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Use of Allele-Specific FAIRE to Determine Functional Regulatory Polymorphism Using Large-Scale Genotyping Arrays

Overview of attention for article published in PLoS Genetics, August 2012
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Title
Use of Allele-Specific FAIRE to Determine Functional Regulatory Polymorphism Using Large-Scale Genotyping Arrays
Published in
PLoS Genetics, August 2012
DOI 10.1371/journal.pgen.1002908
Pubmed ID
Authors

Andrew J. P. Smith, Philip Howard, Sonia Shah, Per Eriksson, Stefan Stender, Claudia Giambartolomei, Lasse Folkersen, Anne Tybjærg-Hansen, Meena Kumari, Jutta Palmen, Aroon D. Hingorani, Philippa J. Talmud, Steve E. Humphries

Abstract

Following the widespread use of genome-wide association studies (GWAS), focus is turning towards identification of causal variants rather than simply genetic markers of diseases and traits. As a step towards a high-throughput method to identify genome-wide, non-coding, functional regulatory variants, we describe the technique of allele-specific FAIRE, utilising large-scale genotyping technology (FAIRE-gen) to determine allelic effects on chromatin accessibility and regulatory potential. FAIRE-gen was explored using lymphoblastoid cells and the 50,000 SNP Illumina CVD BeadChip. The technique identified an allele-specific regulatory polymorphism within NR1H3 (coding for LXR-α), rs7120118, coinciding with a previously GWAS-identified SNP for HDL-C levels. This finding was confirmed using FAIRE-gen with the 200,000 SNP Illumina Metabochip and verified with the established method of TaqMan allelic discrimination. Examination of this SNP in two prospective Caucasian cohorts comprising 15,000 individuals confirmed the association with HDL-C levels (combined beta = 0.016; p = 0.0006), and analysis of gene expression identified an allelic association with LXR-α expression in heart tissue. Using increasingly comprehensive genotyping chips and distinct tissues for examination, FAIRE-gen has the potential to aid the identification of many causal SNPs associated with disease from GWAS.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
Norway 2 3%
New Zealand 1 1%
Austria 1 1%
Japan 1 1%
Spain 1 1%
Unknown 63 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 36%
Student > Ph. D. Student 18 25%
Professor 5 7%
Professor > Associate Professor 5 7%
Student > Bachelor 4 6%
Other 11 15%
Unknown 3 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 58%
Medicine and Dentistry 11 15%
Biochemistry, Genetics and Molecular Biology 9 13%
Computer Science 2 3%
Mathematics 1 1%
Other 2 3%
Unknown 5 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 16 August 2012.
All research outputs
#22,756,649
of 25,371,288 outputs
Outputs from PLoS Genetics
#8,490
of 8,960 outputs
Outputs of similar age
#157,318
of 174,023 outputs
Outputs of similar age from PLoS Genetics
#144
of 172 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 172 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.