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

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 have previously established RNA bisulfite sequencing as a method for the analysis of RNA (cytosine-5) methylation patterns at single-base resolution. Furthermore, next-generation sequencing has provided opportunities to establish transcriptome-wide maps of this modification. We have now established a computational approach that integrates tailored filtering and data-driven statistical modelling to eliminate many of the artifacts that are known to be associated with bisulfite sequencing. Using RNAs from mouse embryonic stem cells we have 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. Furthermore, the catalytic activities of the Dnmt2 tRNA methyltransferase could be resolved at single-base resolution. Of note, mRNAs were found to be very sparsely methylated or not methylated at all, which provides an important reference for further studies. Our approach can be used to profile (cytosine-5) RNA methylation patterns in many experimental contexts be important for understanding the function of (cytosine-5) RNA methylation in RNA biology and in human disease.

ORGANISM(S): Mus musculus

PROVIDER: GSE81823 | GEO | 2017/05/19

SECONDARY ACCESSION(S): PRJNA322645

REPOSITORIES: GEO

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Project description:DNA methylation stabilizes developmentally programmed gene expression states. Aberrant methylation is associated with disease progression and is a common feature of cancer genomes. Presently, few methods enable quantitative, large-scale, single-base resolution mapping of DNA methylation states in desired regions of a complex mammalian genome. Here, we present an approach that combines array-based hybrid selection and massively parallel bisulfite sequencing to profile DNA methylation in genomic regions spanning hundreds of thousands of bases. This single molecule strategy enables methylation variable positions to be quantitatively examined with high sampling precision. Using bisulfite capture, we assessed methylation patterns across 324 randomly selected CpG islands (CGI) representing more than 25,000 CpG sites. A single lane of Illumina sequencing permitted methylation states to be definitively called for >90% of target sties. The accuracy of the hybrid-selection approach was verified using conventional bisulfite capillary sequencing of cloned PCR products amplified from a subset of the selected regions. This confirmed that even partially methylated states could be successfully called. A comparison of human primary and cancer cells revealed multiple differentially methylated regions. More than 25% of islands showed complex methylation patterns either with partial methylation states defining the entire CGI or with contrasting methylation states appearing in specific regional blocks within the island. We observed that transitions in methylation state often correlate with genomic landmarks, including transcriptional start sites and intron-exon junctions. Methylation, along with specific histone marks, was enriched in exonic regions, suggesting that chromatin states can foreshadow the content of mature mRNAs. Keywords: DNA methylation profiling by massively parallel sequencing Keywords: Epigenetics Targeted examination of DNA methylation in two human cell types by combining array capture and bisulfite sequencing. In addition, this study examined two histone marks in the breast tumor cell line MDA-MB-231.

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

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