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New Zealand Tree and Giant Wētā (Orthoptera) Transcriptomics Reveal Divergent Selection Patterns in Metabolic Loci

Exposure to low temperatures requires an organism to overcome physiological challenges. New Zealand wētā belonging to the genera Hemideina and Deinacrida are found across a wide range of thermal environments and therefore subject to varying selective pressures. Here we assess the selection pressures...

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Autores principales: Twort, Victoria G, Newcomb, Richard D, Buckley, Thomas R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6486805/
https://www.ncbi.nlm.nih.gov/pubmed/30957857
http://dx.doi.org/10.1093/gbe/evz070
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author Twort, Victoria G
Newcomb, Richard D
Buckley, Thomas R
author_facet Twort, Victoria G
Newcomb, Richard D
Buckley, Thomas R
author_sort Twort, Victoria G
collection PubMed
description Exposure to low temperatures requires an organism to overcome physiological challenges. New Zealand wētā belonging to the genera Hemideina and Deinacrida are found across a wide range of thermal environments and therefore subject to varying selective pressures. Here we assess the selection pressures across the wētā phylogeny, with a particular emphasis on identifying genes under positive or diversifying selection. We used RNA-seq to generate transcriptomes for all 18 Deinacrida and Hemideina species. A total of 755 orthologous genes were identified using a bidirectional best-hit approach, with the resulting gene set encompassing a diverse range of functional classes. Analysis of ortholog ratios of synonymous to nonsynonymous amino acid changes found 83 genes that are under positive selection for at least one codon. A wide variety of Gene Ontology terms, enzymes, and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways are represented among these genes. In particular, enzymes involved in oxidative phosphorylation, melanin synthesis, and free-radical scavenging are represented, consistent with physiological and metabolic changes that are associated with adaptation to alpine environments. Structural alignment of the transcripts with the most codons under positive selection revealed that the majority of sites are surface residues, and therefore have the potential to influence the thermostability of the enzyme, with the exception of prophenoloxidase where two residues near the active site are under selection. These proteins provide interesting candidates for further analysis of protein evolution.
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spelling pubmed-64868052019-05-01 New Zealand Tree and Giant Wētā (Orthoptera) Transcriptomics Reveal Divergent Selection Patterns in Metabolic Loci Twort, Victoria G Newcomb, Richard D Buckley, Thomas R Genome Biol Evol Research Article Exposure to low temperatures requires an organism to overcome physiological challenges. New Zealand wētā belonging to the genera Hemideina and Deinacrida are found across a wide range of thermal environments and therefore subject to varying selective pressures. Here we assess the selection pressures across the wētā phylogeny, with a particular emphasis on identifying genes under positive or diversifying selection. We used RNA-seq to generate transcriptomes for all 18 Deinacrida and Hemideina species. A total of 755 orthologous genes were identified using a bidirectional best-hit approach, with the resulting gene set encompassing a diverse range of functional classes. Analysis of ortholog ratios of synonymous to nonsynonymous amino acid changes found 83 genes that are under positive selection for at least one codon. A wide variety of Gene Ontology terms, enzymes, and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways are represented among these genes. In particular, enzymes involved in oxidative phosphorylation, melanin synthesis, and free-radical scavenging are represented, consistent with physiological and metabolic changes that are associated with adaptation to alpine environments. Structural alignment of the transcripts with the most codons under positive selection revealed that the majority of sites are surface residues, and therefore have the potential to influence the thermostability of the enzyme, with the exception of prophenoloxidase where two residues near the active site are under selection. These proteins provide interesting candidates for further analysis of protein evolution. Oxford University Press 2019-04-08 /pmc/articles/PMC6486805/ /pubmed/30957857 http://dx.doi.org/10.1093/gbe/evz070 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. 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 Research Article
Twort, Victoria G
Newcomb, Richard D
Buckley, Thomas R
New Zealand Tree and Giant Wētā (Orthoptera) Transcriptomics Reveal Divergent Selection Patterns in Metabolic Loci
title New Zealand Tree and Giant Wētā (Orthoptera) Transcriptomics Reveal Divergent Selection Patterns in Metabolic Loci
title_full New Zealand Tree and Giant Wētā (Orthoptera) Transcriptomics Reveal Divergent Selection Patterns in Metabolic Loci
title_fullStr New Zealand Tree and Giant Wētā (Orthoptera) Transcriptomics Reveal Divergent Selection Patterns in Metabolic Loci
title_full_unstemmed New Zealand Tree and Giant Wētā (Orthoptera) Transcriptomics Reveal Divergent Selection Patterns in Metabolic Loci
title_short New Zealand Tree and Giant Wētā (Orthoptera) Transcriptomics Reveal Divergent Selection Patterns in Metabolic Loci
title_sort new zealand tree and giant wētā (orthoptera) transcriptomics reveal divergent selection patterns in metabolic loci
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6486805/
https://www.ncbi.nlm.nih.gov/pubmed/30957857
http://dx.doi.org/10.1093/gbe/evz070
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