CHARACTERIZATION OF THE YEAST TRANSCRIPTOME

Abstract: Yeast genes which are differentially expressed during the cell cycle are described. They can be used to study, affect, and monitor the cell cycle of a eukaryotic cell. They can be used to obtain human homologs involved in cell cycle regulation. They can be used to identify antifungal agents. They can be formed into arrays on solid supports for interrogation of a cell's transcriptome under various conditions.

Description: CHARACTERIZATION OF THE YEAST TRANSCRIPTOME TECHNICAL FIELD OF THE INVENTION This invention is related to the characterization of the expressed genes of the yeast genome. More particularly, it is related to the identification and use of previously unrecognized genes. BACKGROUND OF THE INVENTION It is by now axiomatic that the phenotype of an organism is largely determined by the genes expressed within it. These expressed genes can be represented by a "transcriptome", conveying the identity of each expressed gene and its level of expression for a defined population of cells. Unlike the genome, which is essentially a static entity, the transcriptome can be modulated by both external and internal factors. The transcriptome thereby serves as a dynamic link between an organism's genome and its physical characteristics. The transcriptome as defined above has not been characterized in any eukaryotic or prokaryotic organism, largely because of technological limitations. However, some general features of gene expression patterns were elucidated two decades ago through RNA-DNA hybridization measurements (Bishop et al., 1974; Hereford and Rosbash, 1977). In many organisms, it was thus found that at least three classes of transcripts could be identified, with either high, medium, or low levels of expression, and the number of transcripts per cell were estimated (Lewin, 1980). These data of course provided little information about the specific genes that were members of each class. Data on the expression levels of individual genes have accumulated as new genes were discovered. However, in only a few instances have the absolute levels of expression of particular genes been measured and compared to other genes in the same cell type. Description of any cell's transcriptome would therefore provide new information useful for understanding numerous aspects of cell biology and biochemistry. SUMMARY OF THE INVENTION It is an object of the present invention to provide genes which are involved in cell cycle progression. It is another object of the present invention to provide methods of using the genes to affect the cell cycle. It is an object of the present invention to provide methods for screening candidate antifungal drugs. Another object of the invention is to provide a method for obtaining human homologs of the yeast genes which are involved in cell cycle progression. Another object of the invention is to provide probes for ascertaining phase in the cell cycle of a cell. These and other objects of the invention are achieved by providing the art with one or more of the embodiments described below. According to one embodiment of the invention an isolated DNA molecule is provided. It comprises a yeast gene which is involved in cell cycle progression selected from the group of NORF genes identified in Table 3 or 4. According to another embodiment of the invention a method of using yeast genes is provided. The method is for affecting the cell cycle of a cell. The method comprises the step of: administering to a cell an isolated DNA molecule comprising a yeast gene which is involved in cell cycle progression selected from the differentially expressed genes identified in Tables 1, 2, 3 and 4. In yet another embodiment of the invention a method for screening candidate antifungal drugs is provided. The method comprises the steps of: contacting a test substance with a yeast cell; monitoring expression of a yeast gene which is involved in cell cycle progression selected from the group of yeast genes identified in Tables 1, 2, 3 and 4, wherein a test substance which modifies the expression of the yeast gene is a candidate antifungal drug. In still another embodiment of the invention a method for identifying human genes which are involved in cell cycle progression is provided. The method comprises the step of: hybridizing a probe comprising at least 14 contiguous nucleotides of a yeast gene which is differentially expressed between at least two phases selected from the group consisting of log phase, S phase, and G2/M phase, wherein the yeast gene is identified in Table 1, 2, 3, or 4. Also provided by the present invention are isolated DNA molecules, which comprise probes for ascertaining phase in the cell cycle of a cell, wherein the probe comprises at least 14 contiguous nucleotides of aNORF gene as identified in Table 3 or 4. These and other embodiments of the invention which will be apparent to those of skill in the art upon reading the detailed disclosure provided below, make available to the art hitherto unrecognized genes, and information about the expression of genes globally at the organismal level. We provide the first description of a transcriptome, determined in S. cerevisiae cells. This organism was chosen because it is widely used to clarify the biochemical and physiologic parameters underlying eukaryotic cellular functions and because it is the only eukaryote in which the entire genome has been defined at the nucleotide level (GofFeau, et al., 1996). BRIEF DESCRIPTION OF THE DRAWINGS Figure 1. Schematic of SAGE Method and Genome Analysis. In applying SAGE to the analysis of yeast gene expression patterns, the 3' most Nlalll site was used to define a unique position in each transcript and to provide a site for ligation of a linker with a BsmFI site. The type IIs enzyme BsmFI, which cleaves a defined distance from its non-palindromic recognition site, was then used to generate a 15bp SAGE tag (designated by the black arrows), which includes the Nlalll site. Automated sequencing of concatenated SAGE tags allowed the routine identification of about a thousand tags per sequencing gel. Once sequenced, the abundance of each SAGE tag was calculated, and each tag was used to search the entire yeast genome to identify its corresponding gene. The lower panel shows a small region of Chromosome 15. Gray arrows indicate all potential SAGE tags (NlaLπ sites) and black arrows indicate 3' most SAGE tags. The total number of tags observed for each potential tag is indicated above (+ strand) or below (- strand) the tag. As expected, the observed SAGE tags were associated with the 3' end of expressed genes. Figure 2. Sampling of Yeast Gene Expression. Analysis of increasing amounts of ascertained tags reveals a plateau in the number of unique expressed genes. Triangles represent genes with known functions, squares