Dataset Information

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

ACCESS DATA

Similar Datasets

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.

Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track was produced as part of the ENCODE project. It reports the percentage of DNA molecules that exhibit cytosine methylation. In general, DNA methylation within a gene's promoter is associated with gene silencing, and DNA methylation within the exons and introns of a gene is associated with gene expression. Proper regulation of DNA methylation is essential during development and aberrant DNA methylation is a hallmark of cancer. DNA methylation status was assayed with Whole Genome Bisulfite Sequencing (WGBS). Genomic DNA was sheared by sonication, end-repaired and then ligated to methylated sequencing adapters. The library fragments were treated with sodium bisulfite and amplified by PCR to convert every unmethylated cytosine to a thymine while leaving methylated cytosines intact. The sequenced fragments were aligned to a bisulfite-converted reference genome. For each assayed cytosine, the number of sequencing reads covering that C and the percentage of those reads that were methylated were reported. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf DNA methylation at cytosines across the genome was assayed with Whole Genome Bisulfite Sequencing (WGBS). WGBS was performed on cell lines grown by ENCODE production groups. WGBS was carried out by the Myers production group at the HudsonAlpha Institute for Biotechnology. Isolation of Genomic DNA: Genomic DNA was isolated from each cell line using the QIAGEN DNeasy Blood & Tissue Kit according to the instructions provided by the manufacturer. DNA concentrations for each genomic DNA preparation were determined using fluorescent DNA-binding dye and a fluorometer (Invitrogen Quant-iT dsDNA High Sensitivity Kit and Qubit Fluorometer). Typically, 2 µg of genomic DNA is used to make WGBS libraries. WGBS Library Construction and Sequencing: WGBS library construction started with sonication of genomic DNA on a Covaris S2 instrument. Sheared ends were then repaired and blunted with DNA polymerase I, T4 DNA polymerase and T4 polynucleotide kinase in the presence of dATP, dGTP and dTTP. After end repair, Klenow exo- DNA Polymerase was used to add an adenosine as a 3' overhang. Next, a methylated version of the Illumina paired-end adapters was ligated onto the DNA. Adapter-ligated 400 bp genomic DNA fragments were selected using a 2% agarose SizeSelect E-gel. The selected adapter-ligated fragments were treated with sodium bisulfite using the Zymo Research EZ DNA Methylation Gold Kit, which converts unmethylated cytosines to uracils and leaves methylated cytosines unchanged. Bisulfite-treated DNA was amplified in a final PCR reaction which was optimized to uniformly amplify diverse fragment sizes and sequence contexts in the same reaction. During this final PCR reaction, uracils were copied as thymines, resulting in a thymine in the PCR products wherever an unmethylated cytosine existed in the genomic DNA. These libraries were then sequenced with an Illumina HiSeq 2000 according to the manufacturer's recommendations as paired-end 50 bp reads. Libraries were sequenced to a depth of 600 million aligned reads. Data Analysis: To analyze the sequence data, Bismark (Krueger and Andrews, 2011) was used to align sequences reads. Generally, each read went through a conversion of Cs to Ts and was then aligned to fully converted plus and minus strands of the hg19 build of the human genome. A few custom refinements were made to the Bismark program. Since these libraries were made in a directional orientation with the first read always being C-poor, we skipped unnecessary alignments to impossible orientations. We also implemented a more stringent uniqueness filter, only allowing reads that have one acceptable alignment (based on default Bowtie parameters) across both strands. Once reads were aligned, the percent methylation was calculated for each cytosine using the original sequence reads. The percent methylation and number of reads is reported for each CpG in the wgEncodeHaibMethylWgbsXXXXCpg.bigBed file and for each non CpG cytosine in the wgEncodeHaibMethylWgbsXXXXNoncpg.bigBed file.

Dataset Information

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure