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Functional analysis of the yeast genome
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Functional analysis of the yeast genome Elizabeth A Winzeler* and Ronald W Davist The release of the complete genome sequence of the yeast Saccharomyces cerevisiae has ushered in a new phase of genome research in which sequence function will be assigned. The goal is to determine the biological function of each of the >6,000 open reading frames in the yeast genome. Innovative approaches have been developed that exploit the sequence data and yield information about gene expression levels, protein levels, subcellular localization and gene function for the entire genome.
Addresses Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305-5307, USA *e-mail: [email protected] te-mail: [email protected] Current Opinion in Genetics & Development 1997, 7:771-776 http://biomednet.com/elecref/095943?X00700771 © Current Biology Ltd ISSN 0959-437X Abbreviations ORF open reading frame SAGE serial analysis of gene expression
Introduction T h e yeast genome consists of 13,389kb and encodes -6,000 predicted open reading frames (ORFs) [1°,2°°]. T h o u g h analysts have assigned a function to many of the proteins encoded by the predicted ORFs [1",2°'], there is clearly a need for further experimental development. As of July 1997, biological data had been collected for only -46% of the predicted proteins. Although the function of another 22% can be inferred on the basis of homology to other experimentally characterized proteins, the role of 32% remains obscure [3"]. Determining the function of these uncharacterized ORFs would greatly benefit the larger biomedical community: yeast is the first eukaryotic organism to have its genome fully sequenced. As of N o v e m b e r 1996, 20% of all positionally-cloned genes mutated in human disease processes arc known to have homologues in yeast [4°]. As the number of sequenced human genes grows, so will the number of yeast genes with human homologues [4°,5]. Yeast is inexpensive to cultivate, can exist in either haploid or a diploid states, and is extremely facile to genetic manipulation. To understand as much as possible about each and every gene encoded by the yeast genome is an essential scientific endeavor. Ambitious projects have been initiated with this end in mind. This review describes recent work devoted to assigning function to the yeast genome. Expression analysis One way to acquire functional information about a genome is to analyze gene expression. Northern blot analysis has
been performed on many of the O R F s in chromosomes III, VI, and XI [6°,7-9]. Although limited data about a transcript's abundance can also be obtained, the chief advantage of Northern analysis is that a transcript's size can be measured. Northerns may also be used to identify new potential O R F s and to uncover genes that encode RNAs which are neither translated nor polyadenylated. Some RNAs cannot, however, be unambiguously assigned to genes and examining expression for all genes with gel-based Nottherns under a larger number of conditions will be difficult. An innovative alternative to Northern blots for measuring transcript abundance is SAGE (serial analysis of gene expression) [10]. In SAGE, polyadenylated R N A is isolated from yeast cells and then, using a series of enzymatic manipulations, each messenger RNA molecule is reduced to an 11 bp c D N A fragment which serves as an identifier. T h e s e small fragments are ligated to one another and the concatenated product is sequenced. By comparing these fragment sequences to the yeast genomic sequence, it is generally possible to assign each fragment to a specific location within the yeast genome. T h e frequency with which each tag appears in the concatenated sequence indicates transcript abundance. Using SAGE, it has been shown that 76% of the O R F s in the yeast genome produce R N A molecules that are detected at least once [11"°]. For this analysis, 60,000 tags were analyzed: 20,000 from cells in GI, 20,000 from cells in S phase, and 20,000 from cells in G 2 phase. T h e method was sensitive enough to detect RNAs that were transcribed at levels of <0.3 copies per cell in yeast [11°°]. Although SAGE depends on the presence of a polyA tail on an RNA, it makes no assumption about what an O R F is and can therefore function as a vehicle for discovering new ORFs. 160 small non-annotated O R F s were identified in the yeast study [11"]. T h e chief disadvantage of SAGE is that a large number of tags need to be sequenced to detect rare R N A molecules. In some cases it can be difficult to assign a tag to an ORF, especially if the tag maps to a region that lies far outside of a predicted O R E Although clearly superior to Northern analysis for assaying global gene expression, it is again difficult to examine a large number of different conditions using SAGE. Array-based hybridization technology offers an efficient way for monitoring gene expression under many conditions (Figure 1). In this massively parallel method, miniature ordered collections of nucleic acid probes are synthesized on [12-14] or attached to [15,16,17 °] a solid surface. T h e s e arrays can contain from 1,000 up to 100,000 single or double-stranded probes ranging in length from 20 to several thousand nucleotides. After labeling with a fluorescent marker, RNA targets are hybridized to the
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array. T h e hybridization signal for a given probe reflects the expression level of the corresponding ORF and the levels of thousands of different ORFs can be monitored simultaneously.
