2026-04-14T05:45:12Zhttps://recercat.cat/oai/request
oai:recercat.cat:2445/1372852025-12-04T19:01:55Zcom_2072_1057col_2072_478777col_2072_478780col_2072_478916col_2072_478917col_2072_478929
RECERCAT author Pantano, Lorena author Friedlaender, Marc R. author Escaramís Babiano, Geòrgia author Lizano, Esther author Pallarès Albanell, Joan author Ferrer, Isidro (Ferrer Abizanda) author Estivill, Xavier, 1955- author Martí Puig, Eulàlia 2019-07-16T12:38:06Z2019-07-16T12:38:06Z2016-03-012019-07-16T12:38:06Z 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. (c) Pantano, Lorena et al., 2016 info:eu-repo/semantics/openAccess Malaltia de Parkinson RNA Parkinson's disease RNA Specific small-RNA signatures in the amygdala at premotor and motor stages of Parkinson's disease revealed by deep sequencing analysis info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion