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Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation
BACKGROUND: A number of factors have been investigated in the context of gene function prediction and analysis, such as sequence identity, gene expressions, and gene co-evolution. However, three-dimensional (3D) conformation of the genome has not been tapped to analyse gene function, probably largel...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4625479/ https://www.ncbi.nlm.nih.gov/pubmed/26511362 http://dx.doi.org/10.1186/s12864-015-2093-0 |
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author | Cao, Renzhi Cheng, Jianlin |
author_facet | Cao, Renzhi Cheng, Jianlin |
author_sort | Cao, Renzhi |
collection | PubMed |
description | BACKGROUND: A number of factors have been investigated in the context of gene function prediction and analysis, such as sequence identity, gene expressions, and gene co-evolution. However, three-dimensional (3D) conformation of the genome has not been tapped to analyse gene function, probably largely due to lack of genome conformation data until recently. METHODS: We construct the genome-wide spatial gene-gene interaction networks for three different human B-cells or cell lines from their chromosomal contact data generated by the Hi-C chromosome conformation capturing technique. The G-SESAME and Fast-SemSim are used to calculate function similarity between interacted / non-interacted genes. The Gene Ontology statistics computed from the gene-gene interaction networks is used for gene function prediction. RESULTS: We compare the function similarity of gene pairs that do not spatially interact and that have interactions. We find that genes that have strong spatial interactions tend to have highly similar function in terms of biological process, molecular function and cellular component of the Gene Ontology. And even though the level of gene-gene interactions generally have no or weak correlation with either sequential genomic distance or sequence identity between genes, the interacted genes with high function similarity tend to have stronger interactions, somewhat shorter genomic distance and significantly higher sequence identity. And combining genomic distance or sequence identity with spatial gene-gene interaction information informs gene-gene function similarity much better than using either one of them alone, suggesting gene-gene interaction information is largely complementary with genomic distance and sequence identity in the context of gene function analysis. We develop and evaluate a new gene function prediction method based on gene-gene interacting networks, which can predict gene function well for a large number of human genes. CONCLUSIONS: In this work, we demonstrate that the spatial conformation of the human genome is relevant to gene function similarity and is useful for gene function prediction. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-2093-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4625479 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46254792015-10-30 Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation Cao, Renzhi Cheng, Jianlin BMC Genomics Research Article BACKGROUND: A number of factors have been investigated in the context of gene function prediction and analysis, such as sequence identity, gene expressions, and gene co-evolution. However, three-dimensional (3D) conformation of the genome has not been tapped to analyse gene function, probably largely due to lack of genome conformation data until recently. METHODS: We construct the genome-wide spatial gene-gene interaction networks for three different human B-cells or cell lines from their chromosomal contact data generated by the Hi-C chromosome conformation capturing technique. The G-SESAME and Fast-SemSim are used to calculate function similarity between interacted / non-interacted genes. The Gene Ontology statistics computed from the gene-gene interaction networks is used for gene function prediction. RESULTS: We compare the function similarity of gene pairs that do not spatially interact and that have interactions. We find that genes that have strong spatial interactions tend to have highly similar function in terms of biological process, molecular function and cellular component of the Gene Ontology. And even though the level of gene-gene interactions generally have no or weak correlation with either sequential genomic distance or sequence identity between genes, the interacted genes with high function similarity tend to have stronger interactions, somewhat shorter genomic distance and significantly higher sequence identity. And combining genomic distance or sequence identity with spatial gene-gene interaction information informs gene-gene function similarity much better than using either one of them alone, suggesting gene-gene interaction information is largely complementary with genomic distance and sequence identity in the context of gene function analysis. We develop and evaluate a new gene function prediction method based on gene-gene interacting networks, which can predict gene function well for a large number of human genes. CONCLUSIONS: In this work, we demonstrate that the spatial conformation of the human genome is relevant to gene function similarity and is useful for gene function prediction. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-2093-0) contains supplementary material, which is available to authorized users. BioMed Central 2015-10-28 /pmc/articles/PMC4625479/ /pubmed/26511362 http://dx.doi.org/10.1186/s12864-015-2093-0 Text en © Cao and Cheng. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Cao, Renzhi Cheng, Jianlin Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation |
title | Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation |
title_full | Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation |
title_fullStr | Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation |
title_full_unstemmed | Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation |
title_short | Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation |
title_sort | deciphering the association between gene function and spatial gene-gene interactions in 3d human genome conformation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4625479/ https://www.ncbi.nlm.nih.gov/pubmed/26511362 http://dx.doi.org/10.1186/s12864-015-2093-0 |
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