Figure 1
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Alternatively, scientists at Affymetrix Inc. have synthesized probes to the whole yeast genome in high-density oligonucleotide arrays on chemically treated glass slides using a combination of oligonucleotide chemistry and photolithography (DJ Lockhart, L Wodicka, personal communication). These arrays contain 20 or more 25met oligonucleotide probes for every annotated ORF in the yeast genome. These 25mer probes were selected from the sequence of each ORF to be as unique as possible and to have good hybridization properties. When fluorescently-labeled RNA or cDNA is hybridized to the chip, the averaged intensity over all probes is highly reproducible and quantitative [20°°]. Using RNA from yeast grown in rich media, scientists at Affymetrix have detected transcripts for >85% of predicted ORFs, some at levels of one copy per 20 cells (DJ Lockhart, L Wodicka, personal communication).
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Two types of arrays have been used for gene expression analysis in yeast. First, researchers at Stanford University have used the yeast genome sequence and a highly efficient 96-well oligonucleotide synthesizer to generate oligonucleotide primers that permit the amplification of entire coding regions from yeast [18,19"]. T h e amplified ORFs are then placed at defined locations on a microscope slide using a robotic microarraying device [15]. In a preliminary study, 40% of the genome was arrayed and probed with RNA isolated from yeast grown under different conditions [19°°]. Many genes could be classified on the basis of their response to stimuli, such as heat or cold shock. This work has now been extended to
Although these arrays are useful for characterizing patterns of gene expression, they can also be used to probe genome content. Duplications, deletions, recombination hotspots and origins of DNA replication may be identified. Arrays will be the tool of choice for assaying genetic diversity. In the future, the entire yeast genome could be synthesized as a series of oligonucleotides in a high-density array format. Arrays may also become dense enough to allow resequencing of an entire genome in a single hybridization [21"]. The yeast
proteome
Scientists have coined the term 'proteomics' to describe analysis of the combined set of all protein products encoded by an organism's genome [22]. T h e behavior of many of the proteins in the proteome can be monitored using two-dimensional gel electrophoresis [23] in a technique that is, in some ways, analogous to the massively parallel array technology used for characterizing global gene expression. It is estimated that 25% to 35% of the soluble proteins encoded by the yeast genome can be separated and resolved from one another on a polyacrylamide gel on the basis of molecular weight and is•electric point [24,25]. Once the identity of a spot is known, changes in the level of that p r o t e i n - - a s well as post-translational modifications such as phosphorylation or glycosylation--can be monitored on the gel. Prior to the completion of the yeast genome project, however, making the connection between different spots on the gel and cloned yeast genes was difficult and tedious. Now, the availability of the completed genome sequence, plus better software and more sensitive instruments, has greatly accelerated the process of pairing two-dimensional gel spots and yeast genes. Recently, Shevchenko and co-workers [26 °°] assigned unambiguous identities to 150 spots in the yeast proteome using a highly automated procedure. 90% of the spots
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were identified by their tryptic digest peptide-mass spectra alone, though the remainder required partial Edman degradation sequencing using nano-electrospray tandem mass spectrometry for positive identification. Though not all proteins are sufficiently abundant or soluble for resolution on a two-dimensional gel, instrumentation is becoming more sensitive: even femtomole quantities of protein can be identified now by mass-spectrometry [27].
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S u b c e l l u l a r localization The location of a protein in a cell also provides significant information about its possible function. Burns et al. [28] constructed 2,800 yeast strains carrying translational fusions of lacZ to random genes using transposon mutagenesis and then localized the [3-galactosidase fusion proteins using immunofluorescence microscopy. Distinct staining patterns were observed for 68% of the fusion proteins. 10% of fusions were localized to discrete subcellular locations. On the basis of frequency of cells expressing lacZ and assuming random integration, they estimated that 74.2% of the ORFs in yeast are expressed under vegetative growth conditions.
