Working together: Combinatorial regulation by microRNAs

Yitzhak Friedman, Ohad Balaga, Michal Linial*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

22 Scopus citations

Abstract

MicroRNAs (miRNAs) negatively regulate gene expression level of mRNA post-transcriptionally. Deep sequencing and large-scale screening methods have yielded about 1,500 miRNA sequences in human. Each miRNA contains a seed sequence that is required, but not sufficient, for the correct matching with its targets. Recent technological advances make it possible to capture the miRNAs with their cognate mRNAs at the RISC complex. These experiments have revealed thousands of validated mRNA-miRNA pairing events. In the context of human stem cells, 90% of the identified transcripts appear to be paired with at least two different miRNAs. In this chapter, we present a comprehensive outline for a combinatorial regulation mode by miRNAs. Initially, we summarize the computational and experimental evidence that support a combined effect of multiple miRNAs. Then, we describe miRror2.0, a platform specifically convened to consider the likelihood of miRNAs cooperativity in view of the targets, tissues and cell lines. We show that results from miRror2.0 can be further refined by an iterative procedure, calls Psi-miRror that gauges the robustness of the regulation. We illustrate the combinatorial regulation projected onto graphs of human pathways and show that these pathways are amenable to disruption by a small set of miRNAs. Finally, we propose that miRNA combinatorial regulation is an attractive regulatory strategy not only at the level of single target, but also at the level of pathways and cellular homeostasis. The joint operation of miRNAs is a powerful means to overcome the low specificity inherent in each individual miRNA.

Original languageAmerican English
Title of host publicationMicroRNA Cancer Regulation
Subtitle of host publicationAdvanced Concepts, Bioinformatics and Systems Biology Tools
PublisherSpringer New York LLC
Pages317-337
Number of pages21
ISBN (Print)9789400755895
DOIs
StatePublished - 2013

Publication series

NameAdvances in Experimental Medicine and Biology
Volume774
ISSN (Print)0065-2598

Keywords

  • 3′ -UTR
  • Bioinformatics
  • Database
  • Deep sequencing
  • Genomics
  • MicroRNA
  • Prediction tools
  • Regulatory pathway

Fingerprint

Dive into the research topics of 'Working together: Combinatorial regulation by microRNAs'. Together they form a unique fingerprint.

Cite this