Evidence map›Paper›PMID 32987404›Full record

ArticleBriefings in bioinformatics2021

Spatial density of open chromatin: an effective metric for the functional characterization of topologically associated domains.

Shuai Jiang, Hao Li, Hao Hong, Guifang Du, Xin Huang, Yu Sun, Junting Wang, Huan Tao, Kang Xu, Cheng Li and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 37% of its field
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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 3D genomic organization in cancers.Quantitative biology (Beijing, China) · 2023
    Review
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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

13 authors at 4 institutions in 3 countries.

Shuai JiangBeijing Institute of Ratiation Medicine, Department of Biotechnology.
Hao LiBeijing Institute of Radiation Medicine.
Hao HongBeijing Institute of Ratiation Medicine, Department of Biotechnology.
Guifang DuBeijing Institute of Ratiation Medicine, Department of Biotechnology.
Xin HuangBeijing Institute of Ratiation Medicine, Department of Biotechnology.
Yu SunBeijing Institute of Ratiation Medicine, Department of Biotechnology.
Junting WangBeijing Institute of Radiation Medicine.
Huan TaoBeijing Institute of Radiation Medicine.
Kang XuBeijing Institute of Radiation Medicine.
Cheng LiPeking-Tsinghua Center for Life Sciences, School of Life Sciences, Peking University. He is also a Professor at the Center for Statistical Science and the Center for Bioinformatics in Peking University.
Yang ChenMOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, School of Medicine and Department of Automation in Tsinghua University.
Hebing ChenBeijing Institute of Radiation Medicine.
Xiaochen BoBeijing Institute of Radiation Medicine.ORCID 0000-0003-1911-7922
Beijing Radiation Center · CNCzech Academy of Sciences, Institute of Biotechnology · CZPeking University · CNTsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Topologically associated domains (TADs) are spatial and functional units of metazoan chromatin structure. Interpretation of the interplay between regulatory factors and chromatin structure within TADs is crucial to understand the spatial and temporal regulation of gene expression. However, a computational metric for the sensitive characterization of TAD regulatory landscape is lacking. Here, we present the spatial density of open chromatin (SDOC) metric as a quantitative measurement of intra-TAD chromatin state and structure. SDOC sensitively reflects epigenetic properties and gene transcriptional activity in TADs. During mouse T-cell development, we found that TADs with decreased SDOC are enriched in repressed developmental genes, and the joint effect of SDOC-decreasing and TAD clustering corresponds to the highest level of gene repression. In addition, we revealed a pervasive preference for TADs with similar SDOC to interact with each other, which may reflect the principle of chromatin organization.

Indexed as

AlgorithmsAnimalsCell DifferentiationCell LineChromatinChromatin Assembly and DisassemblyCluster AnalysisComputational BiologyEpigenomicsGene Expression ProfilingGenomeHumansK562 CellsReproducibility of ResultsRNA-SeqT-LymphocytesChromatinHi-Ctopologically associated domainstranscriptional regulation

Identifiers

PMID32987404
PMCPMC8138881
OpenAlexW3090265556

What OpenQuestion 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 OpenQuestion graph.