Characterization of functional methylomes by next-generation capture sequencing identifies novel disease-associated variants.
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Allum F, Shao X, Guénard F, Simon MM, Busche S, Caron M, Lambourne J, Lessard J, Tandre K, Hedman ÅK, Kwan T, Ge B, Multiple Tissue Human Expression Resource Consortium , Rönnblom L, McCarthy MI, Deloukas P, Richmond T, Burgess D, Spector TD, Tchernof A, Marceau S, Lathrop M, Vohl MC, Pastinen T, Grundberg E
Nat Commun 6 (-) 7211 [2015-05-29; online 2015-05-29]
Most genome-wide methylation studies (EWAS) of multifactorial disease traits use targeted arrays or enrichment methodologies preferentially covering CpG-dense regions, to characterize sufficiently large samples. To overcome this limitation, we present here a new customizable, cost-effective approach, methylC-capture sequencing (MCC-Seq), for sequencing functional methylomes, while simultaneously providing genetic variation information. To illustrate MCC-Seq, we use whole-genome bisulfite sequencing on adipose tissue (AT) samples and public databases to design AT-specific panels. We establish its efficiency for high-density interrogation of methylome variability by systematic comparisons with other approaches and demonstrate its applicability by identifying novel methylation variation within enhancers strongly correlated to plasma triglyceride and HDL-cholesterol, including at CD36. Our more comprehensive AT panel assesses tissue methylation and genotypes in parallel at ∼4 and ∼3 M sites, respectively. Our study demonstrates that MCC-Seq provides comparable accuracy to alternative approaches but enables more efficient cataloguing of functional and disease-relevant epigenetic and genetic variants for large-scale EWAS.
PubMed 26021296
DOI 10.1038/ncomms8211
Crossref 10.1038/ncomms8211
pii: ncomms8211
pmc: PMC4544751
mid: EMS63065
GEO: GSE59524