Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution

Broad Institute, Cambridge, Massachusetts, USA.
Nature Methods (Impact Factor: 32.07). 02/2010; 7(2):133-6. DOI: 10.1038/nmeth.1414
Source: PubMed


Bisulfite sequencing measures absolute levels of DNA methylation at single-nucleotide resolution,
providing a robust platform for molecular diagnostics. Here, we optimize bisulfite sequencing for
genome-scale analysis of clinical samples. Specifically, we outline how restriction digestion
targets bisulfite sequencing to hotspots of epigenetic regulation; we show that 30ng of DNA are
sufficient for genome-scale analysis; we demonstrate that our protocol works well on formalinfixed,
paraffin-embedded (FFPE) samples; and we describe a statistical method for assessing
significance of altered DNA methylation patterns.

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Available from: Natalie Jäger, Dec 28, 2013
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    • "For example, a tagmentation WGBS protocol reduces the DNA requirements to 20 ng, albeit at the cost of reduced genomewide coverage (Adey and Shendure, 2012; Wang et al., 2013). As a cost-effective alternative to WGBS, reduced representation bisulfite sequencing (RRBS) yields accurate DNA methylation maps covering 1–2 million CpGs from 30 ng of human DNA (Bock et al., 2010; Gu et al., 2010). RRBS has also been applied to populations of about 100 cells from mouse embryos and oocytes (Smallwood et al., 2011; Smith et al., 2012), yielding data for 1–2 million CpGs out of the approximately 21.9 million CpGs in the mouse genome. "
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    ABSTRACT: Methods for single-cell genome and transcriptome sequencing have contributed to our understanding of cellular heterogeneity, whereas methods for single-cell epigenomics are much less established. Here, we describe a whole-genome bisulfite sequencing (WGBS) assay that enables DNA methylation mapping in very small cell populations (μWGBS) and single cells (scWGBS). Our assay is optimized for profiling many samples at low coverage, and we describe a bioinformatic method that analyzes collections of single-cell methylomes to infer cell-state dynamics. Using these technological advances, we studied epigenomic cell-state dynamics in three in vitro models of cellular differentiation and pluripotency, where we observed characteristic patterns of epigenome remodeling and cell-to-cell heterogeneity. The described method enables single-cell analysis of DNA methylation in a broad range of biological systems, including embryonic development, stem cell differentiation, and cancer. It can also be used to establish composite methylomes that account for cell-to-cell heterogeneity in complex tissue samples. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
    Cell Reports 03/2015; 10(8):1386-97. DOI:10.1016/j.celrep.2015.02.001 · 8.36 Impact Factor
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    • ", thus allowing for sequence - specific discrimi - nation between methylated and unmethylated CpG sites ( Clark et al . , 2006 ) . Sodium bisulfite pre - treatment of DNA coupled with next - generation sequencing has facilitated genome - wide quantita - tive DNA methylation to be studied at single cytosine site resolution ( Lister & Ecker , 2009 ; Gu et al . , 2010 ; Laird , 2010 ) . The high cost of whole - genome bisulfite sequencing ( bis - seq ) , and the uneven distribution of CpG sites in the genome motivated the development of modified approaches such as reduced representation bisulfite sequencing ( RRBS ) ( Meissner et al . , 2005 ; Jeddeloh et al . , 2008 ; Gu et al . , 2011 ) and enhance"
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    ABSTRACT: Motivation: DNA methylation plays critical roles in gene regulation and cellular specification without altering DNA sequences. The wide application of reduced representation bisulfite sequencing (RRBS) and whole genome bisulfite sequencing (bis-seq) opens the door to study DNA methylation at single CpG site resolution. One challenging question is how best to test for significant methylation differences between groups of biological samples in order to minimize false positive findings. Results: We present a statistical analysis package, methylSig, to analyse genome-wide methylation differences between samples from different treatments or disease groups. MethylSig takes into account both read coverage and biological variation by utilizing a beta-binomial approach across biological samples for a CpG site or region, and identifies relevant differences in CpG methylation. It can also incorporate local information to improve group methylation level and/or variance estimation for experiments with small sample size. A permutation study based on data from enhanced RRBS samples shows that methylSig maintains a well-calibrated type-I error when the number of samples is three or more per group. Our simulations show that methylSig has higher sensitivity compared with several alternative methods. The use of methylSig is illustrated with a comparison of different subtypes of acute leukemia and normal bone marrow samples. Availability: methylSig is available as an R package at Supplementary information: Supplementary data are available at Bioinformatics online.
    Bioinformatics 05/2014; 30(17). DOI:10.1093/bioinformatics/btu339 · 4.98 Impact Factor
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    • "In silico digestion can also aid in the selection of fragment sizes for sequencing, after the genomic DNA has been cut with the restriction enzymes (Couldrey et al., unpublished data). For vertebrate genomes, it has been indicated that a fraction of DNA fragments between 40 and 220 bp contains enrichment of most promoter sequences and CpG island regions (Meissner et al., 2008; Gu et al., 2010). However, as utilization of epigenomic technologies in livestock species remain under-utilized, application of this technology has yet to be thoroughly explored and verified in practice. "
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    ABSTRACT: Recent advances made in "omics" technologies are contributing to a revolution in livestock selection and breeding practices. Epigenetic mechanisms, including DNA methylation are important determinants for the control of gene expression in mammals. DNA methylation research will help our understanding of how environmental factors contribute to phenotypic variation of complex production and health traits. High-throughput sequencing is a vital tool for the comprehensive analysis of DNA methylation, and bisulfite-based strategies coupled with DNA sequencing allows for quantitative, site-specific methylation analysis at the genome level or genome wide. Reduced representation bisulfite sequencing (RRBS) and more recently whole genome bisulfite sequencing (WGBS) have proven to be effective techniques for studying DNA methylation in both humans and mice. Here we report the development of RRBS and WGBS for use in sheep, the first application of this technology in livestock species. Important technical issues associated with these methodologies including fragment size selection and sequence depth are examined and discussed.
    Frontiers in Genetics 05/2014; 5:126. DOI:10.3389/fgene.2014.00126
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