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

Fiona Allum, Xiaojian Shao, Frédéric Guénard, Marie-Michelle Simon, Stephan Busche, Maxime Caron, John Lambourne, Julie Lessard, Karolina Tandre, Åsa K. Hedman, Tony Kwan, Bing Ge, Lars Rönnblom, Mark I. McCarthy, Panos Deloukas, Todd Richmond, Daniel Burgess, Timothy D. Spector, André Tchernof, Simon Marceau, Mark Lathrop, Marie-Claude Vohl, Tomi Pastinen and Elin Grundberg ()
Additional contact information
Fiona Allum: McGill University
Xiaojian Shao: McGill University
Frédéric Guénard: Institute of Nutrition and Functional Foods (INAF), Université Laval
Marie-Michelle Simon: McGill University
Stephan Busche: McGill University
Maxime Caron: McGill University
John Lambourne: McGill University
Julie Lessard: Québec Heart and Lung Institute, Université Laval
Karolina Tandre: Uppsala University
Åsa K. Hedman: Molecular Epidemiology, Uppsala University
Tony Kwan: McGill University
Bing Ge: McGill University
Lars Rönnblom: Uppsala University
Mark I. McCarthy: Wellcome Trust Centre for Human Genetics, University of Oxford
Panos Deloukas: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus
Todd Richmond: Roche NimbleGen
Daniel Burgess: Roche NimbleGen
Timothy D. Spector: King's College London, St Thomas' Campus
André Tchernof: Québec Heart and Lung Institute, Université Laval
Simon Marceau: Québec Heart and Lung Institute, Université Laval
Mark Lathrop: McGill University
Marie-Claude Vohl: Institute of Nutrition and Functional Foods (INAF), Université Laval
Tomi Pastinen: McGill University
Elin Grundberg: McGill University

Nature Communications, 2015, vol. 6, issue 1, 1-12

Abstract: Abstract 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.

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/ncomms8211 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms8211

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/ncomms8211

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().