Cargando…

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

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 metho...

Descripción completa

Detalles Bibliográficos
Autores principales: Legrand, Carine, Tuorto, Francesca, Hartmann, Mark, Liebers, Reinhard, Jacob, Dominik, Helm, Mark, Lyko, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5580717/
https://www.ncbi.nlm.nih.gov/pubmed/28684555
http://dx.doi.org/10.1101/gr.210666.116
_version_ 1783260949386362880
author Legrand, Carine
Tuorto, Francesca
Hartmann, Mark
Liebers, Reinhard
Jacob, Dominik
Helm, Mark
Lyko, Frank
author_facet Legrand, Carine
Tuorto, Francesca
Hartmann, Mark
Liebers, Reinhard
Jacob, Dominik
Helm, Mark
Lyko, Frank
author_sort Legrand, Carine
collection PubMed
description 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.
format Online
Article
Text
id pubmed-5580717
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Cold Spring Harbor Laboratory Press
record_format MEDLINE/PubMed
spelling pubmed-55807172017-09-14 Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs Legrand, Carine Tuorto, Francesca Hartmann, Mark Liebers, Reinhard Jacob, Dominik Helm, Mark Lyko, Frank Genome Res Method 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. Cold Spring Harbor Laboratory Press 2017-09 /pmc/articles/PMC5580717/ /pubmed/28684555 http://dx.doi.org/10.1101/gr.210666.116 Text en © 2017 Legrand et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by-nc/4.0/ This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Method
Legrand, Carine
Tuorto, Francesca
Hartmann, Mark
Liebers, Reinhard
Jacob, Dominik
Helm, Mark
Lyko, Frank
Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs
title Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs
title_full Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs
title_fullStr Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs
title_full_unstemmed Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs
title_short Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs
title_sort statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse rnas
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5580717/
https://www.ncbi.nlm.nih.gov/pubmed/28684555
http://dx.doi.org/10.1101/gr.210666.116
work_keys_str_mv AT legrandcarine statisticallyrobustmethylationcallingforwholetranscriptomebisulfitesequencingrevealsdistinctmethylationpatternsformousernas
AT tuortofrancesca statisticallyrobustmethylationcallingforwholetranscriptomebisulfitesequencingrevealsdistinctmethylationpatternsformousernas
AT hartmannmark statisticallyrobustmethylationcallingforwholetranscriptomebisulfitesequencingrevealsdistinctmethylationpatternsformousernas
AT liebersreinhard statisticallyrobustmethylationcallingforwholetranscriptomebisulfitesequencingrevealsdistinctmethylationpatternsformousernas
AT jacobdominik statisticallyrobustmethylationcallingforwholetranscriptomebisulfitesequencingrevealsdistinctmethylationpatternsformousernas
AT helmmark statisticallyrobustmethylationcallingforwholetranscriptomebisulfitesequencingrevealsdistinctmethylationpatternsformousernas
AT lykofrank statisticallyrobustmethylationcallingforwholetranscriptomebisulfitesequencingrevealsdistinctmethylationpatternsformousernas