An integrative computational approach for prioritization of genomic variants

Dubchak, Inna; Balasubramanian, Sandhya; Wang, Sheng; Meydan, Cem; Sulakhe, Dinanath; Poliakov, Alexander; Börnigen, Daniela; Xie, Bingqing; Taylor, Andrew; Ma, Jianzhu; Paciorkowski, Alex R.; Mirzaa, Ghayda M.; Dave, Paul; Agam, Gady; Xu, Jinbo; Al-Gazali, Lihadh; Mason, Christopher E.; Ross, M. Elizabeth; Maltsev, Natalia; Gilliam, T. Conrad; Huang, Qingyang

doi:10.1371/journal.pone.0114903

Title: An integrative computational approach for prioritization of genomic variants

Journal Article · Mon Dec 15 00:00:00 EST 2014 · PLoS ONE

DOI:https://doi.org/10.1371/journal.pone.0114903· OSTI ID:1212419

Dubchak, Inna; Balasubramanian, Sandhya; Wang, Sheng; Meydan, Cem; Sulakhe, Dinanath; Poliakov, Alexander; Börnigen, Daniela; Xie, Bingqing; Taylor, Andrew; Ma, Jianzhu; Paciorkowski, Alex R.; Mirzaa, Ghayda M.; Dave, Paul; Agam, Gady; Xu, Jinbo; Al-Gazali, Lihadh; Mason, Christopher E.; Ross, M. Elizabeth; Maltsev, Natalia; Gilliam, T. Conrad more »

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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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE Office of Science (SC); National Institutes of Health (NIH)

Grant/Contract Number:: AC02-06CH11357; AC02-05CH11231

OSTI ID:: 1212419

Alternate ID(s):: OSTI ID: 1222963

Journal Information:: PLoS ONE, Vol. 9, Issue 12; ISSN 1932-6203

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 7 works

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