BACKGROUND
various types of microarrays have been used extensively for gene expression studies and, more recently, for genotyping and marker discovery  <cit> .
affymetrix microarrays in particular offer a massively-parallel approach to genotyping.
the basis of identifying polymorphisms, termed single feature polymorphisms , is differential hybridization of template rna or dna onto  <dig> bp oligonucleotide probes on the array due to the presence of single nucleotide polymorphisms  or small insertion/deletions .
using this approach, thousands of genes can be queried and simultaneously analyzed allowing whole genome approaches to mapping genes and quantitative trait loci  discovery  <cit> , as well as determining linkage disequilibrium   <cit>  and population structure  <cit> .
when arrays represent coding sequences, they can also be used for genotyping closely related species  <cit> .
although affymetrix expression arrays can be used for genotyping, their drawback is that all except the most recently produced microarrays have been designed with approximately  <dig> perfect match probes per unigene giving only limited coverage of each gene.
gresham et al.
<cit>  showed that an array designed with  <dig> bp oligos in a  <dig> bp overlapping tile format had greater sensitivity  in yeast and increased specificity  in calling sfps.
this overlapping tile design offers technical reproducibility and extensive genome coverage if the number of features on the microarray is sufficient.
genotyping by microarray hybridization has proven to be challenging in species with complex genomes.
microarrays have been successfully used to detect sfps in small genomes, for example the  <dig>  mb genome of yeast  <cit> , the  <dig> mb genome of arabidopsis  <cit>  and, more recently, the  <dig> mb genome of rice  <cit> .
although different algorithms were used for each of these three species, 87% of the sfps in yeast  <cit>  and 75% of those in rice and arabidopsis <cit>  were independently validated.
to identify polymorphisms in the barley genome, complexity was circumvented by using rna to hybridize to the microarray and 67%  <cit>  to 80%  <cit>  validation of sfps was achieved.
when dna from barley  was hybridized directly to the barley <dig> genechip® a significant overlap between sfps identified using genomic dna and those identified and validated using rna was reported  <cit> .
the increased efficiency reported by rostoks et al.
from using rna is, however, complicated by incomplete and variable transcriptome representation due to tissue- and environment-specific gene expression and false sfp discovery due to alternative splicing or adenylation  <cit>  associated with sampling rna versus dna.
several types of analyses have been implemented for sfp detection from microarray data.
generally, the data have been processed using expression analysis software to correct for background signal variation using robust multi-array analysis   <cit>  followed by correction for overall signal variation by quantile normalization across arrays  <cit> .
to call sfps, a modified t-test  <cit> , robustified projection pursuit   <cit>  and sfp de-viation  <cit>  have been developed to first estimate the normalized hybridization of a reference set of probes and then test with appropriate statistics or ratios for differential hybridization of specific probes across genotypes.
in addition, a maximum likelihood procedure using the source of sequence on the chip as a reference was deve-loped by gresham et al.
<cit>  to take advantage of overlapping tile data to call sfps.
as each microarray and experiment design tends to be different, new methods for analysis have been developed in attempts to gain greater specificity and sensitivity.
cultivated lettuce, l. sativa, has substantial genetic and genomic resources including approximately  <dig>  ests and another  <dig>  to  <dig>  ests in each of four related species .
furthermore, several mapping populations have been developed including a reference mapping population of 214f <dig> recombinant inbred lines  between l. sativa cv.
salinas and l. serriola acc.
us96uc <dig> .
this population segregates for multiple agronomic, disease resistance and quality traits.
it has approximately  <dig>  mapped dna markers comprised of approximately  <dig> mapped unigenes with the remainder amplified fragment length polymorphisms , restriction fragment length polymorphisms  and simple sequence repeats   <cit> .
the large number of available sequences and recombinant inbred lines provide ideal resources for further marker discovery and high density mapping.
considerable genetic resources are also available within germplasm collections of l. sativa.
furthermore, several lactuca species have variable cross-compatibility with l. sativa <cit>  and represent a diverse genetic resource for investigations of novel alleles and population structure.
in this paper, we describe the development of a microarray designed to provide extensive gene coverage and maximize detection of sfps for marker discovery and genotyping in lettuce.
we analyzed the parents of the reference l. sativa x l. serriola mapping population to demonstrate that dna representing complex genomes   <cit>  can be effectively hybridized onto microarrays.
parameters affecting dna hybridization and accurate detection of polymorphism were optimized.
algorithms from west et al.
<cit>  and borevitz et al.
<cit>  were modified to take advantage of the overlapping tile design to detect polymorphisms.
the use of the multiple probes covering a single position led to the identification of single position polymorphisms .
additionally, we assessed spps in a diverse panel of lactuca species concentrating on the cultivated l. sativa.
RESULTS
identification of a non-redundant consolidated unigene set from lactuca spp.
for design of an oligonucleotide array
a consolidated lactuca unigene set  was created using stringent cap <dig> conditions  <cit> .
this set represented all the currently available genes in march  <dig> that had been identified in cdna libraries prepared from l. sativa cv.
salinas, plus additional genes that were not present in those libraries from four other related species of lactuca .
the selection of unigenes was performed reiteratively in order of increasing genetic divergence from l. sativa; first, unigenes from l. serriola, us96uc <dig>  were analyzed by tblastx followed by unigenes from l. saligna, l. virosa and lastly l. perennis.
the final set comprised of  <dig>  unigenes from l. sativa plus  <dig> ,  <dig> ,  <dig>  and  <dig>  from l. serriola, l. saligna, l. virosa, and l. perennis respectively, totaling  <dig>  unigenes from the four other lactuca species .
this resulted in a final clus of  <dig>  unigenes .
an additional  <dig> unique l. sativa genomic sequences possessing a tblastx hit  to the arabidopsis genome and characterized mrna sequences were then mined from genbank and added, resulting in a final list of  <dig>  lactuca sequences that were submitted to affymetrix for probe design.
design of microarray with overlapping probes
in collaboration with affymetrix, probes from both sense and anti-sense strands were selected to create a  <dig> bp overlapping tiling path .
the resulting  <dig>  million candidate probes designed from the  <dig>  submitted sequences were triaged down to ~ <dig>  million that could be accommodated on the chip through a series of steps based on: 1) affymetrix probe quality score  except for a select set of unigenes with putative polymorphisms where probes with a quality score above  <dig>  were retained.
2) probes matching mitochondrial or chloroplast genomes were discarded.
