod from the group consisting of disease, drug response, drug efficacy and drug toxicity. 109. The mothod of Claim 107, wherein said biallelic markers were obtained by the method of Claim 61. 110. The method of Claim 107, wherein said biallelic markers were obtained by the method of Claim 78. 1 1 1. A method of using a drug comprising: obtaining a nucleic acid sample from an individual; determining the identity αf tho polymorphic base of one or more biallelic markers obtained by the method of Claim 1 which is associated with a positive response to treatment with said drug or one or more biallelic markets obtained by the method of Claim 1 which is associated with a negative response lo treatment with said drug; and administering said drug tα said individual if said nucleic acid sample contains one or more biallelic markers associated with a positive response to treatment with said drug or if said nucleic acid sample lacks one or more biallelic markers associated with a negative response to said drug. 112. The method of Claim 111, wherein said determining step comprises determining the identity of tha polymorphic base of one or more biallelic markers obtained by tlie method of Claim 62 which is associated with a positive response to troatment with said drug or ono or more bialleric markers obtained by the method of Claim 62 which is associated with a negative response to treatment with said drug. 113. The method of Claim 111, wherein said determining step comprises determining the identity of tho polymorphic base of one or more biallelic markers obtained by the method of Claim 79 which is associated with a positive response to treatment with said drug or ono or more biallelic markers obtained by the method of Claim 79 which is associated with a negative response to troatment with said drug. 114. A mothod of selecting an individual for inclusion in a clinical trial of a drug comprising: obtaining a nucleic acid sample f om an individual; dotormining the identity of the polymorphic base of one or more biallolic markers obtained by the method of Claim 1 which is associated with a positive response to treatment with said drug or one or more biallelic markers associated with a negative response to treatment with said drug in said nucleic acid sample; and including said individual in said clinical trial if said nucleic acid sample contains one or more biallelic markers obtained by the method of Claim 1 wliich is associated with α positive response to treatment with said drug or if said nucleic acid sample locks one or more biallelic markers associated with a negative rcspunse to said drug. 115. The method of Claim 1 14, wherein said determining step comprises determining tho identity of the polymorphic base of one or more biallelic markers obtained by the method of Claim 62 which is associated with a positive response lu treatment with sai drug or one or more biallelic markers obtained by the rnetliud uf Claim C2 which is associated with a negative response to treatment with said drug. 116. The method of Claim 1 14, wherein said determining step comprises duteiiniπing the identity of the polymorphic base of one or more biallelic markers obtained by the method of Claim 79 which is associatod with a positive response to treatment with said drug or one or moro biallolic markors obtained by the method of Claim 79 which is associated with a negative response to treatmont with said drug;. 1 17. A method of identifying a gene associated with a detectable trait comprising the steps αf: determining the frequency αf each allele of one or more biallelic maikors obtained by the method of Claim 1 in individuals having said detectable trait and individuals lacking said detectable trait; identifying one or more alleles of one or more biallelic markors having a statistically significant association with said detectable trait; and identifying a gene in linkage disequilibrium with said ono or more alleles. 1 18. The method ol Claim 78, further comprising identifying a mutation in the gene which is associated with said detectable trait. 1 19. The method of Claim 78, wherein said detectable trait is selected from the group consisting of disease, drug response, drug efficacy, and drug toxicity. 120. Λ method of identifying a gene associated with a detectable trait comprising: selecting a geno suspected of being associated with a detectable trait; and identifying one or more biallelic markers obtained by the method of Claim 1 within the genomic region harboring said gene which aro associated with said detectable trait. 121. The method of Claim 120, wherein said detectable trait is selected from the group consisting of disease, drug response, drug efficacy, and drug toxicity. 1 2. The method of Claim 120, whoroin said identifying step comprises: determining the frequencies of said αnε αr more biallelic markers in individuals who express said detectable trait and individuals who do not express said detectable trait; and identifying one or more biallolic ar ers which are statistically associated with the expression of said detectable trait. 123, A method of identifying a haplotypo associated with a trait comprising the stops of: obtaining nucleic acid samples from trait positive and trait negative individuals: conducting an amplification reaction on said nucleic acid samples using amplification primers capable of generating amplification products containing the polymorphic bases of a plurality of biallelic markers; contacting one or more arrays according to Claim 84 with said amplification products; determining the identities of the polymorphic bases of said amplification products; and identifying a haplotype having a statistically significant association with said trait. 