represent genes predicted on the basis of sequence information, and circles represent total genes. Figure 3. Virtual Rot. (a) Abundance Classes in the Yeast Transcriptome. The transcript abundance is plotted in reverse order on the abscissa, whereas the fraction of total transcripts with at least that abundance is plotted on the ordinate. The dotted lines identify the three components of the curve, 1, 2, and 3. This is analogous to a Rot curve derived from reassociation kinetics where the product of initial RNA concentration and time is plotted on the abscissa, and the percent of labeled cDNA that hybridizes to excess mRNA is plotted on the ordinate. (b) Comparison of Virtual Rot and Rot Components. Transitions and data from virtual Rot components were calculated from the data in Figure 3 A, while data for Rot components were obtained from Hereford and Rosbash, 1977. Figure 4. Chromosomal Expression Map for S. cerevisiae. Individual yeast genes were positioned on each chromosome according to their open reading frame (ORF) start coordinates. Abundance levels of tags corresponding to each gene are displayed on the vertical axis, with transcription from the + strand indicated above the abscissa and that from the - strand indicated below. Yellow bands at ends of the expanded chromosome represent telomeric regions that are undertranscribed (see text for details). Figure 5. Northern Blot Analysis of Representative Genes. TDH2/3, TEF1/2 and NORFl, are expressed relatively equally in all three states (lane 1, G2/M arrested; lane 2, S phase arrested; lane 3, log phase), while RNR4, RNR2 , and NORF5 are highly expressed in S-phase arrested cells. The expression level observed by SAGE (number of tags) is noted below each lane and was highly correlated with quantitation of the Northern blot by Phosphorlmager analysis (r^O.97). Table Legends Table 1. Highly Expressed Genes Tag represents the 10 bp SAGE tag adjacent to the Nlalll site; Gene represents the gene or genes corresponding to a particular tag (multiple genes that match unique tags are from related families, with an average identity of 93%); Locus and Description denote the locus name, and functional description of each ORF, respectively; Copies/cell represents the abundance of each transcript in the SAGE library, assuming 15,000 total transcripts per cell and 60,633 ascertained transcripts. Table 2. Expression of Putative Coding Sequences Table columns are the same as for Table 1. Table 3. Expression of NORF genes SAGE Tag, Locus, and Copies/cell are the same as for Table 1; Chr and Tag Pos denote the chromosome and position of each tag; ORF Size denotes the size of the ORF corresponding to the indicated tag. In each case, the tag was located within or less than 250 bp 3' of the NORF. DETAILED DESCRJTPTION It is a discovery of the present invention that certain hitherto unknown genes (the NORFs) exist and are expressed in yeast. These genes, as well as other previously identified and previously postulated genes, can be used to study, monitor, and affect phase of cell cycle. The present invention provides information on which genes are differentially expressed during the cell cycle. Differentially expressed genes can be used as markers of phases of the cell cycle. They can also be used to affect a change in the phase of the cell cycle. In addition, they can be used to screen for drugs which affect the cell cycle, by affecting expression of the genes. Human homologs of these eukaryotic genes are also presumed to exist, and can be identified using the yeast genes as probes or primers to identify the human homologs. New genes termed NORFs (not previously assigned open reading frames) have been found. They are uniquely identified by their SAGE tags. In addition their entire nucleotide sequence is known and publicly available. In general, these were not previously identified as genes due to their small size. However, they have now been found to be expressed. Differentially expressed yeast genes are those whose expression varies by a statistically significant difference (to greater than 95% confidence level) within different growth phases, particularly log phase, S phase, and G2 M. Preferably the difference is greater than 10%, 25%, 50%, or 100%. The genes which have been found to have such differential expression characteristics are: NORF N β 1, 2, 4, 5, 6, 17, 25, 27, TEF1/TEF2, EN02, ADH1, ADH2, PGK1, CUPIA/CUPIB, PYK1, YKL056C, YMR116C, YEL033W, YOR182C, YCR013C, ribonucleotide reductase 2 and 4, and YJR085C. The DNA molecules according to the invention can be genomic or cDNA. Preferably they are isolated free of other cellular components such as membrane components, proteins, and lipids. They can be made by a cell and isolated, or synthesized using PCR or an automatic synthesizer. Any technique for obtaining a DNA of known sequence may be used. Methods for purifying and isolating DNA are routine and are known in the art. To administer yeast genes to cells, any DNA delivery techniques known in the art may be used, without limitation. These include liposomes, transfection, transduction, transformation, viral infection, electroporation. Vectors for particular purposes and characteristics can be selected by the skilled artisan for their known properties. Cells which can be used as gene recipients are yeast and other fungi, mammalian cells, including humans, and bacterial cells. Antifungal drugs can be identified using yeast cells as described herein. Expression of a differentially expressed gene can be monitored by any means known in the art. When a test substance affects the expression of such a differentially expressed gene, it is a candidate drug for affecting the growth properties of fungi, and may be useful as an antifungal agent. Because differentially expressed genes are likely to be involved in cell cycle progression, it is likely that these genes are conserved among species. The differentially expressed genes identified by the present invention can be used to identify homologs in humans and other mammals. Means for identifying homologous genes among different species are well known in the art. Briefly, stringency of hybridization can be reduced so that imperfectly matching sequences hybridize. This can be in the context of inter alia Southern blots, Northern blots, colony hybridization or PCR. Any hybridization technique which is known in the art can be used. Probes according to the present invention are isolated DNA molecules which have at least 10, and preferably at least 12, 14, 16, 18, 20, or 25 contiguous nucleotides of a particular NORF gene or other differentially expressed gene. The probes may or may not be labeled. They may be used as primers for PCR or for Southern or Northern blots. Preferably the probes are anchored to a solid support. More preferably they are present on an array