Characterizing the role of miRNAs within gene regulatory networks using integrative genomics techniques

• Published in: Molecular systems biology Vol. 7; no. 1; pp. 490 - n/a
• Main Authors: Su, Wan‐Lin, Kleinhanz, Robert R, Schadt, Eric E
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 24.05.2011; John Wiley & Sons, Ltd; EMBO Press; Nature Publishing Group; Springer Nature
• Subjects: Animals; Biological activity; causal associations; Control theory; EMBO09; eQTL mapping; expression QTL; Fat metabolism; Feedback; Feedback loops; Gene expression; Gene Expression Profiling; Gene Regulatory Networks; Genetic diversity; Genetic Linkage; Genetics; Genomics; Genotypes; High-Throughput Screening Assays; Hypotheses; Liver; Loci; Male; Metabolism; Mice; Mice, Inbred C57BL; Mice, Inbred DBA; Mice, Transgenic; microRNA; MicroRNAs; MicroRNAs - genetics; MicroRNAs - metabolism; miRNA; Molecular chains; Networks; Nodes; Oligonucleotide Array Sequence Analysis; Phenotypes; Quantitative Trait Loci; Ribonucleic acid; RNA; RNA, Messenger - genetics; RNA, Messenger - metabolism; Sensors; Transcription; causal associations; expression QTL; microRNA; eQTL mapping
• ISSN: 1744-4292; 1744-4292
• DOI: 10.1038/msb.2011.23

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. By integrating genotype information, microRNA transcript abundances and mRNA expression levels, Eric Schadt and colleagues provide insights into the genetic basis of microRNA gene expression and the role of microRNAs within the liver gene‐regulatory network. Synopsis By integrating genotype information, microRNA transcript abundances and mRNA expression levels, Eric Schadt and colleagues provide insights into the genetic basis of microRNA gene expression and the role of microRNAs within the liver gene‐regulatory network. Since their discovery less than two decades ago, microRNAs (miRNAs) have repeatedly been shown to play a regulatory role in important biological processes. These small single‐stranded molecules have been found to regulate multiple pathways—such as developmental timing in worms; fat metabolism in flies; and stress response in plants—and have been established as key regulatory molecules with potential widespread influence on both fundamental biology and various diseases. In the past decade, a new approach referred to by a number of names (‘integrative genomics’, ‘systems genetics’ or ‘genetical genomics’) has shown increasing levels of success in elucidating the complex relationships found in gene regulatory networks. This approach leverages multiple layers of information (such as genotype, gene expression and phenotype) to infer causal associations that are then used for a number of different purposes, including identifying drivers of diseases and characterizing molecular networks. More importantly, many of the causal relationships that have been identified using this approach have been experimentally tested and verified. By integrating miRNA transcript abundances with messenger RNA (mRNA) expression data and genetic data, we have demonstrated how integrative genomics approaches can be used to characterize the global role played by miRNAs within complex gene regulatory networks. Overall, we investigated approximately 30% of the registered mouse miRNAs with a focus on liver networks. Our analysis reveals that miRNAs exist as highly connected hub nodes and function as key sensors within the gene regulatory network. Further comparisons between the regulatory loci contributing to the variation observed in miRNA and mRNA expression levels indicate that while miRNAs are controlled by more loci than have previously been observed for mRNAs, the contribution from each locus is on average smaller for miRNAs. We also provide evidence supporting two key hypotheses in the field: (i) miRNAs can act cooperatively or redundantly to regulate a given pathway; and (ii) miRNAs may regulate expression of their target gene through the use of feedback loops. This article demonstrates how integrative genomics techniques can be used to investigate novel classes of RNA molecules. Moreover, it represents one of the first examinations of the genetic basis of variation in miRNA gene expression. Our results suggest that miRNA transcript abundances are under more complex regulation than previously observed for mRNA abundances. We also demonstrate that miRNAs typically exist as highly connected hub nodes and function as key sensors within the liver transcriptional network. Additionally, our results provide support for two key hypotheses—namely, 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.