GENOME-WIDE LOCATION AND FUNCTION OF DNA BINDING PROTEINS

Abstract: The present invention relates to a method of identifying a region (one or more) of a genome of a cell to which a protein of interest binds. In the methods described herein, DNA binding protein of a cell is linked (e.g., covalently crosslinked) to genomic DNA of a cell. The genomic DNA to which the DNA binding protein is linked is removed and combined or contacted with DNA comprising a sequence complementary to genomic DNA of the cell under conditions in which hybridization between the identified genomic DNA and the sequence complementary to genomic DNA occurs. Region(s) of hybridization are region(s) of the genome of the cell to which the protein of binds. A method of identifying a set of genes where cell cycle regulator binding correlates with gene expression and of identifying genomic targets of cell cycle transcription activators in living cells is also encompassed.

Description: Genome-Wide Location and Function of DNA Binding Proteins RELATED APPLICATION(S) This application is a continuation-in-part of U.S. Application No. 09/654,409, filed September 1, 2000, which claims the benefit of U.S. Provisional Application No. 60/151,972, filed on September 1, 1999. This application also claims the benefit of U.S. Provisional Application No. 60/257,455, filed on December 21, 2000 and U.S. Provisional Application No. 60/323,620, filed September 20, 2001. The entire teachings ofthe above application(s) are incorporated herein by reference. GOVERNMENT SUPPORT The invention was supported, in whole or in part, by a grant GM34365 from the National Institutes of Health. The Government has certain rights in the invention. BACKGROUND OF THE INVENTION Many proteins involved in regulating genome expression, chromosomal replication and cellular proliferation function through their ability to bind specific sites in the genome. Transcriptional activators, for example, bind to specific promoter sequences and recruit chromatin modifying complexes and the transcription apparatus to initiate RNA synthesis. The remodeling of gene expression that occurs as cells move through the cell cycle, or when cells sense changes in their environment, is effected in part by changes in the DNA-binding status of transcriptional activators. Distinct DNA-binding proteins are also associated with centromeres, telomeres, and origins of DNA replication, where they regulate chromosome replication and maintenance. Although considerable knowledge of many fundamental aspects of gene expression and DNA replication has been obtained from studies of DNA-binding proteins, an understanding of these proteins and their functions is limited by our knowledge of their binding sites in the genome. In addition, regulation ofthe cell cycle clock is effected through a controlled program of gene expression and oscillations in the activity ofthe cyclin-dependent (CDK) family of protein kinases. Much is known about the control of stage-specific functions by CDKs and their regulators during the cell cycle (Mendenhall and Hodge, 1998; Morgan, 1997; Nurse, 2000). A more complete understanding of cell cycle regulation is constrained, however, by our limited knowledge ofthe transcriptional regulatory network that controls the clock. Additional knowledge of cell cycle regulation would make it clearer how the transcriptional and post- transcriptional regulatory networks that control the complex and highly regulated processes are involved in the cell cycle and make it possible to produce a genetic/regulatory network map and to not only identify steps in the pathway, but also connect the cell cycle with other cellular functions. Proteins which bind to a particular region of DNA can be detected using known methods. However, a need exists for a method which allows examination of the binding of proteins to DNA across the entire genome of an organism. SUMMARY OF THE INVENTION The present invention relates to a method of identifying a region (one or more) of a genome of a cell to which a protein of interest binds. In the methods described herein, DNA binding protein of a cell is linked (e.g., covalently crosslinked) to genomic DNA of a cell. The genomic DNA to which the DNA binding protein is linked is identified and combined or contacted with DNA comprising a sequence complementary to genomic DNA ofthe cell (e.g., all or a portion of a cell's genomic DNA such as one or more chromosome or chromosome region) under conditions in which hybridization between the identified genomic DNA and the sequence complementary to genomic DNA occurs. Region(s) of hybridization are region(s) ofthe genome ofthe cell to which the protein of interest binds. The methods ofthe present invention are preferably performed using living cells. h one embodiment, proteins which bind DNA in a cell are crosslinked to the cellular DNA. The resulting mixture, which includes DNA bound by protein and DNA which is not bound by protein is subject to shearing conditions. As a result, DNA fragments ofthe genome crosslinked to DNA binding protein are generated and the DNA fragment (one or more) to which the protein of interest is bound is removed from the mixture. The resulting DNA fragment is then separated from the protein of interest and amplified, using known methods. The DNA fragment is combined with DNA comprising a sequence complementary to genomic DNA ofthe cell, under conditions in which hybridization between the DNA fragment and a region ofthe sequence complementary to genomic DNA occurs; and the region of the sequence complementary to genomic DNA to which the DNA fragment hybridizes is identified. The identified region (one or more) is a region ofthe genome ofthe cell, such as a selected chromosome or chromosomes, to which the protein of interest binds. In a particular embodiment, the present invention relates to a method of identifying a region of a genome (such as a region of a chromosome) of a cell (test sample) to which a protein of interest binds, wherein the DNA binding protein ofthe cell is crosslinked to genomic DNA ofthe cell using formaldehyde. DNA fragments ofthe crosslinked genome are generated and the DNA fragment to which the protein of interest is bound is removed or separated from the mixture, such as through immunoprecipitation using an antibody that specifically binds the protein of interest. This results in separation ofthe DNA-protein complex. The DNA fragment in the complex is separated from the protein of interest, for example, by subjecting the complex to conditions which reverse the crosslinks. The separated DNA fragment is amplified (e.g., non-specifically) using ligation-mediated polymerase chain reaction (LM-PCR), and then fluorescently labeled. The labeled DNA fragment is contacted with a DNA microarray comprising a sequence complementary to genomic DNA of the cell, under conditions in which hybridization between the DNA fragment and a region ofthe sequence complementary to genomic DNA occurs. The region ofthe sequence complementary to genomic DNA to which the DNA fragment hybridizes is identified by measuring fluorescence intensity, and the fluorescence intensity ofthe region ofthe sequence complementary to genomic DNA to which the DNA fragment hybridizes is compared to the fluorescence intensity of a control. Fluorescence intensity in a region ofthe sequence complementary to genomic DNA which is greater than the fluorescence intensity ofthe control in that region ofthe sequence complementary to genomic DNA marks the region ofthe genome in the cell to which the protein of interest binds. Also encompassed by the present invention is a method of determining a function of a protein of interest which binds to the genomic DNA of a cell. In this method, DNA binding protein ofthe cell is crosslinked to the genomic DNA ofthe cell. DNA fragments ofthe genome crosslinked to DNA binding protein are then generated, as described above, and the DNA fragment (one or more) to which the protein of interest is bound is removed from the mixture. The resulting DNA fragment is then separated from the protein of interest and amplified. The DNA fragment is combined with DNA comprising a sequence complementary to genomic DNA ofthe cell, under conditions in which hybridization between the DNA fragment and a region ofthe sequence complementary to genomic DNA occurs; and the region of the sequence complementary to genomic DNA to which the DNA fragment hybridizes is identified. This identified region is a region ofthe genome of the cell to which the protein of interest binds. The identified region is characterized and the characteristic ofthe identified region indicates the function ofthe protein of interest (e.g., a regulatory protein such as a transcription factor; an oncoprotein). The present invention also relates to a method of determining whether a protein of interest which binds to genomic DNA of a cell functions as a transcription factor. In one embodiment, DNA binding protein ofthe cell is crosslinked to the genomic DNA ofthe cell. DNA fragments ofthe crosslinked genome are generated and the DNA fragment to which the protein of interest is bound is removed from the mixture. The resulting DNA fragment is separated from the protein of interest and amplified. The DNA fragment is combined with DNA comprising a sequence complementary to genomic DNA ofthe cell, under conditions in which hybridization between the DNA fragment and a region ofthe sequence complementary to genomic DNA occurs. The region ofthe sequence complementary to genomic DNA to which the DNA fragments hybridizes is identified; wherein if the region ofthe genome is a regulatory region, then the protein of interest is a transcription factor. The present invention also relates to a method of identifying a set of genes, the members of which are genes for which cell cycle regulator binding correlates with gene expression. The method comprises identifying a set of genes that is bound in vivo by at least one cell cycle regulator (e.g., transcriptional activator) in a selected cell type (e.g., mammalian cell, yeast cell); comparing the set of genes identified with genes whose expression levels vary in a periodic manner during the cell cycle ofthe selected cell type; and identifying genes that are bound by one or more ofthe cell cycle regulators, thus identifying a set of genes, the members of which are genes whose expression levels vary in a periodic manner during the cell cycle and are bound by at least one cell cycle regulator, wherein the set identified is referred to as a set of genes, the members of which are genes for which cell cycle regulator binding correlates with gene expression. The methods described herein facilitate the dissection ofthe cells regulatory network of gene expression across the entire genome and aid in the identification of gene function. Work described herein provides the basis for constructing a complete map ofthe transcriptional regulatory network that controls the cell cycle. In one embodiment, it forms the foundation for a complete map ofthe transcriptional regulatory network that controls the yeast cell cycle. BRIEF DESCRIPTION OF THE DRAWINGS The file of this patent contains at least one drawing executed in color. Copies of this patent with color drawing(s) will be provided by the Patent and Trademark Office upon request and payment ofthe necessary fee. 2/059371 -6- Figure 1 is an illustration ofthe Genome-wide Monitoring Protein-DNA interactions described herein. Figure 2 shows how the relative binding ofthe protein of interest to each sequence represented on an array was calculated using a weighted average analysis. Figure 3 is a graph of chromosomal position versus fold change of Genome- wide Monitoring Protein-DNA interactions. Figure 4 is a graph of chromosome position versus ratio of tagged to untagged for binding of ORC1 to yeast chromosome HI. Figure 5 A is an example of a scanned image. The unenriched and IP enriched DNA generates green fluorescence and red fluorescence respectively. The close-up image shows examples of spots for which the red intensity is over- represented, indicating binding ofthe targeted protein to these DNA sequences. Figure 5B show that small amounts of DNA can be quantitatively amplified and labeled with Cy3 and Cy5 fluorophores. Cy3- and Cy5-labeled DNA from 1 ng of yeast genomic DNA was prepared using the LM-PCR method described in the text. The resulting DNA samples were mixed and hybridized to a yeast intragenic DNA microarray. Low intensity spots have larger variations than high intensity spots, probably due to background noise. Figure 6A shows the set of 24 genes whose promoter regions are most likely to be bound by Gal4 by the analysis criteria described herein. Figure 6B is a schematic ofthe Gal4 binding intergenic regions. Figure 6C shows the results of conventional ChlP analysis. Figure 6D shows the results ofthe AlignAce program used to identify a consensus binding site for the Gal4 activator. Figure 6E is a bar graph showing relative expression of PLC10 and MTHl . Figure 6F is a schematic illustrating how the identification of MTHl and MTH, PCL10 and FUR4 as Gal4-regulated genes reveals how several different metabolic pathways are interconnected. Figure 6G contains three graphs showing galactose-induced expression of FUR4, MTHl and PLC10 is GAL4-dependent; samples from wild-type and gal4- strains were taken before and after addition of galactose. The expression of FUR4, /059371 -7- MTH1 and PLC10 was monitored by quantitative reverse transcriptase-PCR (RT- PCR) ans was quantified by phosphoimaging. Figure 7 lists the set of genes whose promoter regions are most likely to be bound by Stel 12 by the analysis criteria described herein. Figure 8 is a schematic of a model summarizing the role of Stel 2 target genes in the yeast mating pathway. Gray boxes denote the cellular processes known to be involved in mating; yellow boxes denote cellular processes that are likely associated with mating. Genes in black were previously reported to be associated with the mating process; genes in red are Stel 2 targets that likely play a role in mating. Figures 9A-9C show the cell cycle transcriptional regulators study design. Figure 9A depicts the stages ofthe cell cycle together with yeast cell morphology (brown) and transcriptional regulators (blue); the transcriptional regulators are positioned at the stage during which they have been reported to function (Breedon et al, Curr. Biol, 70.R586-R588(2000), Mendenhall et al, Mol Biol. Rev., 67. 1191-1243 (1998)). Figure 9B is a scatter plot of Cy5 versus Cy3 intensities for a control experiment in which aliquots of whole cell extract (WCE) were independently labeled with Cy3 and Cy5 and hybridized to a DNA microarray containing all yeast intergenic regions. The red and blue lines border the regions with confidence levels ofpθ.001 and pθ.01, respectively. Figure 9C is a scatter plot of an experiments in which the Fkh2 IP-enriched DNA was labeled with Cy5 and the WCE was labeled with Cy3. The red and blue lines border the regions with confidence levels of pO.OOl and pO.Ol, respectively. The cpols whose values have confidence levels of pO.OOl represent promoters most likely bound by the Fkh2 factor. Figures 10A-10B show genome-wide location ofthe nine cell cycle transcription factors. Figure 10A show the 213 ofthe 800 cell cycle genes whose promoter regions were bound by a myc-tagged version of at least one ofthe nine cell cycle transcription factors (p<0.001) are represented as horizontal lines. The weight- /059371 -8- averaged binding ratios are displayed using a blue and white color scheme (genes with p values <0.001 are displayed in blue). The expression ratios of an α factor synchronization time course from Spellman et al, Mol Cell Biol. Cell, /3273-3297 (1998) are displayed using a red (induced) and green (repressed) color scheme. Figure 1 OB is a schematic in which the circle represents a smoothed distribution ofthe transcription timing (phase) ofthe 800 cell cycle genes (Spellman et al, Mol. Cell Biol Cell, P/3273-3297 (1998)). The intensity ofthe red color, normalized by the maximum intensity value for each factor, represents the fraction of genes expressed at that point that are bound by a specific activator. The similarity in the distribution of color for specific factors (with Swi4, Swi6, and Mbpl, for example) shows that these factors bind to genes that are expressed during the same time frame. Figures 11 A-l IB are schematics showing transcriptional regulation of cell cycle transcription factor genes. Figure 11 A shows a summary of previous evidence for regulation of cell cycle transcription factor genes and CLN3 transcriptional regulators (Althoefer et al, Mol. Cell Biol, /J/5917-5928 (1998); Foster et al. Mol. Cell Biol, 13:3792- 3801 (1993); Koranda et al, Nature, 406:94-98 (2000); Kumar et al. Curr. Biol, 10:896-906 (2000); Kuo et al, Mol. Cell Biol. ,14:3348-359 (1994); Loy et al Mol. Cell Biol, 19:3312-3327 (1999); Mackay et α/. Mol Cell Biol, 21.-4140-4148 (2001); Mclnemy et al Genes Dev., ii: 1277- 1288 (1997); Pic et al. Embo J., P/3750-3761 (2000); Zhu et al. Nature, 406:90-94 (2000)). The relationships between the transcription factors and their target genes are indicated by red arrows; solid lines represent evidence for direct regulation by these factors; and dashed lines represent inferences from indirect evidence. The blue arrows represent posttranscriptional regulation by Cln3/Cdc28 (Dirick et al. Embo. J., 7^/4803-4813 (1995)). Figure 1 IB is a model for the closed regulatory circuit produced by cell cycle transcriptional regulators based on genome-wide binding data. The genome-wide location data indicate that each group of transcriptional activators regulates activators acting in the next cell cycle stage. The red arrows represent binding of a transcription factor to the promoter of another regulatory factor. The blue arrows represent posttranslational regulation. Figures 12A-12B are schematics showing transcriptional regulation of cyclin and cyclin/CDK regulator genes. Figure 12A shows a summary of previous evidence for transcriptional regulation of genes encoding the cyclins (green) and cyclin CDK regulators (red) by the cell cycle transcription factors (Althoefer et al. Mol. Cell Biol, 15:5917-5928 (1998); Dirick et al. Nature, 557/508-513 (1992); Hollenhorst et al. Genetics, 75 1533-1548 (2000); Iyer et al. Nature, 409:533-536 (2001); Knapp et al. Mol. Cell Biol, 76/5701-5707 (1998); Koch et al. Science, 261:1551-1557 (1993); Koranda et al. Science, 267/1551-1557 (1993); Kumar et al Curr. Biol, 10:896- 906 (2000); Kuo et al, Mol. Cell Biol, 14:3348-359 (1994); Loy et al. Mol. Cell Biol, 7P/3312-3327 (1999); Mackay et al. Mol. Cell Biol, 27/4140-4148 (2001); McBride et al. J. Biol. Chem., 274:21029-21036 (1999); Mclnerny et al Genes £>ev., 77/1277-1288 (1997); Nasmyth et al. Genes Dev., 77/1277-1288 (1997); Oehlen et al. Mol. Cell Biol, 76/2830-2837 (1996); Ogas et al. Cell, 66/1015-1025 (1991); Partridge et al. J. Biol. Chem., 272:9071-9077 (1997); Pic et al Embo J., 19:3750-3761 (2000); Schwab et al. Genes Dev., 7/1160-1175 (1993); Toyn et al. Genetics, 145:85-96 (1997); Zhu et al. Nature, 406:90-94 (2000)). The factors, as well as their targets, are positioned according to their approximate time of function. The relationships between the transcription factors and their target genes are indicated by arrows, solid lines represent evidence for direct regulation by these factors, and dashed lines represent inferences from indirect evidence. Figure 12B is a model for transcriptional regulation of cyclin and cyclin CDK regulators based on previous studies and on genome-wide binding data. Each group of transcription factors regulates key cell cycle regulators that are needed for progression through the cell cycle. Figure 13 is a schematic ofthe regulation of cell cycle functions by the activators. Stage-specific cell cycle functions under the control of specific factors are shown. The budding category include genes involved in budding and in cell wall biogenesis; the DNA replication category includes genes involved in replication, /059371 -10- repair, and sister chromatid cohesion; the chromatin category includes genes encoding histones, chromatin modifiers, and telomere length regulators. The identity and functions of genes in each category are listed in Table 3. Figures 14A-14C are diagrams showing partial redundancy between homologous activators. Figure 14A are Venn diagrams depicting the overlap between the targets of pairs of homologous cell cycle transcriptional regulatory proteins. The numbers in parenthesis under each activator represent the sum of cell cycle genes whose promoters were bound by the protein. The number in the intersection between two circles reflects the numbers of genes whose promoters were bound by both proteins. Figure 14B are Venn diagrams representing the overlap in target sites between pairs of regulatory proteins that reside within the same complex. Figure 14C is a Verm diagram representing the overlap in target sites between two transcriptional regulators that are not known to be related. DETAILED DESCRIPTION OF THE INVENTION Understanding how DNA-binding proteins control global gene expression, chromosomal replication and cellular proliferation would be facilitated by identification ofthe chromosomal locations at which these proteins function in vivo. Described herein is a genome-wide location profiling method for DNA-bound proteins, which has been used to monitor dynamic binding of gene-specific transcription factors and components ofthe general transcription apparatus in yeast cells. The genome-wide location method correctly identified known sites of action for the transcriptional activators Gal4 and Stel2 and revealed unexpected functions for these activators. The combination of expression and location profiles identified the global set of genes whose expression is under the direct control of specific activators and components ofthe transcription apparatus as cells responded to changes in their extracellular environment. Genome-wide location analysis provides a powerful tool for further dissecting gene regulatory networks, annotating gene functions and exploring how genomes are replicated. 