Biological Sciences Division
Published December 15, 2014 | Version v1
Journal article Open

An Integrative Computational Approach for Prioritization of Genomic Variants

Creators

  • 1. Lawrence Berkeley National Laboratory
  • 2. University of Chicago
  • 3. Toyota Technological Institute at Chicago
  • 4. Cornell University
  • 5. Department of Energy
  • 6. University of Rochester Medical Center
  • 7. University of Washington
  • 8. Illinois Institute of Technology
  • 9. United Arab Emirates University

Description

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.

Data availability

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.

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Additional details

Identifiers

DOI
10.1371/journal.pone.0114903
Other
oai:uchicago.tind.io:10749

Funding

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

UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Human Genetics