Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE81825 | GEO | 2017/05/19
SECONDARY ACCESSION(S): PRJNA322635
REPOSITORIES: GEO
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Project 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.
| S-EPMC5580717 | biostudies-literature
Project 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 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.
2017-05-19 | GSE81823 | GEO
Project 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 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.
2017-05-19 | GSE81824 | GEO
Project description:Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs
| PRJNA322635 | ENA
Project description:Whole genome methylation profiling at a single cytosine resolution is now feasible due to the advent of high-throughput sequencing techniques together with bisulfite treatment of the DNA. To obtain the methylation value of each individual cytosine, the bisulfite-treated sequence reads are first aligned to a reference genome, and then the profiling of the methylation levels is done from the alignments. A huge effort has been made to quickly and correctly align the reads and many different algorithms and programs to do this have been created. However, the second step is just as crucial and non-trivial, but much less attention has been paid to the final inference of the methylation states. Important error sources do exist, such as sequencing errors, bisulfite failure, clonal reads, and single nucleotide variants. We developed MethylExtract, a user friendly tool to: i) generate high quality, whole genome methylation maps and ii) detect sequence variation within the same sample preparation. The program is implemented into a single script and takes into account all major error sources. MethylExtract detects variation (SNVs - Single Nucleotide Variants) in a similar way to VarScan, a very sensitive method extensively used in SNV and genotype calling based on non-bisulfite-treated reads. The usefulness of MethylExtract is shown by means of extensive benchmarking based on artificial bisulfite-treated reads and a comparison to a recently published method, called Bis-SNP. MethylExtract is able to detect SNVs within High-Throughput Sequencing experiments of bisulfite treated DNA at the same time as it generates high quality methylation maps. This simultaneous detection of DNA methylation and sequence variation is crucial for many downstream analyses, for example when deciphering the impact of SNVs on differential methylation. An exclusive feature of MethylExtract, in comparison with existing software, is the possibility to assess the bisulfite failure in a statistical way. The source code, tutorial and artificial bisulfite datasets are available at http://bioinfo2.ugr.es/MethylExtract/ and http://sourceforge.net/projects/methylextract/, and also permanently accessible from 10.5281/zenodo.7144.
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Project description:Bisulfite treatment of DNA followed by high-throughput sequencing (Bisulfite-seq) is an important method for studying DNA methylation and epigenetic gene regulation, yet current software tools do not adequately address single nucleotide polymorphisms (SNPs). Identifying SNPs is important for accurate quantification of methylation levels and for identification of allele-specific epigenetic events such as imprinting. We have developed a model-based bisulfite SNP caller, Bis-SNP, that results in substantially better SNP calls than existing methods, thereby improving methylation estimates. At an average 30× genomic coverage, Bis-SNP correctly identified 96% of SNPs using the default high-stringency settings. The open-source package is available at http://epigenome.usc.edu/publicationdata/bissnp2011.
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| S-BSST618 | biostudies-other
Project description:While DNA methylation is established as a major regulator of gene expression in the nucleus, the existence of mitochondrial DNA (mtDNA) methylation remains controversial. Here, we characterized the mtDNA methylation landscape in the prefrontal cortex of neurological healthy individuals (n=26) and patients with Parkinson's disease (n=27), using a combination of whole-genome bisulphite sequencing (WGBS) and bisulphite-independent methods. Accurate mtDNA mapping from WGBS data required alignment to an mtDNA reference only, to avoid misalignment to nuclear mitochondrial pseudogenes. Once correctly aligned, WGBS data provided ultra-deep mtDNA coverage (16,723 ± 7,711) and revealed overall very low levels of cytosine methylation. The highest methylation levels (5.49 ± 0.97%) were found on CpG position m.545, located in the heavy-strand promoter 1 region. The m.545 methylation was validated using a combination of methylation-sensitive DNA digestion and quantitative PCR analysis. We detected no association between mtDNA methylation profile and Parkinson's disease. Interestingly, m.545 methylation correlated with the levels of mtDNA transcripts, suggesting a putative role in regulating mtDNA gene expression. In addition, we propose a robust framework for methylation analysis of mtDNA from WGBS data, which is less prone to false-positive findings due to misalignment of nuclear mitochondrial pseudogene sequences.
| S-EPMC9423827 | biostudies-literature
Project description:AIMS/INTRODUCTION:The incidence of type 2 diabetes mellitus is increasing worldwide, and it might partly cause metabolic disorder and type 2 diabetes mellitus susceptibility in patients' offspring through epigenetic modification. However, the underlying mechanisms remain largely unclear. Recent studies have shown a potential link between deoxyribonucleic acid methylation in paternal sperm and susceptibility to type 2 diabetes mellitus in offspring, so this article focuses on whether the whole-genome methylation profiles of spermatozoa in type 2 diabetes mellitus patients have changed. MATERIALS AND METHODS:We investigated the genome-wide deoxyribonucleic acid methylation profiles in spermatozoa by comparing eight individuals with type 2 diabetes mellitus and nine non-diabetic controls using whole-genome bisulfite sequencing method. RESULTS:First, we found that the proportion of methylated cytosine in the whole genome of the type 2 diabetes mellitus group was slightly lower than that of the control group. Interestingly, the proportion of methylated cytosines in the CG context decreased, and the proportion of methylated cytosines in the CHG context (H = A, T or C) increased in the type 2 diabetes mellitus group, but the proportion of methylated cytosines in the CHH context (H = A, T or C) barely changed. The methylated cytosines in the CG context were mainly distributed at the high methylated level, whereas methylated cytosines in the CHG context and methylated cytosines in the CHH context were mainly distributed at the low and middle methylated level in both groups. Second, functional enrichment analysis showed that differentially methylated genes played a significant role in nervous system development and cell metabolism. Finally, we identified 10 top type 2 diabetes mellitus-related differentially methylated genes, including IRS1, PRKCE, FTO, PPARGC1A, KCNQ1, ATP10A, GHR, CREB1, PRKAR1A and HNF1B. CONCLUSIONS:Our study provides the first evidence for deoxyribonucleic acid methylation reprogramming in spermatozoa of type 2 diabetes mellitus patients, and provides a new basis for explaining the complex mechanism of type 2 diabetes mellitus susceptibility in offspring.
| S-EPMC7378413 | biostudies-literature