search for conserved sequences in coding regions reveals that the let-7 microRNA targets Dicer within its coding sequence

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 105; no. 39; pp. 14879 - 14884
• Main Authors: Forman, Joshua J, Legesse-Miller, Aster, Coller, Hilary A
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 30.09.2008; National Acad Sciences
• Subjects: 3' untranslated regions; Algorithms; Amino acids; Animals; Base Sequence; Binding sites; Biological Sciences; Cattle; Codons; Computational Biology; Conserved Sequence; conserved sequences; Datasets; Dogs; Down regulation; Evolution; Feedback, Physiological - genetics; Genes; Genomes; Genomics; Humans; Mice; MicroRNA; MicroRNAs - metabolism; Rabbits; Rats; Ribonuclease III - genetics; Ribonucleic acid; Ribozymes; RNA; Sequence Analysis, DNA; Software; Untranslated regions
• ISSN: 0027-8424; 1091-6490; 1091-6490
• DOI: 10.1073/pnas.0803230105

Recognition sites for microRNAs (miRNAs) have been reported to be located in the 3' untranslated regions of transcripts. In a computational screen for highly conserved motifs within coding regions, we found an excess of sequences conserved at the nucleotide level within coding regions in the human genome, the highest scoring of which are enriched for miRNA target sequences. To validate our results, we experimentally demonstrated that the let-7 miRNA directly targets the miRNA-processing enzyme Dicer within its coding sequence, thus establishing a mechanism for a miRNA/Dicer autoregulatory negative feedback loop. We also found computational evidence to suggest that miRNA target sites in coding regions and 3' UTRs may differ in mechanism. This work demonstrates that miRNAs can directly target transcripts within their coding region in animals, and it suggests that a complete search for the regulatory targets of miRNAs should be expanded to include genes with recognition sites within their coding regions. As more genomes are sequenced, the methodological approach that we used for identifying motifs with high sequence conservation will be increasingly valuable for detecting functional sequence motifs within coding regions.