Detection of a microRNA signal in an in vivo expression set of mRNAs.

Tsunglin Liu,Linda Petzold,Kenneth S Kosik,Kathy Puskar,Fernando Santiago,Yohan Lee,Thales Papagiannakopoulos,Boris Shraiman,Stanley F Nelson,William Clay,Kaiqin Lao,Frank Doyle,Shuping Qi,Harley I Kornblum,Laszlo Tora

doi:10.1371/journal.pone.0000804

Abstract

BackgroundmicroRNAs (miRNAs) are approximately 21 nucleotide non-coding transcripts capable of regulating gene expression. The most widely studied mechanism of regulation involves binding of a miRNA to the target mRNA. As a result, translation of the target mRNA is inhibited and the mRNA may be destabilized. The inhibitory effects of miRNAs have been linked to diverse cellular processes including malignant proliferation, apoptosis, development, differentiation, and metabolic processes. We asked whether endogenous fluctuations in a set of mRNA and miRNA profiles contain correlated changes that are statistically distinguishable from the many other fluctuations in the data set.Methodology/Principal FindingsRNA was extracted from 12 human primary brain tumor biopsies. These samples were used to determine genome-wide mRNA expression levels by microarray analysis and a miRNA profile by real-time reverse transcription PCR. Correlation coefficients were determined for all possible mRNA-miRNA pairs and the distribution of these correlations compared to the random distribution. An excess of high positive and negative correlation pairs were observed at the tails of these distributions. Most of these highest correlation pairs do not contain sufficiently complementary sequences to predict a target relationship; nor do they lie in physical proximity to each other. However, by examining pairs in which the significance of the correlation coefficients is modestly relaxed, negative correlations do tend to predict targets and positive correlations tend to predict physically proximate pairs. A subset of high correlation pairs were experimentally validated by over-expressing or suppressing a miRNA and measuring the correlated mRNAs.Conclusions/SignificanceSufficient information exists within a set of tumor samples to detect endogenous correlations between miRNA and mRNA levels. Based on the validations the causal arrow for these correlations is likely to be directed from the miRNAs to the mRNAs. From these data sets, we inferred and validated a tumor suppression pathway linked to miR-181c.

Highlights

MiRNAs regulate both the stability and translatability of their mRNA targets [1]
Following reductions in the level of a protein encoded by a target mRNA, subsequent effects may alter the levels of other mRNAs and changes in miRNA expression will ramify through the transcriptional profile
We asked whether the distribution of 93*7,089 = 659,277 correlation coefficients, r’s, from the data set was significantly different from the random case

Summary

Introduction

MiRNAs regulate both the stability and translatability of their mRNA targets [1]. This regulation occurs by binding of the ,21 nucleotide mature miRNA to an imperfectly matched sequence within the target mRNA in animals. Most descriptions of miRNA function focus either on their role as post-transcriptional regulators of target mRNAs or at a much higher level on their cell biological processes and organismal roles. As the networked link to miRNA fluctuation becomes more distant and diluted, correlative changes in mRNAs may no longer be discernable among the many other factors that control change in mRNA levels across a set of transcriptional profiles. RNA was extracted from 12 human primary brain tumor biopsies These samples were used to determine genome-wide mRNA expression levels by microarray analysis and a miRNA profile by real-time reverse transcription PCR. An excess of high positive and negative correlation pairs were observed at the tails of these distributions Most of these highest correlation pairs do not contain sufficiently complementary sequences to predict a target relationship; nor do they lie in physical proximity to each other. We inferred and validated a tumor suppression pathway linked to miR-181c

Methods

Results

Conclusion