Ruth C. Lovering

The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases

IntAct (freely available at http://www.ebi.ac.uk/intact) is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions. IntAct has developed a sophisticated web-based curation tool, capable of supporting both IMEx- and MIMIx-level curation. This tool is now utilized by multiple additional curation teams, all of whom annotate data directly into the IntAct database. Members of the IntAct team supply appropriate levels of training, perform quality control on entries and take responsibility for long-term data maintenance. Recently, the MINT and IntAct databases decided to merge their separate efforts to make optimal use of limited developer resources and maximize the curation output. All data manually curated by the MINT curators have been moved into the IntAct database at EMBL-EBI and are merged with the existing IntAct dataset. Both IntAct and MINT are active contributors to the IMEx consortium (http://www.imexconsortium.org).

The NLR gene family: a standard nomenclature.

Iimmune regulatory proteins such as CIITA, NAIP, IPAF, NOD1, NOD2, NALP1, cryopyrin/NALP3 are members of a family characterized by the presence of a nucleotide-binding domain (NBD) and leucine-rich repeats (LRR). Members of this gene family encode a protein structure similar to the NB-LRR subgroup of disease-resistance genes in plants and are involved in the sensing of pathogenic products and the regulation of cell signaling and apoptosis. Several members of this family have been associated with immunologic disorders. NOD2 for instance is associated with both Crohns disease and Blau syndrome. A variety of different names are currently used to describe this gene family, its subfamilies and individual genes, including CATERPILLER (CLR), NOD-LRR, NACHT-LRR, CARD, NALP, NOD, PAN and PYPAF, and this lack of consistency has led to a pressing need to unify the nomenclature. Consequently, we collectively propose the family designation NLR (nucleotide-binding domain and leucine-rich repeat containing) and provide unique and standardized gene designations for all family members.

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.

CorrespondenceThe NLR Gene Family: A Standard Nomenclature

Iimmune regulatory proteins such as CIITA, NAIP, IPAF, NOD1, NOD2, NALP1, cryopyrin/NALP3 are members of a family characterized by the presence of a nucleotide-binding domain (NBD) and leucine-rich repeats (LRR). Members of this gene family encode a protein structure similar to the NB-LRR subgroup of disease-resistance genes in plants and are involved in the sensing of pathogenic products and the regulation of cell signaling and apoptosis. Several members of this family have been associated with immunologic disorders. NOD2 for instance is associated with both Crohns disease and Blau syndrome. A variety of different names are currently used to describe this gene family, its subfamilies and individual genes, including CATERPILLER (CLR), NOD-LRR, NACHT-LRR, CARD, NALP, NOD, PAN and PYPAF, and this lack of consistency has led to a pressing need to unify the nomenclature. Consequently, we collectively propose the family designation NLR (nucleotide-binding domain and leucine-rich repeat containing) and provide unique and standardized gene designations for all family members.

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.

The HUGO Gene Nomenclature Committee (HGNC).

The need for standard nomenclature in human genetics was recognised as early as the 1960s, and in 1979 full guidelines for human gene nomenclature were presented at the Edinburgh Human Genome Meeting (HGM) and subsequently published (Shows et al. 1979). The current Chair of the Human Gene Nomenclature Committee, Sue Povey, was elected at the HGM meeting in Heidelberg in 1996. Since then, under the auspices of the international Human Genome Organisations and with the acronym HGNC, we continue to strike a compromise between the convenience and simplicity required for the everyday use of human gene nomenclature and the need for adequate definition of the concepts involved. Numerical identifiers are satisfactory for computers, but when humans need to talk about a gene they prefer to use a name. Increasingly journals are requesting approved gene nomenclature before publication, although more standardisation in this respect would make a significant contribution to the annotation of the human genome (Povey et al. 1997; White et al. 1998). A recent analysis of networks of human genes from 10 million MedLine records illustrates the ingenuity currently required to extract information from the literature (Jenssen et al. 2001). The committee has grown from a single force (Dr Phyllis J. McAlpine) to the equivalent of five professional full-time staff, and operates through the Chair with key policy advice from an International Advisory Committee (IAC, http://www.gene.ucl.ac.uk/nomenclature/IAC.shtml). We also use a team of specialist advisors who provide support on specific gene family nomenclature issues (http://www.gene.ucl.ac.uk/nomenclature/advisors.html). Regular nomenclature workshops are held, frequently to coincide with the annual meeting of the American Society of Human Genetics (ASHG) and the HGM, to ensure that we are approving gene names in line with the needs of the scientific community. Guidelines for human gene nomenclature were last published in 1997 (White et al. 1977) and are also available online. New guidelines will be published in 2002 and a draft version can be inspected at http://www.gene.ucl.ac.uk/nomenclature/guidelines/draft _2001.html. For details of previous and future workshops see http://www.gene.ucl.ac.uk/nomenclature/workshops.html.

