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Functional variation in allelic methylomes underscores a strong genetic contribution and reveals novel epigenetic alterations in the human epigenome

Overview of attention for article published in Genome Biology, March 2017
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  • Above-average Attention Score compared to outputs of the same age (62nd percentile)

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Citations

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74 Dimensions

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129 Mendeley
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Title
Functional variation in allelic methylomes underscores a strong genetic contribution and reveals novel epigenetic alterations in the human epigenome
Published in
Genome Biology, March 2017
DOI 10.1186/s13059-017-1173-7
Pubmed ID
Authors

Warren A. Cheung, Xiaojian Shao, Andréanne Morin, Valérie Siroux, Tony Kwan, Bing Ge, Dylan Aïssi, Lu Chen, Louella Vasquez, Fiona Allum, Frédéric Guénard, Emmanuelle Bouzigon, Marie-Michelle Simon, Elodie Boulier, Adriana Redensek, Stephen Watt, Avik Datta, Laura Clarke, Paul Flicek, Daniel Mead, Dirk S. Paul, Stephan Beck, Guillaume Bourque, Mark Lathrop, André Tchernof, Marie-Claude Vohl, Florence Demenais, Isabelle Pin, Kate Downes, Hendrick G. Stunnenberg, Nicole Soranzo, Tomi Pastinen, Elin Grundberg

Abstract

The functional impact of genetic variation has been extensively surveyed, revealing that genetic changes correlated to phenotypes lie mostly in non-coding genomic regions. Studies have linked allele-specific genetic changes to gene expression, DNA methylation, and histone marks but these investigations have only been carried out in a limited set of samples. We describe a large-scale coordinated study of allelic and non-allelic effects on DNA methylation, histone mark deposition, and gene expression, detecting the interrelations between epigenetic and functional features at unprecedented resolution. We use information from whole genome and targeted bisulfite sequencing from 910 samples to perform genotype-dependent analyses of allele-specific methylation (ASM) and non-allelic methylation (mQTL). In addition, we introduce a novel genotype-independent test to detect methylation imbalance between chromosomes. Of the ~2.2 million CpGs tested for ASM, mQTL, and genotype-independent effects, we identify ~32% as being genetically regulated (ASM or mQTL) and ~14% as being putatively epigenetically regulated. We also show that epigenetically driven effects are strongly enriched in repressed regions and near transcription start sites, whereas the genetically regulated CpGs are enriched in enhancers. Known imprinted regions are enriched among epigenetically regulated loci, but we also observe several novel genomic regions (e.g., HOX genes) as being epigenetically regulated. Finally, we use our ASM datasets for functional interpretation of disease-associated loci and show the advantage of utilizing naïve T cells for understanding autoimmune diseases. Our rich catalogue of haploid methylomes across multiple tissues will allow validation of epigenome association studies and exploration of new biological models for allelic exclusion in the human genome.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 129 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 28%
Researcher 30 23%
Other 11 9%
Student > Bachelor 9 7%
Student > Master 9 7%
Other 21 16%
Unknown 13 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 42 33%
Agricultural and Biological Sciences 35 27%
Medicine and Dentistry 9 7%
Computer Science 7 5%
Nursing and Health Professions 4 3%
Other 13 10%
Unknown 19 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 July 2017.
All research outputs
#7,962,193
of 25,382,440 outputs
Outputs from Genome Biology
#3,393
of 4,468 outputs
Outputs of similar age
#118,821
of 321,209 outputs
Outputs of similar age from Genome Biology
#49
of 60 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 321,209 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.