Systematic calibration of epitranscriptomic maps using a synthetic modification-free RNA library

Zhang, Zhang; Chen, Tao; Chen, Hong-Xuan; Xie, Ying-Yuan; Chen, Liqian; Zhao, Yuli; Liu, Biao-Di; Jin, Lingmei; Zhang, Wutong; Liu, Chang; Ma, Dong-Zhao; Chai, Guoshi; Zhang, Ying; Zhao, Wenshuo; Ng, Wen Hui; Chen, Jiekai; Jia, Guifang; Yang, Jianhua; Luo, Guan‐Zheng

doi:10.1038/s41592-021-01280-7

Cited by 62 publications

(72 citation statements)

References 63 publications

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“…In numerous studies, researchers knocked down or deleted METTL3 and regarded the remaining m 6 A "peaks" as "METTL3-independent m 6 A peaks" [50,59]. However, several studies have shown that even in METTL3 knockout cells where m 6 A cannot be detected, m 6 A peaks can still be observed [60][61][62]. Thus, these m 6 A peaks should be regarded as background noise, rather than "METTL3-independent m 6 A peaks".…”

Section: Discussionmentioning

confidence: 99%

Understanding the source of METTL3-independent m⁶A in mRNA

Poh

Mirza

Pickering

et al. 2021

Preprint

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N6-methyladenosine (m6A) is a highly prevalent mRNA modification which promotes degradation of transcripts encoding proteins that have roles in cell development, differentiation, and other pathways. METTL3 is the major methyltransferase that catalyzes the formation of m6A in mRNA. As 30–80% of m6A can remain in mRNA after METTL3 depletion by CRISPR/Cas9-based methods, other enzymes are thought to catalyze a sizable fraction of m6A. Here, we re-examined the source of m6A in the mRNA transcriptome. We characterized mouse embryonic stem cell lines which continue to have m6A in their mRNA after Mettl3 knockout. We show that these cells express alternatively spliced Mettl3 transcript isoforms that bypass the CRISPR/Cas9 mutations and produce functionally active methyltransferases. We similarly show that other reported METTL3 knockout cell lines express altered METTL3 proteins. We find that gene dependency datasets show that most cell lines fail to proliferate after METTL3 deletion, suggesting that reported METTL3 knockout cell lines express altered METTL3 proteins rather than have full knockout. Finally, we reassessed METTL3’s role in synthesizing m6A using a genomic deletion of Mettl3, and found that METTL3 is responsible for >95% of m6A in mRNA. Overall, these studies suggest that METTL3 is responsible for the vast majority of m6A in the transcriptome, and that remaining m6A in putative METTL3 knockout cell lines is due to the expression of altered but functional METTL3 isoforms.

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Section: Discussionmentioning

confidence: 99%

Understanding the source of METTL3-independent m⁶A in mRNA

Poh

Mirza

Pickering

et al. 2021

Preprint

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“…Besides, all m 5 C sites were filtered by the minimal coverage of 30 (the detail scripts and pipelines for processing the raw data were available in Supplementary Material). In addition, the IVT m 5 C sites were used as the negative data to filter false positive sites ( 29 ).…”

Section: Methodsmentioning

confidence: 99%

m5C-Atlas: a comprehensive database for decoding and annotating the 5-methylcytosine (m5C) epitranscriptome

Song

Wei

et al. 2021

Nucleic Acids Research

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5-Methylcytosine (m5C) is one of the most prevalent covalent modifications on RNA. It is known to regulate a broad variety of RNA functions, including nuclear export, RNA stability and translation. Here, we present m5C-Atlas, a database for comprehensive collection and annotation of RNA 5-methylcytosine. The database contains 166 540 m5C sites in 13 species identified from 5 base-resolution epitranscriptome profiling technologies. Moreover, condition-specific methylation levels are quantified from 351 RNA bisulfite sequencing samples gathered from 22 different studies via an integrative pipeline. The database also presents several novel features, such as the evolutionary conservation of a m5C locus, its association with SNPs, and any relevance to RNA secondary structure. All m5C-atlas data are accessible through a user-friendly interface, in which the m5C epitranscriptomes can be freely explored, shared, and annotated with putative post-transcriptional mechanisms (e.g. RBP intermolecular interaction with RNA, microRNA interaction and splicing sites). Together, these resources offer unprecedented opportunities for exploring m5C epitranscriptomes. The m5C-Atlas database is freely accessible at https://www.xjtlu.edu.cn/biologicalsciences/m5c-atlas.

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“…Thus, for in vitro DART-seq, employing a pre-blocking step with the YTH domain alone may be preferred. Other methods for eliminating false-positives, such as the recently developed use of modification-free libraries ( Zhang et al, 2021 ), are alternative strategies which may further increase the accuracy of the in vitro DART-seq method.…”

Section: Discussionmentioning

confidence: 99%

Improved Methods for Deamination-Based m6A Detection

Zhu

yin

Holley

et al. 2022

Front. Cell Dev. Biol.

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N6-methyladenosine (m6A) is a critical regulator of gene expression and cellular function. Much of our knowledge of m6A has been enabled by the identification of m6A sites transcriptome-wide. However, global m6A profiling methods require high amounts of input RNA to accurately identify methylated RNAs, making m6A profiling from rare cell types or scarce tissue samples infeasible. To overcome this issue, we previously developed DART-seq, which relies on the expression of a fusion protein consisting of the APOBEC1 cytidine deaminase tethered to the m6A-binding YTH domain. APOBEC1-YTH directs C-to-U mutations adjacent to m6A sites, therefore enabling single nucleotide-resolution m6A mapping. Here, we present an improved version of DART-seq which utilizes a variant of the YTH domain engineered to achieve enhanced m6A recognition. In addition, we develop in vitro DART-seq and show that it performs similarly to cellular DART-seq and can map m6A in any sample of interest using nanogram amounts of total RNA. Altogether, these improvements to the DART-seq approach will enable better m6A detection and will facilitate the mapping of m6A in samples not previously amenable to global m6A profiling.

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Systematic calibration of epitranscriptomic maps using a synthetic modification-free RNA library

Cited by 62 publications

References 63 publications

Understanding the source of METTL3-independent m⁶A in mRNA

Understanding the source of METTL3-independent m⁶A in mRNA

m5C-Atlas: a comprehensive database for decoding and annotating the 5-methylcytosine (m5C) epitranscriptome

Improved Methods for Deamination-Based m6A Detection

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Systematic calibration of epitranscriptomic maps using a synthetic modification-free RNA library

Cited by 62 publications

References 63 publications

Understanding the source of METTL3-independent m6A in mRNA

Understanding the source of METTL3-independent m6A in mRNA

m5C-Atlas: a comprehensive database for decoding and annotating the 5-methylcytosine (m5C) epitranscriptome

Improved Methods for Deamination-Based m6A Detection

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Product

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Understanding the source of METTL3-independent m⁶A in mRNA

Understanding the source of METTL3-independent m⁶A in mRNA