so that multiple probes can simultaneously hybridize to a single biological sample. The probes can be spotted onto the array or synthesized in situ on the array. See Lockhart et. al., Nature Biotechnology, Vol. 14, December 1996, "Expression monitoring by hybridization to high-density oligonucleotide arrays." A single array can contain more than 100, 500 or even 1,000 different probes in discrete locations. The above disclosure generally describes the present invention. A more complete understanding can be obtained by reference to the following specific examples which are provided herein for purposes of illustration only, and are not intended to limit the scope of the invention. EXAMPLE Summary We have analyzed the set of genes expressed from the yeast genome, herein called the transcriptome, using serial analysis of gene expression (SAGE). Analysis of 60,633 transcripts revealed 4,665 genes, with expression levels ranging from 0.3 to over 200 transcripts per cell. Of these genes, 1,981 had known functions, while 2,684 were previously uncharacterized. Integration of positional information with gene expression data allowed the generation of chromosomal expression maps, identifying physical regions of transcriptional activity, and identified genes that had not been predicted by sequence information alone. These studies provide insight into global patterns of gene expression in yeast and demonstrate the feasibility of genome-wide expression studies in eukaryotes. Results Characteristics and Rationale of SAGE Approach Several methods have recently been described for the high throughput evaluation of gene expression (Nguyen et al., 1995; Schena et al., 1995; Velculescu et al., 1995). We used SAGE (Serial Analysis of Gene Expression) because it can provide quantitative gene expression data without the prerequisite of a hybridization probe for each transcript. The SAGE technology is based on two basic principles (Figure 1). First, a short sequence tag (9-11 bp) contains sufficient information to uniquely identify a transcript, provided that it is derived from a defined location within that transcript. Second, many transcript tags can be concatenated into a single molecule and then sequenced, revealing the identity of multiple tags simultaneously. The expression pattern of any population of transcripts can be quantitatively evaluated by determining the abundance of individual tags and identifying the gene corresponding to each tag. Genome-wide expression In order to maximize representation of genes involved in normal growth and cell-cycle progression, SAGE libraries were generated from yeast cells in three states: log phase, S phase arrested and G2/M phase arrested. In total, SAGE tags corresponding to 60,633 total transcripts were identified (including 20,184 from log phase, 20,034 from S phase arrested, and 20,415 from G2/M phase arrested cells). Of these tags, 56,291 tags (93%) precisely matched the yeast genome, 88 tags matched the mitochondrial genome, and 91 tags matched the 2 micron plasmid. The number of SAGE tags required to define a yeast transcriptome depends on the confidence level desired for detecting low abundance mRNA molecules. Assuming the previously derived estimate of 15,000 mRNA molecules per cell (Hereford and Rosbash, 1977), 20,000 tags would represent a 1.3 fold coverage even for mRNA molecules present at a single copy per cell, and would provide a 72% probability of detecting such transcripts (as determined by Monte Carlo simulations). Analysis of 20,184 tags from log phase cells identified 3,298 unique genes. As an independent confirmation of mRNA copy number per cell, we compared the expression level of SUP44/RPS4, one of the few genes whose absolute mRNA levels have been reliably determined by quantitative hybridization experiments (Iyer and Struhl, 1996), with expression levels determined by SAGE. SUP44/RPS4 was measured by hybridization at 75 +/- 10 copies/cell (Iyer and Struhl, 1996), in good accord with the SAGE data of 63 copies/cell, suggesting that the estimate of 15,000 mRNA molecules per cell was reasonably accurate. Analysis of SAGE tags from S phase arrested and G2 M phase arrested cells revealed similar expression levels for this gene (range 52 to 55 copies/cell), as well as for the vast majority of expressed genes. As less than 1% of the genes were expressed at dramatically different levels among these three states (see below), SAGE tags obtained from all libraries were combined and used to analyze global patterns of gene expression. Analysis of ascertained tags at increasing increments revealed that the number of unique transcripts plateaued at ~60,000 tags (Figure 2). This suggested that generation of further SAGE tags would yield few additional genes, consistent with the fact that sixty thousand transcripts represented a four-fold redundancy for genes expressed as low as 1 transcript per cell. Likewise, Monte Carlo simulations indicated that analysis of 60,000 tags would identify at least one tag for a given transcript 97% of the time if its expression level was one copy per cell. The 56,291 tags that precisely matched the yeast genome represented 4,665 different genes. This number is in agreement with the estimate of 3,000 to 4,000 expressed genes obtained by RNA-DNA reassociation kinetics (Hereford and Rosbash, 1977). These expressed genes included 85% of the genes with characterized functions (1,981 of 2,340), and 76% of the total genes predicted from analysis of the yeast genome (4,665 of 6,121). These numbers are consistent with a relatively complete sampling of the yeast transcriptome given the limited number of physiological states examined and the large number of genes predicted solely on the basis of genomic sequence analysis. The transcript expression per gene was observed to vary from 0.3 to over 200 copies per cell. Analysis of the distribution of gene expression levels revealed several abundance classes that were similar to those observed in previous studies using reassociation kinetics. A "virtual Rot" of the genes observed by SAGE (Figure 3 A) identified three main components of the transcriptome with abundances ranging over three orders of magnitude. A Rot curve derived from RNA-cDNA reassociation kinetics also contained three main components distributed over a similar range of abundances (Hereford and Rosbash, 1977). Although the kinetics of reassociation of a particular class of RNA and cDNA may be affected by numerous experimental variables, there were striking similarities between Rot and virtual Rot analyses (Figure 3B). Because Rot analysis may not detect all transcripts of low abundance (Lewin, 1980), it is not surprising that SAGE revealed both a larger total number of expressed genes and a higher fraction of the transcriptome belonging to the low abundance transcript class. Integration