Cre-lox recombination sites and an HA epitope have also been introduced into the transposon mutagenesis cassette [29], allowing the lacZ gene to be excised and, in some cases, to leave behind a detectable epitope-tagged protein. Researchers at Yale University have generated 6,500 additional vegetatively-expressed fusion proteins, covering an estimated 25% of ORFs in the yeast genome and are planning to generate 30,000 for 95% coverage (P Ross-McDonald, M Snyder, personal communication). Localization data can also be obtained by constructing fusions to the green fluorescent protein [30].
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Current Opinion in Genetics & Development
Genomic footprinting for two genes in yeast [38°',39]. (a) Tyl elements are induced to a level where there are five insertions per genome on average. Insertions occur throughout the haploid genome in both essential and non-essential genes. The presence of Tyl in a particular ORF is revealed by performing PCR using one fluorescently labeled primer (A or B) complementary to the region upstream of the ORF (gene X or Y) and another primer complementary to the Tyl element itself. (b) The distribution of PCR products for each primer pair as revealed by gel electrophoresis. (c) After selection and outgrowth for several generations, cells carrying insertions in the essential gene X will disappear from the population. (d) When PCR is repeated after selection using primers A and B, a large number of different-sized products will be observed for the non-essential gene (Y) whereas a footprint will be observed for the essential gene (X).
P r o t e i n - p r o t e i n interactions Like genes, proteins can be classified on the basis of their interaction with other proteins. One effective system for identifying such interaction is the yeast two hybrid system [31]. Ideally, one would like to map interactions between every protein in a genome with every other protein. As a test case, an exhaustive screen for interactors was performed on the bacteriophage T7 genome [32"]. Many known interactions and some novel interactions were detected. More efficient, high-throughput, two-hybrid screens have been developed with the goal of generating a yeast full-genome protein linkage map [33°°]. The use of array-based hybridization technology may speed the identification of positive clones in this case (R Cho, personal communication).
Large-scale deletion and m u t a t i o n a l analysis One of the most effective ways to determine the function of an ORF is to mutate it and then examine the phenotype of the mutant organism. Several studies are underway to systematically provide this type of data for every ORF in
the yeast genome. Deletion strains are easily generated in yeast by targeted homologous recombination using as little as 30bp of sequence homology [34,35] on replacement cassettes generated by PCR [36,37]. Such deletions have been generated for all the genes in chromosome VIII, as well as a large proportion of genes in chromosomes I, V, and XIII (M Johnston, personal communication). Similar mutational data can be obtained without constructing deletion strains. Using an elegant method called genomic footprinting [38°',39], functional data was obtained for each of the 268 ORFs in chromosome V. In genomic footprinting, insertional mutagenesis is performed en masse on a large population of yeast cells by overexpressing the Tyl transposon (Figure 2). After induction of Tyl, the mutagenized yeast cells are outgrown under a variety of selective conditions. The presence and location of a Tyl within a gene is revealed by performing PCR on that ORE In the starting population, a distribution of product sizes is observed, as a result of the fact that Tyl has integrated at multiple points within the gene in the total population. If a gene is essential for growth under
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Current Opinion in Genetics & Development
Deletion analysis in yeast. (a) A deletion cassette is generated by PCR using primers that are homologous to a plasmid-based selectable marker [37] at their 3" ends and flanking yeast sequence from the gene to be targeted at their 5' ends. In addition, one primer contains a 20 bp tag sequence. Each unique tag sequence is flanked by common PCR priming sites. Yeast is transformed with the PCR product resulting in homologous recombination and gene replacement at the targeted ORE (b) Different deletion strains are pooled together. Before selection, genomic DNA is isolated from the pool and the tags are amplified using fluorescently-labeled primers. Then the labeled amplicons are hybridized to high-density oligonucleotide arrays that contain probes complementary to the tags. Hybridization is detected using a modified laser confocal scanning device. (c) The pool of yeast is transferred to selective media and outgrown for eight generations. (d) During selective growth, genomic DNA is isolated from the pool at time points, tags are PCR-amplified and hybridized to the array. (e) Strains unable to survive the selection are identified by a loss of signal at defined locations on the array. As each unique probe location is associated with a different deleted gene, the gene responsible for the phenotype can be identified.