059371 -11- Accordingly, the present invention provides methods of examining the binding of proteins to DNA across the genome (e.g., the entire genome or a portion thereof, such as one or more chromosomes or a chromosome regions) of an organism. In particular, the present invention relates to a method of identifying a region (one or more) of genomic DNA of a cell to which a protein of interest binds. In one embodiment, proteins which bind DNA in a cell are crosslinked to the cellular DNA. The resulting mixture, which includes DNA bound by protein and DNA which is not bound by protein is subject to shearing conditions. As a result, DNA fragments ofthe genome crosslinked to DNA binding protein are generated and the DNA fragment (one or more) to which the protein of interest is bound is removed from the mixture. The resulting DNA fragments are then separated from the protein of interest and amplified using known techniques. The DNA fragment is then combined with DNA comprising a sequence complementary to genomic DNA ofthe cell, under conditions in which hybridization between the DNA fragments and the sequence complementary to genomic DNA occurs; and the region ofthe sequence complementary to genomic DNA to which the DNA fragment hybridizes is identified. The identified region is a region ofthe genome ofthe cell to which the protein of interest binds. Also encompassed by the present invention is a method of determining a function of a protein of interest which binds to the genomic DNA of a cell. In this method, DNA binding protein ofthe cell is crosslinked to the genomic DNA ofthe cell. DNA fragments ofthe genome crosslinked to DNA binding protein are then generated, as described above, and the DNA fragment (one or more) to which the protein of interest is bound is removed. The resulting DNA fragment is then separated from the protein of interest and amplified. The DNA fragment is then combined with DNA comprising a sequence complementary to genomic DNA ofthe cell, under conditions in which hybridization between the DNA fragment and a region ofthe sequence complementary to genomic DNA occurs; and the region of the sequence complementary to genomic DNA to which the DNA fragment hybridizes is identified and is a region ofthe genome ofthe cell to which the protein of interest binds. The identified region is characterized (e.g., a regulatory region) 059371 -12- and the characteristic ofthe identified region indicates a function ofthe protein of interest (e.g., a transcription factor; an oncoprotein). The present invention also relates to a method of determining whether a protein of interest which binds to genomic DNA of a cell functions as a transcription factor. In one embodiment, DNA binding protein ofthe cell is crosslinked to genomic DNA ofthe cell and DNA fragments ofthe crosslinked genome are generated. The DNA fragment to which the protein of interest is bound are removed. The resulting DNA fragment is separated from the protein of interest and amplified. The DNA fragment is combined with DNA comprising a sequence complementary to genomic DNA ofthe cell, under conditions in which hybridization between the DNA fragments and sequence complementary to genomic DNA occurs. The region ofthe sequence complementary to genomic DNA to which the DNA fragments hybridizes is identified wherein if the region ofthe genome is a regulatory region, then the protein of interest is a transcription factor. The methods ofthe present invention can be used to examine and/or identify DNA binding of proteins across the entire genome of a eukaryotic organism. For example, DNA binding proteins across the entire genome of eukaryotic organisms such as yeast, Drosophila and humans can be analyzed. Alternatively, they can be used to examine and or identify DNA binding of proteins to an entire chromosome or set of chromosomes of interest. As also described herein, genome-wide location analysis has been used to identify the in vivo genome binding sites for cell cycle transcription factors, in particular genome binding sites for each ofthe known yeast cell cycle transcription factors. Such analysis is useful to identify genome binding sites (genomic targets) of cell cycle regulators (transcriptional activators) in a variety of cell types and, as also described herein, has resulted in identification of genomic targets of each ofthe nine known yeast cell cycle transcription activators. One embodiment ofthe present invention is a method of identifying genes that are expressed in a periodic manner during the cell cycle of a selected cell type and are bound by a cell cycle regulator(s) or cell cycle transcription factors, also referred to transcription(al) regulators/activators. The method is, thus, one of identifying a set of genes where cell cycle factor binding correlates with gene expression. In the method, a set of genes whose factor binding correlates with gene expression at a selected level of stringency of the analysis criteria for binding data is identified. For example, the stringency ofthe analysis criteria for binding data can be p<0.001, pO.Ol, p<0.05 or another selected level and preferably will be selected at such a level that few or no false positives are detected. Cell cycle regulators can be identified by the method of the present invention in a wide variety of cell types (referred to as selected cell types, such as eukaryotic (mammalian, nonmammalian) cells, including human and nonhuman cells (including, but not limited to, yeast and other fungi, worm, fly, avian, murine, canine, bovine, feline, equine, and nonhuman primate cells). The method is carried out, in one embodiment, by identifying a set of genes that is bound in vivo by a cell cycle regulator(s) or transciption factor(s) in a selected cell type (e.g., from a particular organism, which can be human or nonhuman, such as those listed above); comparing that set of genes with genes whose expression levels vary in a periodic manner during the cell cycle of that organism; and identifying genes that are bound by one or more ofthe cell cycle regulators (identifying genes whose factor binding correlates with gene expression), thus identifying genes whose expression levels vary in a periodic manner during the cell cycle and are bound a cell cycle factor(s). Genes identified in this manner can be characterized, as described herein. As described herein, a set of yeast genes for which factor binding correlates with gene expression has been identified by comparing the set of genes bound by the nine cell cycle transcription factors with the approximately 800 genes whose expression levels vary in a periodic fashion during the yeast cell cycle. Those genes whose promoters are bound by one or more ofthe nine transcription factors, particularly those identified with reference to the highest stringency criteria as described herein (highest stringency of analysis criteria for binding data), were investigated and characterized. Results of work described herein generally support the model for stage- specific regulation of gene expression, described by others, by these activators and extend it to encompass promoters for several hundred cell cycle genes; confirmed results of earlier studies, which established that genes encoding several ofthe cell cycle transcriptional regulators are themselves bound by other cell cycle functions; revealed that cell cycle transcriptional control is effected by a connected regulatory network of transcriptional activators; and identified a set of promoters bound in vivo by each ofthe cell cycle regulators, which were further analyzed and shown to comprise consensus binding sequence motifs (see Table 2). A variety of proteins which bind to DNA can be analyzed. For example, any protein involved in DNA replication such as a transcription factor, or an oncoprotein can be examined in the methods ofthe present invention. There are a variety of methods which can be used to link DNA binding protein ofthe cell to the genome ofthe cell. For example, UV light can be used. In a particular embodiment, formaldehyde is used to crosslink DNA binding proteins to the genomic DNA of a cell. hi the methods ofthe present invention, identification of DNA fragments bound to the protein of interest can be removed from the mixture comprising DNA fragment(s) bound to the protein of interest and DNA fragments which are not bound to the protein of interest, using a variety of methods. For example, immunoprecipitation using an antibody (e.g., polyclonal, monoclonal) or antigen binding fragment thereof which binds (specifically) to the protein of interest, can be used. In addition, the protein of interest can be labeled or tagged using, for example, an antibody epitope (e.g., hemagglutinin (HA)). The DNA fragments in the methods described herein can be amplified using any suitable method. In one embodiment, the DNA is amplified using a non-specific amplification method. For example, ligation-mediated polymerase chain reaction (e.g., see Current Protocols in Molecular Biology, Ausubel, F.M. et al, eds. 1991, the teachings of which are incorporated herein by reference) can be used. Thus, the present invention provides a method for non-specifically amplifying DNA fragments from the entire genome of a cell. As shown herein, non-specific amplification can be used without increasing the signal-to-noise ratio. The ability to non-specifically amplify DNA fragments from an entire genome of a cell constitutes a important distinction over other techniques, such as the ChlP technique which relies upon specific primer-based amplification. In one embodiment, the amplified DNA can be labeled (e.g., a radioactive label, a non-radioactive label such as a fluorescent label) to facilitate identification. In one embodiment, the DNA is labeled using a fluorescent dye, such as Cy5 or Cy3. The DNA comprising the complement sequence ofthe genome ofthe cell can be combined with the isolated DNA fragment to which the protein of interest binds using a variety of methods. For example, the complement sequence can be immobilized on a glass slide (e.g., microarray such as the Corning Microarray Technology (CMT™) GAPS™) or on a microchip. In one embodiment, a glass slide is used which can accommodate an entire genome of a cell (e.g., at least about 7200 spots (DNA)). Conditions of hybridization used in the methods ofthe present invention include, for example, high stringency conditions and/or moderate stringency conditions. See e.g., pages 2.10.1-2.10.16 (see particularly 2.10.8-11 ) and pages 6.3.1 -6 in Current Protocols in Molecular Biology). Factors such as probe length, base composition, percent mismatch between the hybridizing sequences, temperature and ionic strength influence the stability of hybridization. Thus, high or moderate stringency conditions can be determined empirically, and depend in part upon the characteristics ofthe known nucleic acids (DNA, RNA) and the other nucleic acids to be assessed for hybridization thereto. The methods ofthe present invention can further comprise comparing the results to a control (control sample). For example, in one embodiment, the methods ofthe present invention can be carried out using a control protein which is not a DNA binding protein. In one embodiment, immunoprecipitation is performed using an antibody against an HA or MYC epitope tag. The results of immunoprecipitating the protein of interest containing the tag, and the protein of interest without the tag are compared. The untagged protein should not be immunoprecipitated, and thus, serves as a negative control. Using the methods ofthe present invention also provides for the ability to compare the sample with the control sample simultaneously. Generally, a test sample if hybridized to an array and compared to a control sample which has been hybridized to a different array and a ratios is cal culated to determine binding results. Using the methods described herein, two samples (e.g., a test sample and a control sample) can be hybridized to the same array which allows for elimination of noise due to the use of two anays (e.g., an array for the test sample and another array for the control sample). The difference between arrays due to manufacturing artifacts is a major source of noise, which can be eliminated using the methods described herein. As described in the exemplification, a particular embodiment ofthe present invention comprises the combined use of Chromatin Immunoprecipitation (ChIP) and Genome-wide expression monitoring microarrays. Chromatin immunoprecipitation allows the detection of proteins that are bound to a particular region of DNA. It involves four steps: (1) formaldehyde cross-linking proteins to DNA in living cells, (2) disrupting and then sonicating the cells to yield small fragments of cross-linked DNA, (3) immunoprecipitating the protein-DNA crosslinks using an antibody which specifically binds the protein of interest, and (4) reversing the crosslinks and amplifying the DNA region of interest using the Polymerase Chain Reaction (PCR). Analysis of the PCR product yield compared to a non-immunoprecipitated control determines whether the protein of interest binds to the DNA region tested. However, each region of DNA must be tested individually by PCR. Thus, the ChIP technique is limited to the small set of DNA regions that are chosen to be tested. In contrast, the present method is not limited to amplifying individual DNA regions by performing PCR with specific primers. Rather the entire genome (test sample) is amplified (e.g., non-specifically) using a Ligation-mediated PCR (LMPCR) strategy. The amplified DNA was fluorescently labeled by including fluorescently- tagged nucleotides in the LM-PCR reaction. Finally, the labeled DNA was hybridized to a DNA microarray containing spots representing all or a subset (e.g., a chromosome or chromosomes) ofthe genome. The fluorescent intensity of each spot on the microarray relative to a non-immunoprecipitated control demonstrated whether the protein of interest bound to the DNA region located at that particular spot. Hence, the methods described herein allow the detection of protein- DNA interactions across the entire genome. In particular, DNA microarrays consisting of most of yeast chromosome HI plus approximately 15 model genes whose expression have been well studied were constructed. These arrays were used in conjunction with the ChIP technique to study the DNA-binding properties of transcription factors and the transcription apparatus genome-wide. The methods described herein provide insights into the mechanism and regulation of gene expression in eukaryotic cells. The genome-wide location analysis method described herein allows protein- DNA interactions to be monitored across the entire yeast genome and is diagramed in Figure 1. The method combines a modified Chromatin Immunoprecipitation (ChIP) procedure, which has been previously used to study in vivo protein-DNA interactions at one or a small number of specific DNA sites, with DNA microarray analysis. Briefly, cells are fixed with formaldehyde, harvested by sonication, and DNA fragments that are crosslinked to a protein of interest are enriched by immunoprecipitation with a specific antibody. After reversal ofthe crosslinking, the enriched DNA is amplified and labeled with a fluorescent dye (e.g., Cy5) using ligation-mediated PCR (LM-PCR). A sample of DNA that has not been enriched by immunoprecipitation is subjected to LM-PCR in the presence of a different fluorophore (e.g., Cy3), and both immunoprecipitation (IP)-enriched and unenriched pools of labeled-DNA are hybridized to a single DNA microarray containing all yeast intergenic sequences. A single-array error model (Roberts, et al, Science,287:972 (2000)) was adopted to handle noise associated with low-intensity spots and to permit a confidence estimate for binding (P value). When independent samples of 1 ng of genomic DNA was amplified with the LM-PCR method, signals for greater than 99.8% of genes were essentially identical within the error range (P value ≤ 10 "3 ). The IP-enriched/unenriched ratio of fluorescence intensity obtained from three independent experiments can be used with a weighted average analysis method to calculate the relative binding ofthe protein of interest to each sequence represented on the array (see Figure 2). Four features ofthe global location profiling method were found to be critical for consistent, high-quality results. First, DNA microarrays with consistent spot quality and even signal background play an obvious role. An example of an image generated by the technique described herein is shown in figure 5A. Second, the LM-PCR method described herein was developed to permit reproducible amplification of very small amounts of DNA; signals for greater than 99.9% of genes were essentially identical within the error range when independent samples of 1 ng of genomic DNA were amplified with the LM-PCR method (Figure 5B). Third, each experiment was carried out in triplicate, allowing an assessment ofthe reproducibility ofthe binding data. And fourth, a single-array error model described by Hughs et al, (2000) was adopted to handle noise associated with low intensity spots and to average repeated experiments with appropriate weights The quantitative amplification of small amount of DNA generates some uncertainty for the low intensity spots. In order to track that uncertainty and to be able to average repeated experiments with appropriate related weights, we adopted an single-array enor model that was first described by Hughs et al, (2000). According to this error model, the significance of a measured ratio at a spot is defined by a statistic X, which takes the form (1) X=(a 2 - a,)/[σ, 2 + σ 2 2 + f 2 (a, 2 + where a 1>2 are the intensities measured in the two channels for each spot, σ, 2 are the uncertainties due to background subtraction, and f is a fractional multiplicative error such as would come from hybridization non-uniformities, fluctuations in the dye incorporation efficiency, scanner gain fluctuations, ets. X is approximately normal. The parameters σ and f were chosen such that X has unit variance. The