An integrated -omics analysis of the epigenetic landscape of gene expression in human blood cells

Gene expression can be influenced by DNA methylation 1) distally, at regulatory elements such as enhancers, as well as 2) proximally, at promoters. Our current understanding of the influence of distal DNA methylation changes on gene expression patterns is incomplete. Here, we characterize genome-wid...

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Bibliographic Details
Published in:BMC genomics 2018-06, Vol.19 (1), p.476-476, Article 476
Main Authors: Kennedy, Elizabeth M, Goehring, George N, Nichols, Michael H, Robins, Chloe, Mehta, Divya, Klengel, Torsten, Eskin, Eleazar, Smith, Alicia K, Conneely, Karen N
Format: Article
Language:English
Subjects:
Adolescent
Adult
Aged
Analysis
Atherosclerosis
Binding sites
Biological effects
Blood
Blood cells
Blood Cells - metabolism
Chromatin
Cohort Studies
CpG Islands
Data mining
Data processing
Deoxyribonucleic acid
DNA
DNA Methylation
Enhancers
Enrichment
Epigenesis, Genetic
Epigenetic inheritance
Epigenetics
Female
Gene expression
Gene Expression Profiling
Gene Ontology
Genes
Genetic transcription
Genomes
Genomics
Humans
Insulators
Male
Methylation
MicroRNAs
Middle Aged
miRNA
Promoters
Regulatory sequences
Ribonucleic acid
RNA
Studies
Transcriptional regulation
Young Adult
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Summary:Gene expression can be influenced by DNA methylation 1) distally, at regulatory elements such as enhancers, as well as 2) proximally, at promoters. Our current understanding of the influence of distal DNA methylation changes on gene expression patterns is incomplete. Here, we characterize genome-wide methylation and expression patterns for ~ 13 k genes to explore how DNA methylation interacts with gene expression, throughout the genome. We used a linear mixed model framework to assess the correlation of DNA methylation at ~ 400 k CpGs with gene expression changes at ~ 13 k transcripts in two independent datasets from human blood cells. Among CpGs at which methylation significantly associates with transcription (eCpGs), > 50% are distal (> 50 kb) or trans (different chromosome) to the correlated gene. Many eCpG-transcript pairs are consistent between studies and ~ 90% of neighboring eCpGs associate with the same gene, within studies. We find that enhancers (P 
ISSN:1471-2164
1471-2164
DOI:10.1186/s12864-018-4842-3