Title |
Chromosome contacts in activated T cells identify autoimmune disease candidate genes
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Published in |
Genome Biology, September 2017
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DOI | 10.1186/s13059-017-1285-0 |
Pubmed ID | |
Authors |
Oliver S. Burren, Arcadio Rubio García, Biola-Maria Javierre, Daniel B. Rainbow, Jonathan Cairns, Nicholas J. Cooper, John J. Lambourne, Ellen Schofield, Xaquin Castro Dopico, Ricardo C. Ferreira, Richard Coulson, Frances Burden, Sophia P. Rowlston, Kate Downes, Steven W. Wingett, Mattia Frontini, Willem H. Ouwehand, Peter Fraser, Mikhail Spivakov, John A. Todd, Linda S. Wicker, Antony J. Cutler, Chris Wallace |
Abstract |
Autoimmune disease-associated variants are preferentially found in regulatory regions in immune cells, particularly CD4(+) T cells. Linking such regulatory regions to gene promoters in disease-relevant cell contexts facilitates identification of candidate disease genes. Within 4 h, activation of CD4(+) T cells invokes changes in histone modifications and enhancer RNA transcription that correspond to altered expression of the interacting genes identified by promoter capture Hi-C. By integrating promoter capture Hi-C data with genetic associations for five autoimmune diseases, we prioritised 245 candidate genes with a median distance from peak signal to prioritised gene of 153 kb. Just under half (108/245) prioritised genes related to activation-sensitive interactions. This included IL2RA, where allele-specific expression analyses were consistent with its interaction-mediated regulation, illustrating the utility of the approach. Our systematic experimental framework offers an alternative approach to candidate causal gene identification for variants with cell state-specific functional effects, with achievable sample sizes. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 13 | 35% |
United States | 8 | 22% |
Germany | 2 | 5% |
New Zealand | 1 | 3% |
Australia | 1 | 3% |
Israel | 1 | 3% |
Unknown | 11 | 30% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 18 | 49% |
Scientists | 17 | 46% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 121 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 26 | 21% |
Student > Ph. D. Student | 25 | 21% |
Student > Bachelor | 11 | 9% |
Student > Doctoral Student | 10 | 8% |
Student > Master | 7 | 6% |
Other | 19 | 16% |
Unknown | 23 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 42 | 35% |
Agricultural and Biological Sciences | 25 | 21% |
Medicine and Dentistry | 8 | 7% |
Immunology and Microbiology | 5 | 4% |
Computer Science | 3 | 2% |
Other | 13 | 11% |
Unknown | 25 | 21% |