significance of a change of magnitude |x| is then calculated as (2) p=2x(l-Erf(|X|)). Thus, in the methods ofthe present invention, the data for the intensity of each spot on an array, as well as the intensity and standard deviation around each spot is measured; and this is calculated for both the test sample and the control sample hybridized on the same array. These measurements are used to calculate the enrichment in a probabilistic fashion using a mathematical model. In the methods described herein, each measurement is weighed allowing replicates to be combined appropriately which addresses the susceptibility of spots with lower signals to generate more noise.. EXEMPLIFICATION Example 1 DESIGN OF YEAST CHROMOSOME IE AND SELECTED MODEL GENES ARRAY FOR THE CHARACTERIZATION OF PROTEIN-DNA INTERACTIONS Array contains all non-overlapping open reading frames (ORF) on Chromosome IH (See Table 1). When a sequence contains part or all of two potential reading frames, the larger sequence was chosen to represent the ORF. Any remaining sequence was included in intergenic fragments. All intergenic regions larger than lOObp are represented by fragments averaging 500bp. Where regions are greater than 700bp, they are broken into multiple fragments of 300 to 600bps. PCR primers for each region were chosen using the Saccharomyces Genomic Database (SGD) "Design Primers" program from Stanford University. The total number of intergenic fragments equals 241 for Chromosome HI. The location and size of open reading frames were determined from the Saccharomyces Genomic Database (SGD) functional chromosomal map. An additional 17 model genes (see the Table) were selected based on their high frequency of citation in transcription literature. Each gene was amplified as well as l-2kb upstream and 500bp downstream ofthe coding region. ChIP - Microarray Protocols PCR generation of unmodified yeast ORF DNA 100 μl reaction generally yields approximately 5-6μg DNA RXN mix: 10.0 μl 10X PCR buffer (Perkin Elmer, AmpliTaq) 8.0 μl 25mM MgC12 (Perkin Elmer, AmpliTaq) 10.0 μl 10X dNTPs (2mM each, Pharmacia lOOmM stocks) 1.0-2.0 μl ORF DNA (Research Genetics, approximately 10 ng) 2.5μl each universal primer (Research Genetics, 20 μM solution) 1.6 μl diluted Pfu DNA polymerase (diluted 1:100 in water, Strategene, 0.02U) 1.0 μl AmpliTaq DNA polymerase (5U, Perkin Elmer) 63.4 μl ddH 2 O PCR Generation of Yeast Intergenic regions 100 μl reaction generally yields approximately 5-6 ug DNA RXN mix: 10.0 μl 10X PCR buffer (Perkin Elmer, AmpliTaq) 8.0 μl 25mM MgC12 (Perkin Elmer, AmpliTaq) 10.0 μl 1 OX dNTPs (2mM each, Pharmacia 1 OOmM stocks) l.Oμl Yeast Genomic DNA (Research Genetics, approximately 100 ng) 5.0 μl each primer (Research Genetics, 20 μM solution) 1.6 μl diluted Pfu DNA polymerase (diluted 1:100 in water, Strategene 0.02U) l.Oμl AmpliTaq DNA polymerase (5U, Perkin Elmer) 58.4 μl ddH 2 O Cycling for ORF and intergenic DNA 95 °C 3 min 30 cycles of: 94°C 30 sec 60°C 30 sec 72°C 2 min PCR Cleanup: Reactions were cleaned by Qiagen QIAquick 96 PCR purification kits according to the manufacturers' protocol with the following exception. DNA was eluted with 120 μl of T.E. 8.0 (lOmmTris, 1mm EDTA, pH8.0). T.E. 8.0 was applied to the Qiagen membrane and allowed to sit 5 minutes before elution. The DNA was collected into a Corning polypropylene 96 well plate. Reactions were quantified by visualizing lμl ofthe purified DNA on an agarose gel compared to a known quantity of lambda DNA cut with Hindrfl (Promega). DNA was stored at -20 until shortly before printing. The DNA was then dried down by speed vac in the Coming microtiter plates to less than 5μl. PRINTING PCR reactions were resuspended to approximately 0.5 mg/ml in 3XSSC. SSC was made as a 20X stock (3M NaCl, 0.3M Na 3 citrate-2H 2 O, pH'd to 7.0 with HCI) and diluted to the desired concentration with H 2 O. 10-15 μl ofthe DNA was placed in a Corning 96 or 384 well plate and GAPS coated slides were printed using the Cartessian Robot. PCR products should be greater than 250 pb. Slide Processing 1. Rehydrated arrays by holding slides over a dish of hot ddH 2 O (~ 10 sec). 2. Snap-dried each array (DNA side up) on a 100°C hot plate for ~ 3 seconds. 3. UV X-linked DNA to the glass by using a Stratalinker set for 60 m Joules. 4. Dissolved 5g of succinic anhybride (Aldrich) in 315mL of n-methyl- pyrrilidinone. 5. To this, added 35mL of 0.2M NaBorate pH 8.0, and stirred until dissolved (Boric Acid pH'd with NaOH). 6. Soaked arrays in this solution for 15 minutes with shaking. 7. Transferred arrays to 95°C water bath for 2 minutes. 8. Quickly transferred arrays to 95%> EtOH for 1 minute. 9. Air dried slides array side up at a slight angle (close to vertical). Slide pre-hybridization 1. Incubated slide in 3.5XSSC, 0.1%SDS, lOmg/ml BSA (Sigma) in a Coplin jar for 20 minutes at 50°C (Place Coplin jar in water bath). 2. Washed slide by dipping in water and then isopropanol. 3. Air dried array side up at slight angle (close to vertical). Probe preparation 1. The probe volume should be 20-30 μl for a small coverslip (25 mm 2 ) and 40- 60 μl for a large cover slip (24 x 60 mm). 2. Brought probe (cDNA or PCR based) up to final hyb volume in 3XSSC, 0.1 % SDS with 10 μg E. coli tRNA (Boehringer-Mannheim). 3. Boiled in heat block for 3-5 minutes. 4. Snaped cool on ice. And spun. Hybridization 1. Pipetted probe onto slide. Dropped cover slip onto liquid avoiding bubbles. 2. Assembled over 50°C waterbath in hybridization chamber. Clamped shut. 3. Submerged in 50°C waterbath overnight. Scanning 1. Dissambled hybridization right side up. 2. Removed coverslip with fingers or tweezers. 3. Placed in 0.1X SSC, 0.1% SDS at room temperature for 5-10 minutes. 4. Transfered slides to 0.1X SSC for 2.5 minutes and again for 2.5 minutes. 5. Blew dry and scan slide. Data Analysis The data generated from scanning was analyzed using the ImaGene software. Table 1 /059371 -30- Example 2 GENOME- WIDE LOCATION AND FUNCTION OF DNA- BINDING PROTEINS Global analysis of Gal4 binding sites To investigate the accuracy ofthe genome-wide location analysis method, the analysis was used to identify sites bound by the transcriptional activator Gal 4 in the yeast genome. Gal4 was selected because it is among the best characterized transcriptional activators, it is known to be responsible for induction of genes necessary for galactose metabolism, and a consensus DNA binding sequence (the UAS G ) has been identified for Gal4 in the promoters ofthe GAL genes. Very little Gal4 is bound at the UAS G ofthe GAL1 and GAL10 promoters when cells are grown in glucose (the repressed state), whereas relatively high levels of Gal 4 are bound in galactose (the activated state). The genome- wide location of epitope-tagged Gal4p in both glucose and galactose media was investigated in three independent experiments, as described in more detail below. The location analysis experiment identified seven genes previously reported to be regulated by Gal 4 and three additional genes encoding activities that are physiologically relevant to cells that utilize galactose as the sole carbon source, but which were not previously known to be regulated by this activator (Figures 6A). The set of 24 genes whose promoter regions are most likely to be bound by Gal 4 by the analysis criteria (p-value < 0.00001) described herein, is listed in Figure 6 A. Gal 4 does not functionally activate all of these genes, however, since only a subset ofthe genes that share intergenic regions bound by Gal4 will be regulated by this activator (Figure 6B). To identify genes that are both bound by Gal4 and activated by galactose, genome-wide expression analysis was carried out. The upper panel of Figure 6A shows genes whose expression is induced in galactose, whereas the lower panel shows genes whose expression is galactose independent. Ten genes were found to be bound by Gal4 (P value ≤ 0.001) and induced in galactose using the critical analysis described herein. These included seven genes previously reported to be regulated by Gal4 (GAL1, GAL2, GAL3, GAL7, GAL10, GAL80 and GCY1) 2/059371 -31- which were bound Gal 4 and were activated in galactose. Three genes whose expression was not previously associated with the Gal 4 activator, MTH, PCL10 and FUR4, were also found to be bound by Gal 4 and activated in galactose. Substantially less Gal 4 was associated with each of these promoters in cells grown in glucose, as expected. Gal4p was not bound to the promoters of GAL4 and PGM2, genes previously thought to be regulated by Gal4, although direct evidence for Gal4 binding to these promoters had not been demonstrated. Each of these results was confirmed by conventional ChIP analysis (Figure 6C), demonstrating that the microarray results accurately reflect results obtained by the conventional approach, which has until now been used to study binding sites individually. The ten genes that are both bound and regulated by Gal4 were selected and the AlignAce program was used to identify a consensus binding site for this activator (Figure 6D). This binding site sequence is similar to, but refines, the sequence previously determined for Gal4. The Gal4 binding sequence occurs at approximately 50 sites through the yeast genome where Gal 4 binding is not detected, indicating that the simple presence of this sequence is not sufficient for Gal 4 binding. Three genes whose expression was not previously associated with the Gal 4 activator, MTH, PCL10 and FUR4, were found to be bound by Gal4 and activated in galactose (Figure 6G). The identification of MTHl, PCL10 and FUR4 as Gal4- regulated genes reveals previously unknown functions for Gal4 and explains how regulators of several different metabolic pathways can be coordinated. It is likely that these three genes are genuine Gal4p targets because they share the following three features with the well established Gal4-dependent GAL genes. MTH, PCL10 and FUR4 are galactose-induced (Figure 6A). Galactose induction depends on Gal 4 (Figure 6C). MTH, PCL10 and FUR4 promoters are bound by Gal4 when cells are grown in galactose but not in glucose (Figure 6A). The binding of Gal4p to the MTH, PCL10 and FUR4 promoters was verified by conventional ChIP analysis (Figure 6C). The identification of MTHl and MTH, PCL10 and FUR4 as Gal4-regulated genes reveals how regulation of several different metabolic pathways are interconnected (Figure 6F). MTHl encodes a transcriptional repressor of many genes involved in metabolic pathways that would be unnecessary when cells utilize galactose as a sole carbon source. Among the most interesting of its targets are a subset ofthe HTX genes involved in hexose transport. The results described herein indicate that the cell responds to galactose by modifying (increasing) the concentration of its galactose transporters at the membrane in a Gal4-dependent fashion at the expense of other transporters, In other words, while Gal 4 activates expression ofthe galactose transporter gene GAL2, Gal4 induction ofthe MTHl repressor gene, leads to reduced levels of glucose transporter expression. The Pel 10 cyclin associates with Pho85p and appears to repress the formation of glycogen. The observation that PCL10 is Gal4-activated indicates that reduced glycogenesis occurs to maximize the energy obtained from galactose metabolism. FUR4 encodes a uracil pennease and its induction by Gal 4 may reflect a need to increase intracellular pools of uracil to permit efficient uridine 5'-diphosphate(UDP) addition to galactose catalyzed by Gal 7. Previous studies have shown that Gal 4 binds to at least some GAL gene promoters when cells are grown on carbon sources other than galactose, as long as glucose is absent. Genome-wide location analysis of Gal 4 in cells grown on raffinose was repeated and it was found that the results were essentially identical to those obtained when cells were grown on galactose. These results indicate that Gal 4 exhibits the same binding behavior at all its genomic binding sites and demonstrate that the genome-wide location method is highly reproducible. Global analysis of Stel2 binding sites The genome-wide binding profile ofthe DNA-binding transcription activator Stel2 was also investigated. Stel2 is of interest because it has a defined cellular role - it is key to the response of haploid yeast to mating pheromones - but only a few genes regulated by Stel 2 have been identified. Activation ofthe pheromone- response pathway by mating pheremones causes cell cycle arrest and transcriptional activation of more than 200 genes in a Stel2-dependent fashion. However, it is not clear which of these genes is directly regulated by Stel 2 and which are regulated by /059371 -33- other ancillary factors. Expression analysis using stel 2 mutant cells has shown that Stel 2 is required for the pheromone induction of all of these genes. However, the mechanism by which Stel 2 activates transcription of these genes in response to pheromone has not been elucidated. The genome-wide location of epitope-tagged Stel2p before and after pheromone treatment was investigated in three independent experiments. The set of genes whose promoter regions are most likely to be bound by Ste 12 by the analysis criteria (p-value < 0.005) described herein is listed in Figure 7; the upper panel shows genes whose expression is induced by alpha factor, whereas the lower panel shows genes whose expression is not significantly induced by alpha factor. Ofthe genes that are induced by alpha factor and are bound by Ste 12, 11 are known to participate in various steps ofthe mating process (FIG2, AFR1, GIC2, STE12, KAR5, FUS1, AGA1, FUS3, CIK1, FAR1, FIG1) (Figure 8). FUS3 and STE12 encode components ofthe signal transduction pathway involved in the response to pheromone (Madhani et al, Trends Genet., 14:151 (1999)); AFR1 and GIC2 are required for the formation of mating projections (Konopka et al, Mol. Cell Biol, 13:6876 (1993); Brown et al, Genes Dev, 77/2972 (1997); Chen et al, Genes Dev., 77/2998 (1997)); FIG2, AGA1, FIG1 and FUS1 are involved in cell fusion (Erdman et al, J. Cell Biol, 140:461 (1999); Roy et al, Mol Cell Biol, 77/4196 (1991); Truehart et al, Mol Cell biol, 7/2316 (1987); McCaffrey et al, Mol Cell Biol. 7/2680 (1987)); and OKI and KAR5 are required for nuclear fusion (Marsh, L. and Rose, M.D. in The Moelcular and Cellular Biology ofthe Yeast Saccharomyces, J.R. Pringle, J.R. Broach, E.W. Jones, Eds. (Cold Spring Harbor Laboratory Press, Cold Spring Harbor, 1997), vol. 3, pp. 827-888). Furthermore, FUS3 and FAR1 are required for pheromone-induced cell cycle arrest (Chang et al, Cell, 63:999 (1990); Fujimura, Curr. Genet., 18:395 (1990)). Stel2 binds to some promoters in the absence of pheromone signaling, however, its binding to most genes is enhanced by alpha factor. Interestingly, Stel2p is bound to its own promoter both before and after pheromone treatment. Together, the binding and expression data argue that the regulation ofthe STE 12 gene involves a positive feedback loop. STE 12 expression is increased immediately after pheromone treatment, indicating that the bound but inactive Ste 12 activator is rapidly converted to an active form. Increased expression of STE 12 gene would allow more Stel2p to be made and this would, in turn, activate its genes. Twenty- four genes whose expression were not previously associated with Ste 12 and the mating process were found to be bound by Ste 12 and activated by alpha factor. Considering that their pheromone induction is eliminated in Stel2 mutant cells, it is likely that these 24 genes are also genuine Stel2 targets. The identities of these genes indicate interesting details about various steps ofthe mating process. For example, one Stel2 target gene, PCL2, encodes a Gl cyclin that forms complexes with the cyclin-dependent kinase (cdk) Pho85. The Pcl2-Pho85 and PCl l-Pho85 complexes act in concert with Clnl-Cdc28 and Cln-2-Cdc28 cyclin dependent kinase complexes to promote Glcell cycle progression (Measday et al, 1994). The Pcl2-Pho85 kinase complex has a substrate specificity that is overlapping but different from that ofthe Clnl-Cdc28 and Cln2-Cdc28. During the mating process, haploid yeast cells are arrested at start ofthe late Gl phase, due to the inhibition of Clnl-Cdc28 and Cln2-Cdc28 activities by Farl, which is encoded by another Ste 12 target gene. Activation of PCL2 by Ste 12 after pheromone treatment indicates that increased Pho85 complex activities are likely necessary to compensate for the loss of Cdc28 activities. Most Stel2 target genes identified by analysis of genome locations of Stel2 and expression profiles during pheromone induction encode proteins involved in various steps of the mating response. Among them are 11 previously uncharacterized. The cellular roles for these genes, including YNL279W, YOR129C, YOR343C, YPL192C, YER019W, YIL083C, YEL037C, YIL169C, YNL105W, YOL155C and YNR064C, are therefore most likely related to mating. Among the Ste 12 target genes identified in this study that were not previously reported to be involved in mating, many are involved in processes likely to be relevant to mating. CSH1, PCL2, ERG24, SPC25, HYM1, and PGM1 encode proteins involved in cell wall biosynthesis, cell morphology, membrane biosynthesis, nuclear congression and regulation of gene expression. Furthermore, /059371 -35- YER019W, YOR129C and SCH9 are among genes that are cell cycle regulated (Spellman et al, Mol. Cell Biol, P/3273 (1999). The genes that are regulated by Ste 12 can be divided into two classes: those bound by Ste 12 both before and after pheromone exposure (e.g., STE 12, PLC2, FIG2 and FUS1), and those bound by Stel2 only after exposure to pheromone (e.g., CKI1 and CHS1). The first class of genes is induced immediately after pheromone exposure, most likely by a mechanism that converts an inactive DNA-bound Ste 12 protein to an active transcriptional activator. This could take place by removal of repressors of Stel2 such as Digl/Rstl and Dig2/Rst2 (Olson et al, Mol. Cell Biol, 20:4199 (2000)). In the second class of genes, induction of transcription is relatively slow. In this case, the binding of Ste 12 appears to be limited before pheromone exposure. It is also possible that the epitope tag on Ste 12 is masked at these promoters before pheromone treatment, perhaps due to the presence of additional regulatory proteins. Stel2 has also been implicated in other cellular processes. Together with Tecl, Ste 12 regulates the filmamentation of diploid cells and invasive growth in haploids. Two genes, TEC1 and FLO11, have been identified as Stel2 targets in filamentous growth pathway. Ste 12 binding to these genes either in the presence or absence of alpha factor was not detected. It is likely that Stel2p's binding to these promoters is regulated by different physiological conditions. As shown herein, a combination of genome-wide location and expression analysis can identify the global set of gens whose expression is controlled directly by transcriptional activators in vivo. The application of location analysis to two yeast transcriptional activators revealed how multiple functional pathways are coordinately controlled in vivo during the response to specific changes in the extracellular environment. All ofthe known targets for these two activators were confirmed, and functional modules were discovered that are regulated directly by these factors. Expression analysis with DNA microarrays allows identification of changes in mRNA levels in living cells, but the inability to distinguish direct from indirect effects limits the interpretation ofthe data in terms ofthe genes that are controlled by specific regulatory factors. Genome-wide location analysis provides information on the binding sites at which proteins reside through the genome under various conditions in vivo. Tr>W= n Consensus Binding Motifs of Promoters Sound by Y ^ ast Cell C vcl * Transcriptional Regulators. y as aa JIIDU toAnanΛ L 10 13 It,- 5 30 • * 10" " Kcrasnoss ol amilai mouiE 0 -38- Example 3 SERIAL REGULATION OF TRANSCRIPTIONAL REGULATORS IN THE YEAST CELL CYCLE Experimental Procedures Tagging and Yeast Strains The cell cycle activators Swi4, Mbpl, Swi5, Fkhl, Fkh2, Nddl