TY - JOUR T1 - The discovery potential of RNA processing profiles JF - bioRxiv DO - 10.1101/049809 SP - 049809 AU - Amadís Pagès AU - Ivan Dotu AU - Roderic Guigó AU - Eduardo Eyras Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/04/22/049809.abstract N2 - 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. ER -