Characterization of Functional Methylomes by Next-Generation Capture Sequencing Identifies Novel Disease Variants in Distal Regulatory Elements
Elin Grundberg, PhD
Tuesday, September 30, 2014
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Chapters
Introduction
Cellular Traits in population for mapping disease loci
Array-based metabolic disease epigenomics
DNA methylation variation dependent on genomic location
Phenotype-associated CpGs enriched in distal regulatory regions
Disease variants regulating methylation maps to enhancer elements
Summary of array-based metabolic disease epigenomics
Unbiased NGS-based metabolic disease epigenomics
Data filtering
Hypomethylated footprints overlap regulatory elements
Global DNA methylation landscape in adipose tissue
Summary of metabolic disease methylome investigation
Interrogation of functional methylome for metabolic trait association studies
First-generation disease-specific SeqCap panel (V1)
Second-generation disease-specific SeqCap panel (V2)
Technical validation of MCC-Seq
Applications of MCC-Seq in populations using SeqCap
Epigenome-wide assocation study of blood lipids-discovery
Epigenome-wide assocation study of blood lipids-validation
Reference epigenome mapping in human adipocytes
Identification of Novel Epigenetic Disease Variants using MCC-Seq/SeqCap
Fine-Mapping of Epigenetic Disease Variants using MCC-Seq/SeqCap
Analysis of methylation quantitative trait loci (metQTLs)
Conclusions
Acknowledgment
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