Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics

Lian Liu; Bowen Song; Jiani Ma; Yi Song; Song Yao Zhang; Yujiao Tang; Xiangyu Wu; Zhen Wei; Kunqi Chen; Jionglong Su; Rong Rong; Zhiliang Lu; João Pedro de Magalhães; Daniel J. Rigden; Lin Zhang; Shao Wu Zhang; Yufei Huang; Xiujuan Lei; Hui Liu; Jia Meng

doi:10.1016/j.csbj.2020.06.010

Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics

Lian Liu, Bowen Song, Jiani Ma, Yi Song, Song Yao Zhang, Yujiao Tang, Xiangyu Wu, Zhen Wei, Kunqi Chen, Jionglong Su, Rong Rong, Zhiliang Lu, João Pedro de Magalhães, Daniel J. Rigden, Lin Zhang, Shao Wu Zhang, Yufei Huang, Xiujuan Lei^*, Hui Liu, Jia Meng

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

43 Citations (Scopus)

Abstract

Post-transcriptional RNA modification occurs on all types of RNA and plays a vital role in regulating every aspect of RNA function. Thanks to the development of high-throughput sequencing technologies, transcriptome-wide profiling of RNA modifications has been made possible. With the accumulation of a large number of high-throughput datasets, bioinformatics approaches have become increasing critical for unraveling the epitranscriptome. We review here the recent progress in bioinformatics approaches for deciphering the epitranscriptomes, including epitranscriptome data analysis techniques, RNA modification databases, disease-association inference, general functional annotation, and studies on RNA modification site prediction. We also discuss the limitations of existing approaches and offer some future perspectives.

Original language	English
Pages (from-to)	1587-1604
Number of pages	18
Journal	Computational and Structural Biotechnology Journal
Volume	18
DOIs	https://doi.org/10.1016/j.csbj.2020.06.010
Publication status	Published - 2020

Keywords

Bioinformatics approaches
Epitranscriptome
Future perspective
RNA modification
Recent progress

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10.1016/j.csbj.2020.06.010

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Liu, L., Song, B., Ma, J., Song, Y., Zhang, S. Y., Tang, Y., Wu, X., Wei, Z., Chen, K., Su, J., Rong, R., Lu, Z., de Magalhães, J. P., Rigden, D. J., Zhang, L., Zhang, S. W., Huang, Y., Lei, X., Liu, H., & Meng, J. (2020). Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics. Computational and Structural Biotechnology Journal, 18, 1587-1604. https://doi.org/10.1016/j.csbj.2020.06.010

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title = "Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics",

abstract = "Post-transcriptional RNA modification occurs on all types of RNA and plays a vital role in regulating every aspect of RNA function. Thanks to the development of high-throughput sequencing technologies, transcriptome-wide profiling of RNA modifications has been made possible. With the accumulation of a large number of high-throughput datasets, bioinformatics approaches have become increasing critical for unraveling the epitranscriptome. We review here the recent progress in bioinformatics approaches for deciphering the epitranscriptomes, including epitranscriptome data analysis techniques, RNA modification databases, disease-association inference, general functional annotation, and studies on RNA modification site prediction. We also discuss the limitations of existing approaches and offer some future perspectives.",

keywords = "Bioinformatics approaches, Epitranscriptome, Future perspective, RNA modification, Recent progress",

author = "Lian Liu and Bowen Song and Jiani Ma and Yi Song and Zhang, {Song Yao} and Yujiao Tang and Xiangyu Wu and Zhen Wei and Kunqi Chen and Jionglong Su and Rong Rong and Zhiliang Lu and {de Magalh{\~a}es}, {Jo{\~a}o Pedro} and Rigden, {Daniel J.} and Lin Zhang and Zhang, {Shao Wu} and Yufei Huang and Xiujuan Lei and Hui Liu and Jia Meng",

note = "Publisher Copyright: {\textcopyright} 2020 The Author(s)",

year = "2020",

doi = "10.1016/j.csbj.2020.06.010",

language = "English",

volume = "18",

pages = "1587--1604",

journal = "Computational and Structural Biotechnology Journal",

issn = "2001-0370",

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Liu, L, Song, B, Ma, J, Song, Y, Zhang, SY, Tang, Y, Wu, X, Wei, Z, Chen, K, Su, J , Rong, R , Lu, Z, de Magalhães, JP, Rigden, DJ, Zhang, L, Zhang, SW, Huang, Y, Lei, X, Liu, H & Meng, J 2020, 'Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics', Computational and Structural Biotechnology Journal, vol. 18, pp. 1587-1604. https://doi.org/10.1016/j.csbj.2020.06.010

TY - JOUR

T1 - Bioinformatics approaches for deciphering the epitranscriptome

T2 - Recent progress and emerging topics

AU - Liu, Lian

AU - Song, Bowen

AU - Ma, Jiani

AU - Song, Yi

AU - Zhang, Song Yao

AU - Tang, Yujiao

AU - Wu, Xiangyu

AU - Wei, Zhen

AU - Chen, Kunqi

AU - Su, Jionglong

AU - Rong, Rong

AU - Lu, Zhiliang

AU - de Magalhães, João Pedro

AU - Rigden, Daniel J.

AU - Zhang, Lin

AU - Zhang, Shao Wu

AU - Huang, Yufei

AU - Lei, Xiujuan

AU - Liu, Hui

AU - Meng, Jia

PY - 2020

Y1 - 2020

N2 - Post-transcriptional RNA modification occurs on all types of RNA and plays a vital role in regulating every aspect of RNA function. Thanks to the development of high-throughput sequencing technologies, transcriptome-wide profiling of RNA modifications has been made possible. With the accumulation of a large number of high-throughput datasets, bioinformatics approaches have become increasing critical for unraveling the epitranscriptome. We review here the recent progress in bioinformatics approaches for deciphering the epitranscriptomes, including epitranscriptome data analysis techniques, RNA modification databases, disease-association inference, general functional annotation, and studies on RNA modification site prediction. We also discuss the limitations of existing approaches and offer some future perspectives.

AB - Post-transcriptional RNA modification occurs on all types of RNA and plays a vital role in regulating every aspect of RNA function. Thanks to the development of high-throughput sequencing technologies, transcriptome-wide profiling of RNA modifications has been made possible. With the accumulation of a large number of high-throughput datasets, bioinformatics approaches have become increasing critical for unraveling the epitranscriptome. We review here the recent progress in bioinformatics approaches for deciphering the epitranscriptomes, including epitranscriptome data analysis techniques, RNA modification databases, disease-association inference, general functional annotation, and studies on RNA modification site prediction. We also discuss the limitations of existing approaches and offer some future perspectives.

KW - Bioinformatics approaches

KW - Epitranscriptome

KW - Future perspective

KW - RNA modification

KW - Recent progress

UR - http://www.scopus.com/inward/record.url?scp=85087151967&partnerID=8YFLogxK

U2 - 10.1016/j.csbj.2020.06.010

DO - 10.1016/j.csbj.2020.06.010

M3 - Review article

AN - SCOPUS:85087151967

SN - 2001-0370

VL - 18

SP - 1587

EP - 1604

JO - Computational and Structural Biotechnology Journal

JF - Computational and Structural Biotechnology Journal

ER -

Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics

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Keywords

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