MicroRNAs (miRNAs) are small regulatory RNAs processed from stem-loop regions of primary transcripts (pri-miRNAs), with the choice of stem loops for initial processing largely determining what becomes a miRNA. To identify sequence and structural features influencing this choice, we determined cleavage efficiencies of >50,000 variants of three human pri-miRNAs, focusing on the regions intractable to previous high-throughput analyses. Our analyses revealed a mismatched motif in the basal stem region, a preference for maintaining or improving base pairing throughout the remainder of the stem, and a narrow stem-length preference of 35 ± 1 base pairs. Incorporating these features with previously identified features, including three primary-sequence motifs, yielded a unifying model defining mammalian pri-miRNAs in which motifs help orient processing and increase efficiency, with the presence of more motifs compensating for structural defects. This model enables generation of artificial pri-miRNAs, designed de novo, without reference to any natural sequence yet processed more efficiently than natural pri-miRNAs.
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