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Landscape genomics provides evidence of climate-associated genetic variation in Mexican populations of Quercus rugosa
Martins, Karina1; Gugger, Paul F.; Llanderal-Mendoza, Jesus; Gonzalez-Rodriguez, Antonio; Fitz-Gibbon, Sorel T.; Zhao, Jian-Li; Rodriguez-Correa, Hernando; Oyama, Ken4; Sork, Victoria L.
2018
Source PublicationEVOLUTIONARY APPLICATIONS
ISSN1752-4571
Volume11Issue:10Pages:1842-1858
Abstract

Local adaptation is a critical evolutionary process that allows plants to grow better in their local compared to non-native habitat and results in species-wide geographic patterns of adaptive genetic variation. For forest tree species with a long generation time, this spatial genetic heterogeneity can shape the ability of trees to respond to rapid climate change. Here, we identify genomic variation that may confer local environmental adaptations and then predict the extent of adaptive mismatch under future climate as a tool for forest restoration or management of the widely distributed high-elevation oak species Quercus rugosa in Mexico. Using genotyping by sequencing, we identified 5,354 single nucleotide polymorphisms (SNPs) genotyped from 103 individuals across 17 sites in the Trans-Mexican Volcanic Belt, and, after controlling for neutral genetic structure, we detected 74 F-ST outlier SNPs and 97 SNPs associated with climate variation. Then, we deployed a nonlinear multivariate model, Gradient Forests, to map turnover in allele frequencies along environmental gradients and predict areas most sensitive to climate change. We found that spatial patterns of genetic variation were most strongly associated with precipitation seasonality and geographic distance. We identified regions of contemporary genetic and climatic similarities and predicted regions where future populations of Q. rugosa might be at risk due to high expected rate of climate change. Our findings provide preliminary details for future management strategies of Q. rugosa in Mexico and also illustrate how a landscape genomic approach can provide a useful tool for conservation and resource management strategies.

KeywordPine Pinus-taeda Local Adaptation Tree Populations Candidate Genes Ecological Genomics Change Projections Natural-selection Neighbor Matrices Spatial-analysis Pollinated Tree
Subject AreaEvolutionary Biology
DOI10.1111/eva.12684
Indexed BySCI
Language英语
WOS IDWOS:000449942900006
Citation statistics
Document Type期刊论文
Identifierhttp://ir.xtbg.org.cn/handle/353005/11263
Collection其他
Affiliation1.[Martins, Karina; Gugger, Paul F.; Fitz-Gibbon, Sorel T.; Sork, Victoria L.] Univ Calif Los Angeles, Dept Ecol & Evolutionary Biol, Los Angeles, CA 90095 USA
2.Univ Fed Sao Carlos, Dept Biol, Sorocaba, SP, Brazil
3.Gugger, Paul F.] Univ Maryland, Ctr Environm Sci, Appalachian Lab, Frostburg, MD USA
4.UNAM, Inst Invest Ecosistemas & Sustentabilidad, Morelia, Michoacan, Mexico
5.UNAM, Unidad Morelia, Escuela Nacl Estudios Super, Morelia, Michoacan, Mexico
6.Chinese Acad Sci, Xishuangbanna Trop Bot Garden, Key Lab Trop Forest Ecol, Mengla, Yunnan, Peoples R China
7.Sork, Victoria L.] Univ Calif Los Angeles, Inst Environm & Sustainabil, Los Angeles, CA USA
Recommended Citation
GB/T 7714
Martins, Karina,Gugger, Paul F.,Llanderal-Mendoza, Jesus,et al. Landscape genomics provides evidence of climate-associated genetic variation in Mexican populations of Quercus rugosa[J]. EVOLUTIONARY APPLICATIONS,2018,11(10):1842-1858.
APA Martins, Karina.,Gugger, Paul F..,Llanderal-Mendoza, Jesus.,Gonzalez-Rodriguez, Antonio.,Fitz-Gibbon, Sorel T..,...&Sork, Victoria L..(2018).Landscape genomics provides evidence of climate-associated genetic variation in Mexican populations of Quercus rugosa.EVOLUTIONARY APPLICATIONS,11(10),1842-1858.
MLA Martins, Karina,et al."Landscape genomics provides evidence of climate-associated genetic variation in Mexican populations of Quercus rugosa".EVOLUTIONARY APPLICATIONS 11.10(2018):1842-1858.
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