RT Journal Article SR Electronic T1 The discovery potential of RNA processing profiles JF bioRxiv FD Cold Spring Harbor Laboratory SP 049809 DO 10.1101/049809 A1 Amadís Pagès A1 Ivan Dotu A1 Roderic Guigó A1 Eduardo Eyras YR 2016 UL http://biorxiv.org/content/early/2016/04/22/049809.abstract AB Small non-coding RNAs are highly abundant molecules that regulate essential cellular processes and are classified according to sequence and structure. Here we argue that read profiles from size-selected RNA sequencing, by capturing the post-transcriptional processing specific to each RNA family, provide functional information independently of sequence and structure. SeRPeNT is a computational method that exploits reproducibility across replicates and uses dynamic time-warping and density-based clustering algorithms to identify, characterize and compare small non-coding RNAs, by harnessing the power of read profiles. SeRPeNT is applied to: a) generate an extended human annotation with 671 new RNAs from known classes and 131 from new potential classes, b) show pervasive differential processing between cell compartments and c) predict new molecules with miRNA-like behaviour from snoRNA, tRNA and long non-coding RNA precursors, dependent on the miRNA biogenesis pathway. SeRPeNT facilitates the fast and accurate discovery and characterization of small non-coding RNAs at unprecedented scale.