124. A method of identifying a haplotype associated wit a trait coπψrsiiij the steps of: obtaining nucleic acid samples from trait positive and trait negative individuals; conducting amplification reactions on said nucleic acid samples using amplification primors capable of gonorating amplification products containing the polymorphic basos of a plurality of biallelic markers; contacting one or ore arrays according to Claim 88 with said amplification products; conducting microsequoncing reactions on said amplification products using microscquoncing |iriιιιι;rs tin said arrays, thereby generating elongated microsequencing primers cnmprising the polymorphic bases of said amplification products; determining the identities of said polymorphic bases; and identifying a haplotype having a statistically significant association with said trait. 125. A method of identifying a haplotype associated with a trait comprising the steps of: obtaining nucleic acid samples from trait positive and trait negative individuals; conducting amplification reactions on said nucleic acid samples uisng amplification primors which are capable of generating amplification products containing the polymoφhic bases ol a plurality of biallolic markors; conducting microsoquencing reactions on said nucleic acid samples, thereby generating microsequencing products containing the polymorphic bases of one or more biallelic markers et their 3' ends, said polymorphic bases being detectably labeled; contacting one or more arrays according to Claim 92 with said mi osequencing products such that said microsequencing products specifically hybridize to said nucleic acids complemantorγ to said microsequencing primers; determining the identities of the polymorphic bases of said microsequencing products; and identifying a haplαtypo having a statistically significant association with said trait. 126. A method αf identifying a haplotype associated with a trait comprising the steps ol: obtaining nucleic acid samples from trait positive and trait negative individuals; contacting one or more arrays according to Claim 86 with said nucleic acid sample; conducting an amplification reaction on said nucleic acid samples using amplification primers on said array which are capable of generating amplification products containing the polymorphic bases of a plurality of biallelic markers; determining the identities of the polymorphic bases of said amplification products; and identifying a haplotype having a statistically significant association with said trait. 127. A method of determining whathor an individual is at risk αf developing Alzheimer's disease or whether the individual suffers from Alzheimer's disease as a result of possessing the Apo E e4 Site A allele comprising: obtaining a nucleic acid sample from said individual; and determiπing the identity αf tlie polymorphic base in one αr more of the sequences solectod from the group consisting of SEQ ID Nos. 301 -305 and SEQ ID Nos. 307-31 1 or the sequences compiumentary thoroto in said nucleic acid sample 128. The method αf Claim 127, furthor comprising determining whothor said nucleic acid sample contains tho sequence of SEQ ID No. 306 or the sequence complementary thereto. 129. The method of Claim 127, wherein said step of determining the identity of the polymorphic bases in one or more of the sequences selected from the group consisting of SEQ ID Nos. 301 -305 and SEO ID Nos. 31)7-31 1 or the soqucnecs complementary thereto cumprises determining whether said nucleic acid sample contains the sequence ol SEQ ID NO: 31 1 or the sequence complementary thereto. 130. The method of Claim 129, further comprising determining whether said nucleic acid sample contains the sequence of SEQ ID No. 306 or the sequence complementary thereto. 131. An isolated nucleic acid comprising a sequence selected from the group consisting of SEQ ID No. 301 , SEQ ID No. 307, the sequences complementary thereto, and fragments comprising at least 8 cimsecutivo nucleotides, including the polymorphic nucleotide. thereof. 132. An isolated nucleic acid comprising a sequence selected from the group consisting of SEQ ID Nu. 302 , SED ID No. 308, the sequencos complementary thereto, and fragments comprising at least 8 consecutive nucleotides thereof. 133. An isolated nucleic acid comprising a sequence selected from the group consisting of SEO ID No. 303, SEQ ID No. 309, the sequencos complementary thereto, and fragments comprising at least 8 consecutive nucleotides, including the polymorphic nuclootide, thereof. 134. An isolated nudβic acid comprising a sequence selected horn the gioup consisting of SEQ ID No. 304, SEQ ID No. 310 , the sequences complementary thoreto. and fragments comprising at least 8 consecutive nucleotides. including tho polymorphic nucleotide, thereof. 135. An isolated nucleic acid comprising a sequence selected from the group consisting of SEQ ID No. 305, SEQ ID No. 311, the sequences complementary thereto, and fragments comprising at least 8 consecutive nucleotides, including the polymorphic nucleotide, thereof. 136. An isolated nucloic acid comprising a sequence selected frαm the group consisting of SEQ ID Nos. 313-317, SEQ ID Nos. 319-323, and fragments comprising at loast 8 consecutive nucleotides thereof. 137. An isolated nucleic acid comprising a sequence selected Irom the group consisting of SEQ ID Nos. 325-329, SEQ ID Nos. 331 -335, the sequoπce complementary thereto, and fragments comprising at least 8 consecutive nucleotides thereof. 138. An set of nucloic acids comprising at least 8 consecutive nucleotides. including the polymorphic nu leαtϊdo, of one or more biallelic markers obtained by tho method of Claim 1. 139. A set of nucloic acids comprising amplification primers for generating an amplification product comprising at least 8 coπsecutivo nucleotides, including the polymorphic nucleotide, of one or more biallelic markers obtained by the method of Claim 1. 140. A set of nucleic acids comprising one or moro microsequencing primers for delermining the idontity of the polymorphic base of one or more nucleic acids comprising at least 8 consecutive nucleotidus, including the polymorphic nucleotide, of one or mure biallolic markers obtained by the method of Claim 1.

Inventors: BLUMENFELD MARTA, COHEN DANIEL, TCHOUMAKOV ILIA, BLUMENFELD, MARTA, COHEN, DANIEL, TCHOUMAKOV, ILIA
Applicants: BLUMENFELD MARTA, COHEN DANIEL, GENSET SA, TCHOUMAKOV ILIA, BLUMENFELD, MARTA, COHEN, DANIEL, GENSET, TCHOUMAKOV, ILIA
Application year: 1998
Main classification: C12Q1
IPC codes: C12Q1