Evidence map›Paper›PMID 40949959›Full record

ArticlebioRxiv : the preprint server for biology2025

Reconstructing the 3D genome organization of Neanderthals reveals that chromatin folding shaped phenotypic and sequence divergence.

Evonne McArthur, David C Rinker, Yang Cheng, Qixuan Wang, Juan Wang, Erin N Gilbertson, Geoff Fudenberg, Maureen Pittman, Kathleen Keough, Feng Yue and 2 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Evonne McArthurDepartment of Medicine, University of Washington, Seattle, WA.ORCID 0000-0003-4566-4321
David C RinkerDepartment of Biological Sciences, Vanderbilt University, Nashville, TN.ORCID 0000-0001-5894-7633
Yang ChengDepartment of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL.
Qixuan WangDepartment of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL.
Juan WangDepartment of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL.
Erin N GilbertsonBakar Computational Health Sciences Institute, University of California, San Francisco, CA.
Geoff FudenbergDepartment of Computational and Quantitative Biology, University of Southern California, Los Angeles, CA.ORCID 0000-0001-5905-6517
Maureen PittmanGladstone Institute of Data Science and Biotechnology, San Francisco, CA.
Kathleen KeoughGladstone Institute of Data Science and Biotechnology, San Francisco, CA.ORCID 0000-0002-7481-0511
Feng YueDepartment of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL.
Katherine S PollardBakar Computational Health Sciences Institute, University of California, San Francisco, CA.
John A CapraVanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN.ORCID 0000-0001-9743-1795

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007347 · NIGMS · VANDERBILT UNIVERSITY · PI WILLIAMS, CHRISTOPHER S. · 1985 to 2023
$26.3M
The Evolution of Gene Regulation and Human DiseaseR35GM127087 · NIGMS · VANDERBILT UNIVERSITY · PI John Anthony Capra · 2018 to 2026
$3.2M
Genomes in 3D: from maps to mechanismsR35GM143116 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI FUDENBERG, GEOFFREY · 2021 to 2025
$2.1M
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 R35 GM143116NIGMS NIH HHS T32 GM007347
6 · The paper itself

Abstract

Changes in gene regulation were a major driver of the divergence of archaic hominins (AHs)-Neanderthals and Denisovans-and modern humans (MHs). The three-dimensional (3D) folding of the genome is critical for regulating gene expression; however, its role in recent human evolution has not been explored because the degradation of ancient samples does not permit experimental determination of AH 3D genome folding. To fill this gap, we apply novel deep learning methods for inferring 3D genome organization from DNA sequence to Neanderthal, Denisovan, and diverse MH genomes. Using the resulting 3D contact maps across the genome, we identify 167 distinct regions with diverged 3D genome organization between AHs and MHs. We show that these 3D-diverged loci are enriched for genes related to the function and morphology of the eye, supra-orbital ridges, hair, lungs, immune response, and cognition. Despite these specific diverged loci, the 3D genome of AHs and MHs is more similar than expected based on sequence divergence, suggesting that the pressure to maintain 3D genome organization constrained hominin sequence evolution. We also find that 3D genome organization constrained the landscape of AH ancestry in MHs today: regions more tolerant of 3D variation are enriched for introgression in modern Eurasians. Finally, we identify loci where modern Eurasians have inherited novel 3D genome folding patterns from AH ancestors and validate folding differences in a high-frequency locus using Hi-C, revealing a putative molecular mechanism for phenotypes associated with archaic introgression. In summary, our application of deep learning to predict archaic 3D genome organization illustrates the potential of inferring molecular phenotypes from ancient DNA to reveal previously unobservable biological differences.

Identifiers

PMID40949959
PMCPMC12424642

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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.