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

Allum, Fiona and Shao, Xiaojian and Guénard, Frédéric and Simon, Marie-Michelle and Busche, Stephan and Caron, Maxime and Lambourne, John and Lessard, Julie and Tandre, Karolina and Hedman, Åsa K and Kwan, Tony and Ge, Bing and Rönnblom, Lars and McCarthy, Mark I and Deloukas, Panos and Richmond, Todd and Burgess, Daniel and Spector, Timothy D and Tchernof, André and Marceau, Simon and Lathrop, Mark and Vohl, Marie-Claude and Pastinen, Tomi and Grundberg, Elin and Tsaprouni, Loukia (2015) Characterization of functional methylomes by next-generation capture sequencing identifies novel disease-associated variants. Nature communications, 6. p. 7211. ISSN 2041-1723

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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.

Item Type: Article
Identification Number:
Date: 29 May 2015
Subjects: A100 Pre-clinical Medicine
C400 Genetics
C700 Molecular Biology, Biophysics and Biochemistry
Divisions: REF UoA Output Collections > REF2021 UoA 03: Allied Health Professions, Dentistry, Nursing & Pharmacy
Faculty of Health, Education and Life Sciences > School of Health Sciences
Depositing User: Loukia Tsaprouni
Date Deposited: 04 Jul 2017 09:13
Last Modified: 13 May 2020 05:30

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