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A network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies
Comparative functional genomics offers a powerful approach to study species evolution. To date, the majority of these studies have focused on the transcriptome in mammalian and yeast phylogenies. Here, we present a novel multi-species proteomic dataset and a computational pipeline to systematically...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797074/ https://www.ncbi.nlm.nih.gov/pubmed/33219668 http://dx.doi.org/10.1093/nar/gkaa1041 |
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author | Shin, Junha Marx, Harald Richards, Alicia Vaneechoutte, Dries Jayaraman, Dhileepkumar Maeda, Junko Chakraborty, Sanhita Sussman, Michael Vandepoele, Klaas Ané, Jean-Michel Coon, Joshua Roy, Sushmita |
author_facet | Shin, Junha Marx, Harald Richards, Alicia Vaneechoutte, Dries Jayaraman, Dhileepkumar Maeda, Junko Chakraborty, Sanhita Sussman, Michael Vandepoele, Klaas Ané, Jean-Michel Coon, Joshua Roy, Sushmita |
author_sort | Shin, Junha |
collection | PubMed |
description | Comparative functional genomics offers a powerful approach to study species evolution. To date, the majority of these studies have focused on the transcriptome in mammalian and yeast phylogenies. Here, we present a novel multi-species proteomic dataset and a computational pipeline to systematically compare the protein levels across multiple plant species. Globally we find that protein levels diverge according to phylogenetic distance but is more constrained than the mRNA level. Module-level comparative analysis of groups of proteins shows that proteins that are more highly expressed tend to be more conserved. To interpret the evolutionary patterns of conservation and divergence, we develop a novel network-based integrative analysis pipeline that combines publicly available transcriptomic datasets to define co-expression modules. Our analysis pipeline can be used to relate the changes in protein levels to different species-specific phenotypic traits. We present a case study with the rhizobia-legume symbiosis process that supports the role of autophagy in this symbiotic association. |
format | Online Article Text |
id | pubmed-7797074 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77970742021-01-13 A network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies Shin, Junha Marx, Harald Richards, Alicia Vaneechoutte, Dries Jayaraman, Dhileepkumar Maeda, Junko Chakraborty, Sanhita Sussman, Michael Vandepoele, Klaas Ané, Jean-Michel Coon, Joshua Roy, Sushmita Nucleic Acids Res Computational Biology Comparative functional genomics offers a powerful approach to study species evolution. To date, the majority of these studies have focused on the transcriptome in mammalian and yeast phylogenies. Here, we present a novel multi-species proteomic dataset and a computational pipeline to systematically compare the protein levels across multiple plant species. Globally we find that protein levels diverge according to phylogenetic distance but is more constrained than the mRNA level. Module-level comparative analysis of groups of proteins shows that proteins that are more highly expressed tend to be more conserved. To interpret the evolutionary patterns of conservation and divergence, we develop a novel network-based integrative analysis pipeline that combines publicly available transcriptomic datasets to define co-expression modules. Our analysis pipeline can be used to relate the changes in protein levels to different species-specific phenotypic traits. We present a case study with the rhizobia-legume symbiosis process that supports the role of autophagy in this symbiotic association. Oxford University Press 2020-11-21 /pmc/articles/PMC7797074/ /pubmed/33219668 http://dx.doi.org/10.1093/nar/gkaa1041 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://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 |
spellingShingle | Computational Biology Shin, Junha Marx, Harald Richards, Alicia Vaneechoutte, Dries Jayaraman, Dhileepkumar Maeda, Junko Chakraborty, Sanhita Sussman, Michael Vandepoele, Klaas Ané, Jean-Michel Coon, Joshua Roy, Sushmita A network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies |
title | A network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies |
title_full | A network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies |
title_fullStr | A network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies |
title_full_unstemmed | A network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies |
title_short | A network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies |
title_sort | network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797074/ https://www.ncbi.nlm.nih.gov/pubmed/33219668 http://dx.doi.org/10.1093/nar/gkaa1041 |
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