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

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

Capturing variation impact on molecular interactions in the IMEx Consortium mutations data set

The current wealth of genomic variation data identified at nucleotide level presents the challenge of understanding by which mechanisms amino acid variation affects cellular processes. These effects may manifest as distinct phenotypic differences between individuals or result in the development of disease. Physical interactions between molecules are the linking steps underlying most, if not all, cellular processes. Understanding the effects that sequence variation has on a molecule's interactions is a key step towards connecting mechanistic characterization of nonsynonymous variation to phenotype. We present an open access resource created over 14 years by IMEx database curators, featuring 28,000 annotations describing the effect of small sequence changes on physical protein interactions. We describe how this resource was built, the formats in which the data is provided and offer a descriptive analysis of the data set. The data set is publicly available through the IntAct website and is enhanced with every monthly release

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.Philippa C. Griffin, Jyoti Khadake, Kate S. LeMay, Suzanna E. Lewis, Sandra Orchard ... Nathan S. Watson-Haigh ... et al

Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility

We analyzed genetic data of 47,429 multiple sclerosis (MS) and 68,374 control subjects and established a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 variants within the extended MHC. We used an ensemble of methods to prioritize 551 putative susceptibility genes that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we observed enrichment for MS genes in these brain-resident immune cells, suggesting that these may have a role in targeting an autoimmune process to the central nervous system, although MS is most likely initially triggered by perturbation of peripheral immune responses

Histone H1 Subtypes Differentially Modulate Chromatin Condensation without Preventing ATP-Dependent Remodeling by SWI/SNF or NURF

Although ubiquitously present in chromatin, the function of the linker histone subtypes is partly unknown and contradictory studies on their properties have been published. To explore whether the various H1 subtypes have a differential role in the organization and dynamics of chromatin we have incorporated all of the somatic human H1 subtypes into minichromosomes and compared their influence on nucleosome spacing, chromatin compaction and ATP-dependent remodeling. H1 subtypes exhibit different affinities for chromatin and different abilities to promote chromatin condensation, as studied with the Atomic Force Microscope. According to this criterion, H1 subtypes can be classified as weak condensers (H1.1 and H1.2), intermediate condensers (H1.3) and strong condensers (H1.0, H1.4, H1.5 and H1x). The variable C-terminal domain is required for nucleosome spacing by H1.4 and is likely responsible for the chromatin condensation properties of the various subtypes, as shown using chimeras between H1.4 and H1.2. In contrast to previous reports with isolated nucleosomes or linear nucleosomal arrays, linker histones at a ratio of one per nucleosome do not preclude remodeling of minichromosomes by yeast SWI/SNF or Drosophila NURF. We hypothesize that the linker histone subtypes are differential organizers of chromatin, rather than general repressors

Publisher Correction: Capturing variation impact on molecular interactions in the IMEx Consortium mutations data set

Correction to: Nature Communications https://doi.org/10.1038/s41467-018-07709-6; published online 02 January 2019

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

Multiple sclerosis is a complex neurological disease, with 3c20% 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, IFN\u3b3 biology, and NF\u3baB 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. In a large multi-cohort study, unexplained heritability for multiple sclerosis is detected in low-frequency coding variants that are missed by GWAS analyses, further underscoring the role of immune genes in MS pathology

Expression of rat histone H1d in Escherichia coli and its purification

Histone H1 is involved in the folding of linear polynucleosomal filament into a 30-nm fiber. In an effort to understand the role of different domains of histone H1 in chromatin folding, we have now expressed rat histone H1d in Escherichia coli using pTrc99A expression vector by providing a 6-His tag at the C-terminus to facilitate its purification. The expressed protein histone H1d was purified from the soluble extract of E. coli by employing Ni<SUP>2+</SUP>NTA-agarose and heparin-agarose chromatography. The recombinant histone H1d was shown to be authentic by its N-terminal amino acid analysis, its secondary structural characteristics, and its ability to (a) condense DNA and (b) bind specifically to synthetic four-way junction DNA