Article

Mouse let-7 miRNA populations exhibit RNA editing that is constrained in the 5′-seed/ cleavage/anchor regions and stabilize predicted mmu-let-7a:mRNA duplexes

Department of Chemistry, University of Houston, Houston, Texas 77204, USA.
Genome Research (Impact Factor: 13.85). 07/2008; DOI: 10.1101/gr.078246.108
Source: PubMed Central

ABSTRACT Massively parallel sequencing of millions of <30-nt RNAs expressed in mouse ovary, embryonic pancreas (E14.5), and insulin-secreting beta-cells (βTC-3) reveals that ∼50% of the mature miRNAs representing mostly the mmu-let-7 family display internal insertion/deletions and substitutions when compared to precursor miRNA and the mouse genome reference sequences. Approximately, 12%–20% of species associated with mmu-let-7 populations exhibit sequence discrepancies that are dramatically reduced in nucleotides 3–7 (5′-seed) and 10–15 (cleavage and anchor sites). This observation is inconsistent with sequencing error and leads us to propose that the changes arise predominantly from post-transcriptional RNA-editing activity operating on miRNA:target mRNA complexes. Internal nucleotide modifications are most enriched at the ninth nucleotide position. A common ninth base edit of U-to-G results in a significant increase in stability of down-regulated let-7a targets in inhibin-deficient mice (Inha−/−). An excess of U-insertions (14.8%) over U-deletions (1.5%) and the presence of cleaved intermediates suggest that a mammalian TUTase (terminal uridylyl transferase) mediated dUTP-dependent U-insertion/U-deletion cycle may be a possible mechanism. We speculate that mRNA target site-directed editing of mmu-let-7a duplex-bulges stabilizes “loose” miRNA:mRNA target associations and functions to expand the target repertoire and/or enhance mRNA decay over translational repression. Our results also demonstrate that the systematic study of sequence variation within specific RNA classes in a given cell type from millions of sequences generated by next-generation sequencing (NGS) technologies (“intranomics”) can be used broadly to infer functional constraints on specific parts of completely uncharacterized RNAs.

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