Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli.

Nat Biotechnol
Authors
Keywords
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.

Year of Publication
2013
Journal
Nat Biotechnol
Volume
31
Issue
4
Pages
342-9
Date Published
2013 Apr
ISSN
1546-1696
URL
DOI
10.1038/nbt.2519
PubMed ID
23503680
PubMed Central ID
PMC3622156
Links
Grant list
R01 CA119176 / CA / NCI NIH HHS / United States
U54 AI057159 / AI / NIAID NIH HHS / United States
DP1 CA174427 / CA / NCI NIH HHS / United States
DP2 OD002230 / OD / NIH HHS / United States
Howard Hughes Medical Institute / United States
P50 HG006193 / HG / NHGRI NIH HHS / United States
5P50HG006193-02 / HG / NHGRI NIH HHS / United States
S10 RR026688 / RR / NCRR NIH HHS / United States