Abstract

The prediction of novel miRNA genes generally requires the availability of genome sequences in order to assess important properties such as the characteristic hairpin-shaped secondary structure. However, although the sequencing costs have decreased over the last years, still many important species lack an assembled genome of certain quality. We implemented an algorithm which for the first time exploits characteristic biogenesis features like the 5 homogeneity that can be assessed without genome sequences. We used a phylogenetically broad spectrum of well annotated animal genomes for benchmarking. We found that between 90-100% of the most expressed miRNA candidates (top quartile) corresponded to known miRNA sequences.