The Gene Ontology of eukaryotic cilia and flagella.

BACKGROUND: Recent research into ciliary structure and function provides important insights into inherited diseases termed ciliopathies and other cilia-related disorders. This wealth of knowledge needs to be translated into a computational representation to be fully exploitable by the research community. To this end, members of the Gene Ontology (GO) and SYSCILIA Consortia have worked together to improve representation of ciliary substructures and processes in GO. METHODS: Members of the SYSCILIA and Gene Ontology Consortia suggested additions and changes to GO, to reflect new knowledge in the field. The project initially aimed to improve coverage of ciliary parts, and was then broadened to cilia-related biological processes. Discussions were documented in a public tracker. We engaged the broader cilia community via direct consultation and by referring to the literature. Ontology updates were implemented via ontology editing tools. RESULTS: So far, we have created or modified 127 GO terms representing parts and processes related to eukaryotic cilia/flagella or prokaryotic flagella. A growing number of biological pathways are known to involve cilia, and we continue to incorporate this knowledge in GO. The resulting expansion in GO allows more precise representation of experimentally derived knowledge, and SYSCILIA and GO biocurators have created 199 annotations to 50 human ciliary proteins. The revised ontology was also used to curate mouse proteins in a collaborative project. The revised GO and annotations, used in comparative 'before and after' analyses of representative ciliary datasets, improve enrichment results significantly. CONCLUSIONS: Our work has resulted in a broader and deeper coverage of ciliary composition and function. These improvements in ontology and protein annotation will benefit all users of GO enrichment analysis tools, as well as the ciliary research community, in areas ranging from microscopy image annotation to interpretation of high-throughput studies. We welcome feedback to further enhance the representation of cilia biology in GO

QuickGO: a user tutorial for the web-based Gene Ontology browser

The Gene Ontology (GO) has proven to be a valuable resource for functional annotation of gene products. At well over 27 000 terms, the descriptiveness of GO has increased rapidly in line with the biological data it represents. Therefore, it is vital to be able to easily and quickly mine the functional information that has been made available through these GO terms being associated with gene products. QuickGO is a fast, web-based tool for browsing the GO and all associated GO annotations provided by the GOA group. After undergoing a redevelopment, QuickGO is now able to offer many more features beyond simple browsing. Users have responded well to the new tool and given very positive feedback about its usefulness. This tutorial will demonstrate how some of these features could be useful to the researcher wanting to discover more about their dataset, particular areas of biology or to find new ways of directing their research

Guidelines for the functional annotation of microRNAs using the Gene Ontology.

MicroRNA regulation of developmental and cellular processes is a relatively new field of study, and the available research data have not been organized to enable its inclusion in pathway and network analysis tools. The association of gene products with terms from the Gene Ontology is an effective method to analyze functional data, but until recently there has been no substantial effort dedicated to applying Gene Ontology terms to microRNAs. Consequently, when performing functional analysis of microRNA data sets, researchers have had to rely instead on the functional annotations associated with the genes encoding microRNA targets. In consultation with experts in the field of microRNA research, we have created comprehensive recommendations for the Gene Ontology curation of microRNAs. This curation manual will enable provision of a high-quality, reliable set of functional annotations for the advancement of microRNA research. Here we describe the key aspects of the work, including development of the Gene Ontology to represent this data, standards for describing the data, and guidelines to support curators making these annotations. The full microRNA curation guidelines are available on the GO Consortium wiki (http://wiki.geneontology.org/index.php/MicroRNA_GO_annotation_manual).R.P.H. and R.C.L are supported by funding from a British Heart Foundation grant (RG/13/5/30112) and the National Institute for Health Research University College London Hospitals Biomedical Research Centre. M.M. is a Senior Research Fellow of the British Heart Foundation (FS/13/2/29892). A.Z. is an Intermediate Fellow of the British Heart Foundation (FS/13/18/30207). D.S. is supported by a grant awarded to the Mouse Genome Database from the National Human Genome Research Institue at the US National Institutes of Health (HG-00330). P.D’E., M.G., M.O-M. are supported by grants from the US National Institutes of Health (P41 HG003751 and U54 GM114833), Ontario Research Fund, and the European Molecular Biology Laboratory. D.H. is supported by a grant awarded to the Zebrafish Information Network fromthe National Human Genome Research Institute at the US National Institutes of Health (HG002659). A.Z.K. is funded by a NIHR University College London Hospitals Biomedical Research Centre, Research Capability Funding award (RCF) (RCF123). L.M. is a Ragnar Söderberg fellow in Medicine (M-14/55), and received funding from Swedish Heart-Lung-Foundation (20120615, 20130664, 20140186). Huntley, RP 22 R.B. and D.O-S. are supported by R.B. and D.O-S. are supported by a grant awarded to The Gene Ontology Consortium (Principal Investigators: JA Blake, JM Cherry, S Lewis, PW Sternberg and P Thomas) by the National Human Genome Research Institute (NHGRI) (#U41 HG22073). V.P. and J.R.S. are supported by a grant from the National Heart, Lung, and Blood Institute on behalf of the National Institutes of Health (HL64541). K.V.A. is supported by a grant awarded to the Gene Ontology Consortium from the National Human Genome Research Institute at the US National Institutes of Health (HG002273). V.W. is supported by a Wellcome Trust grant (104967/Z/14/Z). We would like to thank Leonore Reiser and Tanya Berardini who provided guidance on the plant miRNA processing pathway. Also thanks to David Hill, Harold Drabkin, Judith Blake, Karen Christie, Donghui Li and Pascale Gaudet who contributed to discussions regarding GO curation procedures and to Lisa Matthews and Bruce May who provided helpful feedback on the manuscript. We are very grateful to Tony Sawford and Maria Martin from the European Bioinformatics Institute for access to the online GO curation tool, which is an essential component of this annotation project. Many thanks to members of the GO Editorial Office for useful discussions about the placement and definition of new GO terms. We also thank Alex Bateman and Anton Petrov for being responsive to our feedback regarding RNAcentral functionality. Author contributions: R.C.L. initiated discussions in the GO Consortium regarding miRNA curation guidelines and supervised the project, R.P.H. researched and constructed the guidelines and wrote the manuscript, R.P.H., R.C.L., D.S., R.B., P.D’E., M.G., M.O-M., D.H., V.P., J.R.S., K.V.A. and V.W. contributed to discussions regarding GO curation procedures and provided feedback on the manuscript. D.O-S. provided the expertise on definitions and placements of miRNA-related GO terms and performed the necessary updates and additions to both the GO and to the annotation extension relations used herein. M.M., A.Z., L.M. and A.Z.K. provided guidance with the scientific aspect of the guidelines and provided feedback on the manuscript.This is the final version of the article. It first appeared from Cold Spring Harbor Press via http://dx.doi.org/10.1261/rna.055301.11

