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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
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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
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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
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Journal Article
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
2019
Overview
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. 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. 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.
