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. The 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.
Details
Title
An Integrative Computational Approach for Prioritization of Genomic Variants
Author
Dubchak, Inna : Lawrence Berkeley National Laboratory Balasubramanian, Sandhya : University of Chicago Wang, Sheng : Toyota Technological Institute at Chicago Meyden, Cem : Cornell University Sulakhe, Dinanath : University of Chicago Poliakov, Alexander : Department of Energy Börnigen, Daniela : University of Chicago Xie, Bingqing : University of Chicago Taylor, Andrew : University of Chicago Ma, Jianzhu : Toyota Technological Institute at Chicago Paciorkowski, Alex R. : University of Rochester Medical Center Mirzaa, Ghayda M. : University of Washington Dave, Paul : University of Chicago Agam, Gady : Illinois Institute of Technology Xu, Jinbo : Toyota Technological Institute at Chicago Al-Gazali, Lihadh : United Arab Emirates University Mason, Christopher E. : Cornell University Ross, M. Elizabeth : Cornell University
Data availability statement
The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files.
Funding Information
National Heart, Lung and Blood Institute, R01GM081080A Office of Science of the United States Department of Energy, DE-AC02-05CH11231 National Institute of Neurological Disorders and Stroke, 2R01NS050375-06 Mr. and Ms. Lawrence Hilibrand and the Boler Family Foundation National Institutes of Health, R01HG006798 National Institutes of Health, R01NS076465 Irma T. Hirschl and Monique Weill-Caulier Charitable Trusts STARR Consortium, I7-A765
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