of Expression Information with the Genomic Map The SAGE expression data could be integrated with existing positional information to generate chromosomal expression maps (Figure 4). These maps were generated using the sequence of the yeast genome and the position coordinates of ORFs obtained from the Stanford Yeast Genome Database. Although there were a few genes that were noted to be physically proximal and have similarly high levels of expression, there did not appear to be any clusters of particularly high or low expression on any chromosome. Genes like histones H3 and H4, which are known to have coregulated divergent promoters and are immediately adjacent on chromosome 14 (Smith and Murray, 1983), had very similar expression levels (5 and 6 copies per cell, respectively). The distribution of transcripts among the chromosomes suggested that overall transcription was evenly dispersed, with total transcript levels being roughly linearly related to chromosome size (r 2 =0.85, data not shown). However, regions within 10 kb of telomeres appeared to be uniformly undertranscribed, containing on average 3.2 tags per gene as compared with 12.4 tags per gene for non-telomeric regions (Figure 4). This is consistent with the previously described observations of "telomeric silencing" in yeast (Gottschling et al., 1990). Recent studies have reported telomeric position effects as far as 4 kb from telomere ends (Renauld et al., 1993). Gene Expression Patterns Table 1 lists the 30 most highly expressed genes, all of which are expressed at greater than 60 mRNA copies per cell. As expected, these genes mostly correspond to well characterized enzymes involved in energy metabolism and protein synthesis and were expressed at similar levels in all three growth states (Examples in Figure 5). Some of these genes, including EN02 (McAlister and Holland, 1982), PDC1 (Schmitt et al., 1983), PGK1 (Chambers et al., 1989), PYK1 (Nishizawa et al., 1989), and ADH1 (Denis et al., 1983), are known to be dramatically induced in the glucose-rich growth conditions used in this study. In contrast, glucose repressible genes such as the GAL1/GAL7/GAL10 cluster (St John and Davis, 1979), and GAL3 (Bajwa et al., 1988) were observed to be expressed at very low levels (0.3 or fewer copies per cell). As expected for the yeast strain used in this study, mating type a specific genes, such as the a factor genes (MFA1, MFA2) (Michaelis and Herskowitz, 1988), and alpha factor receptor STE2) (Burkholder and Hartwell, 1985) were all observed to be expressed at significant levels (range 2 to 10 copies per cell), while mating type alpha specific genes MF l, MFcά, STE3) (Hagen et al., 1986; Kurjan and Herskowitz, 1982; Singh et al., 1983) were observed to be expressed at very low levels (<0.3 copies/cell). Three of the highly expressed genes in Table 1 had not been previously characterized. One contained an ORF with predicted ribosomal function, previously identified only by genomic sequence analysis. Analyses of all SAGE data suggested that there were 2,684 such genes corresponding to uncharacterized ORFs which were transcribed at detectable levels. The 30 most abundant of these transcripts were observed more than 30 times, corresponding to at least 8 transcripts per cell (Table 2). The other two highly expressed uncharacterized genes corresponded to ORFs not predicted by analysis of the yeast genome sequence (NORF = Nonannotated ORF). Analyses of SAGE data suggested that there were approximately 160 NORF genes transcribed at detectable levels. The 30 most abundant of these transcripts were observed at least 9 times (Table 3 and examples in Figure 5). Interestingly, one of the NORF genes NORF5) was only expressed in S phase arrested cells and corresponded to the transcript whose abundance varied the most in the three states analyzed (> 49 fold, Figure 5). Comparison of S phase arrested cells to the other states also identified greater than 9 fold elevation of the RNR2 and RNR4 transcripts (Figure 5). Induction of these ribonucleoside reductase genes is likely to be due to the hydroxyurea treatment used to arrest cells in S phase (Elledge and Davis, 1989). Likewise, comparison of G2/M arrested cells identified elevation of RBL2 and dynein light chain, both microtubule associated proteins (Archer et al., 1995; Dick et al., 1996). As with the RΝR inductions, these elevated levels seem likely to be related to the nocodazole treatment used to arrest cells in the G2 M phase. While there were many relatively small differences between the states (for example, NORF1, Figure 5), overall comparison of the three states revealed surprisingly few dramatic differences; there were only 29 transcripts whose abundance varied more than 10 fold among the three different states analyzed. Discussion Analysis of a yeast transcriptome affords a unique view of the RNA components defining cellular life. We observed gene expression levels to vary over three orders of magnitude, with the transcripts involved in energy metabolism and protein synthesis the most highly expressed. Key transcripts, such as those encoding enzymes required for DNA replication (e.g. POL1 and POLS), kinetochore proteins (NDCIO and SKPI), and many other interesting proteins, were present at 1 or fewer copies per cell on average. These abundances are consistent with previous qualitative data from reassociation kinetics which suggested that the largest number of expressed genes was present at 1 or 2 copies per cell. These observations indicate that low transcript copy numbers are sufficient for gene expression in yeast, and suggest that yeast possess a mechanism for rigid control of RNA abundance. The synthesis of chromosomal expression maps presents a cataloging of the expression level of genes, organized by their genomic positions. It is not surprising that gene expression is well balanced throughout the 16 chromosomes of S. cerevisiae. As most genes have independent regulatory elements, it would have been surprising to find a large number of physically adjacent genes that had similar high levels of expression. Of the few genes that were known to have coregulated divergent promoters, like the H3/H4 pair, SAGE data confirmed concordant levels of expression. For areas like telomere ends that are known to be transcriptionally suppressed, SAGE data corroborated low levels of expression. Other expected expression patterns such as high levels of glucose induced glycolytic enzymes, low levels of glucose repressed GAL genes, expression of mating type a specific genes, and low of expression of mating type alpha genes, were observed. Finally, identification of tags corresponding to NORF genes suggests that there is a significant number of small proteins encoded by the yeast genome that were undetected by the criteria used for systematic sequence analysis. The