Quantitative Comparison Of Genome-Wide Dna Methylation Mapping Technologies

Broad Institute, Cambridge, Massachusetts, USA.
Nature Biotechnology (Impact Factor: 41.51). 10/2010; 28(10):1106-14. DOI: 10.1038/nbt.1681
Source: PubMed


DNA methylation plays a key role in regulating eukaryotic gene expression. Although mitotically heritable and stable over time, patterns of DNA methylation frequently change in response to cell differentiation, disease and environmental influences. Several methods have been developed to map DNA methylation on a genomic scale. Here, we benchmark four of these approaches by analyzing two human embryonic stem cell lines derived from genetically unrelated embryos and a matched pair of colon tumor and adjacent normal colon tissue obtained from the same donor. Our analysis reveals that methylated DNA immunoprecipitation sequencing (MeDIP-seq), methylated DNA capture by affinity purification (MethylCap-seq), reduced representation bisulfite sequencing (RRBS) and the Infinium HumanMethylation27 assay all produce accurate DNA methylation data. However, these methods differ in their ability to detect differentially methylated regions between pairs of samples. We highlight strengths and weaknesses of the four methods and give practical recommendations for the design of epigenomic case-control studies.

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    • "Briefly, genomic DNA was fragmented with ultrasonication (Covaris , Woburn, MA) to a median length of ~150 bp, and we used MethylMiner (Invitrogen, Carlsbad, CA) which employs MBD protein-based enrichment of the methylated DNA fraction, followed by single-end sequencing (50 bp reads) on the SOLiD platform (Life Technologies, Foster City, CA). As binding is better in CpG-dense regions (Harris et al., 2010), we used an existing protocol variant that eluted the captured methylated fraction with 0.5 M NaCl to increase the relative number of fragments from CpG-poor regions (Aberg et al., 2012b), which otherwise would not be as well covered (Bock et al., 2010), and improve coverage of the methylome. "
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    ABSTRACT: Methylome-wide association (MWAS) studies present a new way to advance the search for biological correlates for alcohol use. A challenge with methylation studies of alcohol involves the causal direction of significant methylation-alcohol associations. One way to address this issue is to combine MWAS data with genomewide association study (GWAS) data. Here, we combined MWAS and GWAS results for alcohol use from 619 individuals. Our MWAS data were generated by next-generation sequencing of the methylated genomic DNA fraction, producing over 60 million reads per subject to interrogate methylation levels at ~27 million autosomal CpG sites in the human genome. Our GWAS included 5,571,786 single nucleotide polymorphisms (SNPs) imputed with 1000 Genomes. When combining the MWAS and GWAS data, our top finding was a region in an intron of CNTN4 (p = 2.55 × 10(-8) ), located between chr3: 2,555,403 and 2,555,524, encompassing SNPs rs1382874 and rs1382875. This finding was then replicated in an independent sample of 730 individuals. We used bisulfite pyrosequencing to measure methylation and found significant association with regular alcohol use in the same direction as the MWAS (p = 0.021). Rs1382874 and rs1382875 were genotyped and found to be associated in the same direction as the GWAS (p = 0.008 and p = 0.009). After integrating the MWAS and GWAS findings from the replication sample, we replicated our combined analysis finding (p = 0.0017) in CNTN4. Through combining methylation and SNP data, we have identified CNTN4 as a risk factor for regular alcohol use. Copyright © 2015 by the Research Society on Alcoholism.
    Alcoholism Clinical and Experimental Research 07/2015; 39(8). DOI:10.1111/acer.12790 · 3.21 Impact Factor
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    • "However, the array only covers 2% of the >28 million autosomal CpG sites in the human genome, many of which are not located in regions of known functional relevance. In comparing the ability of the array to detect DMRs with other sequencing-based methods, the Infinium assay detected only 20% of those detected by MeDIP or RRBS (Bock et al., 2010). In addition, the array requires relatively large amounts of input DNA (500 ng). "
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    ABSTRACT: The study of epigenetics, or chemical modifications to the genome that may alter gene expression, is a growing area of interest for social scientists. Anthropologists and human biologists are interested in epigenetics specifically, as it provides a potential link between the environment and the genome, as well as a new layer of complexity for the study of human biological variation. In pace with the rapid increase in interest in epigenetic research, the range of methods has greatly expanded over the past decade. The primary objective of this article is to provide an overview of the current methods for assaying DNA methylation, the most commonly studied epigenetic modification. We will address considerations for all steps required to plan and conduct an analysis of DNA methylation, from appropriate sample collection, to the most commonly used methods for laboratory analyses of locus-specific and genome-wide approaches, and recommendations for statistical analyses. Key challenges in the study of DNA methylation are also discussed, including tissue specificity, the stability of measures, timing of sample collection, statistical considerations, batch effects, and challenges related to analysis and interpretation of data. Our hope is that this review serves as a primer for anthropologists and human biologists interested in incorporating epigenetic data into their research programs. Am. J. Hum. Biol., 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
    American Journal of Human Biology 02/2015; 27(3). DOI:10.1002/ajhb.22679 · 1.70 Impact Factor
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    • "Wang and colleagues (Wang et al., 2014) used reduced representational bisulphite sequencing (RRBS) to map methylated CpG in the brains of solitarious and gregarious locusts. This approach allows single-base resolution and absolute quantification of (hydroxy)methylation [albeit with imperfect quantification (Harris et al., 2010)], but is biased towards CpG-rich regions (Bock et al., 2010; Harris et al., 2010) and by the choice of the restriction enzyme used (Deng et al., 2009) and size selection of fragments (Bock et al., 2010). Both RRBS and wholegenome bisulphite sequencing (WGBS) may contain artifacts due to the bisulphite conversion process and subsequent PCR bias. "
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