Mcml, and Ace2 were tagged with a multicopy myc epitope by inserting the epitope coding sequence into the normal chromosomal loci of these genes. Vectors developed by Cosma et al. Cell, 97:299-311 (1998) were used for amplifying a fragment that contains the repeated myc tag coding sequence flanked by 50 bp from both sides of the stop codon ofthe gene. The PCR products were transformed into the 303 strain Z1258 (MATα, ada2-l, lrpl-1, canl-100, leu2-3, 112, his3-l l, 15, ura3) to generate the tagged strains (Z1335, Z1372, Z1373, Z1446, Z1370, Z1369, Z1321, and Z1371, respectively). Clones were selected for growth on TRP plates, the insertion ofthe tagged sequence was confirmed by PCR, and expression ofthe epitope-tagged protein was confirmed by Western blotting using an anti-Myc antibody (9E11). A strain containing a myc-tagged version of Swi5 (Z1407) was obtained from K. Nasmyth). Genome- Wide Location Analysis Genome-wide location analysis as described inRen et al. Science, 290:2306- 2309 (2000) was used to identify genome binding sites for the transcription factors. Briefly, yeast strains containing a myc-tagged version ofthe protein of interest were grown to mid log phase (OD 0.6-1.0), fixed with 1% formaldehyde for 30 minutes, harvested and disrupted by sonication. The DNA fragments crosslinked to the protein were enriched by immunoprecipitation with anti-myc specific monoclonal antibody (9E11), thus obtaining an enrichment ofthe in vivo binding sites. After reversal ofthe crosslinks, the enriched DNA was amplified and labeled with a fluorescent dye (Cy5) with the use of a ligation-mediated polymerase chain reaction (LM-PCR). A sample of DNA that was not enriched by immunoprecipitation was subjected to LM-PCR in the presence of a different fluorophore (Cy3), and both immunoprecipitation (IP)-enriched and -unenriched pools of labeled DNA were hybridized to a single DNA microarray containing all yeast intergenic sequences. Microarray design and production was as described in Ren et al. Science, 290:2306- 2309 (2000). Images of Cy3 and Cy5 fluorescence intensities were generated by scanning the arrays using a GSI Lumonics Scanner. The Cy3 and Cy5 images were analyzed using ArrayVision software, which defined the grid of spots and quantified the average intensity of each spot and the surrounding background intensity. The background intensity was subtracted from the spot intensity to give the final calculated spot intensity. The intensity ofthe two channels was normalized according to the median. For each spot, the ratio of corrected Cy5/Cy3 intensity was computed. Each experiment was carried out in triplicate, and a single-array error model was used to handle noise, to average repeated experiments with appropriate weights, and to rank binding sites by p value as described (See also http://web.wi.mit.edu/young/cellcycle which is incorporated herein by reference; Ren et al. Science, 290:2306-2309 (2000)). The intergenic regions present on the array were assigned to the gene or genes found transcriptionally downstream. Where a single intergenic region contains promoters for two divergently transcribed genes, the intergenic region was assigned to the gene or genes expressed during the cell cycle according to the Spellman et al. Mol. Cell Biol. Cell, P/3273-3297 (1998) analysis. The Spellman et al 1998 analysis was chosen because it incorporates all available yeast cell cycle expression data. Promoter regions detected with a p value O.001 were included for further analysis. Statistics In order to explore the statistical significance ofthe overlap between the set of targets of a factor and the genes expressed in a particular cell cycle stage, the hypergeometric distribution as described in Tavazole et al Nat. Genet., 22:281-285 (1998) was used. Results Genome-wide location analysis (Ren et al, Science, 290:2306-2309 (2000)) was used to identify the in vivo genome binding sites for each ofthe known cell cycle transcription factors (Figures 9A and 9B). Yeast strains, each containing a myc-tagged version of Mbpl, Swi4, Swi6, Mcml, Fkhl, Fkh2, Nddl, Swi5, or Ace2, were grown in asynchronous cultures to mid log phase and subjected to location analysis as described previously (Ren et al, Science, 290:2306-2309 (2000)). Each experiment was carried out in triplicate, and a single array error model was used to handle noise, to average repeated experiments with appropriate weights, and to rank binding sites by p value (Figures 9B and 9C). Asynchronous cultures were used because previous studies showed that the results obtained for Swi4 in genome-wide location experiments are essentially identical in unsynchronized and arrested cultures (Iyar et al, Nature, 409:533-536 (2001)), and because it was not feasible to obtain high quality datasets in triplicate at multiple cell cycle time points for all nine factors. The regulation ofthe cell cycle expression program by each ofthe nine factors is summarized in Figures 10A-10B. The binding of a transcriptional activator to the promoter region of a gene suggests that the activator has a regulatory effect on the gene, but it is also possible that the activator does not fully or even partially control the gene. For this reason, we have identified the set of genes where factor binding correlates with gene expression, an approach that produced highly accurate information on transcription factor function in previous studies with other factors (Ren et al, Science, 290:2306-2309 (2000)). The set of genes bound by the nine cell cycle transcription factors was compared to the set of approximately 800 genes whose expression levels vary in a periodic fashion during the yeast cell cycle (Spellman et al. Mol Cell Biol. Cell, P/3273-3297 (1998)). The proportion ofthe 800 genes whose promoters are bound by one or more ofthe nine transcription factors studied here varies with the stringency ofthe one analysis criteria for binding data (27% at pO.OOl, 37% at pO.Ol; 50% at p< 0.05). Further discussion was focused on results obtained with the highest stringency criteria (p<0.001) because a previous investigation using this approach detected no false positives in followup studies (Ren et al, Science, 290:2306-2309 (2000); http://web.wi.mit.edu/young/cellcycle; http://www.cell.eom/cgi/content full/106/6/697/DCn. Collaboration of Regulators in Periodic Gene Expression A model for transcriptional control of cell cycle genes has been developed that is based on studies involving a relatively small number of genes. In this model, MBF and SBF control expression of late Gl genes (Koch et al, Curr. Opin. Cell Biol, 6/451-459 (1994)); a complex of Mcml, Nddl, and Fkhl/Fkh2 controls G2/M genes (Koranda et al, Nature, 406:94-98 (2000); Kumar et al, Curr. Biol, 10:896- 906 (2000); Pic et al, EmboJ., iP/3750-3761 (2000); Zhu et al, Nature, 406:90-94 (2000)); and Mcml, Swi5, and Ace2 regulate genes expressed in M Gl (McBride et al., J. Biol. Chem., (1999); Mclnerny et al. , Genes Dev., 11:1277- 1288 (1997)). The genome-wide binding data for these activators support this model (Figures 10A-10B) and provide compelling evidence for collaboration among specific factors in genome-wide regulation. Mbpl, Swi4, and Swi6 bound predominantly to promoter regions of late Gl genes (p<10 '14 , p<10 "18 , and p<10 "20 respectively), Swi5 and Ace2 to M Gl genes (p<10 "14 and p<10 "3 , respectively), and Mcml, Fkh2, and Nddl to G2/M genes (p<10 "14 , p<10 '15 , and p<10- 21 , respectively). Thus, the data described herein generally support the model for stage-specific regulation of gene expression by these activators and extend it to encompass promoters for several hundred cell cycle genes. The data described herein also provide novel insights into stage-specific gene regulation by these factors. Previous studies suggested that Fkhl and Fkh2 are homologs that function in concert with Mcml during G2/M (Zhu et al, Nature, 406:90-94 (2000)), but it was found that Fkhl and Fkh2 are also associated with genes expressed in Gl and S, where Mcml binding could not be detected (Figures 10A-10B). The combination of Mcml , Fkh2, and Nddl bound predominantly to G2/M genes, as expected, but Mcml was also bound to genes expressed during M/Gl (p<10 '6 ), where binding by Fkhl, Fkh2, or Nddl could not be detected. These results indicate that differential regulation of Mcml and Fork-head target genes in different stages ofthe cell cycle are likely governed by the association of these factors with different regulatory partners. Further identification ofthe genomic binding sites of all yeast transcriptional activators will likely reveal these partners. Regulation of Transcriptional Regulators The extent to which the cell cycle transcriptional regulate expression of other regulators was examined. Previous studies established that genes encoding several ofthe cell cycle transcriptional regulators are themselves bound by other cell cycle regulators (Figure 11 A), SWI4 is regulated by Mcml and Swi6 (Foster et al, Mol. Cell Biol, 75/3792-3801 (1993); Mackay et al, Mol. Cell Biol, 27/4140-4148 (2001); Mclnerny et al, Genes Dev., 77/1277-1288 (1997)), Swi5 is regulated by Mcml/Fkh2/Nddl complex (Koranda et al, Nature, 406:94-98 (2000); Kumar et al Curr. Biol, 70/896-906 (2000); Pic et al, Embo J., 7P/3750-3761 (2000); Zhu et al, Nature, 406:90-94 (2000)), and expression of ACE2 is affected by depletion of Mcml (Althoefer et al, 1995). The genome-wide location data confirmed these results. The location data also revealed that the set of factors that regulates genes during each phase ofthe cell cycle also regulates expression of one or more activators involved in the next phase ofthe cell cycle, forming a fully connected regulatory network (Figure 1 IB). The regulatory network from the genomic binding data (Figure 1 IB) described herein can be described as follows. SBF (Swi4/Swi6) and MBF (Mbpl/Swi6), which are active during late Gl, both regulate NDDL Nddl protein is a limiting component ofthe complex that activates G2/M genes; Mcml and Fkh2 are bound to promoters throughout the cell cycle, and activation of G2/M genes is dependent on recruitment of Nddl (Koranda et al. Nature, 406:94-98 (200O)). The Mcml/Fkh2/Nddl complex regulates SWI5 and ACEL Swi5, Ace2, and Mcml activate /G7 genes. Mcml binds to the SWL4 promoter and contributes to its activation in M/Gl, leading to accumulation ofthe Swi4 subunit ofthe SBF transcription factor in Gl . All three M/Gl transcription factors regulate CLN3, whose protein product forms a complex with Cdc28, which in turn activates SBF and MBF during late Gl (Dirick et al. Embo. J., 74/4803-4813 (1995)). Swi4 transcription is further regulated in late Gl by both SBF and MBF. Thus, the serial regulation of cell cycle regulators occurs throughout the cycle, forming a fully connected regulatory network that is itself a cycle. Cyclin CDK Regulation The transition between stages ofthe cell cycle is associated with oscillations in the activity of Cdc28-cyclin complexes; cyclin synthesis is necessary for phase entry, and CDK-cyclin inhibition/degradation is necessary for phase exit (Morgan, Annu. Rev. Cell Biol, 73/261-291 (1997)). The Gl and S cyclins Clnl, Cln2, Clb5, and Clb6 accumulate and associate with Cdc28 in late Gl, and cyclins Clbl-Clb4 accumulate and associate with Cdc28 in G2 and M (Nasmyth, 1996). These cyclin- CDK complexes can be inhibited by specific cyclin-CDK inhibitors such as Sicl and Farl (Mendenhall et al. Annu. Rev. Cell Biol, 73/261-291 (1997)), or can be targeted for degradation by, for example, the anaphase promoting complex (APC) (King et al, Science, 274:1652-1659 (1996)). Previous studies identified the transcriptional regulators for most cyclin genes (Figure 12A). SBF and MBF control transcription of Gl and S cyclin genes (Iyar et α/. Nature, 409:533-536 (2001); Koch et al, Curr. Opin. Cell Biol, (5/451- 459 (1994)). SBF also participates in the regulation of CLB1 and CLB2 (Iyar et al. Nature, 409:533-536 (2001)). The Mcml/Fkh2/Nddl complex regulates the CLB2 gene in G2/M (Koranda et al. Nature, 406:94-98 (2000); Kumar et al, Nature, 406:94-98 (2000); Pic et al. Embo J., 7P/3750-3761 (2000); Zhu et al Nature, 406:90-94 (2000)), and Mcml regulates transcription of GLN3 in M/Gl (Mackay et al. Mol. Cell Biol, 27/4140-4148 (2001); Mclnerny et al. Genes Dev., 77/1277-1288 (1997)). Our results confirm these observations and reveal that Fkhl binds the CLB4 promoter. The additional target genes bound by the cell cycle transcriptional regulators described herein reveal that transcriptional regulation is more involved in cell cycle progression than previously reported. Transcription factors that regulate cyclin genes during each phase ofthe cell cycle also regulate genes encoding key components involved in transitioning to the next stage ofthe cell cycle (Figure 12B). The location analysis indicates that SBF and MBF control transcription of Gl/M cyclin genes, but also regulate expression ofthe G2/M cyclin Clb2, which inhibits further expression ofthe Gl/S cyclins Cinl and Cin2 (Amon et al. Cell, 74/993-1007 (1993)) and promotes entry into mitosis (Surana et al. Cell, (55/145-161 (1991)). SBF and MBF also regulate the transcription ofthe transcription factor Nddl, which also binds the CLB2 promoter. Thus, SBF, MBF and Nddl ultimately collaborate to regulate transcription ofthe CLB2 gene. SBF and MBF therefore regulate genes necessary for the transition through Gl/S, as well as genes whose products set the stage for further progression through the cell cycle. The data also reveal that the G2/M activators (Mcml/Fkh2/Nddl) bind genes whose expression is necessary for both entry into and exit from mitosis. The G2/M activators bind and regulate transcription of CLB2, whose product is necessary to enter mitosis (Surana et al. Cell, (55/145-161 (1991)). They also set the stage for exit from mitosis by regulating the gene encoding Cdc20, an activator ofthe APC, which targets the APC to degrade Pdsl and thus initiate chromosome separation (Nisintin et al. Science, 278:450-463 (1997)). Cdc20-activated APC also degrades Clb5 (Shirayama et al. Nature, 402:203-207 (1999)) and thus enables Cdcl4 to promote the transcription and activation of Sicl (Shirayama et al. Nature, 402:203-207 (1999)) and to initiate the degradation of Clb2 (Jaspersen et al, Mol. Biol. Cell, 0:2803-2817 (1998); Nisintin et al, Science, 275/450-463 (1997)). In addition, the G2/M activators Mcml/Fkh2/Νddl regulate transcription of SPO12, which encodes a protein that also regulates mitotic exit (Grether et al, Mol. Biol. Cell, 10:3689- 2703 (1999)). The M/Gl transcriptional regulators (Mcml, Ace2, and Swi5) bind genes that are key to entering and progressing through Gl . Swi5 binds to the S7C7 promoter, and all three transcriptional regulators bind to the GLN3 promoter. Sicl inhibits Clb-Cdc28 during mitosis (Toyn et al. Genetics, 145:85-96 (1997)), thus facilitating exit from mitosis. Cln3-Cdc28 activates SBF and MBF in late Gl (Dirick et al. Embo. J, 74:4803-4813 (1995)), thus setting the stage for another cell cycle circuit. In summary, knowledge ofthe global set of cyclin and CDK regulatory genes that are bound by each ofthe transcriptional activators provides a much enriched model to explain how transcriptional regulation contributes to cell cycle progression (Figure 12B). Regulation of Stage-Specific Functions The genomic location data revealed how specific factors regulate genes associated with stage-specific cell cycle functions (Figure 13). SBF regulates genes involved in the morphological changes associated with cell budding, and MBF controls genes involved in DNA replication and repair, confirming a previous study (Iyer et al, Nature, 409:533-536 (2001)). SBF is also bound to the promoters of several histone genes (HTA1, HTA2, HTA3, HTB1, HTB2 and HHO1), which makes it likely that SBF contributes to the increase in histone gene transcription observed at S phase. Fkhl was found to bind various genes that encode proteins associated with chromatin structure and its regulation; these include histones (HHFl and HHT1), telomere length regulators (TEL2 and CTF18), a shared component of the chromatin remodeling complexes Swi/Snf and RSC (ARP7), and a histone deacetylase (HOS3). The G2/M activators (Mcml/Fkh2/Nddl) bind genes that regulate the transition through mitosis (SWI5, ACE2, CLB1, CDC20 and SP012). Ace2 and Swi5 regulate genes involved in cytokinesis (CTS1 and EGT2), whereas Mcml (apparently in absence of Fkhl, Fkh2 and Nddl) regulates genes encoding proteins involved in prereplication complex formation (MCM3, MCM5/CDC46, MCM6 and CDC6) and in mating (STE2, STE6, FAR1, MFA1, MFA2, AGA1, and AGA2). A summary of binding data for each ofthe transcriptional regulators is presented in Table 3. Table 3 Selected Targets of the Cell Cycle Activators Mcml/ Fkh2/ segregation TEM1 + + GTP-bmding protein of the ras superfamily involved in termination of M-phase CDC20 + + Protein required for microtubule function at mitosis SP012 + + + Sporulation protein required for chromosome division in meiosis I CLN3 + + +/- Gl/S-specific cyclin DBF2 + Serine/threonine protein kinase related to Dbf20p FAR1 + Inhibitor of Cdc28p-Cln1p and Cdc28p-Cln2p kinase complexes Table 3 Continued Mcml/ Fkh2/ Gene SBF MBF Fkhl Fkh2 Nddl Mcml Ace2 Swι5 Short description Cell wall CSH1 + Chitin synthase I biogenesis, budding, and cytokinesis TEC1 + Transcriptional activator EGT2 + + Cell-cycle regulation protein, may be involved in cytokinesis GIC2 + + Putative effector of Cdc42p, important for bud emergence SWC11 + + Putative cell wall protein GIN4 + + Seπne/threonine-protein kinase BUD9 + + + + + Protein required for bipolar budding OCH1 + Alpha-1 , 6-mannosyltransferase CTS1 + + + Endochitinase RSR1 + GTP-bmding protein of the ras superfamily involved in bud site selection CRH1 + + + Protein for which overproduction suppresses bud emergence defects MSB2 + Cell wall protein MNN1 + Exo-beta-1 , 3-glucanase (l/l I) EXG1 + + + + + + Alpha-1 , 3-mannosyltransferase GLS1 + Component of beta-1 , 3-glucan synthase GAS1 + Glycophosphohpid-anchored surface glycoprotein PSA1 + + Mannose-1 -phosphate guanyltransferase KRE6 + Glucan synthase subunit required for synthase of beta-1 , 6-glucan GIC1 + + Putative effector of Cdc42p, important for bud emergence CWP1 + + Mannoprotein of the cell wall, member of the PAU1 family CIS3 + + Cell wall protein CWP2 + + + + + Protein that controls interaction of bud-neck cytoskeleton with G2 nucleus BUD4 + + + Protein required for axial budding but not for bipolar budding WSC4 + Protein required for maintenance of cell wall integrity BUD8 + Protein required for bipolar budding SCW4 + Cell wall protein, similar to gulcanases RAX2 + + + Protein involved in bipolar budding SKN1 + Glucan synthase subunit Table 3 Continued Mcml/ Fkh2/ Gene SBF MBF Fkhl Fkh2 Nddl Mcml Ace2 Swι5 Short descπption DNA RNR1 + + + Ribonucleotide reductase large replication subunit RAD27 + Single-stranded DNA endonuclease and 5'-3' exonuclease CDC21 + Thymidylate synthase, converts dUMP to dTMP IRR1 + Component of cohesin complex MCD1 + Cohesin, protein required for mitotic chromatid cohesion PDS5 + + + Protein required for sister chromatid cohesion RAD51 + + Protein that stimulates paiπng and strand-exchange between homologous DUN1 + Protein kinase required for induction of DNA repair genes after DNA damage ALK1 + DNA damage-responsive protein Chromatin CTF18 + Protein required for maintenance of normal telomere length HHF1 +/- Histone H4, identical to Hhf2p HHT1 +/- Histone H3, identical to Hht2p HTB2 + Histone H2B, nearly identical to Htblp HTB1 + Histone H2B HTA1 + Histone H2A, identical to Hta2p HTA2 + Histone H2A, identical to Htalp HH01 + Histone H1 TEL2 + Protein involved in controlling telomere length and telomerre position effect ARP7 + Component of SWI-SNF and RSC chromatin remodeling complex HTA3 + Histone-related protein that can suppress histone H4 point mutation H0S3 + Protein with similiaπty to Hdal p, Rpd3p, Hos2p, and Hosl p Table 3 Continued Mcml/ Fkh2/ Gene SBF : MBF Fkhl Fkh2 Nddl Mcml Ace2 Swι5 Short description Prereplication MCM3 + Protein that acts at ARS elements complex to initiate replication CDC6 + + + Protein that regulates initiation of DNA replication CDC46 + Protein that acts at ARS elements to initiate replication CDC45 + Protein required for initiation of chromosomal DNA replication MCM2 + Protein that acts at ARS elements to initiate replication MCM6 + Protein involved in DNA replication, member of the MCM/P1 family of proteins Mating ASH1 + GATA-type transcription factor, negative regulator of HO expression AGA2 + a-Agglutinin binding subunit AGA1 + + + a-Agglutinm anchor subunit HO + Homothalhc switching endonuclease MFA1 + Mating pheromone a-factor, exported from cell by Steδp MFA2 + Mating pheromone a-factor, exported from cell by Ste6p STE6 + Membrane transporter responsible for export of "a" factor mating pheromone STE2 + Pheromone alpha-factor receptor, has seven transmembrane segments FAR1 + Inhibitor of Cdc28p-Cln1p and Cdc28p-Cln2p kinase complexes A partial list of cell cycle genes whose promoter regions were bound by the indicated cell cycle regulators + indicates binding with P<0 001 , +/- indicates binding with P<0 0015 A full list of target genes is available at the author's web site (http //web wi mit edu/young/cellcycle) The DNA replication category includes genes that function in DNA synthesis, in DNA repair and in sister chromatid cohesion Functional Redundancy The factor location data demonstrate that each ofthe nine cell cycle transcription factors binds to critical cell cycle genes, yet cells with a single deletion of MBP1, SWI4, SWI6, FKH1, FKH2, ACE2, or SWI5 are viable; only MCM1 and NDD1 are essential for yeast cell survival (Breeden Curr. Biol, 70.