yeast genome sequence has been annotated for all ORFS larger than 300bp, (encoding proteins 100 amino acids or greater). Genes encoding proteins below this cut off are therefore commonly unannotated. This class of genes might also be underrepresented in mutational collections because of the small target size for mutagenesis, and given their small size, may encode proteins with novel functions. The systematic knockout of these NORF genes will therefore be of great interest. Comparison of gene expression patterns from altered physiologic states can provide insight into genes that are important in a variety of processes. Comparison of transcriptomes from a variety of physiologic states should provide a minimum set of genes whose expression is required for normal vegetative growth, and another set composed of genes that will be expressed only in response to specific environmental stimuli, or during specialized processes. For example, recent work has defined a minimal set of 250 genes required for prokaryotic cellular life (Mushegian and Koonin, 1996). Examination of the yeast genome readily identified homologous genes for 196 of these, over 90% of which were observed to be expressed in the SAGE analysis. Detailed analyses of yeast transcriptomes, as well as transcriptomes from other organisms, should ultimately allow the generation of a minimal set of genes required for eukaryotic life. Like other genome-wide analyses, SAGE analysis of yeast transcriptomes has several potential limitations. First, a small number of transcripts would be expected to lack an Nlalll site and therefore would not be detected by our analysis. Second, our analysis was limited to transcripts found at least as frequently as 0.3 copies per cell. Transcripts expressed in only a minute fraction of the cell cycle, or transcripts expressed in only a fraction of the cell population, would not be reliably detected by our analysis. Finally, mRNA sequence data are practically unavailable for yeast, and consequently, some SAGE tags cannot be unambiguously matched to corresponding genes. Tags which were derived from overlapping genes, or genes which have unusually long 3' untranslated regions may be misassigned. Increased availability of 3' UTR sequences in yeast mRNA molecules should help to resolve the ambiguities. Despite these potential limitations, it is clear that the analyses described here furnish both global and local pictures of gene expression, precisely defined at the nucleotide level. These data, like the sequence of the yeast genome itself, provide simple, basic information integral to the interpretation of many experiments in the future. The availability of mRNA sequence information from EST sequencing as well as various genome projects, will soon allow definition of transcriptomes from a variety of organisms, including human. The data recorded here suggest that a reasonably complete picture of a human cell transcriptome will require only about 10 - 20 fold more tags than evaluated here, a number well within the practical realm achievable with a small number of automated sequencers. The analysis of global expression patterns in higher eukaryotes is expected, in general, to be similar to those reported here for S. cerevisiae. However, the analysis of the transcriptome in different cells and from different individuals should yield a wealth of information regarding gene function in normal, developmental, and disease states. Experimental Procedures Yeast cell culture The source of transcripts for all experiments was S. cerevisiae strain YPH499 {MATa ura3-52 fys2-801 ade2-101 Ieu2-Δl his3-Δ200 trpl-Δ63) (Sikorski andJEeter, 1989). Logarithmically growing cells were obtained by growing yeast cells to early log phase (3 x 10 6 cells/ml) in YPD (Rose et al., 1990) rich medium (YPD supplemented with 6mM uracil, 4.8 mM adenine and 24 mM tryptophan) at 30°C. For arrest in the Gl/S phase of the cell cycle, hydroxyurea (0.1M) was added to early log phase cells, and the culture was incubated an additional 3.5 hours at 30 °C. For arrest in the G2 M phase of the cell cycle, nocodazole (15ug/ml) was added to early log phase cells and the culture was incubated for an additional 100 minutes at 30°C. Harvested cells were washed once with water prior to freezing at -70 °C. The growth states of the harvested cells were confirmed by microscopic and flow cytometric analyses (Basrai et al., 1996). RNA isolation and Northern Blot Analysis Total yeast RNA was prepared using the hot phenol method as described (Leeds et al., 1991). mRNA was obtained using the MessageMaker Kit (Gibco BRL) following the manufacturer's protocol. Northern blot analysis was performed as described (El-Deiry et al., 1993), using probes PCR amplified from yeast genomic DNA. SAGE protocol The SAGE method was performed as previously described (Velculescu et al., 1995), with exceptions noted below. PolyA RNA was converted to double- stranded cDNA with a BRL synthesis kit using the manufacturer's protocol except for the inclusion of primer biotin-5'-T lg -3'. The cDNA was cleaved with Nlalll (Anchoring Enzyme). As Nlalll sites were observed to occur once every 309 base pairs in three arbitrarily chosen yeast chromosomes (1, 5, 10), 95% of yeast transcripts were predicted to be detectable with a Nlalll- based SAGE approach. After capture of the 3' cDNA fragments on streptavidin coated magnetic beads (Dynal), the bound cDNA was divided into two pools, and one of the following linkers containing recognition sites for BsmFI was ligated to each pool: Linker 1, 5'- TTTGGATTTGCTGGTGCAGTACAACTAGGCTTAATAGGGACATG-3 , ( S E D I D N O : 1 ) . 5 ' - TCCCTATTAAGCCTAGTTGTACTGCACCAGCAAATCC [amino mod. C7]-3'(SED ID NO:2).; Linker 2,5'- TTTCTGCTCGAATTCAAGCTTCTAACGATGTACGGGGACATG-3* ( S E D I D N O : 3 ) 5 ' - TCCCCGTACATCGT AGAAGCπGAAπCGAGCAG[amino mod. C7]- 3' (SED ID NO:4). As BsmFI (Tagging Enzyme) cleaves 14 bp away from its recognition site, and the Nlaiπ site overlaps the BsmFI site by 1 bp, a 15 bp SAGE tag was released with BsmFI. SAGE tag overhangs were filled-in with Klenow, and tags from the two pools were combined and ligated to each other. The ligation product was diluted and then amplified with PCR for 28 cycles with 5'-GGATTTGCTGGTGCAGTACA-3' (SED ID NO: 5) and 5'- CTGCTCGAATTCAAGCTTCT-3* (SED ID NO:6), as primers. The PCR product was analyzed by polyacrylamide gel electrophoresis (PAGE), and the PCR product containing two tags ligated tail to tail (ditag) was excised. The PCR product was then cleaved with NlalH, and the band containing the ditags was excised and self-ligated. After ligation, the concatenated products were separated by PAGE and products between 500 bp and 2 kb were excised. These products were cloned into the Sphl site of pZero (Invitrogen). Colonies were screened for inserts by PCR with M13 forward and M13 reverse