Evidence map›Paper›PMID 26150425›Full record

ArticleNucleic acids research2015

Structural heterogeneity and functional diversity of topologically associating domains in mammalian genomes.

Xiao-Tao Wang, Peng-Fei Dong, Hong-Yu Zhang, Cheng Peng

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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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3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Article
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  4. LDB1 establishes multi-enhancer networks to regulate gene expression.bioRxiv : the preprint server for biology · 2024
    Article
  5. Article
  6. Article
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  11. Methods for mapping 3D chromosome architecture.Nature reviews. Genetics · 2020
    Review
  12. Article
  13. Article
  14. The TAD-pathway for GWAS signals.European journal of human genetics : EJHG · 2017
    Article
  15. Review
  16. Review
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.

Xiao-Tao WangAgricultural Bioinformatics Key Laboratory of Hubei Province, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.
Peng-Fei DongAgricultural Bioinformatics Key Laboratory of Hubei Province, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.
Hong-Yu ZhangAgricultural Bioinformatics Key Laboratory of Hubei Province, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.
Cheng PengAgricultural Bioinformatics Key Laboratory of Hubei Province, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China pengcheng@mail.hzau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent chromosome conformation capture (3C) derived techniques have revealed that topologically associating domain (TAD) is a pervasive element in chromatin three-dimensional (3D) organization. However, there is currently no parameter to quantitatively measure the structural characteristics of TADs, thus obscuring our understanding on the structural and functional differences among TADs. Based on our finding that there exist intrinsic chromatin interaction patterns in TADs, we define a theoretical parameter, called aggregation preference (AP), to characterize TAD structures by capturing the interaction aggregation degree. Applying this defined parameter to 11 Hi-C data sets generated by both traditional and in situ Hi-C experimental pipelines, our analyses reveal that heterogeneous structures exist among TADs, and this structural heterogeneity is significantly correlated to DNA sequences, epigenomic signals and gene expressions. Although TADs can be stable in genomic positions across cell lines, structural comparisons show that a considerable number of stable TADs undergo significantly structural rearrangements during cell changes. Moreover, the structural change of TAD is tightly associated with its transcription remodeling. Altogether, the theoretical parameter defined in this work provides a quantitative method to link structural characteristics and biological functions of TADs, and this linkage implies that chromatin interaction pattern has the potential to mark transcription activity in TADs.

Indexed as

GenomeAnimalsBase SequenceCell LineChromatinDNAEpigenesis, GeneticGenome, HumanHumansMiceTranscription, GeneticChromatinDNA

Identifiers

PMID26150425
PMCPMC4551926

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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.