Characterization of functional methylomes by next-generation capture sequencing identifies novel disease-associated variants
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- 20.500.11794/66730
- 2041-1723
- doi: 10.1038/ncomms8211
- 26021296
http://purl.org/coar/access_right/c_abf2
Mots-clés
ADN -- Méthylation Tissu adipeux Polymorphisme de nucléotide simple Triglycérides Lipoprotéines de haute densitéSujets proches
Data bases Data bases Data bases Database systems Databanks Data banks Socratic method Interrogation Structural plates Panels Disks (Mechanics) illnessCiter ce document
Fiona Allum et al., « Characterization of functional methylomes by next-generation capture sequencing identifies novel disease-associated variants », CorpusUL, l'archive ouverte de l'université Laval, ID : 10.1038/ncomms8211
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Résumé
Most genome-wide methylation studies (EWAS) of multifactorial disease traits use targetedarrays or enrichment methodologies preferentially covering CpG-dense regions, tocharacterize sufficiently large samples. To overcome this limitation, we present here a newcustomizable, cost-effective approach, methylC-capture sequencing (MCC-Seq), forsequencing functional methylomes, while simultaneously providing genetic variationinformation. To illustrate MCC-Seq, we use whole-genome bisulfite sequencing on adiposetissue (AT) samples and public databases to design AT-specific panels. We establish itsefficiency for high-density interrogation of methylome variability by systematic comparisonswith other approaches and demonstrate its applicability by identifying novel methylationvariation within enhancers strongly correlated to plasma triglyceride and HDL-cholesterol,including atCD36. Our more comprehensive AT panel assesses tissue methylation andgenotypes in parallel atB4 andB3 M sites, respectively. Our study demonstrates thatMCC-Seq provides comparable accuracy to alternative approaches but enables more efficientcataloguing of functional and disease-relevant epigenetic and genetic variants for large-scale EWAS.
