Evidence map›Paper›PMID 39435341›Full record

ArticleComputational and structural biotechnology journal2024

Long-range transcription factor binding sites clustered regions may mediate transcriptional regulation through phase-separation interactions in early human embryo.

Mengge Tian, Xiaohan Tang, Zhangyi Ouyang, Yaru Li, Xuemei Bai, Bijia Chen, Shutong Yue, Pengzhen Hu, Xiaochen Bo, Chao Ren and 2 more

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

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

12 authors.

Mengge TianThe First Affiliated Hospital of Harbin Medical University, Harbin 150001, China.
Xiaohan TangThe First Affiliated Hospital of Harbin Medical University, Harbin 150001, China.
Zhangyi OuyangAcademy of Military Medical Sciences, Beijing 100850, China.
Yaru LiAcademy of Military Medical Sciences, Beijing 100850, China.
Xuemei BaiAcademy of Military Medical Sciences, Beijing 100850, China.
Bijia ChenAcademy of Military Medical Sciences, Beijing 100850, China.
Shutong YueAcademy of Military Medical Sciences, Beijing 100850, China.
Pengzhen HuAcademy of Military Medical Sciences, Beijing 100850, China.
Xiaochen BoAcademy of Military Medical Sciences, Beijing 100850, China.
Chao RenAcademy of Military Medical Sciences, Beijing 100850, China.
Hebing ChenAcademy of Military Medical Sciences, Beijing 100850, China.
Meisong LuThe First Affiliated Hospital of Harbin Medical University, Harbin 150001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In mammals, during the post-fertilization pre-implantation phase, the expression of cell type-specific genes is crucial for normal embryonic development, which is regulated by cis-regulatory elements (CREs). TFs control gene expression by interacting with CREs. Research shows that transcription factor binding sites (TFBSs) reflect the general characteristics of the regulatory genome. Here, we identified TFBSs from chromatin accessibility data in five stages of early human embryonic development, and quantified transcription factor binding sites-clustered regions (TFCRs) and their complexity (TC). Assigning TC values to TFCRs has made it possible to assess the functionality of these regulatory elements in a more quantitative way. Our findings reveal a robust correlation between TFCR complexity and gene expression starting from the 8Cell stage, which is when the zygotic genome is activated in humans. Furthermore, we have defined long-range TFCRs (LR-TFCRs) and conjecture that LR-TFCRs may regulate gene expression through phase-separation mechanisms during the early stages of human embryonic development.

Indexed as

Early embryoTranscriptional regulationTranscription factors binding sites clustered regions (TFCRs)

Identifiers

PMID39435341
PMCPMC11492133

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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.