Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs

Abstract

Cytosine-5 RNA methylation plays an important role in several biologically and pathologically relevant processes. However, owing to methodological limitations, the transcriptome-wide distribution of this mark has remained largely unknown. We previously established RNA bisulfite sequencing as a method for the analysis of RNA cytosine-5 methylation patterns at single-base resolution. More recently, next-generation sequencing has provided opportunities to establish transcriptome-wide maps of this modification. Here, we present a computational approach that integrates tailored filtering and data-driven statistical modeling to eliminate many of the artifacts that are known to be associated with bisulfite sequencing. By using RNAs from mouse embryonic stem cells, we performed a comprehensive methylation analysis of mouse tRNAs, rRNAs, and mRNAs. Our approach identified all known methylation marks in tRNA and two previously unknown but evolutionary conserved marks in 28S rRNA. In addition, mRNAs were found to be very sparsely methylated or not methylated at all. Finally, the tRNA-specific activity of the DNMT2 methyltransferase could be resolved at single-base resolution, which provided important further validation. Our approach can be used to profile cytosine-5 RNA methylation patterns in many experimental contexts and will be important for understanding the function of cytosine-5 RNA methylation in RNA biology and in human disease.

Autoren

Carine Legrand
Francesca Tuorto
Mark Hartmann
Reinhard Liebers
Dominik Jacob
Mark Helm
Frank Lyko

DOI

10.1101/gr.210666.116

eISSN

1549-5469

ISSN

1088-9051

Ausgabe der Veröffentlichung

9

Zeitschrift

Genome Research

Sprache

en

Online publication date

2017

Paginierung

1589 - 1596

Datum der Veröffentlichung

2017

Status

Published

Herausgeber

Cold Spring Harbor Laboratory

Herausgeber URL

http://dx.doi.org/10.1101/gr.210666.116

Datum der Datenerfassung

2021

Titel

Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs

Ausgabe der Zeitschrift

27

Datenquelle: Crossref

Abstract

Cytosine-5 RNA methylation plays an important role in several biologically and pathologically relevant processes. However, owing to methodological limitations, the transcriptome-wide distribution of this mark has remained largely unknown. We previously established RNA bisulfite sequencing as a method for the analysis of RNA cytosine-5 methylation patterns at single-base resolution. More recently, next-generation sequencing has provided opportunities to establish transcriptome-wide maps of this modification. Here, we present a computational approach that integrates tailored filtering and data-driven statistical modeling to eliminate many of the artifacts that are known to be associated with bisulfite sequencing. By using RNAs from mouse embryonic stem cells, we performed a comprehensive methylation analysis of mouse tRNAs, rRNAs, and mRNAs. Our approach identified all known methylation marks in tRNA and two previously unknown but evolutionary conserved marks in 28S rRNA. In addition, mRNAs were found to be very sparsely methylated or not methylated at all. Finally, the tRNA-specific activity of the DNMT2 methyltransferase could be resolved at single-base resolution, which provided important further validation. Our approach can be used to profile cytosine-5 RNA methylation patterns in many experimental contexts and will be important for understanding the function of cytosine-5 RNA methylation in RNA biology and in human disease.

Addresses

Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, 69120 Heidelberg, Germany.

Autoren

Carine Legrand
Francesca Tuorto
Mark Hartmann
Reinhard Liebers
Dominik Jacob
Mark Helm
Frank Lyko

DOI

10.1101/gr.210666.116

eISSN

1549-5469

Externe Identifier

PubMed Identifier: 28684555
PubMed Central ID: PMC5580717

Funding acknowledgements

Landesstiftung Baden-Württemberg: ncRNA_019
Deutsche Forschungsgemeinschaft: Priority Programme 1784

Open access

true

ISSN

1088-9051

Ausgabe der Veröffentlichung

9

Zeitschrift

Genome research

Schlüsselwörter

Animals
Humans
Mice
Methyltransferases
RNA, Messenger
RNA, Ribosomal, 28S
RNA, Transfer
DNA Methylation
RNA Processing, Post-Transcriptional
High-Throughput Nucleotide Sequencing
Transcriptome

Sprache

eng

Medium

Print-Electronic

Online publication date

2017

Open access status

Open Access

Paginierung

1589 - 1596

Datum der Veröffentlichung

2017

Status

Published

Publisher licence

CC BY-NC

Datum der Datenerfassung

2017

Titel

Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs.

Sub types

Research Support, Non-U.S. Gov't
research-article
Journal Article

Ausgabe der Zeitschrift

27

Files

http://genome.cshlp.org/content/27/9/1589.full.pdf https://europepmc.org/articles/PMC5580717?pdf=render

Datenquelle: Europe PubMed Central

Abstract

Cytosine-5 RNA methylation plays an important role in several biologically and pathologically relevant processes. However, owing to methodological limitations, the transcriptome-wide distribution of this mark has remained largely unknown. We previously established RNA bisulfite sequencing as a method for the analysis of RNA cytosine-5 methylation patterns at single-base resolution. More recently, next-generation sequencing has provided opportunities to establish transcriptome-wide maps of this modification. Here, we present a computational approach that integrates tailored filtering and data-driven statistical modeling to eliminate many of the artifacts that are known to be associated with bisulfite sequencing. By using RNAs from mouse embryonic stem cells, we performed a comprehensive methylation analysis of mouse tRNAs, rRNAs, and mRNAs. Our approach identified all known methylation marks in tRNA and two previously unknown but evolutionary conserved marks in 28S rRNA. In addition, mRNAs were found to be very sparsely methylated or not methylated at all. Finally, the tRNA-specific activity of the DNMT2 methyltransferase could be resolved at single-base resolution, which provided important further validation. Our approach can be used to profile cytosine-5 RNA methylation patterns in many experimental contexts and will be important for understanding the function of cytosine-5 RNA methylation in RNA biology and in human disease.

Date of acceptance

2017

Autoren

Carine Legrand
Francesca Tuorto
Mark Hartmann
Reinhard Liebers
Dominik Jacob
Mark Helm
Frank Lyko

Autoren-URL

https://www.ncbi.nlm.nih.gov/pubmed/28684555

DOI

10.1101/gr.210666.116

eISSN

1549-5469

Externe Identifier

PubMed Central ID: PMC5580717

Ausgabe der Veröffentlichung

9

Zeitschrift

Genome Res

Schlüsselwörter

Animals
DNA Methylation
High-Throughput Nucleotide Sequencing
Humans
Methyltransferases
Mice
RNA Processing, Post-Transcriptional
RNA, Messenger
RNA, Ribosomal, 28S
RNA, Transfer
Transcriptome

Sprache

eng

Country

United States

Paginierung

1589 - 1596

PII

gr.210666.116

Datum der Veröffentlichung

2017

Status

Published

Datum, an dem der Datensatz öffentlich gemacht wurde

2018

Titel

Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs.

Sub types

Journal Article
Research Support, Non-U.S. Gov't

Ausgabe der Zeitschrift

27

Datenquelle: PubMed

Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs

Files

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