A method for increasing expressivity of Gene Ontology annotations using a compositional approach.

BACKGROUND: The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational analyses for interpretation of high-throughput experimental and clinical data. The core data structure is the annotation, an association between a gene product and a term from one of the three ontologies comprising the GO. Historically, it has not been possible to provide additional information about the context of a GO term, such as the target gene or the location of a molecular function. This has limited the specificity of knowledge that can be expressed by GO annotations. RESULTS: The GO Consortium has introduced annotation extensions that enable manually curated GO annotations to capture additional contextual details. Extensions represent effector-target relationships such as localization dependencies, substrates of protein modifiers and regulation targets of signaling pathways and transcription factors as well as spatial and temporal aspects of processes such as cell or tissue type or developmental stage. We describe the content and structure of annotation extensions, provide examples, and summarize the current usage of annotation extensions. CONCLUSIONS: The additional contextual information captured by annotation extensions improves the utility of functional annotation by representing dependencies between annotations to terms in the different ontologies of GO, external ontologies, or an organism's gene products. These enhanced annotations can also support sophisticated queries and reasoning, and will provide curated, directional links between many gene products to support pathway and network reconstruction

Annotation of gene product function from high-throughput studies using the Gene Ontology.

High-throughput studies constitute an essential and valued source of information for researchers. However, high-throughput experimental workflows are often complex, with multiple data sets that may contain large numbers of false positives. The representation of high-throughput data in the Gene Ontology (GO) therefore presents a challenging annotation problem, when the overarching goal of GO curation is to provide the most precise view of a gene's role in biology. To address this, representatives from annotation teams within the GO Consortium reviewed high-throughput data annotation practices. We present an annotation framework for high-throughput studies that will facilitate good standards in GO curation and, through the use of new high-throughput evidence codes, increase the visibility of these annotations to the research community

Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology.

BACKGROUND: A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. METHODS AND RESULTS: In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. CONCLUSIONS: We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. Circ Genom Precis Med 2018 Feb; 11(2):e001813

The impact of focused Gene Ontology curation of specific mammalian systems.

The Gene Ontology (GO) resource provides dynamic controlled vocabularies to provide an information-rich resource to aid in the consistent description of the functional attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). System-focused projects, such as the Renal and Cardiovascular GO Annotation Initiatives, aim to provide detailed GO data for proteins implicated in specific organ development and function. Such projects support the rapid evaluation of new experimental data and aid in the generation of novel biological insights to help alleviate human disease. This paper describes the improvement of GO data for renal and cardiovascular research communities and demonstrates that the cardiovascular-focused GO annotations, created over the past three years, have led to an evident improvement of microarray interpretation. The reanalysis of cardiovascular microarray datasets confirms the need to continue to improve the annotation of the human proteome. AVAILABILITY: GO ANNOTATION DATA IS FREELY AVAILABLE FROM: ftp://ftp.geneontology.org/pub/go/gene-associations