3) probes that matched to more than one target were synthesized only once on the chip and computationally associated to corresponding unigene for analysis.
in addition to lettuce probes, background and standard affymetrix control probes  <cit>  were included on the microarray.
in order to determine background hybridization signal,  <dig>  anti-genomic  background probes were synthesized on the microarray, with an average of  <dig>  probes representing each g/c bin .
these ag probes represent sequences that had no blast hits in genbank at the time of chip design.
the use of ag probes reduced the number of probes included on the chip for background correction by 99% compared to the use of mismatch probes , without substantially compromising the ability to perform accurate background correction  <cit> .
from  <dig>  visually interrogated est contigs, ~ <dig>  putatively polymorphic regions  were represented from  <dig>  contigs.
in total,  <dig> , <dig> lettuce probes representing  <dig>  unigenes were synthesized on the microarray.
the average and median number of probes representing a unigene were both  <dig>  with ~80% of the unigenes being represented by  <dig> to  <dig> probes per sequence .
each unigene had an average of  <dig> bps and median of  <dig> bps covered by probes; the average number of contiguous stretches of overlapping probes per unigene is  <dig> .
due to the selection parameters described above, a contiguous overlapping tile across the unigenes was not possible.
consequently, the average and median lengths of the contiguous stretches of overlapping probes within probe sets are  <dig> and  <dig> bps, respectively.
regions of high or low g/c content were sparsely covered by probes  likely due to the removal of probes with low affymetrix probe quality scores.
the total number of probes on the array was  <dig> , <dig>
preparation and hybridization of genomic dna to the lettuce genechip
large amounts of high quality genomic dna were a critical prerequisite for robust hybridization signals .
to meet these criteria we compared fragmented genomic dna to amplified dna using whole genome amplification  from sigma .
analysis of scatter plots comparing hybridization intensities resulting from amplified and unamplified genomic dna revealed that wga resulted in marked biases .
high quality dna was extracted for each of l. sativa cv.
salinas and l. serriola acc.
us96uc <dig>  each of these extractions were hybridized twice providing two technical replicates and hybridization intensities were evaluated using scatter plots of  <dig>  random probes  or probes belonging to a set of ultra-conserved sequences .
comparison between replicates showed a nearly 97% correlation while between species showed approximately 93% correlation indicating infrequent hybridization differences as expected with low rates of polymorphism between the two species.
we investigated several methods for fragmentation and labeling of genomic dna including the bioprime kit .
although incorpo-ration of biotinylated dctp during amplification of target sequence via random priming resulted in elevated hybridization intensities compared to end-labeling of fragmented dna, hybridization intensity of both lettuce and background probes increased with gc content dramatically , resulting in a decreased number of informative probes  with high gc content .
we concluded that direct fragmentation of genomic dna by digestion with dnase i and end-labeling was the most cost and time effective, least biased , and most informative method for preparing genomic dna for hybridization to microarrays.
to determine the quantity of genomic dna required to achieve adequate hybridization, three different quantities of genomic dna,  <dig>  ,  <dig>  and  <dig> μg, from l. sativa cv.
salinas were sheared with dnase i and end-labeled.
the number of lettuce-specific probes with fluorescent intensities above the 90th percentile intensity for the ag control probes in the same gc bin was determined for each sample .
the  <dig> μg sample of fragmented dna yielded the highest percent of probes above the 90th percentile  in these gc bins when compared to the  <dig>   and  <dig> μg  dna samples .
dnase i fragmentation conditions were consequently optimized for this amount to consistently provide fragments predominantly between  <dig> and  <dig> bp in length .
thirty micrograms was selected as the standard concentration of genomic dna for subsequent experiments.
improvement of the algorithm for detecting polymorphisms
the algorithms developed previously by west et al.
<cit> , were modified to take advantage of the tiling design of the lettuce genechip®.
the new algorithm calculated the sfpdev value for each of the probes that overlap a given position and then performed a sliding window analysis to calculate an average weighted sfpdev value for each  <dig> bp position across the unigene covered by at least one probe.
this strategy markedly reduced background noise relative to individual probe measurements .
additionally, removal of probes below the 90th percentile of ag probes in the same gc bin increased confidence in calls while identifying polymorphisms missed by inclusion of poorly performing probes .
an empirically determined weighting factor based on sensitivity of bases within an oligo to sequence polymorphisms  was included in our custom algorithm to give more significance to the  <dig> most centrally located bases in a probe.
this weighting factor allowed us to retain probes nearest the edges of tiling blocks where polymorphism could be found, but reduced the emphasis given to spps detected by those probes rather than disregarding them completely, allowing users to potentially filter out or retain them.
as our algorithm uses data from multiple informative features that interrogated each  <dig> base pair position rather than a single feature, we designated the polymorphisms detected as single position polymorphisms .
we also modified the algorithm described by borevitz et al.
<cit>  for detection of sfps to exploit the tiling array design.
this modified sfp algorithm  interrogated all weighted probes above background at every  <dig> bp position, and calculated a d-stat similar to that described by borevitz et al.
<cit> .
this, however, was done for each position rather than each probe.
a false disco-very rate was calculated for each threshold cutoff value for both pairwise analyses using permutation analysis as described by borevitz et al.
<cit> .
detection of spps betweenl.
sativa cv.
salinasandl.
serriola acc.
us96uc23
genomic dna from l. sativa cv.
salinas  and wild l. serriola acc.
us96uc <dig>  were hybridized to the genechip® in three technical replicates.
the affymetrix .cel file data were background-corrected by rma and quantile-normalized across all chips.
the data were analyzed for spps using both our modified sfpdev and msa algorithms.
spps were filtered to require a minimum  <dig> bp range and two informative probes covering the interrogated position to increase confidence in the spps called.
spps were defined by the range of positions  that met a selected fdr value of  <dig>  and a delta value of  <dig>  for the sfpdev and msa methods, respectively.
furthermore, only the sfpdev values with a ratio  less than  <dig> were considered, as values above one had an actual fdr of 79%.
with these requirements the sfpdev method identified  <dig>  spps in  <dig>  contigs; while  <dig>  spps in  <dig>  contigs were identified with the msa method.
the coincidence of reported spps between the two methods showed that  <dig> % of spps detected by the sfpdev method were found by msa, and  <dig> % of spps reported by msa were found by sfpdev.
to provide an independent assessment of polymorphisms, illumina mrna-seq reads  from l. sativa cv.
salinas and l. serriola acc.
us96uc <dig> were aligned to the unigenes used for chip design to identify a set of snps.
identified spps were compared to this set as well as spps identified and mapped in the reference ril population  <cit>  to validate the true and false positive rate of our detection methods.
further, if the spp regions were identified as being duplicated in the genome they were removed as they were falsely called one third of the time .
using the modified sfpdev method with an estimated fdr of  <dig> ,  <dig>  spps with an actual fdr of  <dig> % were identified.
our msa method at a delta value of  <dig>  with an estimated fdr of  <dig> % filtered for the same conditions as above called  <dig>  spps with an actual fdr of  <dig> %.
table  <dig> shows the relative numbers of spps identified and their corresponding fdrs for each method.
the modified sfpdev and msa methods provide pair-wise comparisons but are too computationally intensive to assess polymorphisms between many pairs of lines.
therefore, a third analysis was performed using the ril algorithm method described by truco et al.
