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Mirtrons are intronic hairpin substrates of the dicing machinery that generate functional microRNAs. In this study, we describe experimental assays that defined the essential requirements for entry of introns into the mirtron pathway. These data informed a bioinformatic screen that effectively identified functional mirtrons from the Drosophila melanogaster transcriptome. These included 17 known and six confident novel mirtrons among the top 51 candidates, and additional candidates had limited read evidence in available small RNA data. Our computational model also proved effective on Caenorhabditis elegans, for which the identification of 14 cloned mirtrons among the top 22 candidates more than tripled the number of validated mirtrons in this species. A few low-scoring introns generated mirtron-like read patterns from atypical RNA structures, but their paucity suggests that relatively few such loci were not captured by our model. Unexpectedly, we uncovered examples of clustered mirtrons in both fly and worm genomes, including a &lt;8-kb region in C. elegans harboring eight distinct mirtrons. Altogether, we demonstrate that discovery of functional mirtrons, unlike canonical miRNAs, is amenable to computational methods independent of evolutionary constraint.

Computational and experimental identification of mirtrons in Drosophila melanogaster and Caenorhabditis elegans