Evidence map›Paper›PMID 40234426›Full record

ArticleNPJ systems biology and applications2025

Predicting gene expression changes from chromatin structure modification.

Swayamshree Senapati, Inayat Ullah Irshad, Ajeet K Sharma, Hemant Kumar

Abstract read
In one paragraph

Article in NPJ systems biology and applications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

4 authors.

Swayamshree SenapatiSchool of Basic Sciences, Indian Institute of Technology Bhubaneswar, Argul, Odisha, 752050, India.
Inayat Ullah IrshadDepartment of Physics, Indian Institute of Technology Jammu, Jammu, 181221, India.
Ajeet K SharmaDepartment of Physics, Indian Institute of Technology Jammu, Jammu, 181221, India.
Hemant KumarSchool of Basic Sciences, Indian Institute of Technology Bhubaneswar, Argul, Odisha, 752050, India. hemant@iitbbs.ac.in.ORCID http://orcid.org/0000-0003-4339-5711

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spatial organization of chromatin plays a critical role in gene transcription, but connecting population-averaged HiC data to functional outcomes remains a challenge. We present a computational framework linking HiC contact map to gene transcription. Utilizing a bead-spring polymer model informed by HiC contact maps, we generate an ensemble of 3D conformations for a given genomic locus. These conformations are then coupled to gene transcription levels through a Markov chain model, with transition rates derived from molecular dynamics simulations. The efficacy of this framework is demonstrated by simulating the perturbation of a CTCF-mediated TAD boundary, impacting the expression of sox9 and kcnj2. Our model quantitatively reproduces experimentally observed changes in gene expression, revealing that the increased kcnj2 transcription is a consequence of enhancers within the sox9 TAD becoming accessible upon boundary disruption. Quantifying enhancer impact, our model can also identify functional enhancers. This framework enhances our understanding of the relationship between chromosome spatial architecture and gene regulation.

Indexed as

ChromatinGene Expression RegulationCCCTC-Binding FactorComputational BiologyEnhancer Elements, GeneticHumansMarkov ChainsMolecular Dynamics SimulationPotassium Channels, Inwardly RectifyingSOX9 Transcription FactorTranscription, GeneticCCCTC-Binding FactorChromatinPotassium Channels, Inwardly RectifyingSOX9 Transcription Factor

Identifiers

PMID40234426
PMCPMC12000410

What OpenQuestion 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 OpenQuestion graph.