<cit> .
all  <dig> bp windows were assessed for bimodal distributions in hybridization values from a diverse panel of genotypes composed of  <dig> accessions from five lactuca species including the parents, salinas and us96uc <dig>  of the reference ril mapping population.
selection of spps that were identified as polymorphic between these two parental lines using this method identified  <dig>  spps.
this set was filtered with the same criteria as described above and included no inconsistent data points yielding an actual fdr of only  <dig> %.
a venn diagram of contigs with spps was created to show the coincidence of potentially polymorphic contigs detected using each method .
we included polymorphic contigs rather than snps detected in this figure as the spps reported are ranges.
these ranges often covered more than one snp rendering it impossible to determine which polymorphism was the contributor to the detected spp.
overall, the majority of contigs containing spps identified by each of the three methods coincide .
the two methods that have the largest overlap  were the two pair-wise comparison methods .
analysis of a diversity panel
the massively parallel genotyping of  <dig> lines  using the modified ril algorithm was employed to investigate inter- and intra-specific polymorphisms.
the spps were filtered to allow zero missing and zero inconsistent data, coverage by a minimum of two probes at the interrogated position, a minimum spp width of  <dig> bp and a sfpdev ratio of  <dig> .
this resulted in  <dig>  spps from  <dig>  contigs.
the spps detected in the diversity panel, were further filtered to exclude any spps with a duplicate pattern of markers across genotypes within the same unigene yielding  <dig>  distinct haplotypes.
we were able to identify  <dig>  spps that showed polymorphism between species but not within the five species in the diversity panel.
most were private to l. perennis, followed by l. virosa and l. saligna.
note : batavia and iceberg are sub-classes of the crisphead class.
polymorphism within l. sativa is most pertinent to breeding efforts.
to survey polymorphism within this species, spps were filtered from the  <dig>  previously described to include only those polymorphic within l. sativa resulting in  <dig>  spps on  <dig>  contigs.
the leafy and batavia crisphead plant types had the most diversity while iceberg crisphead contained the least .
however,  <dig>  spps were identified even within the iceberg type allowing distinction of cultivars within this genetically narrow plant type.
several spps showed diversity within one plant type, while being monomorphic in other l. sativa types.
a) the number of contigs containing spps and the number of spps private to the genotypes within a species.
these spps distinguish all the genotypes in a species from all others in the panel.
b) the number of contigs containing spps and the number of spps for each l. sativa horticultural class.
these markers are polymorphic within a class but not specific to that class.
a phylogenetic analysis was then performed with the phylip  <dig>  package  <cit> .
using the filtered  <dig>  marker set for the  <dig> genotypes, a bootstrap consensus tree was constructed .
a representative phylogram  estimates the genetic differences between the genotypes in the panel.
the l. sativa genotypes separated into two distinct clades with 100% bootstrap value separating butterheads from the cos and majority of crisphead types.
the leafy lettuce genotypes showed high variability locating within both the butterhead and cos/crisphead clades.
iceberg varieties showed the least amount of polymorphism and grouped together in a monophyletic clade with 100% bootstrap support.
one genotype, bsp <dig>  showed a l. sativa-like morphology but has a seed shattering phenotype characteristic of the wild species, positioned between the wild species and the remaining l. sativa with 100% support.
upon further analysis, branch lengths of l. sativa genotypes indicate similar divergence from their common ancestor with the exception of bsp <dig> and ucd <dig>  .
two separate principal component analyses  were performed on the entire diversity panel as well as on just l. sativa.
the first three eigenvalues account for  <dig> % of the variation seen across all five species.
while each of the three principal components  were significant at < <dig>  when separated by species, two dimensional scatter plots of pc values for each genotype using the first two pc show clear separation of species .
when considering separation between types within l. sativa, the first three pcs accounted for  <dig> % of the variation within the population with the first and third pcs being significant at < <dig> .
a two dimensional plot  of the first and third pc values showed some overlap of types consistent with figure 7a.
two genotypes, ucd <dig> and bsp <dig>  are again outliers and show drastic deviation from the rest of the l. sativas .
discussion
highly parallel genotyping has become an important component of genomics.
hybridization of genomic dna and rna to microarrays has been used in the past for detection of polymorphisms between genotypes  <cit> .
however, the previously available arrays for complex genomes only provided limited transcriptome coverage.
we developed an array designed to maximize transcriptome coverage while maintaining the possibility of performing other analyses.
our custom designed lettuce genechip® combined the benefits of overlapping probes across unigenes, similar to that demonstrated by gresham et al.
<cit>  for yeast, with the use of anti-genomic probes to maximize the possible coverage of unigenes while maintaining the sensitivity to detect polymorphisms and retaining appropriate controls to normalize and correct for background noise.
the tiling path design allows for multiple assessments of hybridization differences between lines for single positions rather than single assessments of a few positions as obtained with most expression arrays.
we developed custom scripts for analysis of our hybridization data taking into account the multiple probes covering a single position as well as filtering out poorly performing probes.
we used recent advances in high throughput sequencing technology to validate our spp calls as well as filter out potentially unreliable data.
genomic dna and cdna are two options for hybridization to an array for sfp detection.
the decision of which to use becomes more difficult as genome size and complexity increases.
dna as well as cdna are both viable targets for species with smaller genomes such as arabidopsis  <cit>  and rice  <cit> .
however, with larger and more complex genomes such as barley, cdna was indicated as a more reliable option for hybridization even with the added difficulty of subtracting out expression effects  <cit> .
the genome of lettuce is nearly 17x larger than arabidopsis although it is half the size of barley.
given the difficulty of accounting for spatio-temporal expression effects as seen in cdna, we focused on developing methods to use genomic dna.
rostoks et al.
