Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli

• Main Authors: Gat-Viks, Irit (Author), Chevrier, Nicolas (Author), Wilentzik, Roni (Author), Eisenhaure, Thomas (Author), Raychowdhury, Raktima (Author), Steuerman, Yael (Author), Shalek, Alex K. (Author), Hacohen, Nir (Author), Amit, Ido (Author), Regev, Aviv (Contributor)
• Other Authors: move to dc.description.sponsorship (Contributor), Massachusetts Institute of Technology. Department of Biology (Contributor)
• Format: Article
• Language: English
• Published: Nature Publishing Group, 2014-02-18T21:01:05Z.
• Subjects: Article
• Online Access: Get fulltext

Individual genetic variation affects gene responsiveness to stimuli, often by influencing complex molecular circuits. Here we combine genomic and intermediate-scale transcriptional profiling with computational methods to identify variants that affect the responsiveness of genes to stimuli (responsiveness quantitative trait loci or reQTLs) and to position these variants in molecular circuit diagrams. We apply this approach to study variation in transcriptional responsiveness to pathogen components in dendritic cells from recombinant inbred mouse strains. We identify reQTLs that correlate with particular stimuli and position them in known pathways. For example, in response to a virus-like stimulus, a trans-acting variant responds as an activator of the antiviral response; using RNA interference, we identify Rgs16 as the likely causal gene. Our approach charts an experimental and analytic path to decipher the mechanisms underlying genetic variation in circuits that control responses to stimuli.
Howard Hughes Medical Institute
National Institutes of Health (U.S.). Pioneer Award
Burroughs Wellcome Fund (Career Award at the Scientific Interface)
National Human Genome Research Institute (U.S.) (Center for Excellence in Genome Science Grant 5P50HG006193-02)
Klarman Cell Observatory