Transcript specific regulation of expression influences susceptibility to multiple sclerosis

Genome-wide association studies (GWAS) have identified over 100 loci containing single nucleotide variants (SNVs) that influence the risk of developing multiple sclerosis (MS). Most of these loci lie in non-coding regulatory regions of the genome that are active in immune cells and are therefore thought to modify risk by altering the expression of key immune genes. To explore this hypothesis we screened genes flanking MS-associated variants for evidence of allele specific expression (ASE) by quantifying the transcription of coding variants in linkage disequilibrium with MS-associated SNVs. In total, we were able to identify and successfully analyse 200 such coding variants (from 112 genes) in both CD4+ and CD8+ T cells from 106 MS patients and 105 controls. Fifty-six of these coding variants (from 43 genes) showed statistically significant evidence of ASE in one or both cell types. In the Lck interacting transmembrane adaptor 1 gene (LIME1), for example, we were able to show that in both cell types, the MS-associated variant rs2256814 increased the expression of some transcripts while simultaneously reducing the expression of other transcripts. In CD4+ cells from an additional independent set of 96 cases and 93 controls we were able to replicate the effect of this SNV on the balance of alternate LIME1 transcripts using qPCR (p = 5 × 10^-24). Our data thus indicate that some of the MS-associated SNVs identified by GWAS likely exert their effects on risk by distorting the balance of alternate transcripts rather than by changing the overall level of gene expression.

Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk

Multiple sclerosis is a complex neurological disease, with ∼20% of risk heritability attributable to common genetic variants, including >230 identified by genome-wide association studies. Multiple strands of evidence suggest that much of the remaining heritability is also due to additive effects of common variants rather than epistasis between these variants or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that up to 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common-variant signals, highlighting key pathogenic roles for regulatory T cell homeostasis and regulation, IFNγ biology, and NFκB signaling. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS.

Best practice data life cycle approaches for the life sciences

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a 'life cycle' view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on 'omics' datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

Genome-wide meta-analysis of cognitive empathy: heritability, and correlates with sex, neuropsychiatric conditions and cognition

We conducted a genome-wide meta-analysis of cognitive empathy using the 'Reading the Mind in the Eyes' Test (Eyes Test) in 88,056 research volunteers of European Ancestry (44,574 females and 43,482 males) from 23andMe Inc., and an additional 1497 research volunteers of European Ancestry (891 females and 606 males) from the Brisbane Longitudinal Twin Study. We confirmed a female advantage on the Eyes Test (Cohen's d=0.21, P<2.2 × 10^-16), and identified a locus in 3p26.1 that is associated with scores on the Eyes Test in females (rs7641347, P_meta=1.58 × 10^-8). Common single nucleotide polymorphisms explained 5.8% (95% CI: 4.5%-7.2%; P=1.00 × 10^-17) of the total trait variance in both sexes, and we identified a twin heritability of 28% (95% CI: 13%-42%). Finally, we identified significant genetic correlation between the Eyes Test and anorexia nervosa, openness (NEO-Five Factor Inventory), and different measures of educational attainment and cognitive aptitude.

Best practice data life cycle approaches for the life sciences

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a 'life cycle' view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on 'omics' datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

Further studies of the down-regulation by Factor I of the C3b feedback cycle using endotoxin as a soluble activator and red cells as a source of CR1 on sera of different complotype

In this paper we have extended our earlier studies of the action of increasing Factor I concentration on complement activation by using a soluble activator, lipopolysaccharide (LPS) endotoxin, and using human erythrocytes as a source of CR1 - the co-factor needed for the final clip of iC3b to C3dg by Factor I. Using this more physiological system, the results show that we can predict that a quite modest increase in Factor I concentration - 22 µg/ml of extra Factor I - will convert the activity of the highest risk sera to those of the lowest risk. Preliminary experiments have been performed with erythrocytes allotyped for CR1 number. While we have not been able to perform an adequate study of their co-factor activities in our assays, preliminary experiments suggest that when Factor I levels are increased the difference produced by different allotypes of red cells is largely overcome. This suggests that in patients with paroxysmal nocturnal haemoglobinuria (PNH) treated with eculizumab, additional treatment with Factor I may be very useful in reducing the need for blood transfusion. We have also explored the age-related allele frequency for the two polymorphisms of Factor H and the polymorphism of C3. In our population, unlike the 1975 study, we found no age variation in the allele frequency in these polymorphisms. This may, however, reflect that the Cambridge BioResource volunteers do not include many very young or very elderly patients, and in general comprise a population not greatly at risk of death from infectious disease.

