Integrated network analysis reveals distinct regulatory roles of transcription factors and microRNAs.
Analysis of transcription regulatory networks has revealed many principal features that govern gene expression regulation. MicroRNAs (miRNAs) have emerged as another major class of gene regulators that influence gene expression post-transcriptionally, but there remains a need to assess quantitatively their global roles in gene regulation. Here, we have constructed an integrated gene regulatory network comprised of transcription factors (TFs), miRNAs, and their target genes and analyzed the effect of regulation on target mRNA expression, target protein expression, protein-protein interaction, and disease association. We found that while target genes regulated by the same TFs tend to be co-expressed, co-regulation by miRNAs does not lead to co-expression assessed at either mRNA or protein levels. Analysis of interacting protein pairs in the regulatory network revealed that compared to genes co-regulated by miRNAs, a higher fraction of genes co-regulated by TFs encode proteins in the same complex. Although these results suggest that genes co-regulated by TFs are more functionally related than those co-regulated by miRNAs, genes that share either TF or miRNA regulators are more likely to cause the same disease. Further analysis on the interplay between TFs and miRNAs suggests that TFs tend to regulate intramodule/pathway clusters, while miRNAs tend to regulate intermodule/pathway clusters. These results demonstrate that although TFs and miRNAs both regulate gene expression, they occupy distinct niches in the overall regulatory network within the cell.
Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York 14853, USA.|Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York 14853, USA.|Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA.
Yu
Y
Guo
Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA.
Katherine
K
Alexander
Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York 14853, USA.|Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA.
Andrew G
AG
Clark
Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA.
Andrew
A
Grimson
Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York 14853, USA.|Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York 14853, USA.
Haiyuan
H
Yu
D015870:Gene Expression / Q000502:physiology; D053263:Gene Regulatory Networks; D035683:MicroRNAs / Q000502:physiology*; D011506:Proteins / Q000235:genetics; D012313:RNA / Q000235:genetics; D014157:Transcription Factors / Q000502:physiology*
D035683:MicroRNAs; D011506:Proteins; D014157:Transcription Factors; D012313:RNA
biological networks; gene regulation