<cit>  suggested that genomic dna may be a feasible target in larger genomes with added replication.
with the redundancy of the overlapping probes in the lettuce array, the need for additional replication was reduced because they provide technical replicates within a chip.
the need for additional replication may also have been reduced by using elevated amounts of genomic dna and the use of end-labeling rather than bioprime may have increased the reliability of calls.
the protocol used for hybridization of lettuce genomic dna was also subsequently highly effective for pepper  and other solanaceae  <cit> .
furthermore, the use of genomic dna is a desirable target because sfps identified using cdna may be a result of alternate splicing or gene expression differences  <cit> .
rostoks et al.
<cit>  indicated that 40% of the sfps they identified may have been falsely called and partially explained them as being mrna structural variants.
they also reported a high predicted false positive rate of 22%  for sfps detected using genomic dna.
we concluded that fragmented, end-labeled genomic dna provided a suitable target for detection of polymorphisms while reducing false positive sequence polymorphism .
the overlapping tile design increases the likelihood of detecting polymorphisms due to redundancy at individual positions, coverage along the contigs and optimal position of the snp within a probe  <cit> .
furthermore, the number of probes and hence the possible genome coverage was increased by substituting mismatch probes with ag probes for background correction and normalization of data.
because the peripheral  <dig> to  <dig> bases of a  <dig> bp oligonucleotide are less sensitive than the central bases, in terms of detecting sequence polymorphisms  <cit> , figure  <dig>   <cit> , the tiling strategy reduces the loss of coverage due to probe position.
the number and reliability of spp calls in our experiments demonstrates that the overlapping tiling array design has improved coverage, sensitivity and specificity to detect polymorphisms.
spp calls were validated using several approaches.
the data from the two pair-wise comparisons  yielded  <dig> to  <dig> thousand and  <dig> to  <dig> thousand spps respectively, depending on the criteria used for specificity and sensitivity.
when spps from msa and sfpdev were compared to the  <dig>  snps detected between rnaseq reads of salinas and us96uc <dig>   <dig> % and  <dig> % were found in or within at least  <dig> bp of the spp range respectively, similar to that described by gresham et al.
<cit> .
however, because of the high fdr associated with duplicated sequences, spps that were found to have a duplicated locus within the chip assembly, the gene space assembly or the genome assembly were removed from consideration; one third of the spps called that had duplicated loci did not contain a snp in any of our validation tests.
these identified spps likely were due to differences between paralogs rather than alleles at a single locus.
due to the increased redundancy  provided by the mapping population of  <dig> rils compared to the pair-wise comparison of the parents, spps in the sfpdev and msa pair-wise comparisons that coincided with spp mapped by truco et al.
<cit>  but were absent of a snp were considered real.
removal of duplicated loci and inclusion of mapped spps provided a balance between false positive and false negative rates and allowed us to optimize fdr while still discovering a high number of spps.
taking into consideration the lower observed fdr  we concluded that the msa method performed best as a pairwise comparison; however using multiple detection methods would yield a higher confidence in the subset of spps identified by both methods.
the spps identified in the diversity panel  that were polymorphic between l. sativa cv.
salinas  and l. serriola acc.
us96uc <dig>  showed a low fdr.
however, as a result of the filtering, sensitivity of this analysis  was reduced compared to the two-genotype analyses by msa and sfpdev.
specific analysis of the dp data for regions containing known snps showed that sfpdev values would have been significant in a pair-wise comparison, between sal and ser but due to inclusion of data from all genotypes in the dp, the two were not called as polymorphic .
the lack of some called spps in the dp may be due to larger genetic differences between l. perennis, l. virosa, or l. saligna relative to l. serriola and l. sativa.
as a result of smaller hybridization differences between the more closely related genotypes, genotypes differing at a locus may have been grouped together reducing the number of spps called between the two genotypes.
consequently, the dp analysis showed a lower false positive rate, but a higher false negative rate when comparing sal and ser to sequence and mapping data.
as part of our goal was to investigate the diversity and relationships of the genotypes in the dp, spps identified by the dp analysis were evaluated.
removal of spps in duplicated regions with inconsistent data or missing data  was a reasonable method of removing unreliable data as these data may be from poorly performing probes in one or all replicates, heterozygous loci, paralogous genes or deleted genes.
there was not a large difference in the observed fdrs for the three spfdev cutoff values  for the dp analysis; so in order to maximize the number of markers used in our phylogenetic analysis and principal component analysis, we used the least stringent cutoff value of  <dig> .
as the assumptions for analysis with the phylip  <cit>  package were not violated with the large number of markers, they were left as independent.
to meet the constraints of the pc analysis software, markers were limited to those that were mapped.
the markers discovered in our dp analysis were used to generate a phylogenetic tree showing species separation with 100% boot strap support.
l. virosa and l. saligna are sexually incompatible species with l. sativa <cit>  and appear to be more closely related to each other than to other species in the dp.
our data supports the conclusion by kesseli et al.
<cit> , that these two species are not progenitors of l. sativa.
by limiting markers to those polymorphic within cultivated lettuce we are able to separate most genotypes into classes representing each of the plant types.
the butterhead type formed a distinct clade from the iceberg and cos types with 100% bootstrap support.
however, the leafy type and the batavia type both showed a wide distribution across the l. sativa clade.
this is not unexpected and may reflect admixture between types during breeding programs.
alternatively, this distribution may indicate that these types are artificial polyphyletic groups based on loose morphological criteria  <cit> .
the leafy types are non-heading with a broad range of leaf morphology  <cit> .
batavia types vary from heading to non-heading phenotypes.
batavia and iceberg cultivars are both considered crisphead types  <cit> ; however our phylogenetic and pc analyses showed that the two did not cluster together and are significantly different from each other .
rapid advancements in sequencing technology today are changing the methods for genetic analyses.
microarray technology presented in this paper yielded an in depth analysis of diversity for lettuce germplasm separating even closely related lines such as the crisphead class.
it also has potentially several other uses including: detection of copy number variants, splice site identification, expression analysis or use with other species within the compositae.
the spps identified in this study were highly reproducible and showed similar false positive results to current sequencing methods in the literature  <cit> .
this technology has also been used to create an ultra-dense, inter-specific genetic map between l. sativa cv.
salinas and l. serriola acc.
us96uc <dig> to dissect phenotypic traits as well as validate and align genomic assemblies of lettuce into chromosomal linkage groups  <cit> .
CONCLUSIONS
we designed and exploited a custom lettuce microarray using an overlapping tiling path and by using anti-genomic probes rather than mismatch probes to provide comprehensive unigene coverage.
our protocols for genomic dna preparation and labeling, assisted by positional vs. feature-based analyses reliably identified dna polymorphisms using both pair-wise genotype comparisons as well as a highly parallel comparison within a diverse panel of genotypes including five species and focused on the cultivated l. sativa.
the phylogenetic and principal component analyses clearly distinguished species while the analysis of l. sativa supports previous analyses of cultivated lettuce and revealed differences among the more heterogeneous horticultural types as well as polymorphisms within the most genetically narrow type.