sequences located outside the cloning site as primers. PCR products from selected clones were sequenced with the TaqFS DyePrimer kits (Perkin Elmer) and analyzed using a 377 ABI automated sequencer (Perkin Elmer), following the manufacturer's protocol. Each successful sequencing reaction identified an average of 26 tags; given a 90% sequencing reaction success rate, this corresponded to an average of about 850 tags per sequencing gel. SAGE data analysis Sequence files were analyzed by means of the SAGE program group (Velculescu et al., 1995), which identifies the anchoring enzyme site with the proper spacing and extracts the two intervening tags and records them in a database. The 68,691 tags obtained contained 62,965 tags from unique ditags and 5,726 tags from repeated ditags. The latter were counted only once to eliminate potential PCR bias of the quantitation, as described (Velculescu et al., 1995). Of 62,965 tags, 2,332 tags corresponded to linker sequences, and were excluded from further analysis. Of the remaining tags, 4,342 tags could not be assigned, and were likely due to sequencing errors (in the tags or in the yeast genomic sequence). If all of these were due to tag sequencing errors, this corresponds to a sequencing error rate of about 0.7% per base pair (for a lObp tag), not far from what we would have expected under our automated sequencing conditions. However, some unassigned tags had a much higher than expected frequency of A's as the last five base pairs of the tag (5 of the 52 most abundant unassigned tags), suggesting that these tags were derived from transcripts containing anchoring enzyme sites within several base pairs from their polyA tails. Given the frequency of Nlaiπ sites in the genome (one in 309 base pairs), approximately 3% of transcripts were predicted to contain Nlalll sites within 10 bp of their polyA tails. As very sparse data are available for yeast mRNA sequences and efforts to date have not been able to identify a highly conserved polyadenylation signal (Irniger and Braus, 1994; Zaret and Sherman, 1982), we used 14 bp of SAGE tags (i.e. the Nlalll site plus the adjacent 10 bp) to search the yeast genome directly (yeast genome sequence obtained from the Stanford yeast genome ftp site (genome-ftp.stanford.edu) on August 7, 1996). Because only coding regions are annotated in the yeast genome, and SAGE tags can be derived from 3' untranslated regions of genes, a SAGE tag was considered to correspond to a particular gene if it matched the ORF or the region 500 bp 3 1 of the ORF (locus names, gene names and ORF chromosomal coordinates were obtained from Stanford yeast genome ftp site, and ORF descriptions were obtained from MIPS www site (http://www.mips.biochem. mpg.de/) on August 14, 1996). ORFs were considered genes with known functions if they were associated with a three letter gene name, while ORFs without such designations were considered uncharacterized. As expected, SAGE tags matched transcribed portions of the genome in a highly non-random fashion, with 88% matching ORFs or their adjacent 3' regions in the correct orientation (chi-squared P value <10 "30 ). In instances when more than one tag matched a particular ORF in the correct orientation, the abundance was calculated to be the sum of the matched tags (for Figure 2, Figure 3, and Figure 4). Tags that matched ORFs in the incorrect orientation were not used in abundance calculations. In instances when a tag matched more than one region of the genome (for example an ORF and non- ORF region) only the matched ORF was considered. In some cases the 15th base of the tag could also be used to resolve ambiguities. For Figure 4, only tags that matched the genome once were used. For the identification of NORF genes, only tags were considered that matched portions of the genome that were further than 500 bp 3* of a previously identified ORF, and were observed at least two times in the SAGE libraries. Table! Highly expressed genes GGTGTTAACG " ?DH2tTDH3 " YJR009CYGR19 2 C ™v 425 glyceraldehyde-3-phosphatβ dehydrogenase 2 & 3 AGACAAACTG TEF1/TEF2 YPR080WYBR118W 248 cytosolic elongation factor eEF-1 alpha-A chain TACCACTCCT EN02 YHR17 W 229 2-phosphoglycerate dehydratase GGTTTCGGTT RPLA1.A2, A3, 10E YDL081 CYOL039WYDL130WYLR30W 207 acidic πbosomal protein a1 / P2 beta / L44prιme / L10 TTGCCAGTCT PDC1 YLR044C 207 pyruvate decarboxylase isozyme 1 GGTGAAAACG ADH1, ADH2 YOL086CYMR303C 182 alcohol dehydrogenase I / II ATCGCCGCTC GP 1 YKL15 2 C 168 phosphoglycerate mutasβ GGTGCTAAGA FBA1 YKL060C 166 fructose-bisphosphate aldolase II TTAGTTTCTA RPL47A YD 18 C 143 πbosomal protein TCTCTACTGG PGK1 YCR01 2 W 139 phosphoglycerate kinase GG 1111 GGTT RPLA4 YDR38 2 W 138 acidic πbosomal protein L45 GGTCCAGCTT SSM1A SSM1B YPL2 2 0W/YG 135W 128 nbosomal protein AATCCAGTTG RPL5A / RPL5B YIL018W/YFR031AC 102 πbosomal protein TTCGTTCACT NORF1 94 nonannotated ORF AACAGACCAG RPL16A/RPL16B YPR10 2 C/YGR085C 83 πbosomal protein CTGCTCTGGG CUP1A/CUP1B YHR053C / YHR055C 75 metallothionem GCAATACTAC YOR 2 93W / Y R 2 30W 73 πbosomal protein S10 / similarity to nbosomal protein S10 GCTCTCCCCC NORF 2 73 nonannotated ORF AAAGACAGAG RPS31A YGR0 2 7C 72 nbosomal protein TGTCGTGGTG RPL2A/RPL2B YBR031W/YDR01 2 W 70 nbosomal protein CCAAGGGTAT RPS28A YGR118W 69 nbosomal protein TCTCCAGAAG RPL35B YDR500C 69 πbosomal protein G 11111 CTTT PYK1 YAL038W 69 pyruvate kinase ATCACTGGTG RPL9A/RPL9B YGL1 7C/YNL067W 68 πbosomal protein L9 ATGAAGGTTC RPL27A YHR010W 68 πbosomal protein L27 GTAGAGCCGG RPS21 YOL040C 67 πbosomal protein GGTACTGATG RPL43A YDL075W 67 nbosomal protein L31 CCAGATTTGT NAB1A/NAB1B YGR 2 1 4 W/Y R048W 67 40S πbosomal protein p40 homolog A GTGCCGTCCA URP1A YBR191W 62 πbosomal protein L21 CAAAACCCAA RPS18EB YML0Σ6C 60 πbosomal protein S18 Table 2. Putative coding sequences TTGAACTACC YKL056C 58 strong similarity to human IgE-dependent histamine-releasing factor (21 K tumor protein) TTCGGGTCAC YDR276C 56 strong similarity to Hordeum vuigare blt101 protein CCAGATATGA YIL093C 41 hypothetical protein TTTAAAATGG YMR116C 38 similarity to N crassa CPC2 protein GGTGTCGTTG YBR078W 34 strong similarity to sporulation specific Sps2p TACTCTTCGC YEL033W 33 hypothetical protein TGTAATTAAA YOR182C 26 homology to human ubiquitin-like protein/πbosomal protein S30 GGAGATCTTG YCR013C 24 weak similarity to lepra B1496_F1_41 protein TCAAGAAGTT YER056AC 20 strong similarity to nbosomal protein L34 AAAAACTTTG YIL051C 18 strong similarity to YER057c AAGTTGAACA YPR043W 17 nbosomal protein L37 GGGTGCGGGT YDR032C 16 strong similarity to YCR004c and S pombe obrl TGACTCTTTG YLR390W 14 hypothetical protein GGTCAATGGC YJR105W 11 hypothetical protein l\D TAAGAATTCT YJL158C 11 member of the Pιr1p/Hsp150p/Pιr3p family l\3 TCAATTATGT YDR033W 11 strong similarity to putative heat shock protein YR02 ACGGCCAAGA YBR162C 10 