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Phylostratigraphic analysis of gene co-expression network reveals the evolution of functional modules for ovarian cancer
Ovarian cancer (OV) is an extremely lethal disease. However, the evolutionary machineries of OV are still largely unknown. Here, we used a method that combines phylostratigraphy information with gene co-expression networks to extensively study the evolutionary compositions of OV. The present co-expr...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6384884/ https://www.ncbi.nlm.nih.gov/pubmed/30796309 http://dx.doi.org/10.1038/s41598-019-40023-9 |
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author | Zhang, Luoyan Tan, Yi Fan, Shoujin Zhang, Xuejie Zhang, Zhen |
author_facet | Zhang, Luoyan Tan, Yi Fan, Shoujin Zhang, Xuejie Zhang, Zhen |
author_sort | Zhang, Luoyan |
collection | PubMed |
description | Ovarian cancer (OV) is an extremely lethal disease. However, the evolutionary machineries of OV are still largely unknown. Here, we used a method that combines phylostratigraphy information with gene co-expression networks to extensively study the evolutionary compositions of OV. The present co-expression network construction yielded 18,549 nodes and 114,985 edges based on 307 OV expression samples obtained from the Genome Data Analysis Centers database. A total of 20 modules were identified as OV related clusters. The human genome sequences were divided into 19 phylostrata (PS), the majority (67.45%) of OV genes was already present in the eukaryotic ancestor. There were two strong peaks of the emergence of OV genes screened by hypergeometric test: the evolution of the multicellular metazoan organisms (PS5 and PS6, P value = 0.002) and the emergence of bony fish (PS11 and PS12, P value = 0.009). Hence, the origin of OV is far earlier than its emergence. The integrated analysis of the topology of OV modules and the phylogenetic data revealed an evolutionary pattern of OV in human, namely, OV modules have arisen step by step during the evolution of the respective lineages. New genes have evolved and become locked into a pathway, where more and more biological pathways are fixed into OV modules by recruiting new genes during human evolution. |
format | Online Article Text |
id | pubmed-6384884 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63848842019-02-26 Phylostratigraphic analysis of gene co-expression network reveals the evolution of functional modules for ovarian cancer Zhang, Luoyan Tan, Yi Fan, Shoujin Zhang, Xuejie Zhang, Zhen Sci Rep Article Ovarian cancer (OV) is an extremely lethal disease. However, the evolutionary machineries of OV are still largely unknown. Here, we used a method that combines phylostratigraphy information with gene co-expression networks to extensively study the evolutionary compositions of OV. The present co-expression network construction yielded 18,549 nodes and 114,985 edges based on 307 OV expression samples obtained from the Genome Data Analysis Centers database. A total of 20 modules were identified as OV related clusters. The human genome sequences were divided into 19 phylostrata (PS), the majority (67.45%) of OV genes was already present in the eukaryotic ancestor. There were two strong peaks of the emergence of OV genes screened by hypergeometric test: the evolution of the multicellular metazoan organisms (PS5 and PS6, P value = 0.002) and the emergence of bony fish (PS11 and PS12, P value = 0.009). Hence, the origin of OV is far earlier than its emergence. The integrated analysis of the topology of OV modules and the phylogenetic data revealed an evolutionary pattern of OV in human, namely, OV modules have arisen step by step during the evolution of the respective lineages. New genes have evolved and become locked into a pathway, where more and more biological pathways are fixed into OV modules by recruiting new genes during human evolution. Nature Publishing Group UK 2019-02-22 /pmc/articles/PMC6384884/ /pubmed/30796309 http://dx.doi.org/10.1038/s41598-019-40023-9 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Zhang, Luoyan Tan, Yi Fan, Shoujin Zhang, Xuejie Zhang, Zhen Phylostratigraphic analysis of gene co-expression network reveals the evolution of functional modules for ovarian cancer |
title | Phylostratigraphic analysis of gene co-expression network reveals the evolution of functional modules for ovarian cancer |
title_full | Phylostratigraphic analysis of gene co-expression network reveals the evolution of functional modules for ovarian cancer |
title_fullStr | Phylostratigraphic analysis of gene co-expression network reveals the evolution of functional modules for ovarian cancer |
title_full_unstemmed | Phylostratigraphic analysis of gene co-expression network reveals the evolution of functional modules for ovarian cancer |
title_short | Phylostratigraphic analysis of gene co-expression network reveals the evolution of functional modules for ovarian cancer |
title_sort | phylostratigraphic analysis of gene co-expression network reveals the evolution of functional modules for ovarian cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6384884/ https://www.ncbi.nlm.nih.gov/pubmed/30796309 http://dx.doi.org/10.1038/s41598-019-40023-9 |
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