How Do You Identify m6 A Methylation in Transcriptomes at High Resolution? A Comparison of Recent Datasets

被引:14
作者
Capitanchik, Charlotte [1 ]
Toolan-Kerr, Patrick [1 ,2 ]
Luscombe, Nicholas M. [1 ,3 ,4 ]
Ule, Jernej [1 ,2 ]
机构
[1] Francis Crick Inst, London, England
[2] UCL Queen Sq Inst Neurol, Dept Neuromuscular Dis, London, England
[3] UCL Genet Inst, Dept Genet Environm & Evolut, London, England
[4] Okinawa Inst Sci & Technol Grad Univ, Okinawa, Japan
基金
英国医学研究理事会; 英国惠康基金;
关键词
RNA; N6-methyladenosine; m(6)A; epitranscriptomics; bioinformatics; MESSENGER-RNA METHYLATION; NUCLEOTIDE-SEQUENCES; REVEALS; N-6-METHYLADENOSINE; EXPRESSION; ARRAY; GENE;
D O I
10.3389/fgene.2020.00398
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
A flurry of methods has been developed in recent years to identify N6-methyladenosine (m(6)A) sites across transcriptomes at high resolution. This raises the need to understand both the common features and those that are unique to each method. Here, we complement the analyses presented in the original papers by reviewing their various technical aspects and comparing the overlap between m(6)A-methylated messenger RNAs (mRNAs) identified by each. Specifically, we examine eight different methods that identify m(6)A sites in human cells with high resolution: two antibody-based crosslinking and immunoprecipitation (CLIP) approaches, two using endoribonuclease MazF, one based on deamination, two using Nanopore direct RNA sequencing, and finally, one based on computational predictions. We contrast the respective datasets and discuss the challenges in interpreting the overlap between them, including a prominent expression bias in detected genes. This overview will help guide researchers in making informed choices about using the available data and assist with the design of future experiments to expand our understanding of m(6)A and its regulation.
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页数:12
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