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Data from: Contrasted patterns of local adaptation to climate change across the range of an evergreen oak, Quercus aquifolioides

Citation

Du, Fang et al. (2020), Data from: Contrasted patterns of local adaptation to climate change across the range of an evergreen oak, Quercus aquifolioides, Dryad, Dataset, https://doi.org/10.5061/dryad.f1vhhmgtk

Abstract

Long-lived tree species are genetically differentiated and locally adapted with respect to fitness-related traits, but the genetic basis of local adaptation remains largely unresolved. Recent advances in population genetics and landscape genomic analyses enable identification of putative adaptive loci and specific selective pressures acting on local adaptation. Here we sampled 60 evergreen oak (Quercus aquifolioides) populations throughout the species’ range and pool-sequenced 587 individuals at drought stress candidate genes. We analyzed patterns of genetic diversity and differentiation for 381 single nucleotide polymorphisms (SNPs) from 65 candidate genes and eight microsatellites. Outlier loci were identified by genetic differentiation analysis and genome–environment associations. The response pattern of genetic variation to environmental gradient was assessed by linear isolation by distance/environment tests, redundancy analysis and non-linear methods. SNPs and microsatellites revealed two genetic lineages: Tibet and Hengduan Mountains-Western Sichuan Plateau (HDM-WSP), with reduced genetic diversity in Tibet lineage. More outlier loci were detected in HDM-WSP lineage than Tibet lineage. Among these, three SNPs in two genes responded to dry season precipitation in the HDM-WSP lineage but not in Tibet. By contrast, genetic variation in the Tibet lineage was related to geographic distance instead of the environment. Furthermore, Risk of Non-Adaptedness (RONA) analyses suggested HDM-WSP lineage will have a better capacity to adapt in the predicted future climate compared to the Tibet lineage. We detected genetic imprints consistent with natural selection and molecular adaptation to drought on the Qinghai-Tibet Plateau (QTP) over a range of long-lived and widely distributed oak species in a changing environment. Our results suggest that different within-species adaptation processes occur in species occurring in heterogeneous environments.Long-lived tree species are genetically differentiated and locally adapted with respect to fitness-related traits, but the genetic basis of local adaptation remains largely unresolved. Recent advances in population genetics and landscape genomic analyses enable identification of putative adaptive loci and specific selective pressures acting on local adaptation. Here we sampled 60 evergreen oak (Quercus aquifolioides) populations throughout the species’ range and pool-sequenced 587 individuals at drought stress candidate genes. We analyzed patterns of genetic diversity and differentiation for 381 single nucleotide polymorphisms (SNPs) from 65 candidate genes and eight microsatellites. Outlier loci were identified by genetic differentiation analysis and genome–environment associations. The response pattern of genetic variation to environmental gradient was assessed by linear isolation by distance/environment tests, redundancy analysis and non-linear methods. SNPs and microsatellites revealed two genetic lineages: Tibet and Hengduan Mountains-Western Sichuan Plateau (HDM-WSP), with reduced genetic diversity in Tibet lineage. More outlier loci were detected in HDM-WSP lineage than Tibet lineage. Among these, three SNPs in two genes responded to dry season precipitation in the HDM-WSP lineage but not in Tibet. By contrast, genetic variation in the Tibet lineage was related to geographic distance instead of the environment. Furthermore, Risk of Non-Adaptedness (RONA) analyses suggested HDM-WSP lineage will have a better capacity to adapt in the predicted future climate compared to the Tibet lineage. We detected genetic imprints consistent with natural selection and molecular adaptation to drought on the Qinghai-Tibet Plateau (QTP) over a range of long-lived and widely distributed oak species in a changing environment. Our results suggest that different within-species adaptation processes occur in species occurring in heterogeneous environments.

Usage Notes

SNP calls for all samples in VCF format (before filtering)

SNP call data for all samples across in Southwest China, produced by GATK in VCF format, before final filtering steps.

SNP_All.vcf

SNP calls for all samples, final in table format

SNP calls in tab-separated format with columns as individual samples and rows as loci as inferred from GATK. These are the final data that were filtered such that the minor allele frequency is greater than 0.025 and there is no more than 50% missing data at a locus. This file contains all samples of Quercus aquifolioides.

SNP_All_MAF_2.5_Mis50.xlsx

SNP calls for Tibet samples, final in table format

SNP calls in tab-separated format with columns as individual samples and rows as loci as inferred from GATK. These are the final data that were filtered such that the minor allele frequency is greater than 0.025 and there is no more than 50% missing data at a locus. This file contains Tibet samples of Quercus aquifolioides.

SNP_Tibet_MAF_2.5_Mis50.xlsx

SNP calls for HDM-WSP samples, final in table format

SNP calls in tab-separated format with columns as individual samples and rows as loci as inferred from GATK. These are the final data that were filtered such that the minor allele frequency is greater than 0.025 and there is no more than 50% missing data at a locus. This file contains HDM-WSP samples of Quercus aquifolioides.

SNP_HDM-WSP_MAF_2.5_Mis50.xlsx

SSR for All samples, final in table format

SSR data in tab-separated format with columns as neutral nuclear microsatellite markers and rows as individual samples as obtained from FlexiBinv2. Missing data is represented by “?”. This file contains all samples of Quercus aquifolioides.

SSR_All.xlsx

Funding

Fundamental Research Funds for the Central Universities, Award: 2015ZCQ-LX-03

National Natural Science Foundation of China, Award: 41671039