A robust toolkit for functional profiling of the yeast genome

Study of mutant phenotypes is a fundamental method for understanding gene function. The construction of a near-complete collection of yeast knockouts (YKO) and the unique molecular barcodes (or TAGs) that identify each strain has enabled quantitative functional profiling of Saccharomyces cerevisiae. By using these TAGs and the SGA reporter, MFA1pr-HIS3, which facilitates conversion of heterozygous diploid YKO strains into haploid mutants, we have developed a set of highly efficient microarray-based techniques, collectively referred as dSLAM (diploid-based synthetic lethality analysis on microarrays), to probe genome-wide gene-chemical and gene-gene interactions. Direct comparison revealed that these techniques are more robust than existing methods in functional profiling of the yeast genome. Widespread application of these tools will elucidate a comprehensive yeast genetic network.     

Large Scale Identification of Genes Involved in Cell Surface Biosynthesis and Architecture in Saccharomyces Cerevisiae

The sequenced yeast genome offers a unique resource for the analysis of eukaryotic cell function and enables genome-wide screens for genes involved in cellular processes. We have identified genes involved in cell surface assembly by screening transposon-mutagenized cells for altered sensitivity to calcofluor white, followed by supplementary screens to further characterize mutant phenotypes. The mutated genes were directly retrieved from genomic DNA and then matched uniquely to a gene in the yeast genome database. Eighty-two genes with apparent perturbation of the cell surface were identified, with mutations in 65 of them displaying at least one further cell surface phenotype in addition to their modified sensitivity to calcofluor. Fifty of these genes were previously known, 17 encoded proteins whose function could be anticipated through sequence homology or previously recognized phenotypes and 15 genes had no previously known phenotype.     

Improved statistical analysis of budding yeast TAG microarrays revealed by defined spike-in pools

Saccharomyces cerevisiae knockout collection TAG microarrays are an emergent platform for rapid, genome-wide functional characterization of yeast genes. TAG arrays report abundance of unique oligonucleotide ‘TAG’ sequences incorporated into each deletion mutation of the yeast knockout collection, allowing measurement of relative strain representation across experimental conditions for all knockout mutants simultaneously. One application of TAG arrays is to perform genome-wide synthetic lethality screens, known as synthetic lethality analyzed by microarray (SLAM). We designed a fully defined spike-in pool to resemble typical SLAM experiments and performed TAG microarray hybridizations. We describe a method for analyzing two-color array data to efficiently measure the differential knockout strain representation across two experimental conditions, and use the spike-in pool to show that the sensitivity and specificity of this method exceed typical current approaches.     

Identification of evolutionarily conserved genetic regulators of cellular aging

To identify new genetic regulators of cellular aging and senescence, we performed genome-wide comparative RNA profiling with selected human cellular model systems, reflecting replicative senescence, stress-induced premature senescence, and distinct other forms of cellular aging. Gene expression profiles were measured, analyzed, and entered into a newly generated database referred to as the GiSAO database. Bioinformatic analysis revealed a set of new candidate genes, conserved across the majority of the cellular aging models, which were so far not associated with cellular aging, and highlighted several new pathways that potentially play a role in cellular aging. Several candidate genes obtained through this analysis have been confirmed by functional experiments, thereby validating the experimental approach. The effect of genetic deletion on chronological lifespan in yeast was assessed for 93 genes where (i) functional homologues were found in the yeast genome and (ii) the deletion strain was viable. We identified several genes whose deletion led to significant changes of chronological lifespan in yeast, featuring both lifespan shortening and lifespan extension. In conclusion, an unbiased screen across species uncovered several so far unrecognized molecular pathways for cellular aging that are conserved in evolution.     

Broad network-based predictability of <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis>gene loss-of-function phenotypes

We demonstrate that loss-of-function yeast phenotypes are predictable by guilt-by-association in functional gene networks. Testing 1,102 loss-of-function phenotypes from genome-wide assays of yeast reveals predictability of diverse phenotypes, spanning cellular morphology, growth, metabolism, and quantitative cell shape features. We apply the method to extend a genome-wide screen by predicting, then verifying, genes whose disruption elongates yeast cells, and to predict human disease genes. To facilitate network-guided screens, a web server is available .     