VRK1 interacts with p53 forming a basal complex that is activated by UV-induced DNA damage

DNA damage immediate cellular response requires the activation of p53 by kinases. We found that p53 forms a basal stable complex with VRK1, a Ser-Thr kinase that responds to UV-induced DNA damage by specifically phosphorylating p53. This interaction takes place through the p53 DNA binding domain, and frequent DNA-contact mutants of p53, such as R273H, R248H or R280K, do not disrupt the complex. UV-induced DNA damage activates VRK1, and is accompanied by phosphorylation of p53 at Thr-18 before it accumulates. We propose that the VRK1-p53 basal complex is an early-warning system for immediate cellular responses to DNA damage.

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).

Protein interaction data curation: the International Molecular Exchange (IMEx) consortium

The International Molecular Exchange (IMEx) consortium is an international collaboration between major public interaction data providers to share literature-curation efforts and make a nonredundant set of protein interactions available in a single search interface on a common website (http://www.imexconsortium.org/). Common curation rules have been developed, and a central registry is used to manage the selection of articles to enter into the dataset. We discuss the advantages of such a service to the user, our quality-control measures and our data-distribution practices.

New gene functions in megakaryopoiesis and platelet formation

Platelets are the second most abundant cell type in blood and are essential for maintaining haemostasis. Their count and volume are tightly controlled within narrow physiological ranges, but there is only limited understanding of the molecular processes controlling both traits. Here we carried out a high-powered meta-analysis of genome-wide association studies (GWAS) in up to 66,867 individuals of European ancestry, followed by extensive biological and functional assessment. We identified 68 genomic loci reliably associated with platelet count and volume mapping to established and putative novel regulators of megakaryopoiesis and platelet formation. These genes show megakaryocyte-specific gene expression patterns and extensive network connectivity. Using gene silencing in Danio rerio and Drosophila melanogaster, we identified 11 of the genes as novel regulators of blood cell formation. Taken together, our findings advance understanding of novel gene functions controlling fate-determining events during megakaryopoiesis and platelet formation, providing a new example of successful translation of GWAS to function.

The IntAct molecular interaction database in 2012

IntAct is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions. Two levels of curation are now available within the database, with both IMEx-level annotation and less detailed MIMIx-compatible entries currently supported. As from September 2011, IntAct contains approximately 275 000 curated binary interaction evidences from over 5000 publications. The IntAct website has been improved to enhance the search process and in particular the graphical display of the results. New data download formats are also available, which will facilitate the inclusion of IntAct's data in the Semantic Web. IntAct is an active contributor to the IMEx consortium (http://www.imexconsortium.org). IntAct source code and data are freely available at http://www.ebi.ac.uk/intact.

The IntAct molecular interaction database in 2010

IntAct is an open-source, open data molecular interaction database and toolkit. Data is abstracted from the literature or from direct data depositions by expert curators following a deep annotation model providing a high level of detail. As of September 2009, IntAct contains over 200.000 curated binary interaction evidences. In response to the growing data volume and user requests, IntAct now provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows 'zooming in' on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available at http://www.ebi.ac.uk/intact.

MINT and IntAct contribute to the Second BioCreative challenge: serving the text-mining community with high quality molecular interaction data

Background

In the absence of consolidated pipelines to archive biological data electronically, information dispersed in the literature must be captured by manual annotation. Unfortunately, manual annotation is time consuming and the coverage of published interaction data is therefore far from complete. The use of text-mining tools to identify relevant publications and to assist in the initial information extraction could help to improve the efficiency of the curation process and, as a consequence, the database coverage of data available in the literature. The 2006 BioCreative competition was aimed at evaluating text-mining procedures in comparison with manual annotation of protein-protein interactions.

Results

To aid the BioCreative protein-protein interaction task, IntAct and MINT (Molecular INTeraction) provided both the training and the test datasets. Data from both databases are comparable because they were curated according to the same standards. During the manual curation process, the major cause of data loss in mining the articles for information was ambiguity in the mapping of the gene names to stable UniProtKB database identifiers. It was also observed that most of the information about interactions was contained only within the full-text of the publication; hence, text mining of protein-protein interaction data will require the analysis of the full-text of the articles and cannot be restricted to the abstract.

Conclusion

The development of text-mining tools to extract protein-protein interaction information may increase the literature coverage achieved by manual curation. To support the text-mining community, databases will highlight those sentences within the articles that describe the interactions. These will supply data-miners with a high quality dataset for algorithm development. Furthermore, the dictionary of terms created by the BioCreative competitors could enrich the synonym list of the PSI-MI (Proteomics Standards Initiative-Molecular Interactions) controlled vocabulary, which is used by both databases to annotate their data content.

IntAct--open source resource for molecular interaction data

IntAct is an open source database and software suite for modeling, storing and analyzing molecular interaction data. The data available in the database originates entirely from published literature and is manually annotated by expert biologists to a high level of detail, including experimental methods, conditions and interacting domains. The database features over 126 000 binary interactions extracted from over 2100 scientific publications and makes extensive use of controlled vocabularies. The web site provides tools allowing users to search, visualize and download data from the repository. IntAct supports and encourages local installations as well as direct data submission and curation collaborations. IntAct source code and data are freely available from .