Wellcome Trust Sanger Institute

About: Wellcome Trust Sanger Institute is a nonprofit organization based out in Cambridge, United Kingdom. It is known for research contribution in the topics: Population & Genome. The organization has 4009 authors who have published 9671 publications receiving 1224479 citations.

Structure and dynamics of the pan-genome of Streptococcus pneumoniae and closely related species

Abstract: Background Streptococcus pneumoniae is one of the most important causes of microbial diseases in humans. The genomes of 44 diverse strains of S. pneumoniae were analyzed and compared with strains of non-pathogenic streptococci of the Mitis group.

The DNA sequence and comparative analysis of human chromosome 20.

Abstract: Chromosome 5 is one of the largest human chromosomes and contains numerous intrachromosomal duplications, yet it has one of the lowest gene densities. This is partially explained by numerous gene-poor regions that display a remarkable degree of noncoding conservation with non-mammalian vertebrates, suggesting that they are functionally constrained. In total, we compiled 177.7 million base pairs of highly accurate finished sequence containing 923 manually curated protein-coding genes including the protocadherin and interleukin gene families. We also completely sequenced versions of the large chromosome-5-specific internal duplications. These duplications are very recent evolutionary events and probably have a mechanistic role in human physiological variation, as deletions in these regions are the cause of debilitating disorders including spinal muscular atrophy.

Dense genotyping of immune-related disease regions identifies 14 new susceptibility loci for juvenile idiopathic arthritis

Abstract: Anne Hinks and colleagues identify 14 new susceptibility loci for juvenile idiopathic arthritis through targeted analyses of genomic regions implicated in immune function. Their study implicates several pathways, including IL-2 signaling, in the pathogenesis of this common childhood autoimmune disease.

EGASP: the human ENCODE Genome Annotation Assessment Project

Abstract: Background: We present the results of EGASP, a community experiment to assess the state-ofthe-art in genome annotation within the ENCODE regions, which span 1% of the human genome sequence. The experiment had two major goals: the assessment of the accuracy of computational methods to predict protein coding genes; and the overall assessment of the completeness of the current human genome annotations as represented in the ENCODE regions. For the computational prediction assessment, eighteen groups contributed gene predictions. We evaluated these submissions against each other based on a ‘reference set’ of annotations generated as part of the GENCODE project. These annotations were not available to the prediction groups prior to the submission deadline, so that their predictions were blind and an external advisory committee could perform a fair assessment. Results: The best methods had at least one gene transcript correctly predicted for close to 70% of the annotated genes. Nevertheless, the multiple transcript accuracy, taking into account alternative splicing, reached only approximately 40% to 50% accuracy. At the coding nucleotide level, the best programs reached an accuracy of 90% in both sensitivity and specificity. Programs relying on mRNA and protein sequences were the most accurate in reproducing the manually curated annotations. Experimental validation shows that only a very small percentage (3.2%) of

Open Targets: a platform for therapeutic target identification and validation.

Abstract: We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.