Evidence map›Paper›PMID 30478436›Full record

ArticleNature genetics2019

High-resolution genetic mapping of putative causal interactions between regions of open chromatin.

Natsuhiko Kumasaka, Andrew J Knights, Daniel J Gaffney

Abstract read
In one paragraph

Article in Nature genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 2 pooled it
5.6field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

80 citing papers in PubMed, 2 syntheses or guidelines pooled it, 120 citations in OpenAlex.

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  11. Hybrids reveal accessible chromatinbioRxiv : the preprint server for biology · 2025
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20 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Natsuhiko KumasakaWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Andrew J KnightsWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.ORCID http://orcid.org/0000-0003-2107-4175
Daniel J GaffneyWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK. dg13@sanger.ac.uk.ORCID http://orcid.org/0000-0002-1529-1862
Wellcome Sanger Institute · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

Physical interaction of regulatory elements in three-dimensional space poses a challenge for studies of disease because non-coding risk variants may be great distances from the genes they regulate. Experimental methods to capture these interactions, such as chromosome conformation capture, usually cannot assign causal direction of effect between regulatory elements, an important component of fine-mapping studies. We developed a Bayesian hierarchical approach that uses two-stage least squares and applied it to an ATAC-seq (assay for transposase-accessible chromatin using sequencing) data set from 100 individuals, to identify over 15,000 high-confidence causal interactions. Most (60%) interactions occurred over <20 kb, where chromosome conformation capture-based methods perform poorly. For a fraction of loci, we identified a single variant that alters accessibility across multiple regions, and experimentally validated the BLK locus, which is associated with multiple autoimmune diseases, using CRISPR genome editing. Our study highlights how association genetics of chromatin state is a powerful approach for identifying interactions between regulatory elements.

Indexed as

Autoimmune DiseasesBayes TheoremChromatinChromosome MappingChromosomesClustered Regularly Interspaced Short Palindromic RepeatsGene EditingGenome, HumanGenome-Wide Association StudyHigh-Throughput Nucleotide SequencingHumansPolymorphism, Single NucleotideRegulatory Sequences, Nucleic AcidTransposasesChromatinTransposases

Identifiers

PMID30478436
PMCPMC6330062
OpenAlexW2901749533

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.