ArticleComputational and structural biotechnology journal2019
Revealing Gene Function and Transcription Relationship by Reconstructing Gene-Level Chromatin Interaction.
Article in Computational and structural biotechnology journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 18 citations in OpenAlex.
- Prediction of CTCF loop anchor based on machine learning.Frontiers in genetics · 2023Article
- A global high-density chromatin interaction network reveals functional long-range and trans-chromosomal relationships.Genome biology · 2022Article
- A c-di-GMP Signaling Cascade Controls Motility, Biofilm Formation, and Virulence in Burkholderia thailandensis.Applied and environmental microbiology · 2022Article
- Application of artificial intelligence and machine learning for COVID-19 drug discovery and vaccine design.Briefings in bioinformatics · 2021Article
- A computational framework for identifying the transcription factors involved in enhancer-promoter loop formation.Molecular therapy. Nucleic acids · 2021Article
- Application of Sparse Representation in Bioinformatics.Frontiers in genetics · 2021Review
- Chromatin Interaction Responds to Breast Muscle Development and Intramuscular Fat Deposition Between Chinese Indigenous Chicken and Fast-Growing Broiler.Frontiers in cell and developmental biology · 2021Article
- Application of Multilayer Network Models in Bioinformatics.Frontiers in genetics · 2021Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chromatin is hierarchically organized in human interphase nuclei. Dynamic chromatin interactions are thought to influence gene transcription and cell fate determination. A consensus concept is that genes may form transcription factories within nucleus by spatially interaction. However, it is still not well known whether the function-related genes co-locate in three-dimensional (3D) space for co-transcription. Especially, there is a lack of visualization method that directly reflect the relationship between gene spatial interaction, gene function and co-transcription. In this study, we constructed three kinds of matrices based on gene ontology annotations, high-through chromosome conformation capture (Hi-C) data and RNA-seq data from twenty human tissues and cell lines. The comparative analysis for gene pairs revealed that 3D genome organization influences gene transcription predominantly at local scale. We found that the local genes within family clusters have similar transcription patterns. We also found that spatial reorganization of a histone gene cluster could control gene transcription. These observations suggest that function-related genes are close in space and activated or repressed together. Our work provided a framework for genome-wide studying the relationship between gene function, co-transcription and spatial interaction.
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