↓ Skip to main content

Chromosome contacts in activated T cells identify autoimmune disease candidate genes

Overview of attention for article published in Genome Biology, September 2017
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
37 X users
wikipedia
7 Wikipedia pages

Citations

dimensions_citation
73 Dimensions

Readers on

mendeley
121 Mendeley
citeulike
2 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Chromosome contacts in activated T cells identify autoimmune disease candidate genes
Published in
Genome Biology, September 2017
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

X Demographics

The data shown below were collected from the profiles of 37 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.

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%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 22 February 2024.
All research outputs
#1,564,577
of 25,382,440 outputs
Outputs from Genome Biology
#1,274
of 4,468 outputs
Outputs of similar age
#30,415
of 323,619 outputs
Outputs of similar age from Genome Biology
#30
of 55 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
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 has gotten more attention than average, scoring higher than 71% of its peers.
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 323,619 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.