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Detecting the genetic basis of local adaptation in loblolly pine (Pinus taeda L.) using whole exome‐wide genotyping and an integrative landscape genomics analysis approach

In the Southern United States, the widely distributed loblolly pine contributes greatly to lumber and pulp production, as well as providing many important ecosystem services. Climate change may affect the productivity and range of loblolly pine. Nevertheless, we have insufficient knowledge of the ad...

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Autores principales: Lu, Mengmeng, Loopstra, Carol A., Krutovsky, Konstantin V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6662259/
https://www.ncbi.nlm.nih.gov/pubmed/31380016
http://dx.doi.org/10.1002/ece3.5225
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author Lu, Mengmeng
Loopstra, Carol A.
Krutovsky, Konstantin V.
author_facet Lu, Mengmeng
Loopstra, Carol A.
Krutovsky, Konstantin V.
author_sort Lu, Mengmeng
collection PubMed
description In the Southern United States, the widely distributed loblolly pine contributes greatly to lumber and pulp production, as well as providing many important ecosystem services. Climate change may affect the productivity and range of loblolly pine. Nevertheless, we have insufficient knowledge of the adaptive potential and the genetics underlying the adaptability of loblolly pine. To address this, we tested the association of 2.8 million whole exome‐based single nucleotide polymorphisms (SNPs) with climate and geographic variables, including temperature, precipitation, latitude, longitude, and elevation data. Using an integrative landscape genomics approach by combining multiple environmental association and outlier detection analyses, we identified 611 SNPs associated with 56 climate and geographic variables. Longitude, maximum temperature of the warm months and monthly precipitation associated with most SNPs, indicating their importance and complexity in shaping the genetic variation in loblolly pine. Functions of candidate genes related to terpenoid synthesis, pathogen defense, transcription factors, and abiotic stress response. We provided evidence that environment‐associated SNPs also composed the genetic structure of adaptive phenotypic traits including height, diameter, metabolite levels, and gene transcript abundance. Our study promotes understanding of the genetic basis of local adaptation in loblolly pine and provides promising tools for selecting genotypes adapted to local environments in a changing climate.
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spelling pubmed-66622592019-08-02 Detecting the genetic basis of local adaptation in loblolly pine (Pinus taeda L.) using whole exome‐wide genotyping and an integrative landscape genomics analysis approach Lu, Mengmeng Loopstra, Carol A. Krutovsky, Konstantin V. Ecol Evol Original Research In the Southern United States, the widely distributed loblolly pine contributes greatly to lumber and pulp production, as well as providing many important ecosystem services. Climate change may affect the productivity and range of loblolly pine. Nevertheless, we have insufficient knowledge of the adaptive potential and the genetics underlying the adaptability of loblolly pine. To address this, we tested the association of 2.8 million whole exome‐based single nucleotide polymorphisms (SNPs) with climate and geographic variables, including temperature, precipitation, latitude, longitude, and elevation data. Using an integrative landscape genomics approach by combining multiple environmental association and outlier detection analyses, we identified 611 SNPs associated with 56 climate and geographic variables. Longitude, maximum temperature of the warm months and monthly precipitation associated with most SNPs, indicating their importance and complexity in shaping the genetic variation in loblolly pine. Functions of candidate genes related to terpenoid synthesis, pathogen defense, transcription factors, and abiotic stress response. We provided evidence that environment‐associated SNPs also composed the genetic structure of adaptive phenotypic traits including height, diameter, metabolite levels, and gene transcript abundance. Our study promotes understanding of the genetic basis of local adaptation in loblolly pine and provides promising tools for selecting genotypes adapted to local environments in a changing climate. John Wiley and Sons Inc. 2019-05-29 /pmc/articles/PMC6662259/ /pubmed/31380016 http://dx.doi.org/10.1002/ece3.5225 Text en © 2019 The Authors. Ecology and Evolution 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 Research
Lu, Mengmeng
Loopstra, Carol A.
Krutovsky, Konstantin V.
Detecting the genetic basis of local adaptation in loblolly pine (Pinus taeda L.) using whole exome‐wide genotyping and an integrative landscape genomics analysis approach
title Detecting the genetic basis of local adaptation in loblolly pine (Pinus taeda L.) using whole exome‐wide genotyping and an integrative landscape genomics analysis approach
title_full Detecting the genetic basis of local adaptation in loblolly pine (Pinus taeda L.) using whole exome‐wide genotyping and an integrative landscape genomics analysis approach
title_fullStr Detecting the genetic basis of local adaptation in loblolly pine (Pinus taeda L.) using whole exome‐wide genotyping and an integrative landscape genomics analysis approach
title_full_unstemmed Detecting the genetic basis of local adaptation in loblolly pine (Pinus taeda L.) using whole exome‐wide genotyping and an integrative landscape genomics analysis approach
title_short Detecting the genetic basis of local adaptation in loblolly pine (Pinus taeda L.) using whole exome‐wide genotyping and an integrative landscape genomics analysis approach
title_sort detecting the genetic basis of local adaptation in loblolly pine (pinus taeda l.) using whole exome‐wide genotyping and an integrative landscape genomics analysis approach
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6662259/
https://www.ncbi.nlm.nih.gov/pubmed/31380016
http://dx.doi.org/10.1002/ece3.5225
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