Biclustering analysis of transcriptome big data identifies condition-specific microRNA targets

Nucleic Acids Research
Sora YoonDougu Nam

Abstract

We present a novel approach to identify human microRNA (miRNA) regulatory modules (mRNA targets and relevant cell conditions) by biclustering a large collection of mRNA fold-change data for sequence-specific targets. Bicluster targets were assessed using validated messenger RNA (mRNA) targets and exhibited on an average 17.0% (median 19.4%) improved gain in certainty (sensitivity + specificity). The net gain was further increased up to 32.0% (median 33.4%) by incorporating functional networks of targets. We analyzed cancer-specific biclusters and found that the PI3K/Akt signaling pathway is strongly enriched with targets of a few miRNAs in breast cancer and diffuse large B-cell lymphoma. Indeed, five independent prognostic miRNAs were identified, and repression of bicluster targets and pathway activity by miR-29 was experimentally validated. In total, 29 898 biclusters for 459 human miRNAs were collected in the BiMIR database where biclusters are searchable for miRNAs, tissues, diseases, keywords and target genes.

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Citations

Jun 30, 2019·GigaScience·Patryk OrzechowskiJason H Moore
Nov 12, 2020·Frontiers in Genetics·Chenchen XiongJunpeng Zhang
Mar 5, 2021·Life Science Alliance·Elena A AfanasyevaFrank Westermann
Oct 5, 2021·Genome Génome / Conseil National De Recherches Canada·Ayse Gokce KeskusOzlen Konu

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Datasets Mentioned

BETA
GSE22216

Methods Mentioned

BETA
transfection
PCR
protein
electrophoresis
ISA

Software Mentioned

ISA
miRanda
Perl
MATLAB
BiMIR R
DIANA
mirSVR
TargetScan
R ‘ affy ’ package
DAVID

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