Spatial proximity and gene function: a new dimension in prokaryotic gene association network analysis with 3D-GeneNet
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Understanding the biological functions and processes of genes, particularly those not yet characterized, is crucial for advancing molecular biology and identifying therapeutic targets. The hypothesis guiding this study is that the 3D proximity of genes correlates with their functional interactions and relevance in prokaryotes. We introduced 3D-GeneNet, an innovative software tool that utilizes high-throughput sequencing data from chromosome conformation capture techniques and integrates topological metrics to construct gene association networks. Through a series of comparative analyses focused on spatial versus linear distances, we explored various dimensions such as topological structure, functional enrichment levels, distribution patterns of linear distances among gene pairs, and the area under the receiver operating characteristic curve by utilizing model organism Escherichia coli K-12. Furthermore, 3D-GeneNet was shown to maintain good accuracy compared to multiple algorithms (neighbourhood, co-occurrence, coexpression, and fusion) across multiple bacteria, including E. coli, Brucella abortus, and Vibrio cholerae. In addition, the accuracy of 3D-GeneNet’s prediction of long-distance gene interactions was identified by bacterial two-hybrid assays on E. coli K-12 MG1655, where 3D-GeneNet not only increased the accuracy of linear genomic distance tripled but also achieved 60% accuracy by running alone. Finally, it can be concluded that the applicability of 3D-GeneNet will extend to various bacterial forms, including Gram-negative, Gram-positive, single-, and multi-chromosomal bacteria through Hi-C sequencing and analysis. Such findings highlight the broad applicability and significant promise of this method in the realm of gene association network. 3D-GeneNet is freely accessible at https://github.com/gaoyuanccc/3D-GeneNet.
Date Issued
2024-07-01
Date Acceptance
2024-06-18
Citation
Briefings in Bioinformatics, 2024, 25 (4)
ISSN
1467-5463
Publisher
Oxford University Press
Journal / Book Title
Briefings in Bioinformatics
Volume
25
Issue
4
Copyright Statement
© The Author(s) 2024. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/ licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/38975892
PII: 7709087
Subjects
3D genome
Biochemical Research Methods
Biochemistry & Molecular Biology
CHROMOSOME
CLUSTERS
CONDENSIN
DATABASE
ESCHERICHIA-COLI
gene association networks
hi-C
HI-C
Life Sciences & Biomedicine
long-distance interactions
Mathematical & Computational Biology
ORGANIZATION
PRINCIPLES
prokaryotic
PROTEINS
Science & Technology
STREPTOCOCCUS-SUIS
Publication Status
Published
Coverage Spatial
England
Article Number
bbae320
Date Publish Online
2024-07-08