TY - JOUR
T1 - A Stringent Systems Approach Uncovers Gene-Specific Mechanisms Regulating Inflammation
AU - Tong, Ann Jay
AU - Liu, Xin
AU - Thomas, Brandon J.
AU - Lissner, Michelle M.
AU - Baker, Mairead R.
AU - Senagolage, Madhavi D.
AU - Allred, Amanda L.
AU - Barish, Grant D.
AU - Smale, Stephen T.
N1 - Funding Information:
We thank Christopher Glass, Alexander Hoffmann, Steven Ley, Ranjan Sen, and Trevor Siggers for helpful discussions, and the UCLA Broad Stem Cell Research Center Core for sequencing. This work was supported by NIH grants R01GM086372 (S.T.S.), P50AR063030 (S.T.S.), T32CA009120 (A.-J.T.), and T32GM008042 (B.J.T.), and by the China Scholarship Council and Whitcome pre-doctoral training program (X.L.). Received: July 17, 2015 Revised: November 1, 2015 Accepted: January 13, 2016 Published: February 25, 2011.
Funding Information:
We thank Christopher Glass, Alexander Hoffmann, Steven Ley, Ranjan Sen, and Trevor Siggers for helpful discussions, and the UCLA Broad Stem Cell Research Center Core for sequencing. This work was supported by NIH grants R01GM086372 (S.T.S.), P50AR063030 (S.T.S.), T32CA009120 (A.-J.T.), and T32GM008042 (B.J.T.), and by the China Scholarship Council and Whitcome pre-doctoral training program (X.L.).
Publisher Copyright:
© 2016 Elsevier Inc.
PY - 2016/3/24
Y1 - 2016/3/24
N2 - Summary Much has been learned about transcriptional cascades and networks from large-scale systems analyses of high-throughput datasets. However, analysis methods that optimize statistical power through simultaneous evaluation of thousands of ChIP-seq peaks or differentially expressed genes possess substantial limitations in their ability to uncover mechanistic principles of transcriptional control. By examining nascent transcript RNA-seq, ChIP-seq, and binding motif datasets from lipid A-stimulated macrophages with increased attention to the quantitative distribution of signals, we identified unexpected relationships between the in vivo binding properties of inducible transcription factors, motif strength, and transcription. Furthermore, rather than emphasizing common features of large clusters of co-regulated genes, our results highlight the extent to which unique mechanisms regulate individual genes with key biological functions. Our findings demonstrate the mechanistic value of stringent interrogation of well-defined sets of genes as a complement to broader systems analyses of transcriptional cascades and networks.
AB - Summary Much has been learned about transcriptional cascades and networks from large-scale systems analyses of high-throughput datasets. However, analysis methods that optimize statistical power through simultaneous evaluation of thousands of ChIP-seq peaks or differentially expressed genes possess substantial limitations in their ability to uncover mechanistic principles of transcriptional control. By examining nascent transcript RNA-seq, ChIP-seq, and binding motif datasets from lipid A-stimulated macrophages with increased attention to the quantitative distribution of signals, we identified unexpected relationships between the in vivo binding properties of inducible transcription factors, motif strength, and transcription. Furthermore, rather than emphasizing common features of large clusters of co-regulated genes, our results highlight the extent to which unique mechanisms regulate individual genes with key biological functions. Our findings demonstrate the mechanistic value of stringent interrogation of well-defined sets of genes as a complement to broader systems analyses of transcriptional cascades and networks.
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U2 - 10.1016/j.cell.2016.01.020
DO - 10.1016/j.cell.2016.01.020
M3 - Article
C2 - 26924576
AN - SCOPUS:84975784410
VL - 165
SP - 165
EP - 179
JO - Cell
JF - Cell
SN - 0092-8674
IS - 1
ER -