-R586- R588(2000); Loy et αl Mol. Cell Biol, 7P.-3312-3327 (1999); Mendenhall et αl, Mol. Biol. Rev., (52:1191-1243 (1998)). The conventional explanation for this observation is that each nonessential gene product shares its function with another. Swi4 and Mbpl share 50% identity in their DNA binding domains (Koch et αl Science, 261:1551-1557 (1993)). Similarly, Fkhl and Fkh2 are 72% identical (Kumar et αl. Curr. Biol, 70:896-906 (2000)), and Swi5 and Ace2 are 83% identical in their respective DNA binding domains (McBride et αl. J. Biol Chem., 274:21029- 21036 (1999)). Each of these pairs of proteins recognizes similar DNA motifs, so it is likely that functional redundancy rescues cells with mutations in individual factors. However, it was not clear whether each ofthe pairs of factors had truly redundant functions in normal cells, or whether they exhibit redundant function only in mutant cells that lack the other factor. The data described herein demonstrates that each ofthe cell cycle factor pairs discussed above does bind overlapping sets of genes in wild-type cells, revealing that the two members of each ofthe pairs are partially redundant in normal cell populations (Figures 14A-14B). Mbpl and Swi4 share 34% of their target genes, Fkhl and Fkh2 share 22%, and Ace2 and Swi5 share 25%. It is also clear, however, that this redundancy does not apply to all genes regulated by a pair of related activators in wild-type cells. The partial overlap in genes under the control of pairs of regulators explains why one gene of a pair can rescue defects in the other, yet each member ofthe pair can be responsible for distinct functions in wild-type cells. Discussion Identification ofthe transcriptional regulatory network that controls the cell cycle clock is essential to fully understand how cell cycle control is effected. As described herein, the genomic targets of each of the nine known yeast cell cycle regulators have now been identified using a combination of genome- wide location and expression analysis. The investigation revealed that a connected, circular transcriptional regulatory network has evolved to control the cell cycle, and showed how each ofthe transcriptional regulators contributes to diverse stage-specific functions Cell Cycle Transcriptional Regulatory Networks A key concept that emerged from this study is that cell cycle transcriptional control is effected by a connected regulatory network of transcriptional activators. The cell cycle transcriptional regulators that function during one stage ofthe cell cycle regulate the transcriptional regulators that function during the next stage, and this serial regulation of transcriptional regulators forms a complete regulatory circuit. Thus, the transcriptional regulatory network that controls the cell cycle is itself a cycle of regulators regulating regulators. The discovery of this connected transcriptional regulatory network is important for several reasons. It provides additional understanding ofthe regulatory mechanism by which cells ensure transitions from one stage into the appropriate next stage. It supplies the foundation for future work on the mechanisms that coordinate gene expression and other aspects of cell cycle regulation. Furthermore, it suggest that a connected, circular transcriptional regulatory network is likely a fundamental feature of cell cycle regulation in other, more complex, organisms. It is interesting to consider why cells have pairs of cell cycle transcriptional regulators with partially redundant functions. This configuration may help ensure that the cell cycle is completed efficiently, which is critical since the inability to complete the cycle leads to death. At the same time, devoting each ofthe pair to distinct functional groups of genes enables coordinate regulation of those functions. It is also likely that partial redundancy helps the cell to make a smoother temporal transition from one mode of operation to another during the cell cycle. The results described herein identify how the cyclin genes regulated, by the nine transcriptional activators. In addition, the results reveal that transcription factors that regulate the cyclin genes during each phase ofthe cell cycle also regulate genes that are involved in transitioning to the next stage ofthe cycle (Figures 12A- 12B). For example, the Gl/S activators SBF and MBF control transcription of Gl/S cyclin genes, but also regulate expression of G2/M cyclin Clb2, which subsequently inhibits further expression ofthe Gl/S cyclins Cinl and Cin2 and promotes entry into mitosis. Thus, the cell cycle transcriptional regulatory network has evolved so that some transcriptional regulators contribute to the control of both stage entry and exit. The identification of sets of genes that are bound by each of these regulators reveals how coordinate regulation of a wide variety of stage-specific cell cycle functions is regulated (Figure 13). For example, the Gl/S activators regulate genes involved in cell budding, DNA replication and repair, and chromosome maintenance. The G2/M activators bind genes that regulate transition through mitosis. The late M factors regulate genes involved in cytokinesis and prereplication complex formation. A more comprehensive picture of cell cycle regulation emerges when existing knowledge of cell cycle regulatory mechanisms is combined with the new information on the transcriptional regulatory network. Several key features of this integrated view have important implications for cell cycle regulation. Cells commit to a new cell cycle at START, but only after cell growth is sufficient to ensure completion ofthe cycle, since the inability to complete the cell cycle can be lethal (Mendenhall et al, Mol. Biol. Rev., 62:1191-1243 (1998)). The emphasis on regulation at the Gl/S boundary is evident from the regulatory events involving Swi4 in the model shown in Figure 3B. The Swi4 regulator becomes functionally active at START, via a mechanism that is dependent on Cln3-Cdc28, when the cell reaches a critical size (Dirick et al, Embo. J., 74:4803-4813 (1995)). The SWL4 promoter is bound by Swi4 itself, indicating that a positive feedback loop exists to ensure that adequate levels of Swi4, and thus, SBF, are present prior to commitment. The observation that the Gl/S regulators SBF and MBF both regulate NDD1 suggests how adequate levels of Nddl are produced to initiate the G2/M transcriptional program. Nddl protein is a limiting component ofthe complex that activates G2/M genes; Mcml and Fkh2 are bound to promoters throughout the cell cycle, and activation of G2/M genes is dependent on recruitment of Nddl (Koranda et al, Nature, 406:94-98 (2000). The Mcml/Fkh2/Nddl complex regulates SWL5 and ACE2, whose products become functional only in late anaphase after relocalization to the nucleus in a mechanism that is dependent on low Clb-Cdc28 activity (Nasmyth et al, Cell, 62:631-647 (1990); Shirayama et al, Nature, 402:203-207 (1999)). Later in the cell cycle, the Swi5, Ace2, and Mcml factors all bind to the CLN3 promoter, thus assuring adequate levels ofthe Cln3 cyclin at START. The cell cycle transcriptional regulatory network model accounts for several observations relevant to cell cycle regulation. The use of multiple transcription factors to regulate key transcription and cyclin regulators explains why mutations in single transcription factors generally have only limited effects on progression through the cell cycle, whereas mutations in activator pairs can have substantial effects (Breedon, Curr. Biol, 70:R586-R588(2000); Koch, et al, Science, 261:1551-1557 (1993); Mendenhall et al, Mol. Biol. Rev., (52:1191-1243 (1998)). Nutrient limitation causes yeast cells to arrest cell cycle progression, but rather than counting at the time of nutrient limitation, the arrest is delayed until the cells reach Gl (Mendenhall et al, Mol. Biol Rev., 62:1191-1243 (1998)). Cells that have entered the cell cycle at START may progress through an entire cycle because ofthe design ofthe connected transcriptional regulatory network (Figure 1 IB), and perhaps then arrest in Gl because ofthe requirement for adequate levels of Cln3/Cdc28. Several cell cycle checkpoint controls are mediated by regulation of Cdc28 activity (Mendenhall et al, Mol. Biol Rev., 62:1191-1243 (1998)), but how Cdc28 activity affects the transcription program is not well understood. Since the activity of several ofthe cell cycle transcriptional regulators is dependent on Cdc28 activity, some checkpoint controls may effect arrest by perturbing the connected transcriptional regulatory circuit. Importance of Direct Binding Information An impetus for the development of methods that identify the genomic binding sites of factors in vivo was the realization that regulatory networks cannot be accurately deduced from global expression profiles because it is not possible to discriminate between direct and indirect effects due to genetic or other perturbations in living cells (Ren et al, Science, 290:2306-2309 (2000)). A further challenge for understanding global gene regulation is that comparison of wild-type and mutant expression profiles produce valuable information on dependencies when the mutant gene is essential, but it is more difficult to interpret such information when the mutant gene can be rescued by functionally redundant gene products. It was found herein that the direct binding data obtained in the present study was remarkably confirming of previous evidence for gene regulation by specific transcription factors when that evidence was direct. In contrast, evidence in support of many studies in which the involvement of a factor in the regulation of a gene was deduced from indirect evidence was not obtained (Althoefer et al, Mol. Cell Biol, 15:5917-5928 (1998); Gordon, et al, Proc. Natl. Acad. Sci., USA, 88:6058-6062 (1991); Koch, et al, Science, 267:1551-1557 (1993); Lowndes et al/. Nature, 350:247-250 (1991); Platt et al, Embo J., 74:3788-3799 (1995); Pizzagalli et al, Proc. Natl. Acad. Sci., USA, 55:3772-3776 (1988); Toone et al, (1995); Nerma et al, Proc. Natl. Acad. Sci., USA, 55:7155-7158 (1991)). The identification ofthe set of promoters bound in vivo by each ofthe cell cycle regulators allowed identification of consensus sequence motifs (see http://web.wi.mit.edu young/cellcycle). Two general insights emerged from this analysis. First the binding motifs identified for some factors are found in most, but not all, ofthe promoters that they bind, indicating that variations of the consensus sequence exist that are not easily recognized by search algorithms or that the transcription factor is modified or associated with binding partners that generate a new binding preference at some genes. In this context, it is interesting that the Mcml binding motif is somewhat different in the promoters of its G2/M targets than in its M/Gl targets, probably reflecting the influence of its binding partners. Second, the presence ofthe DΝA binding motif in genomic DΝA is not by itself a predictor of protein binding in vivo, as the predicted motifs are found at many sites in the genome other than those bound in vivo. There is, therefore, a need for empirical binding data such as that described here in order to accurately identify genuine binding sites. Discovering Genetic Regulatory Networks Understanding how biological processes are regulated on a genomic scale is a fundamental problem for the coming decades. Maps of metabolic pathways have been key to studying basic biology, uncovering disease mechanisms, and discovering new drugs over the last century. Maps of genomic regulatory networks will play an equally important role in future biological discovery. The location data presented herein are well adapted to new computational approaches to discovering genetic regulatory networks. The binding of a transcriptional activator to the promoter region of a gene indicates that the activator has a regulatory effect on the gene. However, it is also possible that the activator does not fully or even partially control the gene. Thus, location information must be fused with other data, such as expression data, to fully elaborate the complete mechanism of transcriptional regulation and the form of regulatory networks. New computational approaches will synergistically combine location data with other data types to form a well-focused picture of cellular function. For example, one way to combine location and expression data is to use the location data to first suggest tentative factor-target pairs with associated p-values. These factor-target pairs represent constraints on the possible genetic regulatory network models, and they can be used to guide the search of network models based on expression data. This process can discover alternative models of regulatory networks, with a principled measure of likelihood assigned to each hypothesis. The likelihood measure appropriately reflects how consistent the hypothesis is with both location and expression data. This likelihood-based approach can accommodate location data, expression data, and other forms of data (Ross-MacDonald, et al, Nature, 402:413- 418 (1999); Uetz, et al, Nature, 403:623-627 (2000)) that can be usefully employed to assign probabilities to potential interaction. Example 4 STUDY DESIGN FOR SERIAL REGULATION OF TRANSCRIPTIONAL REGULATORS Serial Regulation of Transcriptional Regulators Study Design Genetic Reagents ' Oligo Table Strain List Technology Location Analysis Protocols Analysis Location Analysis Quality Control Search for Activator Binding Sites Download Datasets Table of Regulated Genes Previous Evidence of Regulation Gene Expression Data Alpha Factor Synchronization Insights Cell Cycle Regulation Additional Insights Summary Genetic Reagents The cell cycle activators Swi4, Mbpl, Swi6, Fkhl, Fkh2, Nddl, Mcml and Ace2 were tagged with a 9 or 18 copy myc epitope by inserting its coding sequence into the normal chromosomal loci of these genes. Vectors developed by K Nasmyth (Cosma et al., 1999) was used for recombination ofthe epitope coding sequence into the W303 strain Z1256. The specific oligonucleotides used to generate PCR products are described here. The PCR products were transformed into the strain Z1256 to generate the tagged strains. Clones were selected for growth on TRP- plates, and the insertion was confirmed by PCR and expression ofthe epitope-tagged protein was confirmed by western blotting using an anti-Myc antibody (9E11). A 9 myc tagged version of Swi5 (Z1407) was obtained from K Nasmyth. Protocols - Location Analysis The chromatin imunoprecipitation part of that protocol is based on a protocol obtained from the Nasmyth lab and one from Hecht, A., Strahl-Bolsinger, S., and Grunstein, M. , "Spreading of transcriptional repressor SIR3 from telomeric heterochromatin," Nature 383,92-6 (1996). The Nasmyth protocol was optimized for use with W303α strains tagged with a Myc 18 epitope inserted at the C-terminus of various transcription factors (strains obtained from Pia Cosma). • Microarray Production • Location Analysis Protocols Preparation of cells, cross linking, cell washing and storing Cell lysis, sonication, and immunoprecipitation Bead washing, elution from beads and reversal of cross linking DNA precipitation Blunting DNA and ligation of blunt DNA to linker Ligation-mediated PCR Pre-hybridization, probe preparation, hybridization and wash Appendices: • Preparation of magnetic beads • Preparation of unidirectional linker • Solutions Oligo List Strain Gene Tag Forward primer Backward primer ATAAGGGCGCAGAACAGATCATCACAATCT CTATTTTTCAGTATATGGATACATGTAAAGT Z1372 MBP1 18 myc CAAACGCGAATAGTCATGCAtccggttctgctgclag TCCTCTATTTATGTATATTcctcgaggccagaagac ACATTGACTCAAAATTGGACGATATAGAAA AAAAACTCTGATAATATAGTAAAAATTATTG Z1335 SW14 18 myc AGGATTTGAGGGCAAACGCAtccggttctgctgctag GTACATTGTGAATTAAAATcctcgaggccagaagac AAGACATTGACACTGACGAAATGCAAGATT AATAACTTCAAATAAAGTCATAAAAGTTAAT Z1373 SWI6 18 myc TTTTAAAAAAGCATGCTTCAtccggttctgctgctag GCAATGAAATCACATGCCCcctcgaggccagaagac CATCCATGGACGTAACAACAAACGCAAACG CTTTGTTCTTTATTGTTTAATAATACATATGG Z1448 FKH1 9 myc TGAACAATTCCTCTCTGAGTtccggttctgctgctag GTTCGACGACGCTGAATTcctcgaggccagaagac AGGAACTAATACTAGATACGGATGGTGCAA CCATTTCTCATTCATTTCTTTAGTCTTAGTGA Z1370 FKH2 18 myc AGATCAGTATTATCAACAACtccggttctgctgctag TTCACCTTGTTTCTTGTCcctcgaggccagaagac CAAGGAAAAGCTGTAATTCTAAATCTAATG GCTTGAAATTTCGATTAAAAAAAAAAGGTGA Z1369 NDD1 18 myc GAAATTTATTCAATTCACAGtccggttctgctgctag GATGCAAGTTTGGTTAATAcctcgaggccagaagac AGAATGCTGCCTACCAACAATACTTTCAAG CTTTTTCCTCTTAATGCTCGTCTATGAATTAT Z1321 MCM1 18 myc AACCGCAACAAGGCCAATACtccggttctgctgctag ATACGGAAATCGATAAGAcctcgaggccagaagac CGCACGAGCAAAACTCGAACCGCACCCTTT TATTGTTACTATTATTTATTATGTTAATATCATGC Z1371 ACE2 18 myc CAAACGAAACTGATGCTCTCtccggttctgctgctag ATAGATAAATGTTCGcctcgaggccagaagac GENE SEQ ID NO. Forward Primer SEQ ID NO. Reverse Primer MBP1 13 14 SWI4 15 16 SWI6 17 18 FKH1 19 20 FKH2 21 22 NDD1 23 24 MCM1 25 26 ACE2 27 28 Strain List Strain Genotype Z1256 MATa, ade2-l, tφl-1, canl-100, leu2-3,112, his3-l l,15, ura3, GAL+, psi+ MATa, ade2-l, tφl-1, canl-100, leu2-3,112, his3-l l,15, ura3, GAL+,psi+, Z1372 MBP1::18-Myc-MBP1 MATa, ade2-l, tφl-1, canl-100, leu2-3,112, his3-l l,15, ura3, GAL+,psi+, 21335 SWI4::18-Myc-SWI4 MATa, ade2-l, tφl-1, canl-100, leu2-3,l 12, his3-l 1,15, ura3, GAL+,psi+, Z1373 SWI6::18-Myc-SWI6 MATa, ade2-l, trpl-1, canl-100, leu2-3,112, his3-l l,15, ura3, GAL+,psi+, Z1448 FKH1 ::9-Myc-FKH1 MATa, ade2-l, tφl-1, canl-100, leu2-3,112, his3-l l,15, ura3, GAL+,psi+, Z1370 FKH2::18-Myc-FKH2 MATa, ade2-l, tφl -1, canl-100, leu2-3,112, his3-l l,15, ura3, GAL+,psi+, Z1369 NDD1 ::18-Myc-NDD1 MATa, ade2-l, tφl-1, canl-100, leu2-3,112, his3-l l,15, ura3, GAL+,psi+, Z1321 MCM1 :: 18-Myc-MCM1 MATa, ade2-l, tφl-1, canl-100, leu2-3,112, his3-l l,15, ura3, GAL+,ρsi+, Z1371 ACE2:: 18-Myc-ACE2 MATa, ade2-l, tφl-1, canl-100, leu2-3,112, his3-l l,15, ura3, GAL+,psi+, Z1407 SWI5::9-Myc-SWI5 Technology - Location Analysis The genome-wide location analysis method we have developed (Ren et al., 2000) allows protein-DNA interactions to be monitored across the entire yeast genome. The method combines a modified Chromatin Immunoprecipitation (ChIP) procedure, which has been previously used to study in vivo protein-DNA interactions at one or a small number of specific DNA sites (Aparicio, O.M., in Current Protocols in Molecular Biology. F. M. Ausubel, et al., Eds. (John Wiley and Sons, Inc., New York, 1999) pp. 21.3.1-21.3.12; Orlando V., "Mapping chromosomal proteins in vivo by formaldehyde-crosslinked-chromatin immunoprecipitation," Trends Biochem Sci 25,99-104 (2000)), with DNA microarray