m6A Reader: Epitranscriptome Target Prediction and Functional Characterization of N6-Methyladenosine (m6A) Readers

被引:39
作者
Zhen, Di [1 ]
Wu, Yuxuan [1 ]
Zhang, Yuxin [1 ]
Chen, Kunqi [1 ,2 ]
Song, Bowen [3 ,4 ]
Xu, Haiqi [1 ]
Tang, Yujiao [1 ,4 ]
Wei, Zhen [1 ,2 ]
Meng, Jia [1 ,4 ,5 ]
机构
[1] Xian Jiaotong Liverpool Univ, Dept Biol Sci, Suzhou, Peoples R China
[2] Univ Liverpool, Inst Ageing & Chron Dis, Liverpool, Merseyside, England
[3] Xian Jiaotong Liverpool Univ, Dept Math Sci, Suzhou, Peoples R China
[4] Univ Liverpool, Inst Integrat Biol, Liverpool, Merseyside, England
[5] Xian Jiaotong Liverpool Univ, AI Univ Res Ctr, Suzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
N6-methyladenosine; m(6)A reader; machine learning (ML); YTH domain; eIF3a; MESSENGER-RNA METHYLATION; WEB SERVER; IDENTIFICATION; BINDING; PROTEIN; SITES; TRANSLATION; NUCLEOSIDES; DATABASE; WRITERS;
D O I
10.3389/fcell.2020.00741
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
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. Anin silicostudy 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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页数:14
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