TY - JOUR
T1 - An integrative tissue-network approach to identify and test human disease genes
AU - Yao, Victoria
AU - Kaletsky, Rachel
AU - Keyes, William
AU - Mor, Danielle E.
AU - Wong, Aaron K.
AU - Sohrabi, Salman
AU - Murphy, Coleen T.
AU - Troyanskaya, Olga G.
N1 - Funding Information:
We thank K. Yao, R. Hong, and J. Zhou for assistance with video analysis, G. Laevsky for assistance with confocal microscopy, the CGC for strains, and Z. Gitai and the laboratories of O.G.T. and C.T.M. for valuable discussion. Strain UA44 was generously provided by G. Caldwell (University of Alabama), and strain BY250 was a generous gift from R. Blakely (Vanderbilt University). V.Y. was supported in part by US NIH grant T32 HG003284. O.G.T. is supported as a senior fellow of the Genetic Networks program of the Canadian Institute for Advanced Research (CIFAR). C.T.M. is supported as the Director of the Glenn Center for Aging Research at Princeton and as an HHMI-Simons Faculty Scholar. This work was supported by the NIH (R01 GM071966 to O.G.T. and Cognitive Aging R01 and DP1 Pioneer Award to C.T.M.).
Publisher Copyright:
© 2018, Nature Publishing Group. All rights reserved.
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Effective discovery of causal disease genes must overcome the statistical challenges of quantitative genetics studies and the practical limitations of human biology experiments. Here we developed diseaseQUEST, an integrative approach that combines data from human genome-wide disease studies with in silico network models of tissue-and cell-type-specific function in model organisms to prioritize candidates within functionally conserved processes and pathways. We used diseaseQUEST to predict candidate genes for 25 different diseases and traits, including cancer, longevity, and neurodegenerative diseases. Focusing on Parkinson’s disease (PD), a diseaseQUEST-directed Caenhorhabditis elegans behavioral screen identified several candidate genes, which we experimentally verified and found to be associated with age-dependent motility defects mirroring PD clinical symptoms. Furthermore, knockdown of the top candidate gene, bcat-1, encoding a branched chain amino acid transferase, caused spasm-like ‘curling’ and neurodegeneration in C. elegans, paralleling decreased BCAT1 expression in PD patient brains. diseaseQUEST is modular and generalizable to other model organisms and human diseases of interest.
AB - Effective discovery of causal disease genes must overcome the statistical challenges of quantitative genetics studies and the practical limitations of human biology experiments. Here we developed diseaseQUEST, an integrative approach that combines data from human genome-wide disease studies with in silico network models of tissue-and cell-type-specific function in model organisms to prioritize candidates within functionally conserved processes and pathways. We used diseaseQUEST to predict candidate genes for 25 different diseases and traits, including cancer, longevity, and neurodegenerative diseases. Focusing on Parkinson’s disease (PD), a diseaseQUEST-directed Caenhorhabditis elegans behavioral screen identified several candidate genes, which we experimentally verified and found to be associated with age-dependent motility defects mirroring PD clinical symptoms. Furthermore, knockdown of the top candidate gene, bcat-1, encoding a branched chain amino acid transferase, caused spasm-like ‘curling’ and neurodegeneration in C. elegans, paralleling decreased BCAT1 expression in PD patient brains. diseaseQUEST is modular and generalizable to other model organisms and human diseases of interest.
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U2 - 10.1038/nbt.4246
DO - 10.1038/nbt.4246
M3 - Article
C2 - 30346941
AN - SCOPUS:85056412587
SN - 1087-0156
VL - 36
SP - 1091
EP - 1105
JO - Nature Biotechnology
JF - Nature Biotechnology
IS - 11
ER -