a particular selective condition, or at least contributes to the yeast cell's fitness, the number of cells carrying a Tyl insertion in that gene is reduced. 10% decreases in growth rate can be detected. In the chromosome V study [38°°], 61.6 % of genes showed a detectable phenotype under the seven conditions examined. T h e conditions tested included rich-glucose medium, minimal medium, lactate medium, high-temperature, caffeine, high-salt, and mating. T h e most c o m m o n phenotype observed was decreased growth rate in rich-glucose media, though in many cases the growth patterns were more revealing and specific. This analysis is being extended to the entire yeast genome (B Dunn, personal communication).
One shortcoming of both genomic footprinting and conventional deletion analysis is that a large amount of work is expended for each additional condition examined. Even with four-fold multiplexing of the P C R reactions, genomic footprinting of each new condition entails performing and analyzing the products from 1,500 P C R reactions for each time point. For conventional deletion analysis, each of the 6,000 deletion strains must be re-assayed independently. A method of examining a large number of specific stress conditions is to perform the selections in a large pool of deletion strains. If a unique 20bp tag is introduced into the deletion mutant at the time the mutant is
Functional analysis of the yeast genome Winzeler and Davis
constructed [40"'] (Figure 3), the fraction of a given strain in a population can be measured by PCR-amplifying the tags from genomic DNA and then hybridizing the tags to oligonucleotide arrays bearing the tag-complements as probes. As a demonstration of the efficacy of this approach, Shoemaker eta/. [40"'] have constructed tagged deletion strains for eleven auxotrophic genes. T h e strains were pooled and grown in minimal media containing different supplements. When the medium lacked adenine, the adenine auxotrophs disappeared from the population over time; when tryptophan was omitted, the tryptophan auxotrophs disappeared. This method should be expandable to much larger pools and thus allow rapid phenotypic analysis of deletion strains under exotic stress conditions: a similar method, known as signature tagging, has been used successfully to identify virulence genes in bacteria [41]. A consortium of European and North American laboratories, led by Mark Johnston of Washington University, has been formed to generate tagged deletion strains and, to date, -10% of the ORFs have been deleted. Although significant effort will be devoted to making the deletion strains, it should be possible to analyze the collection under a large variety of different selective conditions, once the collection is made, with little additional effort. If a sufficiently large number of conditions are examined, then there is a greater chance that function will be revealed. In addition, the collection--as well as individual deletion strains--will be available to the larger yeast community for use in countless other experiments.
Conclusions and future directions In addition to the availability of genome sequence data being a benefit to researchers by sparing them the relatively dull tasks of sequencing, mapping and subcloning, the availability also marks a point where researchers will be able to adopt new paradigms in experimental analyses. Researchers may now switch from the analysis of single genetic units to the analysis of a complete system [42"']. For example, scientists will be able to perturb the genome by deleting a single gene and then monitor how expression changes for every other gene in the genome, both at the RNA and protein level. Finally, as much of the functional data will be made available on-line, much more research will be performed over the Internet instead of on the laboratory bench. T h e value of the functional analysis projects described above will ultimately depend on how well the resulting data can be organized and analyzed. If the data is presented well, new biological insights may be obtained from the synthetic analysis of thousands of results obtained in dissimilar experiments.
Note added in proof Two papers of exceptional interest (referred to as J DeRisi, personal communication and DJ Lockhart, L Wodicka,
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personal communication in the text, respectively), describing whole genome transcriptional analysis by hybridisation, have now been published [44"',45"'].
Acknowledgements We thank members of the Davis group for helpful comments on the manuscript and Barbara Dunn, Joe DeRisi, David J Lockhart, Lisa Wodicka, Ray Cho, Petra Ross-MacDonald and Mark Johnston for permission to cite unpublished data. Elizabeth Winzeler was supported by the John Wasmuth Fellowship in genomic analysis (HG00185-01). Yeast genome research in the Davis laboratory is supported by National Institutes of Health grant HGO1633-01.