 various types of microarrays have been used extensively for gene expression studies and, more recently, for genotyping and marker discovery. affymetrix microarrays in particular offer a massively-parallel approach to genotyping. the basis of identifying polymorphisms, termed single feature polymorphisms, is differential hybridization of template rna or dna onto bp oligonucleotide probes on the array due to the presence of single nucleotide polymorphisms or small insertion/deletions. using this approach, thousands of genes can be queried and simultaneously analyzed allowing whole genome approaches to mapping genes and quantitative trait loci discovery, as well as determining linkage disequilibrium and population structure. when arrays represent coding sequences, they can also be used for genotyping closely related species. although affymetrix expression arrays can be used for genotyping, their drawback is that all except the most recently produced microarrays have been designed with approximately perfect match probes per unigene giving only limited coverage of each gene. gresham et al. showed that an array designed with bp oligos in a bp overlapping tile format had greater sensitivity in yeast and increased specificity in calling sfps. this overlapping tile design offers technical reproducibility and extensive genome coverage if the number of features on the microarray is sufficient. genotyping by microarray hybridization has proven to be challenging in species with complex genomes. microarrays have been successfully used to detect sfps in small genomes, for example the mb genome of yeast, the mb genome of arabidopsis and, more recently, the mb genome of rice. although different algorithms were used for each of these three species, 87% of the sfps in yeast and 75% of those in rice and arabidopsis were independently validated. to identify polymorphisms in the barley genome, complexity was circumvented by using rna to hybridize to the microarray and 67% to 80% validation of sfps was achieved. when dna from barley was hybridized directly to the barley genechip® a significant overlap between sfps identified using genomic dna and those identified and validated using rna was reported. the increased efficiency reported by rostoks et al. from using rna is, however, complicated by incomplete and variable transcriptome representation due to tissue- and environment-specific gene expression and false sfp discovery due to alternative splicing or adenylation associated with sampling rna versus dna. several types of analyses have been implemented for sfp detection from microarray data. generally, the data have been processed using expression analysis software to correct for background signal variation using robust multi-array analysis followed by correction for overall signal variation by quantile normalization across arrays. to call sfps, a modified t-test, robustified projection pursuit and sfp de-viation have been developed to first estimate the normalized hybridization of a reference set of probes and then test with appropriate statistics or ratios for differential hybridization of specific probes across genotypes. in addition, a maximum likelihood procedure using the source of sequence on the chip as a reference was deve-loped by gresham et al. to take advantage of overlapping tile data to call sfps. as each microarray and experiment design tends to be different, new methods for analysis have been developed in attempts to gain greater specificity and sensitivity. cultivated lettuce, l. sativa, has substantial genetic and genomic resources including approximately ests and another to ests in each of four related species. furthermore, several mapping populations have been developed including a reference mapping population of 214f recombinant inbred lines between l. sativa cv. salinas and l. serriola acc. us96uc. this population segregates for multiple agronomic, disease resistance and quality traits. it has approximately mapped dna markers comprised of approximately mapped unigenes with the remainder amplified fragment length polymorphisms, restriction fragment length polymorphisms and simple sequence repeats. the large number of available sequences and recombinant inbred lines provide ideal resources for further marker discovery and high density mapping. considerable genetic resources are also available within germplasm collections of l. sativa. furthermore, several lactuca species have variable cross-compatibility with l. sativa and represent a diverse genetic resource for investigations of novel alleles and population structure. in this paper, we describe the development of a microarray designed to provide extensive gene coverage and maximize detection of sfps for marker discovery and genotyping in lettuce. we analyzed the parents of the reference l. sativa x l. serriola mapping population to demonstrate that dna representing complex genomes can be effectively hybridized onto microarrays. parameters affecting dna hybridization and accurate detection of polymorphism were optimized. algorithms from west et al. and borevitz et al. were modified to take advantage of the overlapping tile design to detect polymorphisms. the use of the multiple probes covering a single position led to the identification of single position polymorphisms. additionally, we assessed spps in a diverse panel of lactuca species concentrating on the cultivated l. sativa.  identification of a non-redundant consolidated unigene set from lactuca spp. for design of an oligonucleotide array a consolidated lactuca unigene set was created using stringent cap conditions. this set represented all the currently available genes in march that had been identified in cdna libraries prepared from l. sativa cv. salinas, plus additional genes that were not present in those libraries from four other related species of lactuca. the selection of unigenes was performed reiteratively in order of increasing genetic divergence from l. sativa; first, unigenes from l. serriola, us96uc were analyzed by tblastx followed by unigenes from l. saligna, l. virosa and lastly l. perennis. the final set comprised of unigenes from l. sativa plus,, and from l. serriola, l. saligna, l. virosa, and l. perennis respectively, totaling unigenes from the four other lactuca species. this resulted in a final clus of unigenes. an additional unique l. sativa genomic sequences possessing a tblastx hit to the arabidopsis genome and characterized mrna sequences were then mined from genbank and added, resulting in a final list of lactuca sequences that were submitted to affymetrix for probe design. design of microarray with overlapping probes in collaboration with affymetrix, probes from both sense and anti-sense strands were selected to create a bp overlapping tiling path. the resulting million candidate probes designed from the submitted sequences were triaged down to ~ million that could be accommodated on the chip through a series of steps based on: 1) affymetrix probe quality score except for a select set of unigenes with putative polymorphisms where probes with a quality score above were retained. 2) probes matching mitochondrial or chloroplast genomes were discarded. 3) probes that matched to more than one target were synthesized only once on the chip and computationally associated to corresponding unigene for analysis. in addition to lettuce probes, background and standard affymetrix control probes were included on the microarray. in order to determine background hybridization signal, anti-genomic background probes were synthesized on the microarray, with an average of probes representing each g/c bin. these ag probes represent sequences that had no blast hits in genbank at the time of chip design. the use of ag probes reduced the number of probes included on the chip for background correction by 99% compared to the use of mismatch probes, without substantially compromising the ability to perform accurate background correction. from visually interrogated est contigs, ~ putatively polymorphic regions were represented from contigs. in total,, lettuce probes representing unigenes were synthesized on the microarray. the average and median number of probes representing a unigene were both with ~80% of the unigenes being represented by to probes per sequence. each unigene had an average of bps and median of bps covered by probes; the average number of contiguous stretches of overlapping probes per unigene is. due to the selection parameters described above, a contiguous overlapping tile across the unigenes was not possible. consequently, the average and median lengths of the