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

Allum, F, Shao, X, Guénard, F, Simon, MM, Busche, S, Caron, M, Lambourne, J, Lessard, J, Tandre, K, Hedman, ÅK , Kwan, T, Ge, B, Rönnblom, L, McCarthy, MI, Deloukas, P, Richmond, T, Burgess, D, Spector, TD, Tchernof, A, Marceau, S, Lathrop, M, Vohl, MC, Pastinen, T, Grundberg, E, Ahmadi, KR, Ainali, C, Barrett, A, Bataille, V, Bell, JT, Buil, A, Dermitzakis, ET, Dimas, AS, Durbin, R, Glass, D, Hassanali, N, Ingle, C, Knowles, D, Krestyaninova, M, Lindgren, CM, Lowe, CE, Meduri, E, Di Meglio, P, Min, JL, Montgomery, SB, Nestle, FO, Nica, AC, Nisbet, J, O'Rahilly, S, Parts, L, Potter, S, Sandling, J, Sekowska, M, Shin, SY, Small, KS, Soranzo, N, Surdulescu, G, Travers, ME, Tsaprouni, L, Tsoka, S, Wilk, A, Yang, TP and Zondervan, KT (2015) Characterization of functional methylomes by next-generation capture sequencing identifies novel disease-associated variants Nature Communications, 6.

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Abstract

© 2015 Macmillan Publishers Limited. All rights reserved.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 ∼3M 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
Authors :
NameEmailORCID
Allum, F
Shao, X
Guénard, F
Simon, MM
Busche, S
Caron, M
Lambourne, J
Lessard, J
Tandre, K
Hedman, ÅK
Kwan, T
Ge, B
Rönnblom, L
McCarthy, MI
Deloukas, P
Richmond, T
Burgess, D
Spector, TD
Tchernof, A
Marceau, S
Lathrop, M
Vohl, MC
Pastinen, T
Grundberg, E
Ahmadi, KRk.ahmadi@surrey.ac.uk
Ainali, C
Barrett, A
Bataille, V
Bell, JT
Buil, A
Dermitzakis, ET
Dimas, AS
Durbin, R
Glass, D
Hassanali, N
Ingle, C
Knowles, D
Krestyaninova, M
Lindgren, CM
Lowe, CE
Meduri, E
Di Meglio, P
Min, JL
Montgomery, SB
Nestle, FO
Nica, AC
Nisbet, J
O'Rahilly, S
Parts, L
Potter, S
Sandling, J
Sekowska, M
Shin, SY
Small, KS
Soranzo, N
Surdulescu, G
Travers, ME
Tsaprouni, L
Tsoka, S
Wilk, A
Yang, TP
Zondervan, KT
Date : 29 May 2015
Identification Number : 10.1038/ncomms8211
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 10:32
Last Modified : 17 May 2017 14:50
URI: http://epubs.surrey.ac.uk/id/eprint/828238

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