The Gene Ontology in 2010: extensions and refinements

The Gene Ontology (GO) Consortium (http://www.geneontology.org) (GOC) continues to develop, maintain and use a set of structured, controlled vocabularies for the annotation of genes, gene products and sequences. The GO ontologies are expanding both in content and in structure. Several new relationship types have been introduced and used, along with existing relationships, to create links between and within the GO domains. These improve the representation of biology, facilitate querying, and allow GO developers to systematically check for and correct inconsistencies within the GO. Gene product annotation using GO continues to increase both in the number of total annotations and in species coverage. GO tools, such as OBO-Edit, an ontology-editing tool, and AmiGO, the GOC ontology browser, have seen major improvements in functionality, speed and ease of use

Insights into Online microRNA Bioinformatics Tools

MicroRNAs (miRNAs) are members of the small non-coding RNA family regulating gene expression at the post-transcriptional level. MiRNAs have been found to have critical roles in various biological and pathological processes. Research in this field has significantly progressed, with increased recognition of the importance of miRNA regulation. As a result of the vast data and information available regarding miRNAs, numerous online tools have emerged to address various biological questions related to their function and influence across essential cellular processes. This review includes a brief introduction to available resources for an investigation covering aspects such as miRNA sequences, target prediction/validation, miRNAs associated with disease, pathway analysis and genetic variants within miRNAs

GOing Forward With the Cardiac Conduction System Using Gene Ontology

The cardiac conduction system (CCS) comprises critical components responsible for the initiation and coordination of the action potential. Aberrant CCS development can cause conduction abnormalities, including sick sinus syndrome and atrioventricular and bundle branch blocks. Gene Ontology (GO; http://geneontology.org/) is an invaluable global bioinformatics resource which can provide structured, computable knowledge describing the functions of gene products. Many gene products are known be involved in CCS development; however, this information is not comprehensively captured by GO. Our study aimed to describe the specific roles of essential proteins that have been reported in the literature to be involved with development and/or function of the CCS. 14 proteins were prioritised for GO annotation which led to the curation of 15 peer-reviewed primary experimental articles using carefully selected GO terms. 152 descriptive GO annotations, including those describing sinoatrial node and atrioventricular node development were created and submitted to the GO Consortium database. A functional enrichment analysis of the 35 proteins known to have a role in CCS confirmed that this work has improved the in silico interpretation of this CCS dataset. Our contribution to the GO database may help elucidate the key mechanisms involved in CCS disorders as previous annotation projects have focussed predominantly on development of the heart rather than that of the CCS. This work may improve future heart disease investigations applying high-throughput methods such as genome-wide association studies analysis, proteomics and transcriptomics

Student biocuration projects as a learning environment [version 2; peer review: 2 approved]

Background: Bioinformatics is becoming an essential tool for the majority of biological and biomedical researchers. Although bioinformatics data is exploited by academic and industrial researchers, limited focus is on teaching this area to undergraduates, postgraduates and senior scientists. Many scientists are developing their own expertise without formal training and often without appreciating the source of the data they are reliant upon. Some universities do provide courses on a variety of bioinformatics resources and tools, a few also provide biocuration projects, during which students submit data to annotation resources. Methods: To assess the usefulness and enjoyability of annotation projects a survey was sent to University College London (UCL) students who have undertaken Gene Ontology biocuration projects. Results: Analysis of survey responses suggest that these projects provide students with an opportunity not only to learn about bioinformatics resources but also to improve their literature analysis, presentation and writing skills. Conclusion: Biocuration student projects provide valuable annotations as well as enabling students to develop a variety of skills relevant to their future careers. It is also hoped that, as future scientists, these students will critically assess their own manuscripts and ensure that these are written with the biocurators of the future in min

Exploring autophagy with Gene Ontology.

Autophagy is a fundamental cellular process that is well conserved among eukaryotes. It is one of the strategies that cells use to catabolize substances in a controlled way. Autophagy is used for recycling cellular components, responding to cellular stresses and ridding cells of foreign material. Perturbations in autophagy have been implicated in a number of pathological conditions such as neurodegeneration, cardiac disease and cancer. The growing knowledge about autophagic mechanisms needs to be collected in a computable and shareable format to allow its use in data representation and interpretation. The Gene Ontology (GO) is a freely available resource that describes how and where gene products function in biological systems. It consists of 3 interrelated structured vocabularies that outline what gene products do at the biochemical level, where they act in a cell and the overall biological objectives to which their actions contribute. It also consists of \u27annotations\u27 that associate gene products with the terms. Here we describe how we represent autophagy in GO, how we create and define terms relevant to autophagy researchers and how we interrelate those terms to generate a coherent view of the process, therefore allowing an interoperable description of its biological aspects. We also describe how annotation of gene products with GO terms improves data analysis and interpretation, hence bringing a significant benefit to this field of study. Autophagy 2018 Feb 17; 1-18

Exploring autophagy with Gene Ontology.

