Desperately seeking microRNA targets

• Published in: Nature structural & molecular biology Vol. 17; no. 10; pp. 1169 - 1174
• Main Authors: Thomas, Marshall, Lieberman, Judy, Lal, Ashish
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.10.2010; Nature Publishing Group
• Subjects: 3' Untranslated Regions; 631/114; 631/337/384/331; Algorithms; Animals; Autoantigens - physiology; Base Pairing; Base Sequence; Binding Sites; Biochemistry; Biological Microscopy; Biomedical and Life Sciences; Caenorhabditis elegans - genetics; Cellular biology; Computational Biology - methods; Databases, Genetic; Decay; Deoxyribonucleic acid; DNA; Gene expression; Gene Expression Regulation; Gene Knockdown Techniques; Gene Regulatory Networks; Humans; Life Sciences; Membrane Biology; Mice; MicroRNA; MicroRNAs - physiology; Molecular biology; Oligonucleotide Array Sequence Analysis; perspective; Protein Structure; Proteomics; Ribonucleic acid; RNA; RNA Stability; RNA, Messenger - genetics; RNA, Messenger - metabolism; RNA-Binding Proteins - physiology; RNA-Induced Silencing Complex - physiology; United States
• ISSN: 1545-9993; 1545-9985; 1545-9985
• DOI: 10.1038/nsmb.1921

MicroRNAs (miRNAs) suppress gene expression by inhibiting translation, promoting mRNA decay or both. Each miRNA may regulate hundreds of genes to control the cell's response to developmental and other environmental cues. The best way to understand the function of a miRNA is to identify the genes that it regulates. Target gene identification is challenging because miRNAs bind to their target mRNAs by partial complementarity over a short sequence, suppression of an individual target gene is often small, and the rules of targeting are not completely understood. Here we review computational and experimental approaches to the identification of miRNA-regulated genes. The examination of changes in gene expression that occur when miRNA expression is altered and biochemical isolation of miRNA-associated transcripts complement target prediction algorithms. Bioinformatic analysis of over-represented pathways and nodes in protein-DNA interactomes formed from experimental candidate miRNA gene target lists can focus attention on biologically significant target genes.