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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
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.
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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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