Genome-wide high-throughput screens in functional genomics

The availability of complete genome sequences from many organisms has yielded the ability to perform high-throughput, genome-wide screens of gene function. Within the past year, rapid advances have been made towards this goal in many major model systems, including yeast, worms, flies, and mammals. Yeast genome-wide screens have taken advantage of libraries of deletion strains, but RNA-interference has been used in other organisms to knockdown gene function. Examples of recent large-scale functional genetic screens include drug-target identification in yeast, regulators of fat accumulation in worms, growth and viability in flies, and proteasome-mediated degradation in mammalian cells. Within the next five years, such screens are likely to lead to annotation of function of most genes across multiple organisms. Integration of such data with other genomic approaches will extend our understanding of cellular networks.     

Global synthetic-lethality analysis and yeast functional profiling

The Saccharomyces genome-deletion project created >5900 'molecularly barcoded' yeast knockout mutants (YKO mutants). The YKO mutant collections have facilitated large-scale analyses of a multitude of mutant phenotypes. For example, both synthetic genetic array (SGA) and synthetic-lethality analysis by microarray (SLAM) methods have been used for synthetic-lethality screens. Global analysis of synthetic lethality promises to identify cellular pathways that 'buffer' each other biologically. The combination of global synthetic-lethality analysis, together with global protein-protein interaction analyses, mRNA expression profiling and functional profiling will, in principle, enable construction of a cellular 'wiring diagram' that will help frame a deeper understanding of human biology and disease.     

Comprehensive phenotypic analysis for identification of genes affecting growth under ethanol stress in Saccharomyces cerevisiae

We quantified the growth behavior of all available single gene deletion strains of budding yeast under ethanol stress. Genome-wide analyses enabled the extraction of the genes and determination of the functional categories required for growth under this condition. Statistical analyses revealed that the growth of 446 deletion strains under stress induced by 8% ethanol was defective. We classified these deleted genes into known functional categories, and found that many were important for growth under ethanol stress including several categories that have not been characterized, such as peroxisome. We also performed genome-wide screening under osmotic stress and identified 329 osmotic-sensitive strains. We excluded these strains from the 446 ethanol-sensitive strains to extract the genes whose deletion caused sensitivity to ethanol-specific (359 genes), osmotic-specific (242 genes), and both stresses (87 genes). We also extracted the functional categories that are specifically important for growth under ethanol stress. The genes and functional categories identified in the analysis might provide clues to improving ethanol stress tolerance among yeast cells.     

Large-scale analysis of yeast filamentous growth by systematic gene disruption and overexpression

Under certain conditions of nutrient stress, the budding yeast Saccharomyces cerevisiae initiates a striking developmental transition to a filamentous form of growth, resembling developmental transitions required for virulence in closely related pathogenic fungi. In yeast, filamentous growth involves known mitogen-activated protein kinase and protein kinase A signaling modules, but the full scope of this extensive filamentous response has not been delineated. Accordingly, we have undertaken the first systematic gene disruption and overexpression analysis of yeast filamentous growth. Standard laboratory strains of yeast are nonfilamentous; thus, we constructed a unique set of reagents in the filamentous Σ1278b strain, encompassing 3627 integrated transposon insertion alleles and 2043 overexpression constructs. Collectively, we analyzed 4528 yeast genes with these reagents and identified 487 genes conferring mutant filamentous phenotypes upon transposon insertion and/or gene overexpression. Using a fluorescent protein reporter integrated at the MUC1 locus, we further assayed each filamentous growth mutant for aberrant protein levels of the key flocculence factor Muc1p. Our results indicate a variety of genes and pathways affecting filamentous growth. In total, this filamentous growth gene set represents a wealth of yeast biology, highlighting 84 genes of uncharacterized function and an underappreciated role for the mitochondrial retrograde signaling pathway as an inhibitor of filamentous growth.     

