Evidence map›Paper›PMID 33545030›Full record

ArticleAmerican journal of human genetics2021

Topologically associating domain boundaries that are stable across diverse cell types are evolutionarily constrained and enriched for heritability.

Evonne McArthur, John A Capra

Open access · bronzeAbstract read
In one paragraph

Article in American journal of human genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 129 papers.

0numbers the graph read from it
0cells of the map it votes in
129citing papers in PubMed
12.7field-weighted citation impact, top 1% 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

129 citing papers in PubMed, 205 citations in OpenAlex.

  1. Article
  2. Article
  3. The dark genome in cardiovascular medicine.European heart journal · 2026
    Review
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  5. Review
  6. Article
  7. Evolution of CTCF binding sites in the human genome.Molecular biology and evolution · 2026
    Article
  8. Review
  9. Article
  10. Article
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  18. Interaction Between Enhancers and Promoters in Chicken Genome.International journal of molecular sciences · 2025
    Article
  19. Review
  20. Article

69 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

2 authors at 2 institutions in 1 country.

Evonne McArthurVanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37235, USA.
John A CapraVanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37235, USA; Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, 94158; Bakar Institute for Computational Health Sciences, University of California, San Francisco, CA, 94158. Electronic address: tony.capra@ucsf.edu.
University of California, San Francisco · USVanderbilt University Medical Center · US

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007347 · NIGMS · VANDERBILT UNIVERSITY · PI WILLIAMS, CHRISTOPHER S. · 1985 to 2023
$26.3M
Medical Scientist Training ProgramT32GM152284 · NIGMS · VANDERBILT UNIVERSITY · PI Christopher S. Williams · 2024 to 2026
$4.8M
The Evolution of Gene Regulation and Human DiseaseR35GM127087 · NIGMS · VANDERBILT UNIVERSITY · PI John Anthony Capra · 2018 to 2026
$3.2M
Quantifying the relationship between 3D genome structure and the genetic architecture of common complex diseaseF30HG011200 · NHGRI · VANDERBILT UNIVERSITY · PI MCARTHUR, EVONNE · 2020 to 2022
$108k
NHGRI NIH HHS F30 HG011200NIGMS NIH HHS R35 GM127087NIGMS NIH HHS T32 GM007347NIGMS NIH HHS T32 GM152284
6 · The paper itself

Abstract

Topologically associating domains (TADs) are fundamental units of three-dimensional (3D) nuclear organization. The regions bordering TADs-TAD boundaries-contribute to the regulation of gene expression by restricting interactions of cis-regulatory sequences to their target genes. TAD and TAD-boundary disruption have been implicated in rare-disease pathogenesis; however, we have a limited framework for integrating TADs and their variation across cell types into the interpretation of common-trait-associated variants. Here, we investigate an attribute of 3D genome architecture-the stability of TAD boundaries across cell types-and demonstrate its relevance to understanding how genetic variation in TADs contributes to complex disease. By synthesizing TAD maps across 37 diverse cell types with 41 genome-wide association studies (GWASs), we investigate the differences in disease association and evolutionary pressure on variation in TADs versus TAD boundaries. We demonstrate that genetic variation in TAD boundaries contributes more to complex-trait heritability, especially for immunologic, hematologic, and metabolic traits. We also show that TAD boundaries are more evolutionarily constrained than TADs. Next, stratifying boundaries by their stability across cell types, we find substantial variation. Compared to boundaries unique to a specific cell type, boundaries stable across cell types are further enriched for complex-trait heritability, evolutionary constraint, CTCF binding, and housekeeping genes. Thus, considering TAD boundary stability across cell types provides valuable context for understanding the genome's functional landscape and enabling variant interpretation that takes 3D structure into account.

Indexed as

ChromatinEvolution, MolecularGenetic VariationGenome, HumanMultifactorial InheritanceCells, CulturedEmbryonic Stem CellsGene Expression RegulationGenome-Wide Association StudyHumansChromatincomplex diseaseevolutionary conservationgenome 3D structuregenome topologyheritabilityHi-CTAD stabilityTopologically associating domain

Identifiers

PMID33545030
PMCPMC7895846
OpenAlexW3126332871

What OpenQuestion holds

Textmetadata
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.