Literature DB >> 34417605

m6A-express: uncovering complex and condition-specific m6A regulation of gene expression.

Teng Zhang1, Shao-Wu Zhang1, Song-Yao Zhang1, Shou-Jiang Gao2, Yidong Chen3, Yufei Huang4.   

Abstract

N6-methyladenosine (m6A) is the most abundant form of mRNA modification and controls many aspects of RNA metabolism including gene expression. However, the mechanisms by which m6A regulates cell- and condition-specific gene expression are still poorly understood, partly due to a lack of tools capable of identifying m6A sites that regulate gene expression under different conditions. Here we develop m6A-express, the first algorithm for predicting condition-specific m6A regulation of gene expression (m6A-reg-exp) from limited methylated RNA immunoprecipitation sequencing (MeRIP-seq) data. Comprehensive evaluations of m6A-express using simulated and real data demonstrated its high prediction specificity and sensitivity. When only a few MeRIP-seq samples may be available for the cellular or treatment conditions, m6A-express is particularly more robust than the log-linear model. Using m6A-express, we reported that m6A writers, METTL3 and METTL14, competitively regulate the transcriptional processes by mediating m6A-reg-exp of different genes in Hela cells. In contrast, METTL3 induces different m6A-reg-exp of a distinct group of genes in HepG2 cells to regulate protein functions and stress-related processes. We further uncovered unique m6A-reg-exp patterns in human brain and intestine tissues, which are enriched in organ-specific processes. This study demonstrates the effectiveness of m6A-express in predicting condition-specific m6A-reg-exp and highlights the complex, condition-specific nature of m6A-regulation of gene expression.
© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2021        PMID: 34417605      PMCID: PMC8599805          DOI: 10.1093/nar/gkab714

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  113 in total

1.  pRNAm-PC: Predicting N(6)-methyladenosine sites in RNA sequences via physical-chemical properties.

Authors:  Zi Liu; Xuan Xiao; Dong-Jun Yu; Jianhua Jia; Wang-Ren Qiu; Kuo-Chen Chou
Journal:  Anal Biochem       Date:  2015-12-31       Impact factor: 3.365

2.  The m6A methyltransferase METTL3 contributes to Transforming Growth Factor-beta-induced epithelial-mesenchymal transition of lung cancer cells through the regulation of JUNB.

Authors:  Sasithorn Wanna-Udom; Minoru Terashima; Hanbing Lyu; Akihiko Ishimura; Takahisa Takino; Matomo Sakari; Toshifumi Tsukahara; Takeshi Suzuki
Journal:  Biochem Biophys Res Commun       Date:  2020-01-22       Impact factor: 3.575

3.  Exome-based analysis for RNA epigenome sequencing data.

Authors:  Jia Meng; Xiaodong Cui; Manjeet K Rao; Yidong Chen; Yufei Huang
Journal:  Bioinformatics       Date:  2013-04-14       Impact factor: 6.937

4.  Mettl3-/Mettl14-mediated mRNA N6-methyladenosine modulates murine spermatogenesis.

Authors:  Zhen Lin; Phillip J Hsu; Xudong Xing; Jianhuo Fang; Zhike Lu; Qin Zou; Ke-Jia Zhang; Xiao Zhang; Yuchuan Zhou; Teng Zhang; Youcheng Zhang; Wanlu Song; Guifang Jia; Xuerui Yang; Chuan He; Ming-Han Tong
Journal:  Cell Res       Date:  2017-09-15       Impact factor: 25.617

5.  m6A RNA methylation regulates the fate of endogenous retroviruses.

Authors:  Tomasz Chelmicki; Emeline Roger; Aurélie Teissandier; Mathilde Dura; Lorraine Bonneville; Sofia Rucli; François Dossin; Camille Fouassier; Sonia Lameiras; Deborah Bourc'his
Journal:  Nature       Date:  2021-01-13       Impact factor: 49.962

6.  Nuclear TARBP2 Drives Oncogenic Dysregulation of RNA Splicing and Decay.

Authors:  Lisa Fish; Albertas Navickas; Bruce Culbertson; Yichen Xu; Hoang C B Nguyen; Steven Zhang; Myles Hochman; Ross Okimoto; Brian D Dill; Henrik Molina; Hamed S Najafabadi; Claudio Alarcón; Davide Ruggero; Hani Goodarzi
Journal:  Mol Cell       Date:  2019-07-09       Impact factor: 17.970

7.  Structural Basis for Cooperative Function of Mettl3 and Mettl14 Methyltransferases.

Authors:  Ping Wang; Katelyn A Doxtader; Yunsun Nam
Journal:  Mol Cell       Date:  2016-06-30       Impact factor: 17.970

8.  m6A mRNA Methylation Regulates Human β-Cell Biology in Physiological States and in Type 2 Diabetes.

Authors:  Dario F De Jesus; Zijie Zhang; Sevim Kahraman; Natalie K Brown; Mengjie Chen; Jiang Hu; Manoj K Gupta; Chuan He; Rohit N Kulkarni
Journal:  Nat Metab       Date:  2019-07-29

Review 9.  Roles of METTL3 in cancer: mechanisms and therapeutic targeting.

Authors:  Chengwu Zeng; Wanxu Huang; Yangqiu Li; Hengyou Weng
Journal:  J Hematol Oncol       Date:  2020-08-27       Impact factor: 17.388

Review 10.  Hypoxia-inducible factors, stem cells, and cancer.

Authors:  Brian Keith; M Celeste Simon
Journal:  Cell       Date:  2007-05-04       Impact factor: 41.582

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  1 in total

Review 1.  Hidden codes in mRNA: Control of gene expression by m6A.

Authors:  Shino Murakami; Samie R Jaffrey
Journal:  Mol Cell       Date:  2022-06-16       Impact factor: 19.328

  1 in total

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