contiguous stretches of overlapping probes within probe sets are and bps, respectively. regions of high or low g/c content were sparsely covered by probes likely due to the removal of probes with low affymetrix probe quality scores. the total number of probes on the array was, preparation and hybridization of genomic dna to the lettuce genechip large amounts of high quality genomic dna were a critical prerequisite for robust hybridization signals. to meet these criteria we compared fragmented genomic dna to amplified dna using whole genome amplification from sigma. analysis of scatter plots comparing hybridization intensities resulting from amplified and unamplified genomic dna revealed that wga resulted in marked biases. high quality dna was extracted for each of l. sativa cv. salinas and l. serriola acc. us96uc each of these extractions were hybridized twice providing two technical replicates and hybridization intensities were evaluated using scatter plots of random probes or probes belonging to a set of ultra-conserved sequences. comparison between replicates showed a nearly 97% correlation while between species showed approximately 93% correlation indicating infrequent hybridization differences as expected with low rates of polymorphism between the two species. we investigated several methods for fragmentation and labeling of genomic dna including the bioprime kit. although incorpo-ration of biotinylated dctp during amplification of target sequence via random priming resulted in elevated hybridization intensities compared to end-labeling of fragmented dna, hybridization intensity of both lettuce and background probes increased with gc content dramatically, resulting in a decreased number of informative probes with high gc content. we concluded that direct fragmentation of genomic dna by digestion with dnase i and end-labeling was the most cost and time effective, least biased, and most informative method for preparing genomic dna for hybridization to microarrays. to determine the quantity of genomic dna required to achieve adequate hybridization, three different quantities of genomic dna,, and μg, from l. sativa cv. salinas were sheared with dnase i and end-labeled. the number of lettuce-specific probes with fluorescent intensities above the 90th percentile intensity for the ag control probes in the same gc bin was determined for each sample. the μg sample of fragmented dna yielded the highest percent of probes above the 90th percentile in these gc bins when compared to the and μg dna samples. dnase i fragmentation conditions were consequently optimized for this amount to consistently provide fragments predominantly between and bp in length. thirty micrograms was selected as the standard concentration of genomic dna for subsequent experiments. improvement of the algorithm for detecting polymorphisms the algorithms developed previously by west et al., were modified to take advantage of the tiling design of the lettuce genechip®. the new algorithm calculated the sfpdev value for each of the probes that overlap a given position and then performed a sliding window analysis to calculate an average weighted sfpdev value for each bp position across the unigene covered by at least one probe. this strategy markedly reduced background noise relative to individual probe measurements. additionally, removal of probes below the 90th percentile of ag probes in the same gc bin increased confidence in calls while identifying polymorphisms missed by inclusion of poorly performing probes. an empirically determined weighting factor based on sensitivity of bases within an oligo to sequence polymorphisms was included in our custom algorithm to give more significance to the most centrally located bases in a probe. this weighting factor allowed us to retain probes nearest the edges of tiling blocks where polymorphism could be found, but reduced the emphasis given to spps detected by those probes rather than disregarding them completely, allowing users to potentially filter out or retain them. as our algorithm uses data from multiple informative features that interrogated each base pair position rather than a single feature, we designated the polymorphisms detected as single position polymorphisms. we also modified the algorithm described by borevitz et al. for detection of sfps to exploit the tiling array design. this modified sfp algorithm interrogated all weighted probes above background at every bp position, and calculated a d-stat similar to that described by borevitz et al.. this, however, was done for each position rather than each probe. a false disco-very rate was calculated for each threshold cutoff value for both pairwise analyses using permutation analysis as described by borevitz et al.. detection of spps betweenl. sativa cv. salinasandl. serriola acc. us96uc23 genomic dna from l. sativa cv. salinas and wild l. serriola acc. us96uc were hybridized to the genechip® in three technical replicates. the affymetrix.cel file data were background-corrected by rma and quantile-normalized across all chips. the data were analyzed for spps using both our modified sfpdev and msa algorithms. spps were filtered to require a minimum bp range and two informative probes covering the interrogated position to increase confidence in the spps called. spps were defined by the range of positions that met a selected fdr value of and a delta value of for the sfpdev and msa methods, respectively. furthermore, only the sfpdev values with a ratio less than were considered, as values above one had an actual fdr of 79%. with these requirements the sfpdev method identified spps in contigs; while spps in contigs were identified with the msa method. the coincidence of reported spps between the two methods showed that % of spps detected by the sfpdev method were found by msa, and % of spps reported by msa were found by sfpdev. to provide an independent assessment of polymorphisms, illumina mrna-seq reads from l. sativa cv. salinas and l. serriola acc. us96uc were aligned to the unigenes used for chip design to identify a set of snps. identified spps were compared to this set as well as spps identified and mapped in the reference ril population to validate the true and false positive rate of our detection methods. further, if the spp regions were identified as being duplicated in the genome they were removed as they were falsely called one third of the time. using the modified sfpdev method with an estimated fdr of, spps with an actual fdr of % were identified. our msa method at a delta value of with an estimated fdr of % filtered for the same conditions as above called spps with an actual fdr of %. table shows the relative numbers of spps identified and their corresponding fdrs for each method. the modified sfpdev and msa methods provide pair-wise comparisons but are too computationally intensive to assess polymorphisms between many pairs of lines. therefore, a third analysis was performed using the ril algorithm method described by truco et al.. all bp windows were assessed for bimodal distributions in hybridization values from a diverse panel of genotypes composed of accessions from five lactuca species including the parents, salinas and us96uc of the reference ril mapping population. selection of spps that were identified as polymorphic between these two parental lines using this method identified spps. this set was filtered with the same criteria as described above and included no inconsistent data points yielding an actual fdr of only %. a venn diagram of contigs with spps was created to show the coincidence of potentially polymorphic contigs detected using each method. we included polymorphic contigs rather than snps detected in this figure as the spps reported are ranges. these ranges often covered more than one snp rendering it impossible to determine which polymorphism was the contributor to the detected spp. overall, the majority of contigs containing spps identified by each of the three methods coincide. the two methods that have the largest overlap were the two pair-wise comparison methods. analysis of a diversity panel the massively parallel genotyping of lines using the modified ril algorithm was employed to investigate inter- and intra-specific polymorphisms. the spps were filtered to allow zero missing and zero inconsistent data, coverage by a minimum of two probes at the interrogated position, a minimum spp width of bp and a sfpdev ratio of. this resulted in spps from contigs. the spps detected in the diversity panel, were further filtered to exclude any spps with a duplicate pattern of markers across genotypes