Literature DB >> 31257032

Deciphering the "m6A Code" via Antibody-Independent Quantitative Profiling.

Miguel Angel Garcia-Campos1, Sarit Edelheit1, Ursula Toth2, Modi Safra1, Ran Shachar1, Sergey Viukov1, Roni Winkler1, Ronit Nir1, Lior Lasman1, Alexander Brandis3, Jacob H Hanna1, Walter Rossmanith2, Schraga Schwartz4.   

Abstract

N6-methyladenosine (m6A) is the most abundant modification on mRNA and is implicated in critical roles in development, physiology, and disease. A major limitation has been the inability to quantify m6A stoichiometry and the lack of antibody-independent methodologies for interrogating m6A. Here, we develop MAZTER-seq for systematic quantitative profiling of m6A at single-nucleotide resolution at 16%-25% of expressed sites, building on differential cleavage by an RNase. MAZTER-seq permits validation and de novo discovery of m6A sites, calibration of the performance of antibody-based approaches, and quantitative tracking of m6A dynamics in yeast gametogenesis and mammalian differentiation. We discover that m6A stoichiometry is "hard coded" in cis via a simple and predictable code, accounting for 33%-46% of the variability in methylation levels and allowing accurate prediction of m6A loss and acquisition events across evolution. MAZTER-seq allows quantitative investigation of m6A regulation in subcellular fractions, diverse cell types, and disease states.
Copyright © 2019 Elsevier Inc. All rights reserved.

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Year:  2019        PMID: 31257032     DOI: 10.1016/j.cell.2019.06.013

Source DB:  PubMed          Journal:  Cell        ISSN: 0092-8674            Impact factor:   41.582


  114 in total

Review 1.  Small changes, big implications: The impact of m6A RNA methylation on gene expression in pluripotency and development.

Authors:  Adam M Heck; Carol J Wilusz
Journal:  Biochim Biophys Acta Gene Regul Mech       Date:  2019-07-17       Impact factor: 4.490

2.  Occurrence and Functions of m6A and Other Covalent Modifications in Plant mRNA.

Authors:  Laura Arribas-Hernández; Peter Brodersen
Journal:  Plant Physiol       Date:  2019-11-20       Impact factor: 8.340

3.  Five trendy technologies: where are they now?

Authors:  Jyoti Madhusoodanan
Journal:  Nature       Date:  2021-06       Impact factor: 49.962

4.  Deoxyribozyme-based method for absolute quantification of N 6-methyladenosine fractions at specific sites of RNA.

Authors:  Magda Bujnowska; Jiacheng Zhang; Qing Dai; Emily M Heideman; Jingyi Fei
Journal:  J Biol Chem       Date:  2020-04-08       Impact factor: 5.157

Review 5.  So close, no matter how far: multiple paths connecting transcription to mRNA translation in eukaryotes.

Authors:  Boris Slobodin; Rivka Dikstein
Journal:  EMBO Rep       Date:  2020-08-16       Impact factor: 8.807

Review 6.  Epitranscriptomic regulation by m6A RNA methylation in brain development and diseases.

Authors:  Anil K Chokkalla; Suresh L Mehta; Raghu Vemuganti
Journal:  J Cereb Blood Flow Metab       Date:  2020-09-23       Impact factor: 6.200

Review 7.  Emerging role of m6 A RNA methylation in nutritional physiology and metabolism.

Authors:  Jiamin Wu; Katya Frazier; Jingfei Zhang; Zhending Gan; Tian Wang; Xiang Zhong
Journal:  Obes Rev       Date:  2019-09-02       Impact factor: 9.213

8.  A metabolic labeling method detects m6A transcriptome-wide at single base resolution.

Authors:  Xiao Shu; Jie Cao; Mohan Cheng; Siying Xiang; Minsong Gao; Ting Li; Xiner Ying; Fengqin Wang; Yanan Yue; Zhike Lu; Qing Dai; Xiaolong Cui; Lijia Ma; Yizhen Wang; Chuan He; Xinhua Feng; Jianzhao Liu
Journal:  Nat Chem Biol       Date:  2020-04-27       Impact factor: 15.040

Review 9.  A molecular-level perspective on the frequency, distribution, and consequences of messenger RNA modifications.

Authors:  Joshua D Jones; Jeremy Monroe; Kristin S Koutmou
Journal:  Wiley Interdiscip Rev RNA       Date:  2020-01-21       Impact factor: 9.957

10.  Reprogramming of m6A epitranscriptome is crucial for shaping of transcriptome and proteome in response to hypoxia.

Authors:  Yan-Jie Wang; Bing Yang; Qiao Lai; Jun-Fang Shi; Jiang-Yun Peng; Yin Zhang; Kai-Shun Hu; Ya-Qing Li; Jing-Wen Peng; Zhi-Zhi Yang; Yao-Ting Li; Yue Pan; H Phillip Koeffler; Jian-You Liao; Dong Yin
Journal:  RNA Biol       Date:  2020-08-18       Impact factor: 4.652

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