Journal
BIOINFORMATICS
Volume 32, Issue 5, Pages 673-681Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btv632
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Funding
- Spanish Government
- Instituto Carlos III - ISCIII
- European Regional Development Fund (ERDF): PN de I+D+I [PI11/02036, PI1100968]
- Subdireccion General de Evaluacion y Fomento de la Investigacion [SAF2008-00357, SAF2014-60551-R]
- Generalitat de Catalunya [SGR-1502]
- European Union Seventh Framework Programme (FP7) [278486, 62055, 261123]
- Lilly Foundation
- EMBO long-term fellowship
- Spanish Ministry of Economy and Competitiveness, 'Centro de Excelencia Severo Ochoa' [SEV-2012-0208]
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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.
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