Transcriptome-wide profiling and quantification of N6-methyladenosine by enzyme-assisted adenosine deamination

被引:0
|
作者
Yu-Lan Xiao
Shun Liu
Ruiqi Ge
Yuan Wu
Chuan He
Mengjie Chen
Weixin Tang
机构
[1] The University of Chicago,Department of Chemistry
[2] The University of Chicago,Institute for Biophysical Dynamics
[3] The University of Chicago,Howard Hughes Medical Institute
[4] The University of Chicago,Department of Medicine
[5] The University of Chicago,Department of Human Genetics
[6] The University of Chicago,Department of Biochemistry and Molecular Biology
来源
Nature Biotechnology | 2023年 / 41卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
N6-methyladenosine (m6A), the most abundant internal messenger RNA modification in higher eukaryotes, serves myriad roles in regulating cellular processes. Functional dissection of m6A is, however, hampered in part by the lack of high-resolution and quantitative detection methods. Here we present evolved TadA-assisted N6-methyladenosine sequencing (eTAM-seq), an enzyme-assisted sequencing technology that detects and quantifies m6A by global adenosine deamination. With eTAM-seq, we analyze the transcriptome-wide distribution of m6A in HeLa and mouse embryonic stem cells. The enzymatic deamination route employed by eTAM-seq preserves RNA integrity, facilitating m6A detection from limited input samples. In addition to transcriptome-wide m6A profiling, we demonstrate site-specific, deep-sequencing-free m6A quantification with as few as ten cells, an input demand orders of magnitude lower than existing quantitative profiling methods. We envision that eTAM-seq will enable researchers to not only survey the m6A landscape at unprecedented resolution, but also detect m6A at user-specified loci with a simple workflow.
引用
收藏
页码:993 / 1003
页数:10
相关论文
共 50 条
  • [1] Transcriptome-wide profiling and quantification of N6-methyladenosine by enzyme-assisted adenosine deamination
    Xiao, Yu-Lan
    Liu, Shun
    Ge, Ruiqi
    Wu, Yuan
    He, Chuan
    Chen, Mengjie
    Tang, Weixin
    NATURE BIOTECHNOLOGY, 2023, 41 (07) : 993 - +
  • [2] Transcriptome-wide N6-methyladenosine analysis
    Hannah Stower
    Nature Reviews Genetics, 2012, 13 (7) : 452 - 452
  • [3] Erratum: Transcriptome-wide N6-methyladenosine analysis
    Hannah Stower
    Nature Reviews Genetics, 2012, 13 : 594 - 594
  • [4] Transcriptome-wide profiling of N6-methyladenosine via a selective chemical labeling method
    Xie, Yalun
    Han, Shaoqing
    Li, Qiming
    Fang, Zhentian
    Yang, Wei
    Wei, Qi
    Wang, Yafen
    Zhou, Yu
    Weng, Xiaocheng
    Zhou, Xiang
    CHEMICAL SCIENCE, 2022, 13 (41) : 12149 - 12157
  • [5] Transcriptome-Wide Map of N6-Methyladenosine Methylome Profiling in Human Bladder Cancer
    Li, Aolin
    Gan, Ying
    Cao, Congcong
    Ma, Binglei
    Zhang, Quan
    Zhang, Qian
    Yao, Lin
    FRONTIERS IN ONCOLOGY, 2021, 11
  • [6] Transcriptome-wide profiling of mRNA N6-methyladenosine modification in rice panicles and flag leaves
    Wang, Li
    Yang, Chenhui
    Shan, Qianru
    Zhao, Miao
    Yu, Juanjuan
    Li, Yong -Fang
    GENOMICS, 2023, 115 (01)
  • [7] Transcriptome-wide reprogramming of N6-methyladenosine modification by the mouse microbiome
    Wang, Xiaoyun
    Li, Yan
    Chen, Wenjun
    Shi, Hailing
    Eren, A. Murat
    Morozov, Aleksey
    He, Chuan
    Luo, Guan-Zheng
    Pan, Tao
    CELL RESEARCH, 2019, 29 (02) : 167 - 170
  • [8] Transcriptome-wide N6-methyladenosine methylation profile of atherosclerosis in mice
    Zheng, Xinbin
    Zhou, Bo
    Li, Yuzhen
    Zhong, Hengren
    Huang, Zhengxin
    Gu, Minhua
    BMC GENOMICS, 2023, 24 (01)
  • [9] Transcriptome-wide reprogramming of N6-methyladenosine modification by the mouse microbiome
    Xiaoyun Wang
    Yan Li
    Wenjun Chen
    Hailing Shi
    A. Murat Eren
    Aleksey Morozov
    Chuan He
    Guan-Zheng Luo
    Tao Pan
    Cell Research, 2019, 29 : 167 - 170
  • [10] Transcriptome-wide N6-methyladenosine methylation profile of atherosclerosis in mice
    Xinbin Zheng
    Bo Zhou
    Yuzhen Li
    Hengren Zhong
    Zhengxin Huang
    Minhua Gu
    BMC Genomics, 24