Valerie Wood

The Gene Ontology (GO) database and informatics resource.

The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.

Dynamic repertoire of a eukaryotic transcriptome surveyed at single-nucleotide resolution

Recent data from several organisms indicate that the transcribed portions of genomes are larger and more complex than expected, and that many functional properties of transcripts are based not on coding sequences but on regulatory sequences in untranslated regions or non-coding RNAs. Alternative start and polyadenylation sites and regulation of intron splicing add additional dimensions to the rich transcriptional output. This transcriptional complexity has been sampled mainly using hybridization-based methods under one or few experimental conditions. Here we applied direct high-throughput sequencing of complementary DNAs (RNA-Seq), supplemented with data from high-density tiling arrays, to globally sample transcripts of the fission yeast Schizosaccharomyces pombe, independently from available gene annotations. We interrogated transcriptomes under multiple conditions, including rapid proliferation, meiotic differentiation and environmental stress, as well as in RNA processing mutants to reveal the dynamic plasticity of the transcriptional landscape as a function of environmental, developmental and genetic factors. High-throughput sequencing proved to be a powerful and quantitative method to sample transcriptomes deeply at maximal resolution. In contrast to hybridization, sequencing showed little, if any, background noise and was sensitive enough to detect widespread transcription in >90% of the genome, including traces of RNAs that were not robustly transcribed or rapidly degraded. The combined sequencing and strand-specific array data provide rich condition-specific information on novel, mostly non-coding transcripts, untranslated regions and gene structures, thus improving the existing genome annotation. Sequence reads spanning exon–exon or exon–intron junctions give unique insight into a surprising variability in splicing efficiency across introns, genes and conditions. Splicing efficiency was largely coordinated with transcript levels, and increased transcription led to increased splicing in test genes. Hundreds of introns showed such regulated splicing during cellular proliferation or differentiation.

The Gene Ontology project in 2008

The Gene Ontology (GO) project (http://www.geneontology.org/) provides a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://www.sequenceontology.org/). The ontologies have been extended and refined for several biological areas, and improvements to the structure of the ontologies have been implemented. To improve the quantity and quality of gene product annotations available from its public repository, the GO Consortium has launched a focused effort to provide comprehensive and detailed annotation of orthologous genes across a number of ‘reference’ genomes, including human and several key model organisms. Software developments include two releases of the ontology-editing tool OBO-Edit, and improvements to the AmiGO browser interface.

Analysis of a genome-wide set of gene deletions in the fission yeast Schizosaccharomyces pombe.

We report the construction and analysis of 4,836 heterozygous diploid deletion mutants covering 98.4% of the fission yeast genome providing a tool for studying eukaryotic biology. Comprehensive gene dispensability comparisons with budding yeast—the only other eukaryote for which a comprehensive knockout library exists—revealed that 83% of single-copy orthologs in the two yeasts had conserved dispensability. Gene dispensability differed for certain pathways between the two yeasts, including mitochondrial translation and cell cycle checkpoint control. We show that fission yeast has more essential genes than budding yeast and that essential genes are more likely than nonessential genes to be present in a single copy, to be broadly conserved and to contain introns. Growth fitness analyses determined sets of haploinsufficient and haploproficient genes for fission yeast, and comparisons with budding yeast identified specific ribosomal proteins and RNA polymerase subunits, which may act more generally to regulate eukaryotic cell growth.

Use and misuse of the gene ontology annotations

The Gene Ontology (GO) project is a collaboration among model organism databases to describe gene products from all organisms using a consistent and computable language. GO produces sets of explicitly defined, structured vocabularies that describe biological processes, molecular functions and cellular components of gene products in both a computer- and human-readable manner. Here we describe key aspects of GO, which, when overlooked, can cause erroneous results, and address how these pitfalls can be avoided.

GeneDB: a resource for prokaryotic and eukaryotic organisms

GeneDB (http://www.genedb.org/) is a genome database for prokaryotic and eukaryotic organisms. The resource provides a portal through which data generated by the Pathogen Sequencing Unit at the Wellcome Trust Sanger Institute and other collaborating sequencing centres can be made publicly available. It combines data from finished and ongoing genome and expressed sequence tag (EST) projects with curated annotation, that can be searched, sorted and downloaded, using a single web based resource. The current release stores 11 datasets of which six are curated and maintained by biologists, who review and incorporate information from the scientific literature, public databases and the respective research communities.