analysis. Briefly, cells are fixed with formaldehyde, harvested by sonication, and DNA fragments that are crosslinked to a protein of interest are enriched by immunoprecipitation with a specific antibody. After reversal ofthe crosslinking, the enriched DNA is amplified and labeled with a fluorescent dye using ligation-mediated PCR (LM-PCR). A sample of DNA that has not been enriched by immunoprecipitation is subjected to LM-PCR in the presence of a different fluorophore, and both IP-enriched and unenriched pools of labeled-DNA are hybridized to a single DNA microarray containing all yeast intergenic sequences. The IP-enriched/unenriched ratio of fluorescence intensity obtained from three independent experiments and a p-value is assign to each spot according to an error model adapted from Roberts, CJ., et al, "Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles," Science 287,873-80 (2000). The average ratio is then calculated using a weighted average analysis method, providing the relative binding ofthe protein of interest to each sequence represented on the array. Microarray design Yeast Intergenic DNA Array. Using the Yeast Intergenic Region Primer set (Research Genetics) we PCR amplified and printed 6361 spots, representing essentially all ofthe known intergenic regions in the yeast genome. The average size ofthe spotted PCR products was 480 bp, and the sizes ranged from 60 bp to 1500 bp. Yeast cells expressing an epitope-tagged protein of interest were used; a Myc- epitope coding sequence was integrated into the genome at the 3'-end ofthe coding sequence for each protein. Cultures of yeast cells were grown to OD600 of 0.8 under appropriate conditions prior to formaldehyde crosslinking. DNA amplification and labeling with LM-PCR was found to produce more reproducible results relative to amplification of enriched DNA as a library in E. coli. Superior and more reproducible results were also obtained when DNA preparations enriched by ChIP were compared to unenriched DNA preparations (rather than DNA preparations obtained from an untagged strain subjected to ChLP). Microarray Production The 6361 intergenic regions were amplified using the Yeast Intergenic Region Primers (Research Genetics) primer set. 50μL PCR reactions were performed in 96- well plates with each primer pair with the following conditions: 0.25 μM of each primer, 20 ng of yeast genomic DNA, 250 μM of each dNTP, 2 mM MgC12, IX PCR buffer (Perkin Elmer), and 0.875 units of Taq DNA polymerase (Perkin Elmer). PCR amplification was performed in MJ Research Thermocyclers beginning with 2 minute denaturation at 95°C, followed by 36 cycles of 30 seconds at 92°C, 45 seconds at 52°C, and 2 minutes at 72°C, with a final extension cycle of 7 minutes at 72°C. 1 μL of each PCR reaction mix was then reamplified in a 100 μL PCR reaction using universal primers (Life Technologies) with the same reagent concentrations and the following thermocycling conditions: 3 minutes at 94 °C, followed by 25 cycles of 30 seconds at 94°C, 30 seconds at 60°C, and 1 minute at 72°C, with a final extension cycle of 7 minutes at 72°C. Each PCR product was verified by gel electrophoresis. The PCR products were then isopropanol precipitated, washed with 70% ethanol, dried overnight, and resuspended in 20 μL of 3XSSC. The resuspended DNA was transfered to 384 well plates and printed on GAPS-coated slides (Corning) using a Cartesian robot (Cartesian Technologies). The printed slides were rehydrated, snap-dried, and UN crosslinked in UV Stratalinker (Stratagene) set at 60 mJoules. The slides were then stored under vacuum for at least 2 days prior to hybridization. Preparation of Cells, Cross Linking, Cell Washing and Storing Step 1 - Preparation of cells and cross linking Inoculate fresh media from an overnight culture to OD600=0.1 and allow yeast to grow to OD600=0.6-1.0 (OD600=0.8 is commonly used). • The experiments are usually done in triplicate, which means you need to put up 3 overnight cultures (inoculated with 3 independent colonies from the same plate). Remove 50 ml cells and add to 50 ml Falcon tubes (cat #352070) containing 1.4 ml of Formaldehyde (37% Formaldehyde stock, final concentration 1%, J.T.Baker cat.#2106-01). • Use the liquid dispenser for the formaldehyde and work in a fume hood. Incubate for 20 minutes at room temperature on a rotating wheel. • For some proteins, you may have to optimize the incubation time with formaldehyde. Transfer to 4°C and incubate overnight on a rotating wheel. Step la - Preparation of beads If you are planning to continue with the protocol the next day, you also need to incubate the magnetic beads with the anti-Myc antibody overnight. 4» » i* sp ♦ > p Ή * *P Step lb - Washing and storage of cells Spin 50 ml Falcon tubes for 5 minutes at speed 6 (~2800 φm) in a tabletop centrifuge (Sorvall RT6000) to harvest the cells and pour off the supernatant. Wash 3 times with -40 ml cold TBS. • Add TBS, mix by inversion until the cells are resuspended, spin and pour off the supernatant. After the last wash, resuspend the yeast pellet using any remaining liquid (add some, if necessary) and transfer to an Eppendorf tube. Spin for 1 minute at maximum speed at 4°C and remove the remaining supernatant using a P-1000 pipette. Snap freeze in liquid nitrogen and store at -80°C, or go directly to step 2. Cell Lysis, Sonication, and Immunoprecipitation Step 2 - Cell lysis Thaw cell pellet on ice. Resuspend in 700 μl lysis buffer and transfer to a 1.5 ml Eppendorf tube (cat #2236320-4). Add the equivalent of a 0.5 ml PCR tube (USA/Scientific Cat.#1405-4400) of glass beads (425-600 μμm, Sigma Cat.# G-8772). Vibrax-VXR at maximum power for 2 hours at 4°C. Pierce the bottom ofthe tube with a needle (Use Becton Dickinson Precision Glide 18G1 1/2) and set up over a 2 ml screw cap tube. Spin 3-4 seconds (the material should be transferred to the 2 ml tube, while the beads stay in the 1.5 ml tube). • Turn the centrifuge on, allow it to reach 7000φm and then turn off. Resuspend and transfer to a new 1.5 ml tube (be sure to have at least 700 μl in each tube. Add lysis buffer to bring the volume up to 700 μl, as necessary. Smaller volumes may splash out during sonication). Step 2a - Sonication Shear chromatin by sonicating 4 times for 20 seconds at power 1.5 using a Branson Sonifer 250 - use the 'Hold' and 'Constant Power' settings. (This should result in sheared DNA with an average size of 400 bp). • Note: Keep samples on ice between each round of sonication. Immerse tip in sample first, turn the power on for 20 seconds, turn the power off and place sample back on ice. Wash the tip with water between sample types (it is not necessary to wash the tip between replicates from the same strain). Before and after use ofthe sonifier, rinse the tip with 98% EtOH. Spin for 5 minutes at maximum speed at 4°C and transfer the supernatant to another tube on ice (Supernatant = yeast whole cell extract (yWCE)). Step 2b - Immunoprecipitation Set up a new tube on ice containing: 500 μl of yWCE and 30 μl of a suspension of washed magnetic beads pre-bound to anti-Myc antibody. • Vortex the beads well before removing each 30 μl aliquot to ensure equal amounts of beads are added to each tube and that the beads remain in suspension. Set aside 5 μl of WCE in a separate tube (to label as a control later) and store it and the rest ofthe yWCE at -20°C. Incubate overnight on a rotating platform at . 4°C. Bead Washing, Elution from Beads and Reversal of Cross Linking Step 3 - Bead Washing ^ sfc s -I* *!* *κ v * -v H* Λλ K in rip t 'ol i R Ϊ Ϊ TΠ *« ! ^ c s ' i *'~*' c ^ = 5 « £ S ' c *t ? ** c *" € Wash beads using appropriate device (e.g. MPC-E magnet, Dynal), as follows: • Put the first 6 tubes into magnet, invert the tubes once, open the tubes and aspirate the supernatant using a vacuum (also aspirate what is left in the cap), add the appropriate washing solution, close the tubes and put them back on the rotating platform. Proceed with the next 6 tubes and so on. Don't forget to turn the rotator on while you are aspirating the supernatant from the next set of tubes etc. • For this step, you don't need to add protease inhibitors to the lysis buffer. Wash 2 times with 1 ml lysis buffer. Wash 2 times with 1 ml lysis buffer containing an additional 360 mM NaCl • 720 μl of 5 M NaCl in 10 ml lysis buffer - the final concentration of NaCl is 500 mM. Wash 2 times with 1ml wash buffer. Wash once with 1 ml TE. After you have removed the TE by aspiration, spin the tubes for 3 minutes at 3000 φm and remove any remaining liquid with a pipette. Step 3a - Elution from beads and reversal of cross links Add 50 μl elution buffer, vortex briefly to resuspend the beads and incubate at 65 °C for 10 minutes. Vortex briefly every 2 minutes during the incubation. ********The next steps should be done at room temperature******** Spin for 30 seconds at maximum speed and transfer 30 μl of supernatant to a new tube. Discard the rest (unless have a special reason to keep it). Add 120 μl of TE/SDS to the supernatant in the new tube in order to reverse the crosslinking reaction. Also add 95 μl of TE/SDS to 5 μl of yWCE (prepare one yWCE for each IP). Incubate overnight at 65 °C in an incubator. DNA Precipitation Step 4 - Precipitation of DNA Add 150 μl of "proteinase K mix" to each sample. Incubate for 2 hours at 37°C in the warm room. Extract 2 times with 1 volume of phenol (Sigma Cat. P-4557; OK to use at 4°C). Spin for about 5 minutes at room temperature for each extraction. Extract once with 1 volume of chloroform/isoamyl alcohol (Sigma Cat.C-0549). Add NaCl to 200 mM final (use 8 μl of 5 M stock for 200 μl of sample). Add 2 volumes of cold EtOH and vortex briefly. Incubate at -20°C for at least 15 minutes. Spin at 14,000 rpra for 10 minutes at 4°C. Pour off the supernatant, add 1 ml cold 70% EtOH, vortex briefly and spin at 14,000 φm for 5 minutes at 4°C. Pour off the supematant, spin briefly and remove the remaining liquid with a pipette. Let the pellet dry for a couple of minutes and resuspend the pellet in 30 μl TE containing 10 μg RNaseA (add 33 μl of 10 mg/ml RNaseA to 1 ml of TE). Incubate for 1 hour at 37°C in the warm room. Purify using Qiagen PCR purification kit. Elute with 50 μl of 10 mM Tris pH 8.0. Store at -20°C or place on ice and proceed to step 5. Stop at this stage if you are just going to do a gene-specific PCR, without hybridizing to glass slide arrays. Blunting DNA and Ligation of Blunt DNA to Linker Step 5 - Blunting DNA In seperate PCR tubes, place 40 μl of immunoprecipitated DNA and 1 μl of whole cell extract DNA plus 39 μl ddH2O. Place on ice. Save the the ramaining DNAs at 20°C for gene specific PCR analysis. Note: If you are going to do a "WCE vs WCE control" (recommended), make 2 extra samples with 1 μl whole cell extract DNA + 39 μl ddH2O, using the same whole cell extract DNA for each. Add 70μl of: 11 μl (1 OX) T4 DNA pol buffer (NE Biolabs cat #007-203) 0.5 μl BSA (10 mg/ml) (NE Biolabs cat #007-BSA) 0.5 μl dNTP mix (20 mM each) 0.2 μl T4 DNA pol (3U/μμl) (NE Biolabs cat #203L) 57.8 μl ddH2O 70 μl Total Mix by pipetting and incubate at 12°C for 20 minutes in a PCR machine The program name is "12/20", under "Main" in the 2 heads PCR machine. Do not use the heated lid option. Place on ice and add 12 μl of: 11.5 μl 3M NaOAc 0.5 μl glycogen (20 mg/ml) (Roche Molecular Biochemicals cat #901393) 12 μl Total Mix, by vortexing, and add 120 μl of phenol/chloroform/isoamyl alcohol (25:24:1, Sigma cat.P-3803). Vortex to mix and spin 5 minutes at maximum speed. Transfer 110 μl to a new 1.5 ml Eppendorf tube and add 230 μl cold EtOH (100%). Vortex to mix and spin for 15 minutes at 4°C. Pour off supernatant and wash pellet with 500 μl cold 70% EtOH. Spin for 5 minutes at 4°C. Pour off supernatant, spin briefly and remove any remaining liquid with pipette. Allow to air dry briefly. Resuspend pellet in 25 μl ddH 2 0 and place on ice. Step 5 a - Ligation of blunt DNA to linker Add 25 μl of cold ligase mix: 8 μl ddH20 10 μl 5X DNA ligase buffer (GibcoBRL) 6.7 μl annealed linkers (15 μM) (see appendix #2) 0.5 μl T4 DNA ligase (Life Technologies) 25.2 μl Total Mix by pipetting and incubate overnight at 16°C. Ligation-mediated PCR Step 6 - Ligation-mediated PCR Add 6 μl of 3M NaOAc (pH 5.2) to linker- ligated DNA. Mix by vortexing and add 130 μl cold EtOH. Mix by vortexing and spin for 15 minutes at 4°C. Pour off supernatant and wash with 500 μl 70% EtOH. Spin for 5 minutes at 4°C. Pour off supernatant, spin and remove any remaining liquid with a pipette. Resuspend in 25 μl ddH 2 O and place on ice. Add 15 μl of PCR labeling mix: 4 μl 1 OX ThermoPol reaction buffer (NE Biolabs) 5.75 μl ddH2O 2 μl low T mix (5 mM each dATP, dCTP, dGTP; 2 mM dTTP) 2 μl Cy3-dUTP or Cy5-dUTP (use Cy5 for IP DNA and Cy3 for WCE DNA) 1.25 μl oligo oJW102 (40 μM stock) 15 μl Total Try to use Cy3 or Cy5 from the same batch i.e. avoid mixing batches. Transfer to PCR tubes on ice, place in PCR machine and start program "Cy3" or Cy5" (the programs are stored under "Main" in our PCR machines or under "FR" in the tetrad PCR machine in the back room): Step Time/Instruction Temp. Notes l mm 55°C (make this longer if you have a lot of samples) 5 min 72 °C 2 min 95°C 30 sec 95°C 30 sec 55°C 1 min 72°C go to step 4 for X* more times 4 min 72°C hold 4°C *32 cycles (total) for Cy5 and 34 cycles for Cy3 Add 10 μl of polymerase mix during step 1 of PCR: 8 μl ddH2O 1 μl 10X ThermoPol reaction buffer (NE Biolabs) 1 μl Taq polymerase (5 U/μl) (Perkin Elmer: Use Cat. #N801-0060 i.e. regular Taq., do not use AmpliTaq Gold) 0.01 μl PFU Turbo (2.5 U/μl) (Stratagene Cat #600250-51) 10 μl Total Run 5 μl on a 1.5% agarose gel. (The PCR product should be a smear ranging from 200 bp to 600 bp with an average size of 400 bp). Purify with Qiaquick PCR purification kit. Elute in 50 μl. Add 6 μl 3M NaOAc, mix and add 130 μl cold EtOH. Mix and spin for 15 minutes at 4°C. Pour off supernatant and wash with 500 μl of 70% EtOH. Spin for 5 minutes at 4°C. Pour off supernatant, spin and remove any remaining liquid with a pipette. Store PCR products at -20°C. Keep in a closed box to prevent exposure to light. Pre-hybridization, Probe Preparation, Hybridization and Wash Step 7 - Pre-hybridization Incubate slide in 3.5X SSC, 0.1% SDS, 10 mg/ml BSA for 20 minutes at room temperature with agitation (use a stir bar on setting "5") and then 20 minutes at 50°C suing a pre-warmed solution (place Coplin jar in water bath; use a fresh solution). Wash slide using RO water. Blow-dry with nitrogen or by placing slides in a rack and spinning in a centrifuge for 2 min @ 1 kxpm. Step 7a - Probe preparation During slide pre-hybridization, resuspend each target in 30 μl of 3X SSC, 0.1% SDS (these may be hard to resuspend, place in 37°C heat block and vortex if necessary. This may take 30-45 min.). Mix both Cy5 and Cy3 resuspended target, add 4 μl of tRNA (8 mg/ml) and mix well by vortexing. Boil for 5 minutes in a heat block. Incubate for 5 minutes at 50°C. Spin briefly. Step 7b - Hybridization Pipette 50 μl of probe onto slide and drop cover slip (use the big one so that it will cover the entire array) onto the liquid. Try to avoid bubbles as they exclude the hybridization solution. Add water to the holes in the hybridization chamber. Assemble the chambers and submerge right side up in a 50°C water bath, allow hybridizing for 20-24 hours. Step 7c - Wash Disassemble hybridization chambers with the right side up. Remove coverslip and immediately place slide in 0.1X SSC, 0.1% SDS at room temperature for 8 minutes with agitation. Transfer to 0.1X SSC for 5 minutes with agitation. Note: Tranfer slide by slide (do not transfer the whole rack). Rotate slides 180° along the long edge when transfering. Repeat 0.1X SSC wash 2 more times. Dry by placing slides in a rack and spinning in a centrifuge for 2 min @ 1 kφm and scan immediately or store in the dark until scanning. Preparation of Magnetic Beads ********* Prepare the day before use ********* Take 50 μl of beads (4 xlO 8 beads/ml stock e.g. 2X 10 7 beads per sample) and place in a 15 ml Falcon tube. Use Dynabeads M-450 pre-coated with rat anti-mouse IgG- 2a; Cat.#110.13. Spin for 1 minute at speed 6 (-3000 φm) in a tabletop centrifuge (Sorvall RT6000). Remove supernatant with a pipette and resuspend in 10 ml PBS containing 5mg/ml BSA (make immediately before use from Sigma BSA powder, cat. A-3350). Wash again. Incubate overnight with antibody on a rotating platform at 4°C (Use 1 μl of anti-Myc 9E11 antibody plus 250 μl PBS + 5 mg/ml BSA per 50 μl of beads). Note: The 9E11 antibody we are using has been purified from acites and concentrated. The amount used has been determined empirically so that the beads are saturated. Spin for 1 minute at speed 6 (-3000 φm) in a tabletop centrifuge (Sorvall RT6000). Remove supernatant with a pipette and resuspend in 10 ml PBS containing 5mg/ml BSA (make immediately before use, as above). Wash again. Resuspend each sample in 30 μl PBS containing 5mg/ml BSA. Preparation of Unidirectional Linker Mix the following: 250 μl Tris-HCl (IM) pH 7.9 375 μl oligo oJW102 (40 μM stock) 375 μl oligo oJW103 (40 μM stock) oJW102: GCGGTGACCCGGGAGATCTGAATTC (SEQ ID NO: 29) oJW103: GAATTCAGATC (SEQ ID NO: 30) NOTE: Order these oligos dessicated, then resuspend in ddH20. Make 50 or lOOμl aliquots in Eppendorf tubes. Place in a 95 °C heat block for 5 minutes. Transfer samples to a 70°C heat block (there should be water in the holes). Place the block at room temperature and allow it to cool to 25 °C. Transfer the block to 4°C and allow to stand overnight. Store at -20°C. Solutions TBS (store at 4°C) IX 5X for lL of 5X 20 mM Tris-HCl pH7.5 100 mM Tris-HCl pH 7.5 100 ml of IM 150 mM NaCl 750 mM NaCl 150 ml of 5M Lysis Buffer (make fresh with cold ddH 2 0) IX for 150 ml for 5 ml 50 mM HEPES-KOH pH7.5 7.5 ml of 1 M 250 μl of 1 M 140 mM NaCl 4.2 ml of 5 M 140 μl of 5 M 1 mM EDTA 300 μμl of 500 mM 10 μl of 500 mM 1 % Triton X- 100 15 ml of 10% 500 μl of 10% 0.1 % Na-deoxycholate 3 ml of 5% 100 μl of 5% 1 mM PMSF, ImM Benzamidine 1.5 ml of 100X 50 μl of 100X 10 μμg/ml Aprotinin, 1 μμg/ml 1.5 ml of 100X 50 μl of 100X Leupeptin 1 μμg/ml Pepstatin 1.5 ml of 100X 50 μl of 100X Wash Buffer (store at 4°C) IX for 500 ml 10 mM Tris-HCl pH 8.0 5 ml of 1 M 250 mM LiCl 25 ml of 5 M 0.5% NP40 2.5 ml of 100% 0.5% Na-deoxycholate 25 ml of 10% 1 mM EDTA 1 ml of 500 mM Elution buffer (make with ddH 2 O, store at room temperature) IX for 100 ml 50 mM Tris-HCl pH8.0 5 ml of 1 M 10 mM EDTA 2 ml of 500 mM 1% SDS 10 ml of 10% TE/SDS (make with ddH2O. store at room temperature) IX for 500 ml lO mM Tris HCl pHδ.O 5 ml of l M 1 mM EDTA 1 ml of 500 mM Proteinase K mix (make fresh) For 1 sample For 26 samples 140 μl ofTE 3640 μl 3 μl of glycogen (Boehringer cat# 901393) 78 μl 7.5 μl of proteinase K (20 mg/ml stock) (Gibco 25530-049) 195 μl 20X SSC 2 OX for IL solution 3 M NaCl 175.32 g 0.3M Na 3 citrate-2H 2 O 88.23 g pH"d to 7.0 with HCI PMSF/Benzamidine mix 100X stock (aliquot and store at -20°C) IX For 10 ml of 1 OOX I mM PMSF 0.1742 g 1 mM Benzamidine 0.1566 g EtOH Bring to a volume of 10 ml Aprotinin/Leupeptinin mix 1 OOX stock (aliquot and store at -20°C) IX For lO ml of lOOX 10 μg/ml Aprotinin 0.01 g 1 μg/ml Leupeptin 0.001 g ddH 2 O Bring to a volume of 10 ml Pepstatin mix 100X (aliquot and store at -20°C) IX For lO ml of lOOX 1 μg/ml Pepstatin 0.001 g DMSO Bring to a volume of 10 ml Location Analysis DNA microarrays with consistent spot quality and even signal background were important for maximizing reproducibility and dynamic range. The LM-PCR method described here was developed to permit reproducible amplification of very small amounts of DNA; signals for greater than 99.8% of genes were essentially identical within the error range (p-value <= 10 "3 ) when independent samples of 1 ng of genomic DNA were amplified with the LM-PCR method. Each experiment was carried out in triplicate, allowing an assessment ofthe reproducibility of the binding data. Furthermore, a single-array error model was adopted to handle noise associated with low intensity spots and to average repeated experiments with appropriate weights. Location Analysis: From Scanning Image to Intensity Images of Cy3 