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    In: Molecular Ecology, Wiley, Vol. 23, No. 19 ( 2014-10), p. 4696-4708
    Abstract: Detecting signatures of selection in tree populations threatened by climate change is currently a major research priority. Here, we investigated the signature of local adaptation over a short spatial scale using 96 European beech ( F agus sylvatica L.) individuals originating from two pairs of populations on the northern and southern slopes of Mont Ventoux (south‐eastern France). We performed both single and multilocus analysis of selection based on 53 climate‐related candidate genes containing 546 SNP s. F ST outlier methods at the SNP level revealed a weak signal of selection, with three marginally significant outliers in the northern populations. At the gene level, considering haplotypes as alleles, two additional marginally significant outliers were detected, one on each slope. To account for the uncertainty of haplotype inference, we averaged the Bayes factors over many possible phase reconstructions. Epistatic selection offers a realistic multilocus model of selection in natural populations. Here, we used a test suggested by O hta based on the decomposition of the variance of linkage disequilibrium. Overall populations, 0.23% of the SNP pairs (haplotypes) showed evidence of epistatic selection, with nearly 80% of them being within genes. One of the between gene epistatic selection signals arose between an F ST outlier and a nonsynonymous mutation in a drought response gene. Additionally, we identified haplotypes containing selectively advantageous allele combinations which were unique to high or low elevations and northern or southern populations. Several haplotypes contained nonsynonymous mutations situated in genes with known functional importance for adaptation to climatic factors.
    Type of Medium: Online Resource
    ISSN: 0962-1083 , 1365-294X
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2014
    detail.hit.zdb_id: 2020749-9
    detail.hit.zdb_id: 1126687-9
    SSG: 12
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