Year: 2014
Type: article
Abstract: 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.
Source: PLoS ONE
Authors: Inna Dubchak, Sandhya Balasubramanian, Sheng Wang, Cem Meyden, Dinanath Sulakhe, Alexander Poliakov, Daniela Börnigen, Bingqing Xie, Andrew Taylor, Jianzhu Ma, Alex R. Paciorkowski, Ghayda M. Mirzaa, Paul Dave, Gady Agam, Jinbo Xu, Lihadh Al-Gazali, Christopher E. Mason, M. Elizabeth Ross, Natalia Maltsev, T. Conrad Gilliam
Institutions: Lawrence Berkeley National Laboratory, Joint Genome Institute, University of Chicago, Toyota Technological Institute at Chicago, Cornell University, Weill Cornell Medicine, Argonne National Laboratory, Illinois Institute of Technology, University of Rochester Medicine, University of Rochester, University of Washington, Seattle Children's Research Institute, United Arab Emirates University
Language: English
Topic: Genomics and Rare Diseases
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,382
Funders: U.S. Department of Energy, University of Chicago, Boler Family Foundation, Joint Genome Institute, National Institutes of Health, Office of Science, National Human Genome Research Institute, National Institute of General Medical Sciences, National Institute of Neurological Disorders and Stroke, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G1286236842, G2897265683, G3083819904, G382641700, G419881185, G42916606, G4501827968, G498139845, G5220200369, G5385845597, The Genetic Basis of Dandy-Walker and Other Mid-Hindbrain Malformations, G6652958823, G7168768249, G7205239661, Epigenome Interactions in Complex Neurogenetic Disorders, G834277795, G835137386, New Computational Methods for Data-driven Protein Structure Prediction, G894015147, G9000285413, G969889393
OpenAlex ID: W1974744518