Genome-wide screening for gene function using RNAi in mammalian cells

Mammalian genome sequencing has identified numerous genes requiring functional annotation. The discovery that dsRNA can direct gene-specific silencing in both model organisms and mammalian cells through RNA interference (RNAi) has provided a platform for dissecting the function of independent genes. The generation of large-scale RNAi libraries targeting all predicted genes within mouse, rat and human cells, combined with the large number of cell-based assays, provides a unique opportunity to perform high-throughput genetics in these complex cell systems. Many different formats exist for the generation of genome-wide RNAi libraries for use in mammalian cells. Furthermore, the use of these libraries in either genetic screens or genetic selections allows for the identification of known and novel genes involved in complex cellular phenotypes and biological processes, some of which underpin human disease. In this review, we examine genome-wide RNAi libraries used in model organisms and mammalian cells and provide examples of how these information rich reagents can be used for determining gene function, discovering novel therapeutic targets and dissecting signalling pathways, cellular processes and complex phenotypes.     

High-throughput RNAi in Caenorhabditis elegans: genome-wide screens and functional genomics

The phenomenon of RNA-mediated interference (RNAi) was first discovered in the nematode Caenorhabditis elegans, in which introduction of double-stranded RNA causes specific inactivation of genes with corresponding sequences. Technical advances in RNAi methodology and the availability of the complete genome sequence have enabled the high-throughput, genome-wide RNAi analysis of this organism. Several groups have used large-scale RNAi to systematically examine every C. elegans gene for knock-down phenotypes, providing basal information to be mined in more detailed studies. Now, in addition to functional genomic RNAi analyses, high-throughput RNAi is also routinely used for rapid, genome-wide screens for genes involved in specific biological processes. The integration of high-throughput RNAi experiments with other large-scale data, such as DNA microarrays and protein-protein interaction maps, enhances the speed and reliability of such screens. The accumulation of RNAi phenotype data dramatically accelerates our understanding of this organism at the genetic level.     

Identification of neural outgrowth genes using genome-wide RNAi

While genetic screens have identified many genes essential for neurite outgrowth, they have been limited in their ability to identify neural genes that also have earlier critical roles in the gastrula, or neural genes for which maternally contributed RNA compensates for gene mutations in the zygote. To address this, we developed methods to screen the Drosophila genome using RNA-interference (RNAi) on primary neural cells and present the results of the first full-genome RNAi screen in neurons. We used live-cell imaging and quantitative image analysis to characterize the morphological phenotypes of fluorescently labelled primary neurons and glia in response to RNAi-mediated gene knockdown. From the full genome screen, we focused our analysis on 104 evolutionarily conserved genes that when downregulated by RNAi, have morphological defects such as reduced axon extension, excessive branching, loss of fasciculation, and blebbing. To assist in the phenotypic analysis of the large data sets, we generated image analysis algorithms that could assess the statistical significance of the mutant phenotypes. The algorithms were essential for the analysis of the thousands of images generated by the screening process and will become a valuable tool for future genome-wide screens in primary neurons. Our analysis revealed unexpected, essential roles in neurite outgrowth for genes representing a wide range of functional categories including signalling molecules, enzymes, channels, receptors, and cytoskeletal proteins. We also found that genes known to be involved in protein and vesicle trafficking showed similar RNAi phenotypes. We confirmed phenotypes of the protein trafficking genes Sec61alpha and Ran GTPase using Drosophila embryo and mouse embryonic cerebral cortical neurons, respectively. Collectively, our results showed that RNAi phenotypes in primary neural culture can parallel in vivo phenotypes, and the screening technique can be used to identify many new genes that have important functions in the nervous system.     

Yeast-based functional genomics and proteomics technologies: the first 15 years and beyond

Yeast-based functional genomics and proteomics technologies developed over the past decade have contributed greatly to our understanding of bacterial, yeast, fly, worm, and human gene functions. In this review, we highlight some of these yeast-based functional genomic and proteomic technologies that are advancing the utility of yeast as a model organism in molecular biology and speculate on their future uses. Such technologies include use of the yeast deletion strain collection, large-scale determination of protein localization in vivo, synthetic genetic array analysis, variations of the yeast two-hybrid system, protein microarrays, and tandem affinity purification (TAP)-tagging approaches. The integration of these advances with established technologies is invaluable in the drive toward a comprehensive understanding of protein structure and function in the cellular milieu.     