Chromosome 9p21.3 Coronary Heart Disease Locus Genotype and Prospective Risk of CHD in Healthy Middle-Aged Men

BACKGROUND We investigated whether chromosome 9p21.3 single-nucleotide polymorphisms (SNPs), identified in coronary heart disease (CHD) genome-wide association scans, added significantly to the predictive utility for CHD of conventional risk factors (CRF) in the Framingham risk score (FRS) algorithm. METHODS In the Northwick Park Heart Study II of 2742 men (270 CHD events occurring during a 15-year prospective study), rs10757274 A>G [mean frequency G = 0.48 (95% CI 0.47-0.50)] was genotyped. Using the area under the ROC curve (A(ROC)) and the likelihood ratio (LR) statistic, we assessed the discriminatory performance of the FRS based on CRFs with and without genotype. RESULTS rs10757274 A>G was associated with incident CHD, with an effect size as reported previously [hazard ratio in GG vs AA men of 1.60 (95% CI 1.12-2.28)], independent of CRFs and family history of CHD. Although the A(ROC) for CRFs alone [0.62 (95% CI 0.58-0.66)] did not increase significantly (P = 0.14) when rs10757274 A>G genotype was added [0.64 (95% CI 0.60-0.68)], including genotype gave better fit (LR P = 0.01) and including rs10757274 moved 369 men (13.5% of the total) into more accurate risk categories. To model polygenic effects, 10 hypothetical, randomly assigned gene variants, with similar effect size and frequencies were added. Two variants made significant A(ROC) improvements to the FRS prediction (P = 0.01), whereas further variants had smaller incremental effects (final A(ROC) = 0.71, P <0.001 vs CRFs; LR vs CRFs P <0.0001). CONCLUSIONS Although overall, rs10757274 did not add substantially to the usefulness of the FRS for predicting future events, it did improve reclassification of CHD risk, and thus may have clinical utility.

Transcriptomic analyses of murine resolution-phase macrophages

Macrophages are either classically (M1) or alternatively-activated (M2). Whereas this nomenclature was generated from monocyte-derived macrophages treated in vitro with defined cytokine stimuli, the phenotype of in vivo-derived macrophages is less understood. We completed Affymetrix-based transcriptomic analysis of macrophages from the resolution phase of a zymosan-induced peritonitis. Compared with macrophages from hyperinflamed mice possessing a pro-inflammatory nature as well as naive macrophages from the uninflamed peritoneum, resolution-phase macrophages (rM) are similar to monocyte-derived dendritic cells (DCs), being CD209a positive but lacking CD11c. They are enriched for antigen processing/presentation (MHC class II [H2-Eb1, H2-Ab1, H2-Ob, H2-Aa], CD74, CD86), secrete T- and B-lymphocyte chemokines (Xcl1, Ccl5, Cxcl13) as well as factors that enhance macrophage/DC development, and promote DC/T cell synapse formation (Clec2i, Tnfsf4, Clcf1). rM are also enriched for cell cycle/proliferation genes as well as Alox15, Timd4, and Tgfb2, key systems in the termination of leukocyte trafficking and clearance of inflammatory cells. Finally, comparison with in vitro-derived M1/M2 shows that rM are neither classically nor alternatively activated but possess aspects of both definitions consistent with an immune regulatory phenotype. We propose that macrophages in situ cannot be rigidly categorized as they can express many shades of the inflammatory spectrum determined by tissue, stimulus, and phase of inflammation.

Gene-centric Association Signals for Lipids and Apolipoproteins Identified via the HumanCVD BeadChip

Blood lipids are important cardiovascular disease (CVD) risk factors with both genetic and environmental determinants. The Whitehall II study (n=5592) was genotyped with the gene-centric HumanCVD BeadChip (Illumina). We identified 195 SNPs in 16 genes/regions associated with 3 major lipid fractions and 2 apolipoprotein components at p<10(-5), with the associations being broadly concordant with prior genome-wide analysis. SNPs associated with LDL cholesterol and apolipoprotein B were located in LDLR, PCSK9, APOB, CELSR2, HMGCR, CETP, the TOMM40-APOE-C1-C2-C4 cluster, and the APOA5-A4-C3-A1 cluster; SNPs associated with HDL cholesterol and apolipoprotein AI were in CETP, LPL, LIPC, APOA5-A4-C3-A1, and ABCA1; and SNPs associated with triglycerides in GCKR, BAZ1B, MLXIPL, LPL, and APOA5-A4-C3-A1. For 48 SNPs in previously unreported loci that were significant at p<10(-4) in Whitehall II, in silico analysis including the British Womens Heart and Health Study, BRIGHT, ASCOT, and NORDIL studies (total n>12,500) revealed previously unreported associations of SH2B3 (p<2.2x10(-6)), BMPR2 (p<2.3x10(-7)), BCL3/PVRL2 (flanking APOE; p<4.4x10(-8)), and SMARCA4 (flanking LDLR; p<2.5x10(-7)) with LDL cholesterol. Common alleles in these genes explained 6.1%-14.7% of the variance in the five lipid-related traits, and individuals at opposite tails of the additive allele score exhibited substantial differences in trait levels (e.g., >1 mmol/L in LDL cholesterol [approximately 1 SD of the trait distribution]). These data suggest that multiple common alleles of small effect can make important contributions to individual differences in blood lipids potentially relevant to the assessment of CVD risk. These genes provide further insights into lipid metabolism and the likely effects of modifying the encoded targets therapeutically.

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.