similarity to YJL171 p TTGGGCTAGT YJL171C 10 similarity to YBR162c CCTTCCAGGT YJR085C 10 hypothetical protein CCTCTCTTGT YOR310C 10 homology to SIK1 protein CCCAAAACTT YEL018W 9 weak similarity to Rad50p AACAAGTACT YGL037C 9 similarity to E.coli hypothetical 23K protein AACAATAAAA YER072W 8 similarity to YFL004W CAAAAGACCG Y L056C 8 homology to human IMP dehydrogenase I GGTTTTTGAT YOR182C 8 homology to human ubiquitin-like protein/πbosomal protein S30 CAATCCATTT YBR106W 8 hypothetical protein TTTTGGGTCT YMR318C 8 putative alcohol-dehydrogenase AACTGTCCAT YDR429C 8 similarity to nuclear RNA binding proteins CCAAGGTTAA VΔDΠΠ ΔΓ 8 strong similarity to YGL002w GGTTTTTGAA YOR273C 8 putative resistance protein Table 3. NORF genes ^$$ ξ!? # ^* U#stt ζ ' R§«S TTCGTTCACt NORF1 94 4 1489450 198 GCTCTCCCCC NORF2 73 16 75633 243 TGTACGCATT NORF3 16 15 301251 189 1 1 1 1 ATTATC NORF4 15 6 223182 177 CTTCTC 1 1 1 1 NORF5 12 13 158973 204 TTTCCTATAA NORF6 11 13 511754 252 TCTAGTCGCC NORF7 10 12 669659 192 ATCG I 1 1 IAT NORF8 8 15 877140 174 GGCCAATGGT NORF9 8 4 1202289 267 ACCCTGTCAT NORF10 7 2 418633 255 AAAAGATCAT NORF11 7 4 1489453 87 CAGAAAATGG NORF12 6 8 115655 279 TGACATTCTT NORF13 6 16 883669 183 TAGACATCTA NORF14 6 2 491117 141 IX) TGCCCTGGCC NORF15 5 5 166452 216 GG I 1 1 I GGCG NORF16 4 3 24169 291 CCATACAGGT NORF17 4 12 673851 114 CCAAATCAAA NORF18 3 4 229494 258 AAGCGGTACT NORF19 3 9 47889 399 AACGC 1 1 1 1 C NORF20 3 2 351456 198 GAGGATAGAG NORF21 3 2 356201 240 CAATGAACCG NORF22 3 16 75541 243 TCTTTATATA NORF23 3 1 73363 90 CGCCTCCAGT NORF24 3 7 485774 108 TACGTAAGTT NORF25 3 10 156139 81 GATTTAAACT NORF26 3 15 254749 93 GCGCCTCCAA NORF27 2 5 42622 222 CAATGGCCCA NORF28 2 13 511751 78 TTGAGGAACG NORF29 2 3 154681 264 GCTAAGAACC NORF30 2 4 302607 204 TABLE 4 Additional NORFs GGCGCAATTT TAAGTGATGA 7 593382 2 TTGTTGAATT 10 608373 2 GAAGCAGTAA 3 155607 2 ACATATGTTA 4 916112 2 CCCTACACGG 6 223289 2 GTAATTGGAC 10 392099 2 ATCAGACAAA 14 687272 2 TTATGAAAGA 15 81263 2 ATTCGTTCTA 15 841970 2 AGCAGGAGTT 16 188350 2 TTCTATTAGG 2 418749 2 TGGATTTCAG 4 1224930 2 CAGATATAAT 5 52488 2 CTGTTTTGGG 11 374761 2 CA 1 I I I IAGT 11 508212 2 TTGAAAAGAT 13 104160 2 TAAGCCCATC 13 251273 2 AGCGTCCTCA 15 832420 2 TTTAGTTAAT 2 477623 2 ATGGTAGCCA 3 56961 2 AATTAGACTA 3 162589 2 AGTGACTCTT 4 1490879 2 GGACTATAAG 5 251266 2 AC I I I I I CAG 10 159213 2 GTCATATAGT 13 158765 2 CAACAAAGTG 13 171166 2 GTGGGAAAGG 13 804600 2 TACTTTATAT 16 366449 2 AATACCAGCG 3 175540 GCCTTGTATA 4 372624 GGTACATTCA 5 67152 GATTTCTCTG 5 187462 TAGTTGCTCC 7 317108 GTAAGAAATC 7 836202 CTTGGGCTAT 8 107992 AAATGGTGAT 11 558686 ATCATTTGGG 12 199358 CTGAACTTTA 12 283720 CCAGAAGGAG 13 652873 CCGGTTACTA 15 803663 CGATGAGAAG 15 1004369 AAACCGTCCC 16 199141 TCATTCATAC 2 164728 TATCTTTTTG 4 169784 TTAGAATAAT 4 603508 GTACGCTGTG 5 118089 TATATTAATT 6 64228 GTTCTTGCCT 7 939579 ATATAGCTGC 10 181144 CCAAAAAAAA 11 91785 GAACTCCACA 11 94125 CCTTCACTGC 11 374172 CACATCATAA 11 625896 GAAGTATTGA 12 603999 TGCGCGTATA 13 206410 GGGTAGTACT 13 671730 TAG 1 1 1 1 GTC 15 33475 CAATTCCTAC 1 172182 0.8 TTTGATTTGA 2 46431 0.8 GGCTCTGGTT 2 414510 0.8 CAGAAATAGC 2 565130 0.8 CTGTTA 1 1 1 1 2 616054 0.8 CGAAGTCAAA 2 680605 0.8 CTCTAGATAA 3 171584 0.8 AGTCAAAATG 4 192750 0.8 GCGAGTTTAG 4 691301 0.8 GCTCCAATAG 4 1131020 0.8 TTTATTTGAG 4 1237501 0.8 GTTATATTGA 4 1401803 0.8 TGGGTTGAAG 5 251266 0.8 A 1 1 1 1 ATTTG 5 447729 0.8 ATCATAAAAA 5 548612 0.8 TTATATAAAA 6 223182 0.8 CTACTTCTGC 8 34653 0.8 ATAAGACAGT 10 227802 0.8 TTCATAAGTT 10 471894 0.8 TAAATCTGAG 11 145617 0.8 CTGGTAGAAA 11 151174 0.8 CACGTACACA 11 403208 0.8 CCAAGATCAA 11 425882 0.8 AGCTTGTTCC 12 234966 0.8 CACATTCGTT 12 759953 0.8 CTTACATATA 12 789781 0.8 TCTATAGCAA 13 228936 0.8 CCTTTCTGAA 13 297985 0.8 CCTTTAGAAT 13 777999 0.8 AATTAACACC 13 842122 0.8 GCGCAGGGGC 14 440984 0.8 TGTTTATAAA 14 661710 0.8 AAAAGTCATT 15 32081 0.8 TTCGTAAACT 15 680625 0.8 TTTTTGGAGT 15 888343 0.8 AGGCATCTTG 16 250284 0.8 AAATCAAAAC 16 453890 0.8 AATTGACGAA 16 560169 0.8 TTGATGA 1 1 1 16 582360 0.8 CCTGTTTTTG 16 643476 0.8 TTTTTAAAAA 1 101436 0.5 AAGTTTGATC 1 199848 0.5 AGCACCTATG 2 46913 0.5 TGATTTATCC 2 418946 0.5 ACTGCATCTG 2 680860 0.5 CAAGTTAGGA 2 744770 0.5 ATACCCAATT 3 29939 0.5 AACTTTGTAT 3 30056 0.5 GCGGCGGGTG 3 41645 0.5 AAAATTGTTC 3 57108 0.5 TCAAGTACTC 3 157855 0.5 AACTGTATGC 3 223882 0.5 CTATCGGCCA 3 278840 0.5 ACAAGCCCAA 3 289917 0.5 GTACAGGGCT 4 93873 0.5 AAGATCATCG 4 254851 0.5 GAACTCCTGG 4 340891 0.5 GAACGAGAAG 4 371850 0.5 1 1 1 1 1 AATAC 4 372058 0.5 TCTCCAGTTG 4 381712 0.5 AATACGTTAC 4 471791 0.5 ACGATTGGCT 4 509158 0.5 TGTTTATAAG 4 521709 0.5 CG 1 1 1 1 CGTC 4 538839 0.5 TCGAACCTCT 4 578702 0.5 TCCACACACA 4 930972 0.5 CCGTGCGTGC 4 1324367 0.5 TTTCTTCAAC 5 116099 0.5 CCAAGTCTCG 5 159320 0.5 AGAGCGAATT 5 207517 0.5 TGTAGATTAT 5 280465 0.5 AAAAGTAGTT 5 286387 0.5 ACTTGGTATG 5 422942 0.5 TTAATGTTAT 5 544523 0.5 TACACGCGCG 5 544555 0.5 GGTCACTCCT 6 62983 0.5 AAGTGATGAA 6 76141 0.5 TTTATCTTGT 6 130327 0.5 AGTGATTGTT 6 256223 0.5 GCTTTGTTGT 7 72577 0.5 TCATTGATTC 7 110590 0.5 TTCACCGGAA 7 323655 0.5 ACTATTCTGT 7 423957 0.5 GGGCCAACCC 7 433787 0.5 AAAATATCTT 7 559397 0.5 TAGTAGTAAC 7 622201 0.5 AAGCGCACAA 7 735909 0.5 TCGCTGTTTT 7 800300 0.5 TGTATTTTTG 7 836202 0.5 CTAAACAAAG 7 836587 0.5 TAGGAAGAAA 7 905046 0.5 GGAAAAATTA 7 958839 0.5 TTTGGATAGT 7 974754 0.5 CGTTTGTGTA 8 202655 0.5 AGAAAAAAAC 8 386651 0.5 TAAAGTCCAG 8 518998 0.5 TAAGCAGATT 8 529129 0.5 ATGAGCATTT 9 97114 0.5 AGGTGCAAAA 9 229077 0.5 TAACAAAGAG 10 628227 0.5 CAATTGGCAA 10 721781 0.5 ACTCCCTGTA 11 93528 0.5 CTCTATTGAT 11 144281 0.5 GCTTTCCTTT 11 146665 0.5 ACCGCAAAGA 11 231872 0.5 CTTGTTCAAA 12 230972 0.5 AATGTGCTGT 12 320426 0.5 GCAGATAGCG 12 341324 0.5 TCTGACTTAG 12 368780 0.5 CCCGGATGTT 12 433912 0.5 GTAACGATTG 12 449917 0.5 GAATAACGAA 12 673851 0.5 ACTGCTATTT 12 712476 0.5 GTTCTCTAGC 12 712712 0.5 CATCACCATC 12 794710 0.5 TTGCACTTCT 12 806833 0.5 ACTGTTTATG 12 867350 0.5 TTGCTATATA 12 1017911 0.5 TACATTCTAA 13 95707 0.5 CTCTTAGTTG 13 158970 0.5 ACGAACACTT 13 278341 0.5 TGCGCAAGTC 13 283795 0.5 1 1 1 1 1 CTTAA 13 363037 0.5 CAAATGCATT 13 390802 0.5 CAAATTGTGT 13 395599 0.5 GCAATACTAT 13 826521 0.5 AGTGACGATG 14 60143 0.5 TACTGGTTTA 14 118854 0.5 GTTTGACCTA 14 335512 0.5 AGCGTTTGAT 14 478481 0.5 CTCTGTTGCG 14 728251 0.5 AAATTCAAAA 15 35952 0.5 TTTGCTTGGT 15 242742 0.5 AGTTTTCCTG 15 304813 0.5 1 1 1 AAAGATA 15 331453 0.5 AAGGAGACAC 15 448624 0.5 CTATATATCA 15 544530 0.5 GATGGAATAG 15 571210 0.5 TCGAGTCGAA 15 758202 0.5 AAAAAAGAAA 15 882567 0.5 TTTCCAGAAT 15 969884 0.5 TGGACAATGT 15 970607 0.5 GGAATTAAGA 15 979894 0.5 ACTATATGTT 16 582230 0.5 GATATATCAT 16 589647 0.5 AGAATTGATT 16 744406 0.5 CACTGTCTCC 16 824649 0.5 References Archer, J. 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Claims: CLAIMS 1. An isolated DNA molecule comprising a yeast gene which is involved in cell cycle progression selected from the group of NORF genes identified in Tables 3 and 4. 