Abstract
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.
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Acknowledgements
We thank C. (Jimmie) Ye, J. Pickerel, M. Daly and E. Lander for comments and discussions. I.G.-V. and I.A. were supported by Human Frontiers Science Program postdoctoral fellowships. Work was supported by Howard Hughes Medical Institute, a US National Institutes of Health PIONEER award, a Burroughs-Wellcome Fund Career Award at the Scientific Interface (A.R.), a Center for Excellence in Genome Science grant 5P50HG006193-02 from the National Human Genome Research Institute (N.H. and A.R.), the Klarman Cell Observatory at the Broad Institute (A.R.), the New England Regional Center for Excellence/Biodefense and Emerging Infectious Disease U54 AI057159 (N.H.), the Israeli Centers of Research Excellence (I-CORE) Gene Regulation in Complex Human Disease, Center No. 41/11 (I.G.-V., R.W. and Y.S.), the Human Frontiers Science Program Career Development Award and an Israeli Science Foundation Bikura Institutional Research Grant Program (I.A.) and the Edmond J. Safra Center for Bioinformatics at Tel-Aviv University (R.W. and Y.S.). A.R. is a fellow of the Merkin Foundation for Stem Cell Research at the Broad Institute. I.G.-V. is a Faculty Fellow of the Edmond J. Safra Center for Bioinformatics at Tel Aviv University and an Alon Fellow.
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I.G.-V., I.A. and A.R. conceived and designed the study. N.C., T.E., R.R., A.S. and I.A. conducted the experiments. I.G.-V. and A.R. conceived computational methods. I.G.-V., R.W. and Y.S. conceived, developed and implemented the computational methods. N.H. participated in study design and interpretation. I.G.-V., I.A. and A.R. wrote the manuscript with input from all the authors.
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Supplementary Text and Figures
Supplementary Figures 1–13, Supplementary Tables 1–6 and Supplementary Notes 1–3 (PDF 8508 kb)
Supplementary Table 7
Dataset 1 (XLS 761 kb)
Supplementary Table 8
Dataset 2 (XLS 739 kb)
Supplementary Table 9
Dataset 3 (XLS 746 kb)
Supplementary Table 10
Dataset 4 (XLS 761 kb)
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Gat-Viks, I., Chevrier, N., Wilentzik, R. et al. Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli. Nat Biotechnol 31, 342–349 (2013). https://doi.org/10.1038/nbt.2519
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DOI: https://doi.org/10.1038/nbt.2519
