Title |
Genetic–epigenetic interactions in cis: a major focus in the post-GWAS era
|
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Published in |
Genome Biology, June 2017
|
DOI | 10.1186/s13059-017-1250-y |
Pubmed ID | |
Authors |
Catherine Do, Alyssa Shearer, Masako Suzuki, Mary Beth Terry, Joel Gelernter, John M. Greally, Benjamin Tycko |
Abstract |
Studies on genetic-epigenetic interactions, including the mapping of methylation quantitative trait loci (mQTLs) and haplotype-dependent allele-specific DNA methylation (hap-ASM), have become a major focus in the post-genome-wide-association-study (GWAS) era. Such maps can nominate regulatory sequence variants that underlie GWAS signals for common diseases, ranging from neuropsychiatric disorders to cancers. Conversely, mQTLs need to be filtered out when searching for non-genetic effects in epigenome-wide association studies (EWAS). Sequence variants in CCCTC-binding factor (CTCF) and transcription factor binding sites have been mechanistically linked to mQTLs and hap-ASM. Identifying these sites can point to disease-associated transcriptional pathways, with implications for targeted treatment and prevention. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 8 | 26% |
United States | 6 | 19% |
Mexico | 1 | 3% |
Tunisia | 1 | 3% |
Japan | 1 | 3% |
France | 1 | 3% |
Canada | 1 | 3% |
Unknown | 12 | 39% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 15 | 48% |
Scientists | 12 | 39% |
Science communicators (journalists, bloggers, editors) | 4 | 13% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | <1% |
Unknown | 240 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 57 | 24% |
Student > Ph. D. Student | 53 | 22% |
Student > Master | 26 | 11% |
Student > Bachelor | 15 | 6% |
Student > Doctoral Student | 11 | 5% |
Other | 39 | 16% |
Unknown | 41 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 70 | 29% |
Agricultural and Biological Sciences | 70 | 29% |
Medicine and Dentistry | 14 | 6% |
Neuroscience | 7 | 3% |
Computer Science | 5 | 2% |
Other | 21 | 9% |
Unknown | 55 | 23% |