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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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Detalles Bibliográficos
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
Descripción
Sumario: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.