Evidence map›Paper›PMID 39657779›Full record

ArticleNucleic acids research2025

Motif distribution in genomes gives insights into gene clustering and co-regulation.

Atreyi Chakraborty, Sumant Chopde, Mallur Srivatsan Madhusudhan

Abstract read
In one paragraph

Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

3 authors.

Atreyi ChakrabortyDepartment of Biology, Indian Institute of Science Education and Research, Dr Homi Bhabha Rd, Pashan, Pune, Maharashtra 411008, India.ORCID 0009-0004-7924-2244
Sumant ChopdeDepartment of Data Science, Indian Institute of Science Education and Research, Dr Homi Bhabha Rd, Pashan, Pune, Maharashtra 411008, India.
Mallur Srivatsan MadhusudhanDepartment of Biology, Indian Institute of Science Education and Research, Dr Homi Bhabha Rd, Pashan, Pune, Maharashtra 411008, India.ORCID 0000-0002-2889-5884

Funding

Department of Biotechnology BT/PR40262/BTIS/137/38/2022Indian Institute of Science Education and Research Pune
6 · The paper itself

Abstract

We read the genome as proteins in the cell would - by studying the distributions of 5-6 base motifs of DNA in the whole genome or smaller stretches such as parts of, or whole chromosomes. This led us to some interesting findings about motif clustering and chromosome organization. It is quite clear that the motif distribution in genomes is not random at the length scales we examined: 1 kb to entire chromosomes. The observed-to-expected (OE) ratios of motif distributions show strong correlations in pairs of chromosomes that are susceptible to translocations. With the aid of examples, we suggest that similarity in motif distributions in promoter regions of genes could imply co-regulation. A simple extension of this idea empowers us with the ability to construct gene regulatory networks. Further, we could make inferences about the spatial proximity of genomic fragments using these motif distributions. Spatially proximal regions, as deduced by Hi-C or pcHi-C, were ∼3.5 times more likely to have their motif distributions correlated than non-proximal regions. These correlations had strong contributions from the CTCF protein recognizing motifs which are known markers of topologically associated domains. In general, correlating genomic regions by motif distribution comparisons alone is rife with functional information.

Indexed as

Gene Expression RegulationMultigene FamilyNucleotide MotifsCCCTC-Binding FactorGene Regulatory NetworksGenome, HumanHumansPromoter Regions, GeneticCCCTC-Binding FactorCTCF protein, human

Identifiers

PMID39657779
PMCPMC11724300

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.