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Functional analysis of the yeast genome Elizabeth A Winzeler* and Ronald W Davist The release of the complete genome sequence of the yeast Saccharomyces cerevisiae has ushered in a new phase of genome research in which sequence function will be assigned. The goal is to determine the biological function of each of the >6,000 open reading frames in the yeast genome. Innovative approaches have been developed that exploit the sequence data and yield information about gene expression levels, protein levels, subcellular localization and gene function for the entire genome.
Addresses Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305-5307, USA *e-mail: [email protected] te-mail: [email protected] Current Opinion in Genetics & Development 1997, 7:771-776 http://biomednet.com/elecref/095943?X00700771 © Current Biology Ltd ISSN 0959-437X Abbreviations ORF open reading frame SAGE serial analysis of gene expression
Introduction T h e yeast genome consists of 13,389kb and encodes -6,000 predicted open reading frames (ORFs) [1°,2°°]. T h o u g h analysts have assigned a function to many of the proteins encoded by the predicted ORFs [1",2°'], there is clearly a need for further experimental development. As of July 1997, biological data had been collected for only -46% of the predicted proteins. Although the function of another 22% can be inferred on the basis of homology to other experimentally characterized proteins, the role of 32% remains obscure [3"]. Determining the function of these uncharacterized ORFs would greatly benefit the larger biomedical community: yeast is the first eukaryotic organism to have its genome fully sequenced. As of N o v e m b e r 1996, 20% of all positionally-cloned genes mutated in human disease processes arc known to have homologues in yeast [4°]. As the number of sequenced human genes grows, so will the number of yeast genes with human homologues [4°,5]. Yeast is inexpensive to cultivate, can exist in either haploid or a diploid states, and is extremely facile to genetic manipulation. To understand as much as possible about each and every gene encoded by the yeast genome is an essential scientific endeavor. Ambitious projects have been initiated with this end in mind. This review describes recent work devoted to assigning function to the yeast genome. Expression analysis One way to acquire functional information about a genome is to analyze gene expression. Northern blot analysis has
been performed on many of the O R F s in chromosomes III, VI, and XI [6°,7-9]. Although limited data about a transcript's abundance can also be obtained, the chief advantage of Northern analysis is that a transcript's size can be measured. Northerns may also be used to identify new potential O R F s and to uncover genes that encode RNAs which are neither translated nor polyadenylated. Some RNAs cannot, however, be unambiguously assigned to genes and examining expression for all genes with gel-based Nottherns under a larger number of conditions will be difficult. An innovative alternative to Northern blots for measuring transcript abundance is SAGE (serial analysis of gene expression) [10]. In SAGE, polyadenylated R N A is isolated from yeast cells and then, using a series of enzymatic manipulations, each messenger RNA molecule is reduced to an 11 bp c D N A fragment which serves as an identifier. T h e s e small fragments are ligated to one another and the concatenated product is sequenced. By comparing these fragment sequences to the yeast genomic sequence, it is generally possible to assign each fragment to a specific location within the yeast genome. T h e frequency with which each tag appears in the concatenated sequence indicates transcript abundance. Using SAGE, it has been shown that 76% of the O R F s in the yeast genome produce R N A molecules that are detected at least once [11"°]. For this analysis, 60,000 tags were analyzed: 20,000 from cells in GI, 20,000 from cells in S phase, and 20,000 from cells in G 2 phase. T h e method was sensitive enough to detect RNAs that were transcribed at levels of <0.3 copies per cell in yeast [11°°]. Although SAGE depends on the presence of a polyA tail on an RNA, it makes no assumption about what an O R F is and can therefore function as a vehicle for discovering new ORFs. 160 small non-annotated O R F s were identified in the yeast study [11"]. T h e chief disadvantage of SAGE is that a large number of tags need to be sequenced to detect rare R N A molecules. In some cases it can be difficult to assign a tag to an ORF, especially if the tag maps to a region that lies far outside of a predicted O R E Although clearly superior to Northern analysis for assaying global gene expression, it is again difficult to examine a large number of different conditions using SAGE. Array-based hybridization technology offers an efficient way for monitoring gene expression under many conditions (Figure 1). In this massively parallel method, miniature ordered collections of nucleic acid probes are synthesized on [12-14] or attached to [15,16,17 °] a solid surface. T h e s e arrays can contain from 1,000 up to 100,000 single or double-stranded probes ranging in length from 20 to several thousand nucleotides. After labeling with a fluorescent marker, RNA targets are hybridized to the
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array. T h e hybridization signal for a given probe reflects the expression level of the corresponding ORF and the levels of thousands of different ORFs can be monitored simultaneously.
