Determining the effect of gene deletion is a fundamental approach to understanding gene function. Conventional genetic screens exhibit biases, and genes contributing to a phenotype are often missed. We systematically constructed a nearly complete collection of gene-deletion mutants (96% of annotated open reading frames, or ORFs) of the yeast Saccharomyces cerevisiae. DNA sequences dubbed 'molecular bar codes' uniquely identify each strain, enabling their growth to be analysed in parallel and the fitness contribution of each gene to be quantitatively assessed by hybridization to high-density oligonucleotide arrays. We show that previously known and new genes are necessary for optimal growth under six well-studied conditions: high salt, sorbitol, galactose, pH 8, minimal medium and nystatin treatment. Less than 7% of genes that exhibit a significant increase in messenger RNA expression are also required for optimal growth in four of the tested conditions. Our results validate the yeast gene-deletion collection as a valuable resource for functional genomics.

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new ‘phylogenetic annotation’ process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.

A genome-wide screen of 4168 homozygous diploid yeast deletion strains has been performed to identify nonessential genes that participate in the bipolar budding pattern. By examining bud scar patterns representing the sites of previous cell divisions, 127 mutants representing three different phenotypes were found: unipolar, axial-like, and random. From this screen, 11 functional classes of known genes were identified, including those involved in actin-cytoskeleton organization, general bud site selection, cell polarity, vesicular transport, cell wall synthesis, protein modification, transcription, nuclear function, translation, and other functions. Four characterized genes that were not known previously to participate in bud site selection were also found to be important for the haploid axial budding pattern. In addition to known genes, we found 22 novel genes (20 are designated BUD13-BUD32) important for bud site selection. Deletion of one resulted in unipolar budding exclusively from the proximal pole, suggesting that this gene plays an important role in diploid distal budding. Mutations in 20 other novel BUD genes produced a random budding phenotype and one produced an axial-like budding defect. Several of the novel Bud proteins were fused to green fluorescence protein; two proteins were found to localize to sites of polarized cell growth (i.e., the bud tip in small budded cells and the neck in cells undergoing cytokinesis), similar to that postulated for the bipolar signals and proteins that target cell division site tags to their proper location in the cell. Four others localized to the nucleus, suggesting that they play a role in gene expression. The bipolar distal marker Bud8 was localized in a number of mutants; many showed an altered Bud8-green fluorescence protein localization pattern. Through the genome-wide identification and analysis of different mutants involved in bipolar bud site selection, an integrated pathway for this process is presented in which proximal and distal bud site selection tags are synthesized and localized at their appropriate poles, thereby directing growth at those sites. Genome-wide screens of defined collections of mutants hold significant promise for dissecting many biological processes in yeast.

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and non-coding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains and updates the GO knowledgebase. The GO knowledgebase consists of three components: 1) the Gene Ontology – a computational knowledge structure describing functional characteristics of genes; 2) GO annotations – evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and 3) GO Causal Activity Models (GO-CAMs) – mechanistic models of molecular “pathways” (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised and updated in response to newly published discoveries, and receives extensive QA checks, reviews and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, as well as guidance on how users can best make use of the data we provide. We conclude with future directions for the project.