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This content will become publicly available on December 15, 2014

Title: An integrative computational approach for prioritization of genomic variants

An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. This study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.
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Publication Date:
OSTI Identifier:
Grant/Contract Number:
AC02-06CH11357; AC02-05CH11231
Accepted Manuscript
Journal Name:
Additional Journal Information:
Journal Volume: 9; Journal Issue: 12; Journal ID: ISSN 1932-6203
Public Library of Science
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org:
USDOE Office of Science (SC); National Institutes of Health (NIH)
Country of Publication:
United States
59 BASIC BIOLOGICAL SCIENCES; 96 KNOWLEDGE MANAGEMENT AND PRESERVATION; genomic databases; genome analysis; spina bifida; protein structure prediction; genomic medicine; phenotypes; bioinformatics; genome evolution