2. The isolated DNA molecule of claim 1 wherein expression of the NORF gene varies by at least 10% between any two phases of the cell cycle selected from the group consisting of: log phase, S phase, and G2/M. 3. The isolated DNA molecule of claim 1 wherein expression of the NORF gene varies by at least 25% between any two phases of the cell cycle selected from the group consisting of: log phase, S phase, and G2/M. 4. The isolated DNA molecule of claim 1 wherein expression of the NORF gene varies by at least 50% between any two phases of the cell cycle selected from the group consisting of: log phase, S phase, and G2 M. 5. The isolated DNA molecule of claim 1 wherein expression of the NORF gene varies by at least 100% between any two phases of the cell cycle selected from the group consisting of: log phase, S phase, and G2/M. 6. The isolated DNA molecule of claim 1 wherein expression of the NORF gene varies by a statistically significant difference (greater than 95% confidence level) between any two phases of the cell cycle selected from the group consisting of: log phase, S phase, and G2/M. 7. The isolated DNA molecule of claim 6 wherein the NORF is selected from the group consisting of NORF N a 1, 2, 4, 5, 6, 17, 25, and 27. 8. The isolated DNA molecule of claim 1 wherein the NORF gene is not expressed in at least one phase of the cell cycle selected from the group consisting of: log phase, S phase, and G2/M. 9. The isolated DNA molecule of claim 1 which is genomic. 10. The isolated DNA molecule of claim 1 which is cDNA. 11. A method of using yeast genes to affect the cell cycle, comprising the step of: administering to a cell an isolated DNA molecule comprising a yeast gene which is involved in cell cycle progression selected from the differentially expressed genes identified in Tables 1, 2, 3, and 4. 12. The method of claim 11 wherein the cell is a yeast cell. 13. The method of claim 11 wherein the cell is a fungal cell. 14. The method of claim 11 wherein the cell is a mammalian cell. 15. The method of claim 11 wherein the yeast gene is selected from the group consisting of NORF N β 1, 2, 4, 5, 6, 17, 25, and 27. 16. The method of claim 11 wherein the yeast gene is selected from the group consisting of: TEF1/TEF2, EN02, ADH1, ADH2, PGK1, CUP 1 A/CUP IB, and PYK1. 17. The method of claim 11 wherein the yeast gene is selected from the group consisting of: YKL056C, YMR116C, YEL033W, YOR182C, YCR013C, and YJR085C. 18. A method for screening candidate antifungal drugs, comprising the steps of: contacting a test substance with a yeast cell; monitoring expression of a yeast gene which is involved in cell cycle progression selected from the group of yeast genes identified in Tables 1, 2, 3, and 4, wherein a test substance which modifies the expression of the yeast gene is a candidate antifungal drug. 19. The method of claim 18 wherein the yeast gene is selected from the group consisting of NORF N e 1, 2, 4, 5, 6, 17, 25, and 27. 20. The method of claim 18 wherein the yeast gene is selected from the group consisting of: TEF1/TEF2, EN02, ADH1, ADH2, PGK1, CUP1A/CUP1B, and PYKl. 21. The method of claim 18 wherein the yeast gene is selected from the group consisting of: YKL056C, YMR116C, YEL033W, YOR182C, YCR013C, and YJR085C. 22. A method for identifying human genes which are involved in cell cycle progression, comprising the steps of: hybridizing a probe comprising at least 10 contiguous nucleotides of a yeast gene which is differentially expressed between at least two phases selected from the group consisting of log phase, S phase, and G2/M phase, wherein the yeast gene is identified in Table 1, 2, 3, or 4. 23. The method of claim 22 wherein the yeast gene is selected from the group consisting of NORF N B 1, 2, 4, 5, 6, 17, 25, and 27. 24. The method of claim 22 wherein the yeast gene is selected from the group consisting of: TEF1/TEF2, EN02, ADH1, ADH2, PGK1, CUPIA/CUPIB, and PYKl. 25. The method of claim 22 wherein the yeast gene is selected from the group consisting of: YKL056C, YMR116C, YEL033W, YOR182C, YCR013C, and YJR085C. 26. A probe for ascertaining phase in the cell cycle of a cell, wherein the probe comprises at least 14 contiguous nucleotides of a NORF gene as identified in Table 3 or 4. 27. The probe of claim 26 wherein expression of the NORF gene varies by at least 10% between any two phases of the cell cycle selected from the group consisting of: log phase, S phase, and G2 M. 28. The probe of claim 26 wherein expression of the NORF gene varies by at least 25% between any two phases of the cell cycle selected from the group consisting of: log phase, S phase, and G2/M. 29. The probe of claim 26 wherein expression of the NORF gene varies by at least 50% between any two phases of the cell cycle selected from the group consisting of: log phase, S phase, and G2 M. 30. The probe of claim 26 wherein expression of the NORF gene varies by at least 100% between any two phases of the cell cycle selected from the group consisting of: log phase, S phase, and G2/M. 31. The probe of claim 26 wherein the NORF gene is not expressed in at least one phase of the cell cycle selected from the group consisting of: log phase, S phase, and G2 M. 32. The probe of claim 26 wherein expression of the NORF gene varies by a statistically significant difference (greater than 95% confidence level) between any two phases of the cell cycle selected from the group consisting of: log phase, S phase, and G2 M. 33. The probe of claim 32 wherein the gene is selected from the group consisting of NORF N β 1, 2, 4, 5, 6, 17, 25, and 27. 34. The method of claim 18 wherein said step of monitoring expression is performed using nucleic acid molecules which are immobilized on a solid support. 35. The method of claim 34 wherein the nucleic acid molecules are in on array. 36. The method of claim 19 wherein a probe which comprises a portion of said yeast gene is in an array on a solid support. 37. An array of probes on a solid support wherein at least one probe comprises at least 14 contiguous nucleotides of a NORF gene as identified in Table 3 or 4. 38. The array of claim 37 wherein the NORF gene is selected from the group consisting of NORF No. 1 2, 4, 5, 6, 17, 25, and 27. 39. The array of claim 37 which comprises at least 100 probes of distinct sequence . 40. The array of claim 37 which comprises at least 500 probes of distinct sequence. 41. The array of claim 37 which comprises at least 1,000 probes of distinct sequence.

Inventors: KINZLER KENNETH W, VELCULESCU VICTOR E, VOGELSTEIN BERT, KINZLER, KENNETH, W., VELCULESCU, VICTOR, E., VOGELSTEIN, BERT
Applicants: UNIV JOHNS HOPKINS MED, THE JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE
Application year: 1998
Main classification: C12N15
IPC codes: C07K14, C12N15, C12Q1, C12R1