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Landscape genomics predicts climate change‐related genetic offset for the widespread Platycladus orientalis (Cupressaceae)
Understanding and quantifying populations' adaptive genetic variation and their response to climate change are critical to reforestation's seed source selection, forest management decisions, and gene conservation. Landscape genomics combined with geographic and environmental information pr...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7086053/ https://www.ncbi.nlm.nih.gov/pubmed/32211059 http://dx.doi.org/10.1111/eva.12891 |
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author | Jia, Kai‐Hua Zhao, Wei Maier, Paul Andrew Hu, Xian‐Ge Jin, Yuqing Zhou, Shan‐Shan Jiao, Si‐Qian El‐Kassaby, Yousry A Wang, Tongli Wang, Xiao‐Ru Mao, Jian‐Feng |
author_facet | Jia, Kai‐Hua Zhao, Wei Maier, Paul Andrew Hu, Xian‐Ge Jin, Yuqing Zhou, Shan‐Shan Jiao, Si‐Qian El‐Kassaby, Yousry A Wang, Tongli Wang, Xiao‐Ru Mao, Jian‐Feng |
author_sort | Jia, Kai‐Hua |
collection | PubMed |
description | Understanding and quantifying populations' adaptive genetic variation and their response to climate change are critical to reforestation's seed source selection, forest management decisions, and gene conservation. Landscape genomics combined with geographic and environmental information provide an opportunity to interrogate forest populations' genome‐wide variation for understanding the extent to which evolutionary forces shape past and contemporary populations' genetic structure, and identify those populations that may be most at risk under future climate change. Here, we used genotyping by sequencing to generate over 11,000 high‐quality variants from Platycladus orientalis range‐wide collection to evaluate its diversity and to predict genetic offset under future climate scenarios. Platycladus orientalis is a widespread conifer in China with significant ecological, timber, and medicinal values. We found population structure and evidences of isolation by environment, indicative of adaptation to local conditions. Gradient forest modeling identified temperature‐related variables as the most important environmental factors influencing genetic variation and predicted areas with higher risk under future climate change. This study provides an important reference for forest resource management and conservation for P. orientalis. |
format | Online Article Text |
id | pubmed-7086053 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-70860532020-03-24 Landscape genomics predicts climate change‐related genetic offset for the widespread Platycladus orientalis (Cupressaceae) Jia, Kai‐Hua Zhao, Wei Maier, Paul Andrew Hu, Xian‐Ge Jin, Yuqing Zhou, Shan‐Shan Jiao, Si‐Qian El‐Kassaby, Yousry A Wang, Tongli Wang, Xiao‐Ru Mao, Jian‐Feng Evol Appl Original Articles Understanding and quantifying populations' adaptive genetic variation and their response to climate change are critical to reforestation's seed source selection, forest management decisions, and gene conservation. Landscape genomics combined with geographic and environmental information provide an opportunity to interrogate forest populations' genome‐wide variation for understanding the extent to which evolutionary forces shape past and contemporary populations' genetic structure, and identify those populations that may be most at risk under future climate change. Here, we used genotyping by sequencing to generate over 11,000 high‐quality variants from Platycladus orientalis range‐wide collection to evaluate its diversity and to predict genetic offset under future climate scenarios. Platycladus orientalis is a widespread conifer in China with significant ecological, timber, and medicinal values. We found population structure and evidences of isolation by environment, indicative of adaptation to local conditions. Gradient forest modeling identified temperature‐related variables as the most important environmental factors influencing genetic variation and predicted areas with higher risk under future climate change. This study provides an important reference for forest resource management and conservation for P. orientalis. John Wiley and Sons Inc. 2019-11-22 /pmc/articles/PMC7086053/ /pubmed/32211059 http://dx.doi.org/10.1111/eva.12891 Text en © 2019 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Jia, Kai‐Hua Zhao, Wei Maier, Paul Andrew Hu, Xian‐Ge Jin, Yuqing Zhou, Shan‐Shan Jiao, Si‐Qian El‐Kassaby, Yousry A Wang, Tongli Wang, Xiao‐Ru Mao, Jian‐Feng Landscape genomics predicts climate change‐related genetic offset for the widespread Platycladus orientalis (Cupressaceae) |
title | Landscape genomics predicts climate change‐related genetic offset for the widespread Platycladus orientalis (Cupressaceae) |
title_full | Landscape genomics predicts climate change‐related genetic offset for the widespread Platycladus orientalis (Cupressaceae) |
title_fullStr | Landscape genomics predicts climate change‐related genetic offset for the widespread Platycladus orientalis (Cupressaceae) |
title_full_unstemmed | Landscape genomics predicts climate change‐related genetic offset for the widespread Platycladus orientalis (Cupressaceae) |
title_short | Landscape genomics predicts climate change‐related genetic offset for the widespread Platycladus orientalis (Cupressaceae) |
title_sort | landscape genomics predicts climate change‐related genetic offset for the widespread platycladus orientalis (cupressaceae) |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7086053/ https://www.ncbi.nlm.nih.gov/pubmed/32211059 http://dx.doi.org/10.1111/eva.12891 |
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