PomBase: a comprehensive online resource for fission yeast

PomBase (www.pombase.org) is a new model organism database established to provide access to comprehensive, accurate, and up-to-date molecular data and biological information for the fission yeast Schizosaccharomyces pombe to effectively support both exploratory and hypothesis-driven research. PomBase encompasses annotation of genomic sequence and features, comprehensive manual literature curation and genome-wide data sets, and supports sophisticated user-defined queries. The implementation of PomBase integrates a Chado relational database that houses manually curated data with Ensembl software that supports sequence-based annotation and web access. PomBase will provide user-friendly tools to promote curation by experts within the fission yeast community. This will make a key contribution to shaping its content and ensuring its comprehensiveness and long-term relevance.

The Gene Ontology's Reference Genome Project: A Unified Framework for Functional Annotation across Species

The Gene Ontology (GO) is a collaborative effort that provides structured vocabularies for annotating the molecular function, biological role, and cellular location of gene products in a highly systematic way and in a species-neutral manner with the aim of unifying the representation of gene function across different organisms. Each contributing member of the GO Consortium independently associates GO terms to gene products from the organism(s) they are annotating. Here we introduce the Reference Genome project, which brings together those independent efforts into a unified framework based on the evolutionary relationships between genes in these different organisms. The Reference Genome project has two primary goals: to increase the depth and breadth of annotations for genes in each of the organisms in the project, and to create data sets and tools that enable other genome annotation efforts to infer GO annotations for homologous genes in their organisms. In addition, the project has several important incidental benefits, such as increasing annotation consistency across genome databases, and providing important improvements to the GOs logical structure and biological content.

A Re-Annotation of the Saccharomyces cerevisiae Genome

Discrepancies in gene and orphan number indicated by previous analyses suggest that S. cerevisiae would benefit from a consistent re-annotation. In this analysis three new genes are identified and 46 alterations to gene coordinates are described. 370 ORFs are defined as totally spurious ORFs which should be disregarded. At least a further 193 genes could be described as very hypothetical, based on a number of criteria. It was found that disparate genes with sequence overlaps over ten amino acids (especially at the N-terminus) are rare in both S. cerevisiae and Sz. pombe. A new S. cerevisiae gene number estimate with an upper limit of 5804 is proposed, but after the removal of very hypothetical genes and pseudogenes this is reduced to 5570. Although this is likely to be closer to the true upper limit, it is still predicted to be an overestimate of gene number. A complete list of revised gene coordinates is available from the Sanger Centre (S. cerevisiae reannotation: ftp://ftp/pub/yeast/SCreannotation).

On the Use of Gene Ontology Annotations to Assess Functional Similarity among Orthologs and Paralogs: A Short Report

A recent paper (Nehrt et al., PLoS Comput. Biol. 7:e1002073, 2011) has proposed a metric for the “functional similarity” between two genes that uses only the Gene Ontology (GO) annotations directly derived from published experimental results. Applying this metric, the authors concluded that paralogous genes within the mouse genome or the human genome are more functionally similar on average than orthologous genes between these genomes, an unexpected result with broad implications if true. We suggest, based on both theoretical and empirical considerations, that this proposed metric should not be interpreted as a functional similarity, and therefore cannot be used to support any conclusions about the “ortholog conjecture” (or, more properly, the “ortholog functional conservation hypothesis”). First, we reexamine the case studies presented by Nehrt et al. as examples of orthologs with divergent functions, and come to a very different conclusion: they actually exemplify how GO annotations for orthologous genes provide complementary information about conserved biological functions. We then show that there is a global ascertainment bias in the experiment-based GO annotations for human and mouse genes: particular types of experiments tend to be performed in different model organisms. We conclude that the reported statistical differences in annotations between pairs of orthologous genes do not reflect differences in biological function, but rather complementarity in experimental approaches. Our results underscore two general considerations for researchers proposing novel types of analysis based on the GO: 1) that GO annotations are often incomplete, potentially in a biased manner, and subject to an “open world assumption” (absence of an annotation does not imply absence of a function), and 2) that conclusions drawn from a novel, large-scale GO analysis should whenever possible be supported by careful, in-depth examination of examples, to help ensure the conclusions have a justifiable biological basis.