Subject Categories: Functional genomics
Molecular Systems Biology 7 Article number: 490 doi:10.1038/msb.2011.23
Published online: 24 May 2011
Citation: Molecular Systems Biology 7:490
Characterizing the role of miRNAs within gene regulatory networks using integrative genomics techniques
Wan-Lin Su1,2, Robert R Kleinhanz2 & Eric E Schadt3
Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA
Department of Genetics, Rosetta Inpharmatics LLC, a wholly owned subsidiary of Merck & Co., Inc., Seattle, WA, USA
Department of Genomics and Multiscale Biology, Pacific Biosciences, Menlo Park, CA, USA
Correspondence to: Eric E Schadt3 Department of Genomics and Multiscale Biology, Pacific Biosciences, 1505 Adams Drive, Menlo Park, CA 94025, USA. Tel.: +1 650 521 8025; Fax: +1 650 847 1034; Email: eric.schadt@gmail.com
Received 19 July 2010; Accepted 8 April 2011; Published online 24 May 2011
This is an open-access article distributed under the terms of the Creative Commons Attribution Noncommercial Share Alike 3.0 Unported License, which allows readers to alter, transform, or build upon the article and then distribute the resulting work under the same or similar license to this one. The work must be attributed back to the original author and commercial use is not permitted without specific permission.
Abstract
Integrative genomics and genetics approaches have proven to be a useful tool in elucidating the complex relationships often found in gene regulatory networks. More importantly, a number of studies have provided the necessary experimental evidence confirming the validity of the causal relationships inferred using such an approach. By integrating messenger RNA (mRNA) expression data with microRNA (miRNA) (i.e. small non-coding RNA with well-established regulatory roles in a myriad of biological processes) expression data, we show how integrative genomics approaches can be used to characterize the role played by approximately a third of registered mouse miRNAs within the context of a liver gene regulatory network. Our analysis reveals that the transcript abundances of miRNAs are subject to regulatory control by many more loci than previously observed for mRNA expression. Moreover, our results indicate that miRNAs exist as highly connected hub-nodes and function as key sensors within the transcriptional network. We also provide evidence supporting the hypothesis that miRNAs can act cooperatively or redundantly to regulate a given pathway and that miRNAs play a subtle role by dampening expression of their target gene through the use of feedback loops.
Keywords: causal associations; eQTL mapping; expression QTL; microRNA
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