Abstract
RNA interference (RNAi) is mediated by small (20-30 nucleotide) RNAs that are produced by complex processing pathways. In animals, three main classes are recognized: microRNAs (miRNAs), small-interfering RNAs (siRNAs) and piwi-interacting RNAs (piRNAs). Understanding of small RNA pathways has benefited from genetic models where key enzymatic events were identified that lead to stereotypical positioning of small RNAs relative to precursor transcripts. Increasingly there is interest in using RNAi in non-model systems due to ease of generating synthetic small RNA precursors for research and biotechnology. Unfortunately, small RNAs are often rapidly evolving, requiring investigation of a species' endogenous small RNAs prior to deploying an RNAi approach. This can be accomplished through small non-coding RNA sequencing followed by applying various computational tools; however, the complexity and separately maintained packages lead to significant challenges for annotating global small RNA populations. To address this need, we developed a simple and efficient R package (MiSiPi-Rna) which can be used to characterize pre-selected loci with plots and statistics, aiding researchers understanding RNAi biology specific to their target species. Additionally, MiSiPi-Rna pioneers several computational approaches to identifying Dicer processing to assist annotation of miRNA and siRNA.