and Cy5 fluorescence intensities were generated by scanning the arrays using a GSI Lumonics Scaimer. The Cy3 and Cy5 images were analyzed using ArrayVision software, which defined the grid of spots and quantified the average intensity of each spot and the surrounding background intensity. The background intensity was subtracted from the spot intensity to give the final calculated spot intensity. The intensities of all ofthe spots from the Cy5 and Cy3 scans were summed, and the ratio of total Cy5/Cy3 intensity was set equal to one. For each spot the ratio of corrected Cy5/Cy3 intensity was computed. Location Analysis: Single Array Error Model The quantitative amplification of small amounts of DNA generates some uncertainty in values for the low intensity spots. In order to track that uncertainty and average repeated experiments with appropriate related weights, we adopted an single-array error model that was first described by Roberts, C. J., et al., " Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles," Science 287,873-80 (2000). According to this error model, the significance of a measured ratio at a spot is defined by a statistic X, which takes the form S ' & t Jf= (σ, 3 + oX + f*{a. + a, 2 )) 1 ' 2 (i) where a, , are the intensities measured in the two channels for each spot, σ 1>2 are the uncertainties due to background subtraction, and f is a fractional multiplicative error such as would come from hybridization non-uniformities, fluctuations in the dye incoφoration efficiency, scanner gain fluctuations, etc. X is approximately normal. The parameters ^ and f were chosen such that X has unit variance. The significance of a change of magnitude |x| is then calculated as (2) p = 2(l-Erf(|X|)) Location Analysis: Weighted Average From Triplicate Measurements For each factor, three independent experiments were performed and each of the three samples were analyzed individually using a single-array error model. The average binding ratio and associated p-value from the triplicate experiments were calculated using a weighted average analysis method (Roberts, C.J., et al., " Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles," Science 287,873-80 (2000)). The method to combine repeated measurements of chromosomal binding is adapted, with a few modifications, from a method by developed by Roberts, C.J., et al., " Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles," Science 287,873-80 (2000) to average multiple measurements of gene expression. Briefly, the binding ratio is expressed as the log 10 (a 2 /a 1 ), where a,,a 2 are the intensities measured in the two channels for each spot. The uncertainty in the log(Ratio) is defined as (3) O losl Ota. / = los, 0 ( a ϊ / a ι ) / x where X is the statistics derived from single array error model. We use the minimum- variance weighted average to compute the mean log 10 (a 2 /a 1 ) of each spot: (4) w = 1 / σ; 1 Σ (5) mifi Here σ , is the error of log 10 (a 2 /a,) from (3), x f stands for i-th measurement of log 10 (a 2 /a,), n is the number of repeats. The error of x can be computed in two ways. One is to propagate the errors σ , , another is from the scatter of x,: (6) < = 1 / $>( For the average of multiple slides, the significance statistic X is computed as: (7) X = x / α p and the confidence is computed using Equation (2) from the single array error model. Location Analysis: Gene Assignment The intergenic regions present on the array were assigned to the gene or genes found transcriptionally downstream. In some cases, a single intergenic region contains the promoter for two divergently transcribed genes (e.g. HHF2 and HHT2 or CLN2 and BBP1). In such cases, the intergenic region was assigned to both genes, and gene expression data were used to "discipline" the binding location data. This was accomplished by selecting genes whose promoters were bound by factors and whose expression oscillates during the cell cycle. Among genes whose promoters were bound by at least one ofthe factors and which were expressed in a cell cycle- dependent fashion, we found only 18 examples of intergenic regions that lie at the center of divergently transcribed genes. Motif Search In order to identify DNA binding motifs we used a set of promoters commonly regulated by a transcription factor (with p<0.001) as input for AlignACE (Hughes, J. D., et al, JMol Biol 296, 1205-14 (2000)). We ran the program with the default parameters, adjusting only the parameter that defines the size ofthe expected motif (numcolumn), which we systematically explored within 7 to 25 nucleotides. The identified motifs were run on ScanACE and on MotifStats (Hughes, J. D., et al, J Mol Biol 296, 1205-14 (2000)) in order to assign motif specificity to the group of promoters that were used as input. In order to determine which promoter contains a given motif, we used ScanACE, and we included all the promoters with scores greater than one standard deviation below the average score ofthe sites found in the initial AlignACE search. Statistics In order to explore the statistical significance ofthe overlap between the set of targets of a factor and the genes expressed in a particular cell cycle stage we used the hypergeometric distribution as described (Tavazoie, S., et al, "Systematic determination of genetic network architecture," Nat Genet 22, 281-5., (1999)) Data and Quality Control Two measures of quality control are described here. First, scatter plots for the array data obtained in each ofthe experiments are provided. Second, we compare results of these experiments with results reported previously by other investigators. Comparison to Literature All but one ofthe transcription factor-promoter interactions previously established in vivo were confirmed by the location data, even when the highest stringency criteria was used (pO.OOl). We confirmed that Mcml, Fkh2 and Nddl bind to the CLB2, SWI5 and YJL051W promoters (Zhu et al. Nature, 406:90-94 (2000); Koranda et al, Nature, 406:94-98 (2000)), SBF binds to the CLN2 promoter (Koch, C, et al, Genes Dev 10, 129-41 (1996)), Mcml binds to the STE2 promoter (Zhu et al. Nature, 406:90-94 (2000)), and Swi4 binds to the HO promoter (Cosma, M. P., et al, Cell 97, 299-311 (1999)). We did not observe Swi5 binding to the HO promoter, which also occurs in vivo (Cosma, M. P., et al, "Ordered recruitment of transcription and chromatin remodeling factors to a cell cycle- and developmentally regulated promoter," Cell 97, 299-311 (1999)), because Swi5 binding can be detected only in synchronized cells, and even then only transiently (5 minutes duration) (Cosma, M. P., et al, "Ordered recruitment of transcription and chromatin remodeling factors to a cell cycle- and developmentally regulated promoter," Cell 97, 299-311 (1999)). Additional genes have been suggested as targets of these cell cycle transcription factors based on indirect evidence, but our data do not confirm that all of these genes are direct targets of these regulators (Althoefer, H., et al, "Mcml is required to coordinate G2-specific transcription in Saccharomyces cerevisiae," Mol Cell Biol 15, 5917-28 (1995); Piatti, S., et al., "Cdc6 is an unstable protein whose de novo synthesis in Gl is important for the onset of S phase and for preventing a 'reductional' anaphase in the budding yeast Saccharomyces cerevisiae," Embo J 14, 3788-99 (1995); Toone et al., 1995; Verma, R., et al, "Identification and purification of a factor that binds to the Mlu I cell cycle box of yeast DNA replication genes," Proc Natl Acad Sci US A 88, 7155-9 (1991); Koch et al. Science, 261:1551-1557 (1993); Gordon, C. B., and Campbell, J. L., "A cell cycle-responsive transcriptional control element and a negative control element in the gene encoding DNA polymerase alpha in Saccharomyces cerevisiae," Proc Natl Acad Sci USA 88, 6058-62 (1991); Pizzagalli, A., et al, "DNA polymerase I gene of Saccharomyces cerevisiae: nucleotide sequence, mapping of a temperature-sensitive mutation, and protein homology with other DNA polymerases," Proc Natl Acad Sci USA 85, 3772-6 (1988); Igual, J. C, et al, "Coordinated regulation of gene expression by the cell cycle transcription factor Swi4 and the protein kinase C MAP kinase pathway for yeast cell integrity," Embo J 15, 5001-13 (1996); Lowndes, N. F., et al., "Coordination of expression of DNA synthesis genes in budding yeast by a cell-cycle regulated trans factor," Nature 350, 247-50 (1991)). Download Raw Data The raw data for the location analysis experiments for each ofthe nine cell cycle activators are available as a single text file with each column separated by tabs. Descriptions ofthe contents of each column are provided in the first two rows. 'spot name' refers to an intergenic region. It has been assigned a systematic name that includes the letter 'i' followed by the systematic ORF name that is to the left of the intergenic region. 'per quality' is a qualitative description ofthe per products as seen on an acrylamide gel. 'good' means that the band was the correct size and cleary visible, 'w' indicates that the band intensity was 'weak', 'vw' indicates 'very weak' intensity, 'no' means that no band was seen, and 's' indicates that the size ofthe band was not what was expected. '# of promoters on spot' denotes the number of genes which the intergenic region contains promoters for. 'assigned gene' is the name of each orf whose promoter is contained in the given intergenic region, 'Orf is the gene name. 'p-value' and 'average ratio' are the combined values for replicate experiments for each ofthe factors tested. The last columns in the file are the cell cycle stage as described by Spellman, P. T., et al, Mol Biol Cell 9, 3273-97 (1998), the phase ofthe gene, and the cell cycle stage as described by Cho, R. J., et al, Mol Cell 2, 65-73 (1998). Serial Regulation of Transcriptional Regulators in the Yeast Cell Cycle Genomic binding sites were identified for the nine known yeast cell cycle transcription activators, revealing how these factors coordinately regulate global gene expression and diverse stage-specific functions to produce a continuous cycle of events. One fundamental insight that emerged from these results is that a complete transcriptional regulatory circuit is formed by activator complexes that control next-stage activators. The results also show that stage-specific activator complexes regulate genes encoding CDK regulators necessary for both stage entry and for progression into the next stage ofthe cell cycle. This global information provides a map ofthe regulatory network that controls the cell cycle. Table 4 Binding of Cell Cycle Activators to Functional Categories v v V v o o o oo o vo > C\ -J Previous Evidence The genome-wide location data described here identifies the promoters bound in vivo by all known yeast cell cycle transcription factors (Table 5). Some of these factor-promoter interactions were suggested previously using different methods, and a summary of all the targets genes identified by the current study for which previous evidence exists is provided here. The previously reported evidence is separated into four categories: . In vivo binding, which includes chromatin immuno-precipitation and in vivo footprinting. 2. In vitro binding, which includes gel retardation assays and DNAse I footprinting. Genetic analysis, which includes the effects of genetic manipulations (such as mutations or overproduction) on target genes. Sequence analysis, which includes the identification of DNA binding motifs in the promoters of target genes. A genome-wide location analysis technique has recently been used to identify the set of cell cycle genes controlled by MBF and SBF (Iyer, V. R., et al, Nature 409, 533-8 (2001)). A list of all the target genes identified by the current study that were also identified by Iyer, V. R., et al, Nature 409, 533-8 (2001) is provided here. The overlap between the genes identified by Iyer et al. and this study is approximately 75%. Table 5 vo t o t t t to t t " Swi4 regulated genes SAT2 YKL044W CLB2 YBR071W CWP1 CWP2 PCL2 PRY2 GAS1 HO UTH1 HCM1 GIC2 YLR084C PSA1 YDR451C GLS1 GIN4 UTR2 YOX1 RNR1 MSB2 CLN1 SWI4 BUD9 PDR16 YER189W YGR151C PCL1 YER190W RSRl YNL300W CLB6 YGR153W YOL011W CDC6 YGR189C HTA3 ELO1 YGR221C YOL114C LAP4 SCW4 SRL1 EXG1 GICl YOR248W SPT21 SMI YOR315W SCW10 CIS3 NDD1 Y L339C SWE1 HHO1 YKL008C SVS1 Mbpl regulated genes ERP3 CDC21 YER190W DUN1 UFE1 CLB6 RAD51 OPY2 CDC6 YHR149C HCM1 ELO1 YJR030C YDR545W EXG1 RAD27 RNR1 SPT2 CDC45 SWI4 YNR009W YMR215W YER189W YPL283C Alpha Factor Synchronization Time course expression data for the cell cycle after alpha factor synchronization of yeast cells is from Spellman, P. T., et al, Mol Biol Cell 9, 3273-97 (1998). Regulation of late Gl genes Previous molecular and genetic analysis of a small number of genes suggests that SBF (Swi4 and Swi6) and MBF (Mbpl and Swi6) are important activators of late Gl genes (Koch and Nasmyth, 1994). Our results confirm this model: Swi4, Mbpl and Swi6 bound predominantly to promoters of late Gl genes (the significance of the bias toward late Gl genes was tested using a hypergeometric distribution and was/ lO-i8,/?<10-i4 and ?<10-20 respectively). Swi6 as a cofactor for Swi4 (SBF) and Mbpl (MBF) Based on studies of several genes, Swi6 has been ' shown to function as a subunit of both SBF and MBF (Dirick et al. Nature, 357/508-513 (1992)). The genome-wide location analysis data indicates that Swi6 binds to almost all ofthe promoter regions bound by Mbpl and Swi4 (Figure 2A), indicating that it is a co-factor of these two regulators throughout the genome. Regulation of genes encoding cyclins and cyclin regulators The targets of SBF and MBF included key cell cycle regulators (Table 5). SBF and MBF were found to bind the promoters of CLN1, CLB6 and PCL1, SBF binds the promoters of CLN2 and PCL2 and MBF binds the promoter of CLB6. The location analysis also shows that SBF participates in the regulation of G2/M cyclin (Clb2) activity at three levels. First, as suggested previously (Iyer et al. Nature, 409:533- 536 (2001)) it binds and presumably directly regulates CLB2. Second, SBF regulates the transcription ofthe transcription factor Nddl, which in rum also regulates CLB2 transcription. Thus, SBF and Nddl collaborate to regulate transcription of the CLB2 gene, whose product is necessary to enter mitosis. Third, SBF and MBF regulate SWE1 and GIN4. Swel is an inhibitor of Cdc28-Clb2 which delays entry into mitosis in response to bud emergence defects (Sia, R. A., et al., "Cdc28 tyrosine phosphorylation and the morphogenesis checkpoint in budding yeast," Mol Biol Cell 7, 1657-66 (1996)), and Gin4 regulates Swel (Barral, Y., et al, "Niml-related kinases coordinate cell cycle progression with the organization ofthe peripheral cytoskeleton in yeast," Genes Dev 13, 176-87 (1999)). Regulation of stage-specific functions SBF and MBF participate in the regulation of genes essential for cellular functions specific to late Gl. SBF regulates genes involved in the morphological changes associated with cell budding and MBF controls genes involved in DNA replication and repair (Table 5), confirming a previous study (Iyer et al. Nature, 409:533-536 (2001)). We also found that SBF is bound to the promoters of several histone genes (HTA1, HTA2, HTA3, HTB1, HTB2 and HHOi), which makes it likely that SBF contributes to the increase in histone gene transcription observed at S phase. Redundancy of activators Neither SWI4 nor MBP1 is essential for cell viability, but a SWI4 IMBP1 double mutant is lethal, suggesting that some redundancy exists between Swi4 and Mbpl (Mendenhall, M. D., and Ηodge, A. E., "Regulation of Cdc28 cyclin-dependent protein kinase activity during the cell cycle ofthe yeast Saccharomyces cerevisiae," Microbiol Mol Biol Rev 62, 1191-243 (1998)). We found that most ofthe cell cycle genes involved in budding are bound by SBF alone and that most cell cycle genes involved in DNA replication are bound by MBF alone. In these cases, it does not appear that SBF and MBF play redundant regulatory roles in wild type cells. Iyer et al. Nature, 409:533-536 (2001) also reported that Swi4 and Mbpl bind to different genes involved in distinct cellular functions. However, 34% of all genes bound by SBF or MBF are bound by both factors, indicating that regulation of these genes in a population of wild type cells is normally under the control of both factors and demonstrating that there is substantial redundancy in the regulation of these cell cycle controlled genes in normal cells. Promoter binding motifs The large number of targets we found enabled us to search for putative DNA binding motifs. To this end we ran AlignACE (Hughes, J. D., et al, JMol Biol 296, 1205-14 (2000)), a program that uses a Gibbs sampling algorithm to find common regulatory elements among a collection of promoters. We found a refined version of the known binding sites of Swi4 and of Mbpl . Although these motifs are highly enriched in the set of target genes identified by our location analysis (p<\0-\4 and p<\0-20 respectively), they also occur in the promoters of many genes that show no evidence of binding to these factors in vivo, suggesting that the presence of this sequence alone is not a predictor of factor binding. Fkhl and Fkh2 Fkhl and Fkh2 are two members of the Forkhead family of proteins that share 82% similarity in amino acid sequence (Kumar et al. Curr. Biol, 70:896-906 (2000)). Genetic analysis has suggested that these two genes are involved in cell cycle control, in pseudohyphal growth, and in silencing of HMRa (Hollenhorst et al. Genetics, 154:1533- 1548 (2000)). Their contribution to the regulation of cell cycle genes appears to be in G2/M, since it has been shown that Fkh2, together with Mcml, recruits Nddl and thereby regulates the G2/M specific transcription of CLB2, SWI5 and YJL051 W (Zhu et al. Nature, 406:90-94 (2000); Koranda et al, Nature, 406:94-98 (2000); Kumar et al Curr. Biol, 10:896-906 (2000); Pic et al Embo J., 19:3750-3761 (2000)). Fkhl appears to have similar roles in regulating G2/M genes as it is also found bound to the CLB2 promoter (Kumar et al. Curr. Biol, 10:896-906 (2000)). Regulation of genes throughout cell cycle Our results confirm that Fkhl and Fkh2 are involved in regulating genes expressed in G2/M, but indicate that these proteins also regulate genes expressed in other cell cycle stages. Fkh2 binds predominantly to promoters of genes expressed in G2/M (p<\0-9), but it is also enriched in Gl (p<\0-4) and S/G2 (p<10-3). Fkhl target genes are expressed in Gl (p<\0-2), S (p<\0-3), S/G2 (p<\0-5) and G2/M (p<\0-4). The association of Fkhl or Fkh2 with Mcml is limited to genes expressed in G2/M; in other stages Fkhl and Fkh2 bind to promoters in the absence of Mcml. Regulation of genes encoding cyclins and cyclin regulators The targets of Fkhl and Fkh2 include several key cell cycle regulators (Table 5). Fkhl bound to the promoter ofthe CLB4 gene, which encodes a S/G2 cyclin (Fitch, I., et al, Mol Biol Cell 3, 805-18 (1992)), and Fkh2 bound to the promoter of HSL7, which encodes a regulator of Swel that is necessary for the transition into mitosis (Shulewitz, M. J., et al, Mol Cell Biol 19, 7123-37 (1999)). Fkhl and Fkh2 also bind to promoters of genes involved in exit from mitosis; these include APC1, which encodes for a component ofthe anaphase-promoting complex (Zachariae, W., and Nasmyth, K. Genes Dev 13, 2039-58 (1999)), and TEM1, which encodes a protein required for activation of Cdcl4p and the mitotic exit pathway (Krishnan, R., et al. Genetics 156, 489-500 (2000)). Regulation of chromatin Fkhl was found to bind various genes that encode proteins associated with chromatin structure and its regulation; these include histones (HHFl and HHT1), telomere length regulators (TEL2 and CTF18), a component ofthe chromatin remodeling complexes Swi/Snf and RSC (ARP7), and histone deacetylase (HOS3). Redundancy of activators Genetic analysis has suggested that Fkhl and Fkh2 have distinct roles in cell cycle progression, but redundant roles in pseudohyphal growth (Hollenhorst et al. Genetics, 154:1533-1548 (2000)). We found that Fkhl and Fkh2 bind to the promoters of 38 and 56 cell cycle genes, respectively, and that 16 of these genes were bound by both proteins. Among the G2/M genes that are targets of Fkh2, three genes (CLB2, ACE2 and BUD4) are also targets of Fkhl. Promoter binding motifs In order to identify the binding motifs for Fkhl and Fkh2, we ran AlignACE (Hughes, J. D., et al, JMol Biol 296, 1205-14 (2000)) on the set of promoters bound by each factor. The program identified the known Forkhead binding motif (GTAAACAA (SEQ ID NO: 31)) in the two sets of promoters (p<10-9). However, this sequence was absent from most ofthe promoters bound by Fkhl and Fkh2, suggesting that additional sequence elements contribute to the binding sites for these proteins. The promoters of Fkhl targets, but not Fkh2 targets, are enriched for several additional motifs. Mcml and its cofactors, Fkh2 and Nddl Regulation of G2/M and M/Gl genes Previous studies have demonstrated that Mcml is involved in the regulation of cell cycle genes that are expressed both in G2/M and in M/Gl. Mcml collaborates with Nddl and Fkhl or Fkh2 to regulate G2/M genes (Zhu et al. Nature, 406:90-94 (2000); Koranda et al, Nature, 406:94-98 (2000); Kumar et al. Curr. Biol, 10:896- 906 (2000); Pic et al. Embo , 79:3750-3761 (2000)). Mcml also regulates M/Gl genes, but less is known about its functions in this stage of the cell cycle (Mclnemy et al. Genes Dev., 77:1277-1288 (1997)). Our results suggest that differential regulation of Mcml target genes in G2/M and M/Gl is governed by Mcml 's association with different regulatory partners. Mcml binds predominantly to promoters of genes in G2/M (p<\0-\4) and in M/Gl (p<\0-6). hi contrast, Mcml 's cofactors Nddl and Fkh2 bind to promoters of G2/M genes (p<\0-2\ and j?