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Alternatively, scientists at Affymetrix Inc. have synthesized probes to the whole yeast genome in high-density oligonucleotide arrays on chemically treated glass slides using a combination of oligonucleotide chemistry and photolithography (DJ Lockhart, L Wodicka, personal communication). These arrays contain 20 or more 25met oligonucleotide probes for every annotated ORF in the yeast genome. These 25mer probes were selected from the sequence of each ORF to be as unique as possible and to have good hybridization properties. When fluorescently-labeled RNA or cDNA is hybridized to the chip, the averaged intensity over all probes is highly reproducible and quantitative [20°°]. Using RNA from yeast grown in rich media, scientists at Affymetrix have detected transcripts for >85% of predicted ORFs, some at levels of one copy per 20 cells (DJ Lockhart, L Wodicka, personal communication).
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Two types of arrays have been used for gene expression analysis in yeast. First, researchers at Stanford University have used the yeast genome sequence and a highly efficient 96-well oligonucleotide synthesizer to generate oligonucleotide primers that permit the amplification of entire coding regions from yeast [18,19"]. T h e amplified ORFs are then placed at defined locations on a microscope slide using a robotic microarraying device [15]. In a preliminary study, 40% of the genome was arrayed and probed with RNA isolated from yeast grown under different conditions [19°°]. Many genes could be classified on the basis of their response to stimuli, such as heat or cold shock. This work has now been extended to
Although these arrays are useful for characterizing patterns of gene expression, they can also be used to probe genome content. Duplications, deletions, recombination hotspots and origins of DNA replication may be identified. Arrays will be the tool of choice for assaying genetic diversity. In the future, the entire yeast genome could be synthesized as a series of oligonucleotides in a high-density array format. Arrays may also become dense enough to allow resequencing of an entire genome in a single hybridization [21"]. The yeast
proteome
Scientists have coined the term 'proteomics' to describe analysis of the combined set of all protein products encoded by an organism's genome [22]. T h e behavior of many of the proteins in the proteome can be monitored using two-dimensional gel electrophoresis [23] in a technique that is, in some ways, analogous to the massively parallel array technology used for characterizing global gene expression. It is estimated that 25% to 35% of the soluble proteins encoded by the yeast genome can be separated and resolved from one another on a polyacrylamide gel on the basis of molecular weight and is•electric point [24,25]. Once the identity of a spot is known, changes in the level of that p r o t e i n - - a s well as post-translational modifications such as phosphorylation or glycosylation--can be monitored on the gel. Prior to the completion of the yeast genome project, however, making the connection between different spots on the gel and cloned yeast genes was difficult and tedious. Now, the availability of the completed genome sequence, plus better software and more sensitive instruments, has greatly accelerated the process of pairing two-dimensional gel spots and yeast genes. Recently, Shevchenko and co-workers [26 °°] assigned unambiguous identities to 150 spots in the yeast proteome using a highly automated procedure. 90% of the spots
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were identified by their tryptic digest peptide-mass spectra alone, though the remainder required partial Edman degradation sequencing using nano-electrospray tandem mass spectrometry for positive identification. Though not all proteins are sufficiently abundant or soluble for resolution on a two-dimensional gel, instrumentation is becoming more sensitive: even femtomole quantities of protein can be identified now by mass-spectrometry [27].
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S u b c e l l u l a r localization The location of a protein in a cell also provides significant information about its possible function. Burns et al. [28] constructed 2,800 yeast strains carrying translational fusions of lacZ to random genes using transposon mutagenesis and then localized the [3-galactosidase fusion proteins using immunofluorescence microscopy. Distinct staining patterns were observed for 68% of the fusion proteins. 10% of fusions were localized to discrete subcellular locations. On the basis of frequency of cells expressing lacZ and assuming random integration, they estimated that 74.2% of the ORFs in yeast are expressed under vegetative growth conditions.
