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Genome‐wide scans detect adaptation to aridity in a widespread forest tree species
Author(s) -
Steane Dorothy A.,
Potts Brad M.,
McLean Elizabeth,
Prober Suzanne M.,
Stock William D.,
Vaillancourt René E.,
Byrne Margaret
Publication year - 2014
Publication title -
molecular ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.619
H-Index - 225
eISSN - 1365-294X
pISSN - 0962-1083
DOI - 10.1111/mec.12751
Subject(s) - biology , local adaptation , adaptation (eye) , outlier , population , arid , evolutionary biology , tree (set theory) , genome , ecology , genetics , artificial intelligence , gene , computer science , mathematical analysis , demography , mathematics , neuroscience , sociology
Patterns of adaptive variation within plant species are best studied through common garden experiments, but these are costly and time‐consuming, especially for trees that have long generation times. We explored whether genome‐wide scanning technology combined with outlier marker detection could be used to detect adaptation to climate and provide an alternative to common garden experiments. As a case study, we sampled nine provenances of the widespread forest tree species, Eucalyptus tricarpa , across an aridity gradient in southeastern Australia. Using a Bayesian analysis, we identified a suite of 94 putatively adaptive (outlying) sequence‐tagged markers across the genome. Population‐level allele frequencies of these outlier markers were strongly correlated with temperature and moisture availability at the site of origin, and with population differences in functional traits measured in two common gardens. Using the output from a canonical analysis of principal coordinates, we devised a metric that provides a holistic measure of genomic adaptation to aridity that could be used to guide assisted migration or genetic augmentation.