Micro- and macro-geographic scale effect on the molecular imprint of selection and adaptation in Norway spruce

Forest tree species of temperate and boreal regions have undergone a long history of demographic changes and evolutionary adaptations. The main objective of this study was to detect signals of selection in Norway spruce (Picea abies [L.] Karst), at different sampling-scales and to investigate, accou...

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Published inPloS one Vol. 9; no. 12; p. e115499
Main Authors Scalfi, Marta, Mosca, Elena, Di Pierro, Erica Adele, Troggio, Michela, Vendramin, Giovanni Giuseppe, Sperisen, Christoph, La Porta, Nicola, Neale, David B
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 31.12.2014
Public Library of Science (PLoS)
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Summary:Forest tree species of temperate and boreal regions have undergone a long history of demographic changes and evolutionary adaptations. The main objective of this study was to detect signals of selection in Norway spruce (Picea abies [L.] Karst), at different sampling-scales and to investigate, accounting for population structure, the effect of environment on species genetic diversity. A total of 384 single nucleotide polymorphisms (SNPs) representing 290 genes were genotyped at two geographic scales: across 12 populations distributed along two altitudinal-transects in the Alps (micro-geographic scale), and across 27 populations belonging to the range of Norway spruce in central and south-east Europe (macro-geographic scale). At the macrogeographic scale, principal component analysis combined with Bayesian clustering revealed three major clusters, corresponding to the main areas of southern spruce occurrence, i.e. the Alps, Carpathians, and Hercynia. The populations along the altitudinal transects were not differentiated. To assess the role of selection in structuring genetic variation, we applied a Bayesian and coalescent-based F(ST)-outlier method and tested for correlations between allele frequencies and climatic variables using regression analyses. At the macro-geographic scale, the F(ST)-outlier methods detected together 11 F(ST)-outliers. Six outliers were detected when the same analyses were carried out taking into account the genetic structure. Regression analyses with population structure correction resulted in the identification of two (micro-geographic scale) and 38 SNPs (macro-geographic scale) significantly correlated with temperature and/or precipitation. Six of these loci overlapped with F(ST)-outliers, among them two loci encoding an enzyme involved in riboflavin biosynthesis and a sucrose synthase. The results of this study indicate a strong relationship between genetic and environmental variation at both geographic scales. It also suggests that an integrative approach combining different outlier detection methods and population sampling at different geographic scales is useful to identify loci potentially involved in adaptation.
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Conceived and designed the experiments: MS MT GGV NLP DBN. Performed the experiments: MS. Analyzed the data: MS EM EADP. Contributed reagents/materials/analysis tools: MS EM EADP MT CS GGV NLP DBN. Wrote the paper: MS EM EADP MT CS GGV NLP DBN. Provided material and collected the data: MT CS GGV.
Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0115499