Cre-lox recombination sites and an HA epitope have also been introduced into the transposon mutagenesis cassette [29], allowing the lacZ gene to be excised and, in some cases, to leave behind a detectable epitope-tagged protein. Researchers at Yale University have generated 6,500 additional vegetatively-expressed fusion proteins, covering an estimated 25% of ORFs in the yeast genome and are planning to generate 30,000 for 95% coverage (P Ross-McDonald, M Snyder, personal communication). Localization data can also be obtained by constructing fusions to the green fluorescent protein [30].
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Current Opinion in Genetics & Development
Genomic footprinting for two genes in yeast [38°',39]. (a) Tyl elements are induced to a level where there are five insertions per genome on average. Insertions occur throughout the haploid genome in both essential and non-essential genes. The presence of Tyl in a particular ORF is revealed by performing PCR using one fluorescently labeled primer (A or B) complementary to the region upstream of the ORF (gene X or Y) and another primer complementary to the Tyl element itself. (b) The distribution of PCR products for each primer pair as revealed by gel electrophoresis. (c) After selection and outgrowth for several generations, cells carrying insertions in the essential gene X will disappear from the population. (d) When PCR is repeated after selection using primers A and B, a large number of different-sized products will be observed for the non-essential gene (Y) whereas a footprint will be observed for the essential gene (X).
P r o t e i n - p r o t e i n interactions Like genes, proteins can be classified on the basis of their interaction with other proteins. One effective system for identifying such interaction is the yeast two hybrid system [31]. Ideally, one would like to map interactions between every protein in a genome with every other protein. As a test case, an exhaustive screen for interactors was performed on the bacteriophage T7 genome [32"]. Many known interactions and some novel interactions were detected. More efficient, high-throughput, two-hybrid screens have been developed with the goal of generating a yeast full-genome protein linkage map [33°°]. The use of array-based hybridization technology may speed the identification of positive clones in this case (R Cho, personal communication).
Large-scale deletion and m u t a t i o n a l analysis One of the most effective ways to determine the function of an ORF is to mutate it and then examine the phenotype of the mutant organism. Several studies are underway to systematically provide this type of data for every ORF in
the yeast genome. Deletion strains are easily generated in yeast by targeted homologous recombination using as little as 30bp of sequence homology [34,35] on replacement cassettes generated by PCR [36,37]. Such deletions have been generated for all the genes in chromosome VIII, as well as a large proportion of genes in chromosomes I, V, and XIII (M Johnston, personal communication). Similar mutational data can be obtained without constructing deletion strains. Using an elegant method called genomic footprinting [38°',39], functional data was obtained for each of the 268 ORFs in chromosome V. In genomic footprinting, insertional mutagenesis is performed en masse on a large population of yeast cells by overexpressing the Tyl transposon (Figure 2). After induction of Tyl, the mutagenized yeast cells are outgrown under a variety of selective conditions. The presence and location of a Tyl within a gene is revealed by performing PCR on that ORE In the starting population, a distribution of product sizes is observed, as a result of the fact that Tyl has integrated at multiple points within the gene in the total population. If a gene is essential for growth under
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Current Opinion in Genetics & Development
Deletion analysis in yeast. (a) A deletion cassette is generated by PCR using primers that are homologous to a plasmid-based selectable marker [37] at their 3" ends and flanking yeast sequence from the gene to be targeted at their 5' ends. In addition, one primer contains a 20 bp tag sequence. Each unique tag sequence is flanked by common PCR priming sites. Yeast is transformed with the PCR product resulting in homologous recombination and gene replacement at the targeted ORE (b) Different deletion strains are pooled together. Before selection, genomic DNA is isolated from the pool and the tags are amplified using fluorescently-labeled primers. Then the labeled amplicons are hybridized to high-density oligonucleotide arrays that contain probes complementary to the tags. Hybridization is detected using a modified laser confocal scanning device. (c) The pool of yeast is transferred to selective media and outgrown for eight generations. (d) During selective growth, genomic DNA is isolated from the pool at time points, tags are PCR-amplified and hybridized to the array. (e) Strains unable to survive the selection are identified by a loss of signal at defined locations on the array. As each unique probe location is associated with a different deleted gene, the gene responsible for the phenotype can be identified.