within the same unigene yielding distinct haplotypes. we were able to identify spps that showed polymorphism between species but not within the five species in the diversity panel. most were private to l. perennis, followed by l. virosa and l. saligna. note: batavia and iceberg are sub-classes of the crisphead class. polymorphism within l. sativa is most pertinent to breeding efforts. to survey polymorphism within this species, spps were filtered from the previously described to include only those polymorphic within l. sativa resulting in spps on contigs. the leafy and batavia crisphead plant types had the most diversity while iceberg crisphead contained the least. however, spps were identified even within the iceberg type allowing distinction of cultivars within this genetically narrow plant type. several spps showed diversity within one plant type, while being monomorphic in other l. sativa types. a) the number of contigs containing spps and the number of spps private to the genotypes within a species. these spps distinguish all the genotypes in a species from all others in the panel. b) the number of contigs containing spps and the number of spps for each l. sativa horticultural class. these markers are polymorphic within a class but not specific to that class. a phylogenetic analysis was then performed with the phylip package. using the filtered marker set for the genotypes, a bootstrap consensus tree was constructed. a representative phylogram estimates the genetic differences between the genotypes in the panel. the l. sativa genotypes separated into two distinct clades with 100% bootstrap value separating butterheads from the cos and majority of crisphead types. the leafy lettuce genotypes showed high variability locating within both the butterhead and cos/crisphead clades. iceberg varieties showed the least amount of polymorphism and grouped together in a monophyletic clade with 100% bootstrap support. one genotype, bsp showed a l. sativa-like morphology but has a seed shattering phenotype characteristic of the wild species, positioned between the wild species and the remaining l. sativa with 100% support. upon further analysis, branch lengths of l. sativa genotypes indicate similar divergence from their common ancestor with the exception of bsp and ucd. two separate principal component analyses were performed on the entire diversity panel as well as on just l. sativa. the first three eigenvalues account for % of the variation seen across all five species. while each of the three principal components were significant at < when separated by species, two dimensional scatter plots of pc values for each genotype using the first two pc show clear separation of species. when considering separation between types within l. sativa, the first three pcs accounted for % of the variation within the population with the first and third pcs being significant at <. a two dimensional plot of the first and third pc values showed some overlap of types consistent with figure 7a. two genotypes, ucd and bsp are again outliers and show drastic deviation from the rest of the l. sativas. discussion highly parallel genotyping has become an important component of genomics. hybridization of genomic dna and rna to microarrays has been used in the past for detection of polymorphisms between genotypes. however, the previously available arrays for complex genomes only provided limited transcriptome coverage. we developed an array designed to maximize transcriptome coverage while maintaining the possibility of performing other analyses. our custom designed lettuce genechip® combined the benefits of overlapping probes across unigenes, similar to that demonstrated by gresham et al. for yeast, with the use of anti-genomic probes to maximize the possible coverage of unigenes while maintaining the sensitivity to detect polymorphisms and retaining appropriate controls to normalize and correct for background noise. the tiling path design allows for multiple assessments of hybridization differences between lines for single positions rather than single assessments of a few positions as obtained with most expression arrays. we developed custom scripts for analysis of our hybridization data taking into account the multiple probes covering a single position as well as filtering out poorly performing probes. we used recent advances in high throughput sequencing technology to validate our spp calls as well as filter out potentially unreliable data. genomic dna and cdna are two options for hybridization to an array for sfp detection. the decision of which to use becomes more difficult as genome size and complexity increases. dna as well as cdna are both viable targets for species with smaller genomes such as arabidopsis and rice. however, with larger and more complex genomes such as barley, cdna was indicated as a more reliable option for hybridization even with the added difficulty of subtracting out expression effects. the genome of lettuce is nearly 17x larger than arabidopsis although it is half the size of barley. given the difficulty of accounting for spatio-temporal expression effects as seen in cdna, we focused on developing methods to use genomic dna. rostoks et al. suggested that genomic dna may be a feasible target in larger genomes with added replication. with the redundancy of the overlapping probes in the lettuce array, the need for additional replication was reduced because they provide technical replicates within a chip. the need for additional replication may also have been reduced by using elevated amounts of genomic dna and the use of end-labeling rather than bioprime may have increased the reliability of calls. the protocol used for hybridization of lettuce genomic dna was also subsequently highly effective for pepper and other solanaceae. furthermore, the use of genomic dna is a desirable target because sfps identified using cdna may be a result of alternate splicing or gene expression differences. rostoks et al. indicated that 40% of the sfps they identified may have been falsely called and partially explained them as being mrna structural variants. they also reported a high predicted false positive rate of 22% for sfps detected using genomic dna. we concluded that fragmented, end-labeled genomic dna provided a suitable target for detection of polymorphisms while reducing false positive sequence polymorphism. the overlapping tile design increases the likelihood of detecting polymorphisms due to redundancy at individual positions, coverage along the contigs and optimal position of the snp within a probe. furthermore, the number of probes and hence the possible genome coverage was increased by substituting mismatch probes with ag probes for background correction and normalization of data. because the peripheral to bases of a bp oligonucleotide are less sensitive than the central bases, in terms of detecting sequence polymorphisms, figure, the tiling strategy reduces the loss of coverage due to probe position. the number and reliability of spp calls in our experiments demonstrates that the overlapping tiling array design has improved coverage, sensitivity and specificity to detect polymorphisms. spp calls were validated using several approaches. the data from the two pair-wise comparisons yielded to thousand and to thousand spps respectively, depending on the criteria used for specificity and sensitivity. when spps from msa and sfpdev were compared to the snps detected between rnaseq reads of salinas and us96uc % and % were found in or within at least bp of the spp range respectively, similar to that described by gresham et al.. however, because of the high fdr associated with duplicated sequences, spps that were found to have a duplicated locus within the chip assembly, the gene space assembly or the genome assembly were removed from consideration; one third of the spps called that had duplicated loci did not contain a snp in any of our validation tests. these identified spps likely were due to differences between paralogs rather than alleles at a single locus. due to the increased redundancy provided by the mapping population of rils compared to the pair-wise comparison of the parents, spps in the sfpdev and msa pair-wise comparisons that coincided with spp mapped by truco et al. but were absent of a snp were considered real. removal of duplicated loci and inclusion of mapped spps provided a balance between false positive and false negative rates and allowed us to optimize fdr while still discovering a high number of spps. taking into consideration the lower observed fdr we concluded that the msa method