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Motivation: Most computational tools for small non-coding RNAs (sRNA) sequencing data analysis focus in microRNAs (miRNAs), overlooking other types of sRNAs that show multi-mapping hits. Here, we have developed a pipeline to non-redundantly quantify all types of sRNAs, and extract patterns of expression in biologically defined groups. We have used our tool to characterize and profile sRNAs in post-mortem brain samples of control individuals and Parkinson's disease (PD) cases at early-premotor and late-symptomatic stages. Results: Clusters of co-expressed sRNAs mapping onto tRNAs significantly separated premotor and motor cases from controls. A similar result was obtained using a matrix of miRNAs slightly varying in sequence (isomiRs). The present framework revealed sRNA alterations at premotor stages of PD, which might reflect initial pathogenic perturbations. This tool may be useful to discover sRNA expression patterns linked to different biological conditions. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are small RNA molecules involved in the regulation of mammalian gene expression. Together with other transcription regulators, miRNAs modulate the expression of genes and thereby potentially contribute to tissue and species diversity. To identify miRNAs that are differentially expressed between tissues and/or species, and the genes regulated by these, we have quantified expression of miRNAs and messenger RNAs in five tissues from multiple human, chimpanzee, and rhesus macaque individuals using high-throughput sequencing. The breadth of this tissue and species data allows us to show that downregulation of target genes by miRNAs is more pronounced between tissues than between species and that downregulation is more pronounced for genes with fewer binding sites for expressed miRNAs. Intriguingly, we find that tissue- and species-specific miRNAs target transcription factor genes (TFs) significantly more often than expected. Through their regulatory effect on transcription factors, miRNAs may therefore exert an indirect influence on a larger proportion of genes than previously thought. [ABSTRACT FROM AUTHOR]