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Computational methods for RNA modification detection from nanopore direct RNA sequencing data.

Authors :
Furlan, Mattia
Delgado-Tejedor, Anna
Mulroney, Logan
Pelizzola, Mattia
Novoa, Eva Maria
Leonardi, Tommaso
Source :
RNA Biology; 2023 Supplement 1, Vol. 18, p31-40, 10p
Publication Year :
2023

Abstract

The covalent modification of RNA molecules is a pervasive feature of all classes of RNAs and has fundamental roles in the regulation of several cellular processes. Mapping the location of RNA modifications transcriptome-wide is key to unveiling their role and dynamic behaviour, but technical limitations have often hampered these efforts. Nanopore direct RNA sequencing is a third-generation sequencing technology that allows the sequencing of native RNA molecules, thus providing a direct way to detect modifications at single-molecule resolution. Despite recent advances, the analysis of nanopore sequencing data for RNA modification detection is still a complex task that presents many challenges. Many works have addressed this task using different approaches, resulting in a large number of tools with different features and performances. Here we review the diverse approaches proposed so far and outline the principles underlying currently available algorithms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15476286
Volume :
18
Database :
Complementary Index
Journal :
RNA Biology
Publication Type :
Academic Journal
Accession number :
164650680
Full Text :
https://doi.org/10.1080/15476286.2021.1978215