a particular selective condition, or at least contributes to the yeast cell's fitness, the number of cells carrying a Tyl insertion in that gene is reduced. 10% decreases in growth rate can be detected. In the chromosome V study [38°°], 61.6 % of genes showed a detectable phenotype under the seven conditions examined. T h e conditions tested included rich-glucose medium, minimal medium, lactate medium, high-temperature, caffeine, high-salt, and mating. T h e most c o m m o n phenotype observed was decreased growth rate in rich-glucose media, though in many cases the growth patterns were more revealing and specific. This analysis is being extended to the entire yeast genome (B Dunn, personal communication).
One shortcoming of both genomic footprinting and conventional deletion analysis is that a large amount of work is expended for each additional condition examined. Even with four-fold multiplexing of the P C R reactions, genomic footprinting of each new condition entails performing and analyzing the products from 1,500 P C R reactions for each time point. For conventional deletion analysis, each of the 6,000 deletion strains must be re-assayed independently. A method of examining a large number of specific stress conditions is to perform the selections in a large pool of deletion strains. If a unique 20bp tag is introduced into the deletion mutant at the time the mutant is
Functional analysis of the yeast genome Winzeler and Davis
constructed [40"'] (Figure 3), the fraction of a given strain in a population can be measured by PCR-amplifying the tags from genomic DNA and then hybridizing the tags to oligonucleotide arrays bearing the tag-complements as probes. As a demonstration of the efficacy of this approach, Shoemaker eta/. [40"'] have constructed tagged deletion strains for eleven auxotrophic genes. T h e strains were pooled and grown in minimal media containing different supplements. When the medium lacked adenine, the adenine auxotrophs disappeared from the population over time; when tryptophan was omitted, the tryptophan auxotrophs disappeared. This method should be expandable to much larger pools and thus allow rapid phenotypic analysis of deletion strains under exotic stress conditions: a similar method, known as signature tagging, has been used successfully to identify virulence genes in bacteria [41]. A consortium of European and North American laboratories, led by Mark Johnston of Washington University, has been formed to generate tagged deletion strains and, to date, -10% of the ORFs have been deleted. Although significant effort will be devoted to making the deletion strains, it should be possible to analyze the collection under a large variety of different selective conditions, once the collection is made, with little additional effort. If a sufficiently large number of conditions are examined, then there is a greater chance that function will be revealed. In addition, the collection--as well as individual deletion strains--will be available to the larger yeast community for use in countless other experiments.
Conclusions and future directions In addition to the availability of genome sequence data being a benefit to researchers by sparing them the relatively dull tasks of sequencing, mapping and subcloning, the availability also marks a point where researchers will be able to adopt new paradigms in experimental analyses. Researchers may now switch from the analysis of single genetic units to the analysis of a complete system [42"']. For example, scientists will be able to perturb the genome by deleting a single gene and then monitor how expression changes for every other gene in the genome, both at the RNA and protein level. Finally, as much of the functional data will be made available on-line, much more research will be performed over the Internet instead of on the laboratory bench. T h e value of the functional analysis projects described above will ultimately depend on how well the resulting data can be organized and analyzed. If the data is presented well, new biological insights may be obtained from the synthetic analysis of thousands of results obtained in dissimilar experiments.
Note added in proof Two papers of exceptional interest (referred to as J DeRisi, personal communication and DJ Lockhart, L Wodicka,
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personal communication in the text, respectively), describing whole genome transcriptional analysis by hybridisation, have now been published [44"',45"'].
Acknowledgements We thank members of the Davis group for helpful comments on the manuscript and Barbara Dunn, Joe DeRisi, David J Lockhart, Lisa Wodicka, Ray Cho, Petra Ross-MacDonald and Mark Johnston for permission to cite unpublished data. Elizabeth Winzeler was supported by the John Wasmuth Fellowship in genomic analysis (HG00185-01). Yeast genome research in the Davis laboratory is supported by National Institutes of Health grant HGO1633-01.
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