<10-15 respectively) but were absent from promoters of M/Gl genes. Regulation ofentiy into and exit from mitosis The location analysis indicates that the G2/M activators (Mcml/Fkh2/Nddl) regulate genes necessary for both entry into and exit from mitosis (Table 5). The G2/M activators regulate transcription of CLB2, whose product is necessary to enter mitosis. They also set the stage for exit from mitosis at several levels. First, they regulate the transcription of SWI5 and ACE2, which encode key M/Gl transcriptional activators. Second they bind the promoter of CDC20, an activator of the anaphase promoting complex (APC), which targets the APC to degrade Pdsl and thus initiate chromosome separation (Nisintin et al. Science, 7<°:450-463 (1997)). Cdc20-activated APC also participates in the degradation of Clb5 (Shirayama et al. Nature, 402:203-207 (1999)), and thus enables Cdcl4 to promote the transcription and activation of Sicl (Shirayama et al. Nature, 402:203-207 (1999)) and to initiate degradation of Clb2 (Jaspersen et al, Mol. Biol. Cell, 9:2803- 2817 (1998); Visintin et al, (1998)). Finally these activators regulate transcription of SPOl 2, which encodes a protein that also functions to regulate mitotic exit (Grether et al, Mol. Biol Cell, 10:3689-2703 (1999)). The involvement of Mcml in the regulation of genes important for the transition through START has been suggested previously (Mclnemy et al. Genes Dev., 77:1277-1288 (1997); Ohelen, L. J., Mol Cell Biol 16, 2830-7 (1996)), and our data confirm this notion. Mcml in the absence of Νddl and Fkh2 binds the promoters of SWI4, a late Gl transcription factor, CLN3, a Gl cyclin that is necessary for the activation of Gl transcription machinery (Dirick et al. Embo. J., 74:4803-4813 (1995)) and FAR1, which encodes an inhibitor ofthe Gl cyclins (Valdivieso, M. H., et al. Mol Cell Biol 13, 1013-22 (1993)). Regulation of stage-specific functions Mcml, in the absence of Νddl and Fkh2, participates in the regulation of genes essential for cellular functions specific to late mitosis and early Gl . It binds to and apparently regulates genes encoding proteins involved in pre-replication complex formation (MCM3, MCM6, CDC6 and CDC46) and in mating (S7E2, STE6, FAR1, MFA1, MFA2, AGA1 and AGA2). Promoter binding motifs In order to identify DΝA binding motifs for Mcml , we ran AlignACE (Hughes, J. D., et al, JMol Biol 296, 1205-14 (2000)) on the set of promoters bound by the combination of Mcml Fkh2 and Νddl and on the promoters bound by Mcml alone. We found that all the promoters ofthe first group contain a motif with a Mcml binding site adjacent to a Fkh binding site. This combined motif was highly specific (p<\0-34) to these promoters. Almost all the promoters from the second group (89%) contain a Mcml binding motif which was also highly specific for these promoters (p<\0-27). Interestingly the Mcml motif found in these two groups of promoters was slightly different, with several more nucleotides conserved in the motif found in the promoters ofthe genes bound by Mcml alone. Ace2 and Swi5 Ace2 and Swi5 have been shown to control certain genes expressed in late mitosis and early Gl phases ofthe cell cycle (McBride et al J. Biol. Chem., 274:21029- 21036 (1999)). Our results confirm that Ace2 and Swi5 bound predominantly to promoters of M/Gl genes (p<\0-3 and/ lO-14, respectively). Regulation of genes encoding cyclins and other cell cycle regulators The targets of Ace2 and Swi5 included cell cycle regulators (Table 5), Ace2 bound to the promoter of PCL9, whose product is the only cyclin known to act in M/Gl (Aerne, B. L., Mol Biol Cell 9, 945-56 (1998)). Both Ace2 and Swi5 bound to promoters of two ofthe Gl cyclin genes (PCL2 and CLN3), and Swi5 bound to the gene encoding the cyclin regulator Sicl, which inhibits Clb-CDK activity, allowing exit from mitosis. Regulation of stage-specific functions Ace2 and Swi5 were bound to the promoters of several genes whose products are involved in cell wall biogenesis and cytokinesis (Table 5). Swi5 bound to the promoters of 17 Y' genes, which are a subgroup of a larger group of sub-telomeric genes that share DNA sequence similarity and whose expression peaks in early Gl (Spellman, P. T., et al, Mol Biol Cell 9, 3273-97 (1998)). Redundancy of activators Genetic analysis has suggested that A CE2 and SWL5 are redundant; a deletion of either ACE2 or SWI5 does not abolish transcription of most of their target genes (McBride et al. J. Biol. Chem., 274:2X029-2X036 (1999)). Our results indicate that the functional overlap seen in mutants reflects partial functional redundancy. Ace2 and Swi5 bind to the promoters of 30 and 55 cell cycle genes respectively, and the promoters of 17 of these genes are bound by both factors. This result suggests that the redundancy is limited to a subset ofthe target genes in wild type cells. Among the targets that are unique to one or the other factor are genes whose transcription is abolished only in the absence of both Ace2 and Swi5, suggesting that in the absence of one factor, the other one can fill its place. However, in wild type cells only one factor is normally bound to these promoters. Promoter binding motifs In order to identify the binding motifs of Ace2 and Swi5 we ran AlignACE (Hughes, J. D., et al, JMol Biol 296, 1205-14 (2000)) on the group of promoters bound by each factor. We were able to identify motifs similar to the published binding sites of these factors that were enriched in the set of promoters bound by Ace2 and Swi5 (p<10-6 and ?<10-18 respectively). These motifs were found only in about 50% ofthe promoters, suggesting Ace2 and Swi5 can bind DNA through additional binding sites; several candidates are shown in the figure below. Redundancy The location analysis data demonstrate that each ofthe nine cell cycle transcription factors binds to critical cell cycle genes, yet cells with a single deletion of MBP1, SWI4, SWI6, FKH1, FKH2, ACE2 or SWI5 are viable; only MCM1 and NDD1 are essential for yeast cell survival. The conventional explanation for this observation is that each non-essential gene product shares its function with another, and the location data support this view, up to a point. Swi4 and Mbpl are identical in 50% of their DNA binding domains (Koch et al. Science, 261X551-1557 (1993)), Fkhl and Fkh2 are 72% identical in their DNA binding domains (Kumar et al. Curr. Biol, 10:896-906 (2000)), and Swi5 and Ace2 are 83% identical in their DNA binding domains (McBride et al. J. Biol. Chem., 274:2X029-2X036 (1999)). Each of these pairs of proteins recognize similar DNA motifs, so it is likely that functional redundancy rescues cells with mutations in individual factors. Until now, however, it was not possible to determine whether each ofthe pairs of factors had truly redundant functions in normal cells, or whether they can rescue function in mutants that lack the other factor. Our data demonstrate that each ofthe cell cycle factor pairs discussed above do bind overlapping sets of genes in wild type cells, revealing that the two members of each ofthe pairs are partially redundant in normal cell populations. Mbpl and Swi4 share 34% of their target genes, Fkhl and Fkh2 share 22%>, and Ace2 and Swi5 share 25%. It is also clear, however, that this redundancy doesn't apply in wild type cells to many genes that are normally bound by one member of these pairs. The partial overlap in genes under the control of pairs of regulators explains why one gene of a pair can rescue defects in the other, yet each member ofthe pair can be responsible for distinct functions in wild type cells. Why might cells have evolved to have pairs of cell cycle transcriptional regulators with partially redundant functions? This configuration provides cells with two useful parameters particularly relevant to cell cycle function. Pairs of regulators with overlapping function may help ensure that the cell cycle is completed efficiently, even when one activator is not fully functional, which is critical since the inability to complete the cycle leads to death. At the same time, devoting each ofthe pair to distinct functional groups of genes ensures coordinate regulation of that function. DNA Binding Motifs Genome-wide location analysis identifies the set of promoters that are bound by the same transcription factor. The availability of a large number of putative targets is ideal for DNA binding motif searching to identify common DNA regulatory elements. In order to identify the consensus binding sites for cell cycle transcription factors, we used the AlignACE program (Hughes, J. D., et al, J Mol Biol 296, 1205-14 (2000)). Several general insights evolved from our analysis. First, the DNA binding motif alone is not a sufficient predictor of protein binding, since these motifs are generally found in many sites in the genome other than the promoters that are bound in vivo. Similar observations have been reported by us and others in previous studies (Ren, B., et al, Science 290, 2306-9 (2000); Iyer et al. Nature, 409:533-536 (2001)). This indicates that there is a need for additional empirical data combined and perhaps improved search algorithms in order for investigators to accurately predict genuine binding sites. Second, the binding sites identified here for Mbpl, Swi4 and Mcml are found in most but not all of the promoters of their target genes. This suggests that variations ofthe consensus sequence that are not easily recognized by search algorithms may also serve for binding, or that the factor of interest is modified or associated with binding partners that generate a new binding preference. In this context, it is interesting that the Mcml binding motif is somewhat different in the promoters of its G2/M targets than in its M/Gl targets, probably reflecting the influence of its binding partners. Finally, we have identified multiple binding motifs for forkhead factors, Ace2 and Swi5, suggesting that these proteins can recognize different motifs or that motif recognition depends on modifications or partnering with as yet unidentified proteins. Summary Using the Genome Wide Location Analysis technique, we identified targets of all known cell cycle transcription activators identified genome-wide. These results reveal how multiple activators collaborate to regulate temporal expression of genes in the cell cycle. • Each activator group regulates at least one activator for the next phase. • Each activator group regulates genes involved in phase entry and CDK cyclin regulators that set the stage for exiting that phase. • Specific activators are associated with specific cell cycle functions. We also identified consensus DNA binding motifs for each ofthe nine activators profiled. Finally, partial redundancy between pairs of activators may serve to ensure that the cell cycle is completed efficiently while allowing each activator to regulate distinct functional groups of genes. While this invention has been particularly shown and described with references to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope ofthe invention encompassed by the appended claims.

Claims: CLAIMS What is claimed is: 1. A method of identifying a region of a genome of a cell to which a protein of interest binds, comprising the steps of: a) crosslinking DNA binding protein in the cell to genomic DNA of the cell, thereby producing DNA binding protein crosslinked to genomic DNA; b) generating DNA fragments of the genomic DNA crosslinked to DNA binding protein in a), thereby producing a mixture comprising DNA fragments to which DNA binding protein is bound; c) removing a DNA fragment to which the protein of interest is bound from the mixture produced in b); d) separating the DNA fragment identified in c) from the protein of interest; e) amplifying the DNA fragment of d); f) combining the DNA fragment of e) with DNA comprising a sequence complementary to genomic DNA ofthe cell, under conditions in which hybridization between the DNA fragment and a region ofthe sequence complementary to genomic DNA occurs; and g) identifying the region ofthe sequence complementary to genomic DNA of f) to which the DNA fragment hybridzes, whereby the region identified in g) is the region ofthe genome in the cell to which the protein of interest binds. 2. The method of Claim 1 wherein the cell is a eukaryotic cell. 3. The method of Claim 1 wherein the protein of interest is selected from the group consisting of: a transcription factor and an oncogene. 4. The method of Claim 1 wherein the DNA binding protein ofthe cell is crosslinked to the genome ofthe cell using formaldehyde. 5. The method of Claim 1 wherein the DNA fragment of c) to which is bound the protein of interest is identified using an antibody which binds to the protein of interest. 6. The method of Claim 1 wherein the DNA fragment of e) is amplified using ligation-mediated polymerase chain reaction. 7. The method of Claim 1 wherein the complement sequence ofthe genome of f) is a DNA microarray. 8. The method of Claim 1 further comprising: h) comparing the region identified in g) with a control. 9. A method of identifying a region of a genome of a cell to which a protein of interest binds, comprising the steps of: a) formaldehyde crosslinking DNA binding protein in the cell to genomic DNA ofthe cell, thereby producing DNA binding protein crosslinked to genomic DNA; b) generating DNA fragments ofthe genomic DNA crosslinked to DNA binding protein in a), thereby producing DNA fragments to which DNA binding protein is bound; c) immunoprecipitating the DNA fragment produced in b) to which the protein of interest is bound using an antibody that specifically binds the protein of interest; d) separating the DNA fragment identified in c) from the protein of interest; e) amplifying the DNA fragment of d) using ligation-mediated polymerase chain reaction; f) fluorescently labeling the DNA fragment of e); g) combining the labeled DNA fragment of e) with a DNA microarray comprising a sequence complementary to genomic DNA of the cell, under conditions in which hybridization between the DNA fragment and a region ofthe sequence complementary to genomic DNA occurs; h) identifying the region ofthe sequence complementary to genomic DNA to which the DNA fragment hybridizes by measuring the fluorescence intensity; and i) comparing the fluorescence intensity measured in h) to the fluorescence intensity of a control, whereby fluorescence intensity in a region ofthe genome which is greater than the fluorescence intensity ofthe control in the region indicates the region ofthe genome in the cell to which the protein of interest binds. 10. A method of determining a function of a protein of interest which binds to a genome of a cell, comprising the steps of: a) crosslinking DNA binding protein in the cell to genomic DNA ofthe cell, thereby producing DNA binding protein crosslinked to genomic DNA; b) generating DNA fragments ofthe genomic DNA crosslinked to DNA binding protein in a), thereby producing a mixture comprising DNA fragments to which DNA binding protein is bound; c) removing the DNA fragment to which the protein of interest is bound from the mixture produced in b); d) separating the DNA fragment identified in c) from the protein of interest; e) amplifying the DNA fragment of d); f) combining the DNA fragment of e) with DNA comprising a sequence complementary to genomic DNA of the cell, under conditions in which hybridization between the DNA fragment and a region ofthe sequence complementary to genomic DNA occurs; g) identifying the region ofthe sequence complementary to genomic DNA of f) to which the DNA fragment hybridzes; and h) characterizing the region identified in g), wherein the characteristics ofthe region of h) indicates a function ofthe protein of interest which binds to the genome ofthe cell. 11. A method of determining whether a protein of interest which binds to the genome of a cell functions as a transcription factor, comprising the steps of: a) crosslinking DNA binding protein in the cell to the genomic DNA of the cell, thereby producing DNA binding protein crosslinked to genomic DNA; b) generating DNA fragments ofthe genomic DNA crosslinked to DNA binding protein in a), thereby producing a mixture comprising DNA fragments to which DNA binding protein is bound; c) removing the DNA fragment to which the protein of interest is bound from the mixture produced in b); d) separating the DNA fragment identified in c) from the protein of interest; e) amplifying the DNA fragment of d); f) combining the DNA fragment of e) with DNA comprising a sequence complementary to genomic DNA ofthe cell, under conditions in which hybridization between the DNA fragment and a region ofthe sequence complementary to genomic DNA occurs; and g) identifying the region ofthe sequence complementary to genomic DNA of f) to which the DNA fragment hybridzes, wherein if the region of the sequence complementary to genomic DNA of g) is a regulatory region, then the protein of interest is a transcription factor. 12. A method of identifying a set of genes, the members of which are genes for which cell cycle regulator binding correlates with gene expression, comprising: (a) identifying a set of genes that is bound in vivo by at least one cell cycle regulator in a selected cell type; (b) comparing the set of genes identified in (a) with genes whose expression levels vary in a periodic manner during the cell cycle of the selected cell type; and (c) identifying genes that are bound by one or more ofthe cell cycle regulators, thus identifying a set of genes, the members of which are genes whose expression levels vary in a periodic manner during the cell cycle and are bound by at least one cell cycle regulator, wherein the set identified in (c) is referred to as a set of genes, the members of which are genes for which cell cycle regulator binding correlates with gene expression. 13. The method of claim 12, wherein the selected cell type is a yeast cell. 14. The method of claim 13, wherein the at least one cell cycle regulator is at least one ofthe nine known yeast cell cycle transcriptional activators.

Inventors: REN BING, ROBERT FRANCOIS, SIMON ITAMAR, WYRICK JOHN, YOUNG RICHARD A, REN, BING, ROBERT, FRANCOIS, SIMON, ITAMAR, WYRICK, JOHN, YOUNG, RICHARD, A.
Applicants: REN BING, ROBERT FRANCOIS, SIMON ITAMAR, WHITEHEAD BIOMEDICAL INST, WYRICK JOHN, YOUNG RICHARD A, REN, BING, ROBERT, FRANCOIS, SIMON, ITAMAR, WHITEHEAD INSTITUTE FOR BIOMEDICAL RESEARCH, WYRICK, JOHN, YOUNG, RICHARD, A.
Application year: 2001
Main classification: C12Q1
IPC codes: C12Q1, G01N33