Genome-wide Introgression Lines and their Use in Genetic and Molecular Dissection of Complex Phenotypes in Rice (Oryza sativa L.)

Tremendous efforts have been taken worldwide to develop genome-wide genetic stocks for rice functional genomic (FG) research since the rice genome was completely sequenced. To facilitate FG research of complex polygenic phenotypes in rice, we report the development of over 20 000 introgression lines (ILs) in three elite rice genetic backgrounds for a wide range of complex traits, including resistances/tolerances to many biotic and abiotic stresses, morpho-agronomic traits, physiological traits, etc., by selective introgression. ILs within each genetic background are phenotypically similar to their recurrent parent but each carries one or a few traits introgressed from a known donor. Together, these ILs contain a significant portion of loci affecting the selected complex phenotypes at which allelic diversity exists in the primary gene pool of rice. A forward genetics strategy was proposed and demonstrated with examples on how to use these ILs for large-scale FG research. Complementary to the genome-wide insertional mutants, these ILs opens a new way for highly efficient discovery, candidate gene identification and cloning of important QTLs for specific phenotypes based on convergent evidence from QTL position, expression profiling, functional and molecular diversity analyses of candidate genes, highlights the importance of genetic networks underlying complex phenotypes in rice that may ultimately lead to more complete understanding of the genetic and molecular bases of quantitative trait variation in rice. Supplementary material to this paper is available in electronic form at http://dx.doi.org/10.1007/s11103-005-8519-3     

The Yeast Deletion Collection: A Decade of Functional Genomics

The yeast deletion collections comprise >21,000 mutant strains that carry precise start-to-stop deletions of ∼6000 open reading frames. This collection includes heterozygous and homozygous diploids, and haploids of both MATa and MATα mating types. The yeast deletion collection, or yeast knockout (YKO) set, represents the first and only complete, systematically constructed deletion collection available for any organism. Conceived during the Saccharomyces cerevisiae sequencing project, work on the project began in 1998 and was completed in 2002. The YKO strains have been used in numerous laboratories in >1000 genome-wide screens. This landmark genome project has inspired development of numerous genome-wide technologies in organisms from yeast to man. Notable spinoff technologies include synthetic genetic array and HIPHOP chemogenomics. In this retrospective, we briefly describe the yeast deletion project and some of its most noteworthy biological contributions and the impact that these collections have had on the yeast research community and on genomics in general.     

Multiple protein tyrosine phosphatase-encoding genes in the yeast Saccharomyces cerevisiae.

In higher eukaryotic organisms, the regulation of tyrosine phosphorylation is known to play a major role in the control of cell division. Recently, a wide variety of protein tyrosine phosphatase (PTPase)-encoding genes (PTPs) have been identified to accompany the many tyrosine kinases previously studied. However, in the yeasts, where the cell cycle has been most extensively studied, identification of the genes involved in the direct regulation of tyrosine phosphorylation has been difficult. We have identified a pair of genes in the yeast Saccharomyces cerevisiae, which we call PTP1 and PTP2, whose products are highly homologous to PTPases identified in other systems. Both genes are poorly expressed, and contain sequence elements consistent with low-abundance proteins. We have carried out an extensive genetic analysis of PTP1 and PTP2, and found that they are not essential either singly or in combination. Neither deletion nor overexpression results in any strong phenotypes in a number of assays. Deletions also do not affect the mitotic blockage caused by deletion of the MIH1 gene (encoding a positive regulator of mitosis) and induction of the heterologous Schizosaccharomyces pombe wee1+ gene (encoding a negative regulator of mitosis). Molecular analysis has shown that PTP1 and PTP2 are quite different structurally and are not especially well conserved at the amino acid sequence level. Low-stringency Southern blots indicate that yeast may contain a family of PTPase-encoding genes. These results suggest that yeast may contain other PTPase-encoding genes that overlap functionally with PTP1 and PTP2.