performed best as a pairwise comparison; however using multiple detection methods would yield a higher confidence in the subset of spps identified by both methods. the spps identified in the diversity panel that were polymorphic between l. sativa cv. salinas and l. serriola acc. us96uc showed a low fdr. however, as a result of the filtering, sensitivity of this analysis was reduced compared to the two-genotype analyses by msa and sfpdev. specific analysis of the dp data for regions containing known snps showed that sfpdev values would have been significant in a pair-wise comparison, between sal and ser but due to inclusion of data from all genotypes in the dp, the two were not called as polymorphic. the lack of some called spps in the dp may be due to larger genetic differences between l. perennis, l. virosa, or l. saligna relative to l. serriola and l. sativa. as a result of smaller hybridization differences between the more closely related genotypes, genotypes differing at a locus may have been grouped together reducing the number of spps called between the two genotypes. consequently, the dp analysis showed a lower false positive rate, but a higher false negative rate when comparing sal and ser to sequence and mapping data. as part of our goal was to investigate the diversity and relationships of the genotypes in the dp, spps identified by the dp analysis were evaluated. removal of spps in duplicated regions with inconsistent data or missing data was a reasonable method of removing unreliable data as these data may be from poorly performing probes in one or all replicates, heterozygous loci, paralogous genes or deleted genes. there was not a large difference in the observed fdrs for the three spfdev cutoff values for the dp analysis; so in order to maximize the number of markers used in our phylogenetic analysis and principal component analysis, we used the least stringent cutoff value of. as the assumptions for analysis with the phylip package were not violated with the large number of markers, they were left as independent. to meet the constraints of the pc analysis software, markers were limited to those that were mapped. the markers discovered in our dp analysis were used to generate a phylogenetic tree showing species separation with 100% boot strap support. l. virosa and l. saligna are sexually incompatible species with l. sativa and appear to be more closely related to each other than to other species in the dp. our data supports the conclusion by kesseli et al., that these two species are not progenitors of l. sativa. by limiting markers to those polymorphic within cultivated lettuce we are able to separate most genotypes into classes representing each of the plant types. the butterhead type formed a distinct clade from the iceberg and cos types with 100% bootstrap support. however, the leafy type and the batavia type both showed a wide distribution across the l. sativa clade. this is not unexpected and may reflect admixture between types during breeding programs. alternatively, this distribution may indicate that these types are artificial polyphyletic groups based on loose morphological criteria. the leafy types are non-heading with a broad range of leaf morphology. batavia types vary from heading to non-heading phenotypes. batavia and iceberg cultivars are both considered crisphead types; however our phylogenetic and pc analyses showed that the two did not cluster together and are significantly different from each other. rapid advancements in sequencing technology today are changing the methods for genetic analyses. microarray technology presented in this paper yielded an in depth analysis of diversity for lettuce germplasm separating even closely related lines such as the crisphead class. it also has potentially several other uses including: detection of copy number variants, splice site identification, expression analysis or use with other species within the compositae. the spps identified in this study were highly reproducible and showed similar false positive results to current sequencing methods in the literature. this technology has also been used to create an ultra-dense, inter-specific genetic map between l. sativa cv. salinas and l. serriola acc. us96uc to dissect phenotypic traits as well as validate and align genomic assemblies of lettuce into chromosomal linkage groups.  we designed and exploited a custom lettuce microarray using an overlapping tiling path and by using anti-genomic probes rather than mismatch probes to provide comprehensive unigene coverage. our protocols for genomic dna preparation and labeling, assisted by positional vs. feature-based analyses reliably identified dna polymorphisms using both pair-wise genotype comparisons as well as a highly parallel comparison within a diverse panel of genotypes including five species and focused on the cultivated l. sativa. the phylogenetic and principal component analyses clearly distinguished species while the analysis of l. sativa supports previous analyses of cultivated lettuce and revealed differences among the more heterogeneous horticultural types as well as polymorphisms within the most genetically narrow type. 
using marker data from our diversity panel comprised of accessions from the five species listed above, we were able to separate accessions by species using both phylogenetic and principal component analyses. however, microarrays designed for gene expression analysis rarely provide sufficient gene coverage for optimal detection of nucleotide polymorphisms, which limits utility in species with low rates of polymorphism such as lettuce. by hybridizing genomic dna to a custom oligonucleotide array designed for maximum gene coverage, we were able to identify polymorphisms using two approaches for pair-wise comparisons, as well as a highly parallel method that compared all genotypes simultaneously. hybridization to microarrays to detect single feature polymorphisms is a powerful technique for marker discovery and genotyping because of its highly parallel nature. this allowed us to detect greater than polymorphisms between the parental lines of our core mapping population, as well as numerous polymorphisms between cultivated lettuce and wild species in the lettuce genepool. we developed protocols for hybridization of genomic dna to the genechip® and refined custom algorithms that utilized coverage from multiple, high quality probes to detect single position polymorphisms in bp sliding windows across each unigene.
 high-resolution genetic maps are needed in many crops to help characterize the genetic diversity that determines agriculturally important traits. hybridization to microarrays to detect single feature polymorphisms is a powerful technique for marker discovery and genotyping because of its highly parallel nature. however, microarrays designed for gene expression analysis rarely provide sufficient gene coverage for optimal detection of nucleotide polymorphisms, which limits utility in species with low rates of polymorphism such as lettuce.  we developed a million feature affymetrix genechip® for efficient polymorphism discovery and genotyping, as well as for analysis of gene expression in lettuce. probes on the microarray were designed from unigenes from cultivated lettuce and an additional unigenes from four related species. where possible, probes were tiled with a bp stagger, alternating on each dna strand; providing an average of probes covering approximately bp for each of over unigenes; resulting in up to fold redundancy in coverage per nucleotide. we developed protocols for hybridization of genomic dna to the genechip® and refined custom algorithms that utilized coverage from multiple, high quality probes to detect single position polymorphisms in bp sliding windows across each unigene. this allowed us to detect greater than polymorphisms between the parental lines of our core mapping population, as well as numerous polymorphisms between cultivated lettuce and wild species in the lettuce genepool. using marker data from our diversity panel comprised of accessions from the five species listed above, we were able to separate accessions by species using both phylogenetic and principal component analyses. additionally, we estimated the diversity between different types of cultivated lettuce and distinguished morphological types.  by hybridizing genomic dna to a custom oligonucleotide array designed for maximum gene coverage, we were able to identify polymorphisms using two approaches for pair-wise comparisons, as well as a highly parallel method that compared all genotypes simultaneously. 