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
Preview |
Text
ncomms8211.pdf - Published Version Available under License Creative Commons Attribution. Download (641kB) |
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.
Item Type: | Article |
---|---|
Identification Number: | 10.1038/ncomms8211 |
Dates: | Date Event 29 May 2015 Published |
Subjects: | CAH01 - medicine and dentistry > CAH01-01 - medicine and dentistry > CAH01-01-01 - medical sciences (non-specific) CAH03 - biological and sport sciences > CAH03-01 - biosciences > CAH03-01-07 - genetics CAH03 - biological and sport sciences > CAH03-01 - biosciences > CAH03-01-08 - molecular biology, biophysics and biochemistry |
Divisions: | Faculty of Health, Education and Life Sciences > College of Health and Care Professions |
Depositing User: | Loukia Tsaprouni |
Date Deposited: | 04 Jul 2017 09:13 |
Last Modified: | 03 Mar 2022 15:38 |
URI: | https://www.open-access.bcu.ac.uk/id/eprint/4778 |
Actions (login required)
![]() |
View Item |