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m(6)A Reader: Epitranscriptome Target Prediction and Functional Characterization of N(6)-Methyladenosine (m(6)A) Readers

N(6)-methyladenosine (m(6)A) is the most abundant post-transcriptional modification in mRNA, and regulates critical biological functions via m(6)A reader proteins that bind to m(6)A-containing transcripts. There exist multiple m(6)A reader proteins in the human genome, but their respective binding s...

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Autores principales: Zhen, Di, Wu, Yuxuan, Zhang, Yuxin, Chen, Kunqi, Song, Bowen, Xu, Haiqi, Tang, Yujiao, Wei, Zhen, Meng, Jia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7431669/
https://www.ncbi.nlm.nih.gov/pubmed/32850851
http://dx.doi.org/10.3389/fcell.2020.00741
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author Zhen, Di
Wu, Yuxuan
Zhang, Yuxin
Chen, Kunqi
Song, Bowen
Xu, Haiqi
Tang, Yujiao
Wei, Zhen
Meng, Jia
author_facet Zhen, Di
Wu, Yuxuan
Zhang, Yuxin
Chen, Kunqi
Song, Bowen
Xu, Haiqi
Tang, Yujiao
Wei, Zhen
Meng, Jia
author_sort Zhen, Di
collection PubMed
description N(6)-methyladenosine (m(6)A) is the most abundant post-transcriptional modification in mRNA, and regulates critical biological functions via m(6)A reader proteins that bind to m(6)A-containing transcripts. There exist multiple m(6)A reader proteins in the human genome, but their respective binding specificity and functional relevance under different biological contexts are not yet fully understood due to the limitation of experimental approaches. An in silico study was devised to unveil the target specificity and regulatory functions of different m(6)A readers. We established a support vector machine-based computational framework to predict the epitranscriptome-wide targets of six m(6)A reader proteins (YTHDF1-3, YTHDC1-2, and EIF3A) based on 58 genomic features as well as the conventional sequence-derived features. Our model achieved an average AUC of 0.981 and 0.893 under the full-transcript and mature mRNA model, respectively, marking a substantial improvement in accuracy compared to the sequence encoding schemes tested. Additionally, the distinct biological characteristics of each individual m(6)A reader were explored via the distribution, conservation, Gene Ontology enrichment, cellular components and molecular functions of their target m(6)A sites. A web server was constructed for predicting the putative binding readers of m(6)A sites to serve the research community, and is freely accessible at: http://m6areader.rnamd.com.
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spelling pubmed-74316692020-08-25 m(6)A Reader: Epitranscriptome Target Prediction and Functional Characterization of N(6)-Methyladenosine (m(6)A) Readers Zhen, Di Wu, Yuxuan Zhang, Yuxin Chen, Kunqi Song, Bowen Xu, Haiqi Tang, Yujiao Wei, Zhen Meng, Jia Front Cell Dev Biol Cell and Developmental Biology N(6)-methyladenosine (m(6)A) is the most abundant post-transcriptional modification in mRNA, and regulates critical biological functions via m(6)A reader proteins that bind to m(6)A-containing transcripts. There exist multiple m(6)A reader proteins in the human genome, but their respective binding specificity and functional relevance under different biological contexts are not yet fully understood due to the limitation of experimental approaches. An in silico study was devised to unveil the target specificity and regulatory functions of different m(6)A readers. We established a support vector machine-based computational framework to predict the epitranscriptome-wide targets of six m(6)A reader proteins (YTHDF1-3, YTHDC1-2, and EIF3A) based on 58 genomic features as well as the conventional sequence-derived features. Our model achieved an average AUC of 0.981 and 0.893 under the full-transcript and mature mRNA model, respectively, marking a substantial improvement in accuracy compared to the sequence encoding schemes tested. Additionally, the distinct biological characteristics of each individual m(6)A reader were explored via the distribution, conservation, Gene Ontology enrichment, cellular components and molecular functions of their target m(6)A sites. A web server was constructed for predicting the putative binding readers of m(6)A sites to serve the research community, and is freely accessible at: http://m6areader.rnamd.com. Frontiers Media S.A. 2020-08-11 /pmc/articles/PMC7431669/ /pubmed/32850851 http://dx.doi.org/10.3389/fcell.2020.00741 Text en Copyright © 2020 Zhen, Wu, Zhang, Chen, Song, Xu, Tang, Wei and Meng. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cell and Developmental Biology
Zhen, Di
Wu, Yuxuan
Zhang, Yuxin
Chen, Kunqi
Song, Bowen
Xu, Haiqi
Tang, Yujiao
Wei, Zhen
Meng, Jia
m(6)A Reader: Epitranscriptome Target Prediction and Functional Characterization of N(6)-Methyladenosine (m(6)A) Readers
title m(6)A Reader: Epitranscriptome Target Prediction and Functional Characterization of N(6)-Methyladenosine (m(6)A) Readers
title_full m(6)A Reader: Epitranscriptome Target Prediction and Functional Characterization of N(6)-Methyladenosine (m(6)A) Readers
title_fullStr m(6)A Reader: Epitranscriptome Target Prediction and Functional Characterization of N(6)-Methyladenosine (m(6)A) Readers
title_full_unstemmed m(6)A Reader: Epitranscriptome Target Prediction and Functional Characterization of N(6)-Methyladenosine (m(6)A) Readers
title_short m(6)A Reader: Epitranscriptome Target Prediction and Functional Characterization of N(6)-Methyladenosine (m(6)A) Readers
title_sort m(6)a reader: epitranscriptome target prediction and functional characterization of n(6)-methyladenosine (m(6)a) readers
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7431669/
https://www.ncbi.nlm.nih.gov/pubmed/32850851
http://dx.doi.org/10.3389/fcell.2020.00741
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