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Characterization of functional methylomes by next-generation capture sequencing identifies novel disease-associated variants

Allum, Fiona (author)
Shao, Xiaojian (author)
Guénard, Frédéric (author)
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Simon, Marie-Michelle (author)
Busche, Stephan (author)
Caron, Maxime (author)
Lambourne, John (author)
Lessard, Julie (author)
Tandre, Karolina (author)
Uppsala universitet,Reumatologi
Hedman, Åsa K (author)
Uppsala universitet,Molekylär epidemiologi,Science for Life Laboratory, SciLifeLab
Kwan, Tony (author)
Ge, Bing (author)
Rönnblom, Lars (author)
Uppsala universitet,Reumatologi
McCarthy, Mark I (author)
Deloukas, Panos (author)
Richmond, Todd (author)
Burgess, Daniel (author)
Spector, Timothy D (author)
Tchernof, André (author)
Marceau, Simon (author)
Lathrop, Mark (author)
Vohl, Marie-Claude (author)
Pastinen, Tomi (author)
Grundberg, Elin (author)
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 (creator_code:org_t)
2015-05-29
2015
English.
In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 6
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • 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.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Reumatologi och inflammation (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Rheumatology and Autoimmunity (hsv//eng)

Keyword

Medical Science
Medicinsk vetenskap

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ref (subject category)
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