TY - JOUR
T1 - Isomirs–hidden soldiers in the mirna regulatory army, and how to find them?
AU - Glogovitis, Ilias
AU - Yahubyan, Galina
AU - Würdinger, Thomas
AU - Koppers-Lalic, Danijela
AU - Baev, Vesselin
N1 - Funding Information: Acknowledgments: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 765492, and the National Science Fund of Bulgaria (KΠ-06 H31/2). Funding Information: Funding: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 765492, and the National Science Fund of Bulgaria (KΠ-06 H31/2). Publisher Copyright: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021
Y1 - 2021
N2 - Numerous studies on microRNAs (miRNA) in cancer and other diseases have been ac-companied by diverse computational approaches and experimental methods to predict and validate miRNA biological and clinical significance as easily accessible disease biomarkers. In recent years, the application of the next-generation deep sequencing for the analysis and discovery of novel RNA biomarkers has clearly shown an expanding repertoire of diverse sequence variants of mature miRNAs, or isomiRs, resulting from alternative post-transcriptional processing events, and affected by (patho)physiological changes, population origin, individual’s gender, and age. Here, we provide an in-depth overview of currently available bioinformatics approaches for the detection and visualization of both mature miRNA and cognate isomiR sequences. An attempt has been made to present in a systematic way the advantages and downsides of in silico approaches in terms of their sensitivity and accuracy performance, as well as used methods, workflows, and processing steps, and end output dataset overlapping issues. The focus is given to the challenges and pitfalls of isomiR expression analysis. Specifically, we address the availability of tools enabling research without extensive bioinformatics background to explore this fascinating corner of the small RNAome universe that may facilitate the discovery of new and more reliable disease biomarkers.
AB - Numerous studies on microRNAs (miRNA) in cancer and other diseases have been ac-companied by diverse computational approaches and experimental methods to predict and validate miRNA biological and clinical significance as easily accessible disease biomarkers. In recent years, the application of the next-generation deep sequencing for the analysis and discovery of novel RNA biomarkers has clearly shown an expanding repertoire of diverse sequence variants of mature miRNAs, or isomiRs, resulting from alternative post-transcriptional processing events, and affected by (patho)physiological changes, population origin, individual’s gender, and age. Here, we provide an in-depth overview of currently available bioinformatics approaches for the detection and visualization of both mature miRNA and cognate isomiR sequences. An attempt has been made to present in a systematic way the advantages and downsides of in silico approaches in terms of their sensitivity and accuracy performance, as well as used methods, workflows, and processing steps, and end output dataset overlapping issues. The focus is given to the challenges and pitfalls of isomiR expression analysis. Specifically, we address the availability of tools enabling research without extensive bioinformatics background to explore this fascinating corner of the small RNAome universe that may facilitate the discovery of new and more reliable disease biomarkers.
KW - Data analysis
KW - IsomiRs
KW - MicroRNAs
KW - NGS
KW - Tools
UR - http://www.scopus.com/inward/record.url?scp=85099087366&partnerID=8YFLogxK
U2 - https://doi.org/10.3390/biom11010041
DO - https://doi.org/10.3390/biom11010041
M3 - Review article
C2 - 33396892
SN - 2218-273X
VL - 11
SP - 1
EP - 21
JO - BIOMOLECULES
JF - BIOMOLECULES
IS - 1
M1 - 41
ER -