Autophagy is a fundamental cellular process that is well conserved among eukaryotes. It is one of the strategies that cells use to catabolize substances in a controlled way. Autophagy is used for recycling cellular components, responding to cellular stresses and ridding cells of foreign material. Perturbations in autophagy have been implicated in a number of pathological conditions such as neurodegeneration, cardiac disease and cancer. The growing knowledge about autophagic mechanisms needs to be collected in a computable and shareable format to allow its use in data representation and interpretation. The Gene Ontology (GO) is a freely available resource that describes how and where gene products function in biological systems. It consists of 3 interrelated structured vocabularies that outline what gene products do at the biochemical level, where they act in a cell and the overall biological objectives to which their actions contribute. It also consists of \u27annotations\u27 that associate gene products with the terms. Here we describe how we represent autophagy in GO, how we create and define terms relevant to autophagy researchers and how we interrelate those terms to generate a coherent view of the process, therefore allowing an interoperable description of its biological aspects. We also describe how annotation of gene products with GO terms improves data analysis and interpretation, hence bringing a significant benefit to this field of study. Autophagy 2018; 14(3):419-436

Nomenclature for the human Arf family of GTP-binding proteins: ARF, ARL, and SAR proteins

The Ras superfamily is comprised of at least four large families of regulatory guanosine triphosphate–binding proteins, including the Arfs. The Arf family includes three different groups of proteins: the Arfs, Arf-like (Arls), and SARs. Several Arf family members have been very highly conserved throughout eukaryotic evolution and have orthologues in evolutionally diverse species. The different means by which Arf family members have been identified have resulted in an inconsistent and confusing array of names. This confusion is further compounded by differences in nomenclature between different species. We propose a more consistent nomenclature for the human members of the Arf family that may also serve as a guide for nomenclature in other species

Weighted protein interaction network analysis of frontotemporal dementia

The genetic analysis of complex disorders has undoubtedly led to the identification of a wealth of associations between genes and specific traits. However, moving from genetics to biochemistry one gene at a time has, to date, rather proved inefficient and under-powered to comprehensively explain the molecular basis of phenotypes. Here we present a novel approach, weighted protein−protein interaction network analysis (W-PPI-NA), to highlight key functional players within relevant biological processes associated with a given trait. This is exemplified in the current study by applying W-PPI-NA to frontotemporal dementia (FTD): We first built the state of the art FTD protein network (FTD-PN) and then analyzed both its topological and functional features. The FTD-PN resulted from the sum of the individual interactomes built around FTD-spectrum genes, leading to a total of 4198 nodes. Twenty nine of 4198 nodes, called inter-interactome hubs (IIHs), represented those interactors able to bridge over 60% of the individual interactomes. Functional annotation analysis not only reiterated and reinforced previous findings from single genes and gene-coexpression analyses but also indicated a number of novel potential disease related mechanisms, including DNA damage response, gene expression regulation, and cell waste disposal and potential biomarkers or therapeutic targets including EP300. These processes and targets likely represent the functional core impacted in FTD, reflecting the underlying genetic architecture contributing to disease. The approach presented in this study can be applied to other complex traits for which risk-causative genes are known as it provides a promising tool for setting the foundations for collating genomics and wet laboratory data in a bidirectional manner. This is and will be critical to accelerate molecular target prioritization and drug discovery

Old Drugs To Treat Resistant Bugs: Methicillin-Resistant Staphylococcus aureus Isolates with mecC Are Susceptible to a Combination of Penicillin and Clavulanic Acid.

β-Lactam resistance in methicillin-resistant Staphylococcus aureus (MRSA) is mediated by the expression of an alternative penicillin-binding protein 2a (PBP2a) (encoded by mecA) with a low affinity for β-lactam antibiotics. Recently, a novel variant of mecA, known as mecC, was identified in MRSA isolates from both humans and animals. In this study, we demonstrate that mecC-encoded PBP2c does not mediate resistance to penicillin. Rather, broad-spectrum β-lactam resistance in MRSA strains carrying mecC (mecC-MRSA strains) is mediated by a combination of both PBP2c and the distinct β-lactamase encoded by the blaZ gene of strain LGA251 (blaZLGA251), which is part of mecC-encoding staphylococcal cassette chromosome mec (SCCmec) type XI. We further demonstrate that mecC-MRSA strains are susceptible to the combination of penicillin and the β-lactam inhibitor clavulanic acid in vitro and that the same combination is effective in vivo for the treatment of experimental mecC-MRSA infection in wax moth larvae. Thus, we demonstrate how the distinct biological differences between mecA- and mecC-encoded PBP2a and PBP2c have the potential to be exploited as a novel approach for the treatment of mecC-MRSA infections.This work was supported by a Medical Research Council (MRC) Partnership Grant (G1001787/1) held between the Department of Veterinary Medicine, University of Cambridge (M. A. H.), the School of Clinical Medicine, University of Cambridge (S. J. P.), the Moredun Research Institute (R. N. Z.) and the Wellcome Trust Sanger Institute (J. P. and S. J. P.).This is the author accepted manuscript. The final version is available from American Society for Microbiology via http://dx.doi.org/10.1128/AAC.01469-1