Evidence map›Paper›PMID 42468531›Full record

ArticleCell systems2026

Foundation model reveals the shared organization of transcription and topologically associating domains.

Huan Liang, Bonnie Berger, Rohit Singh

Abstract read
In one paragraph

Article in Cell systems, 2026. 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

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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

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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

5 · Who and what money

Authors and funding

3 authors.

Huan LiangDepartment of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
Bonnie BergerComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA. Electronic address: bab@mit.edu.
Rohit SinghDepartment of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA; Department of Cell Biology, Duke University, Durham, NC, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA. Electronic address: rohit.singh@duke.edu.

Funding

Structure-Based Prediction of the InteractomeR01GM081871 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BERGER, BONNIE · 2008 to 2020
$4.3M
Privacy-preserving genomic medicine at scaleR01HG010959 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BERGER, BONNIE · 2020 to 2023
$2.6M
Manifold representations and active learning for 21 st century biologyR35GM141861 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BERGER, BONNIE · 2021 to 2025
$1.9M
NHGRI NIH HHS R01 HG010959NIGMS NIH HHS R01 GM081871NIGMS NIH HHS R35 GM141861
6 · The paper itself

Abstract

The three-dimensional organization of chromatin into topologically associating domains (TADs) may impact gene regulation by bringing distant genes into contact. However, studies of TADs' function and their influence on transcription have been constrained by ambiguities in TAD boundary definitions and challenges in directly measuring their regulatory effects. We overcome these limitations by developing species-level consensus TAD maps for human and mouse by using a bag-of-genes approach that exposes an emergent regulatory structure. To quantify TAD-mediated relationships, we use a foundation model trained on 33 million transcriptomes to define a contextual similarity metric that captures higher-order relationships missed by co-expression. We find that TADs are regions of elevated co-regulation, with our framework yielding testable hypotheses about chromatin organization across cellular states. This TAD-linked enhancement is strongest during early development and declines with aging, while cancer cells show distinct TAD usage that shifts with chemotherapy. Together, these findings suggest that chromatin organization acts through probabilistic rather than deterministic mechanisms.

Indexed as

ChromatinTranscription, GeneticAnimalsChromatin Assembly and DisassemblyGene Expression RegulationHumansMiceTranscriptomeChromatin3D genomebag of genescontextual transcriptional similaritygene expressionnuclear plasticitysingle-cell foundation modelstopologically associating domain

Identifiers

PMID42468531
PMCPMC13418072

What Socratic holds

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Registered trials

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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 Socratic graph.