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Data from: Footprints of divergent selection in natural populations of Castanopsis fargesii (Fagaceae)

Citation

Sun, Ye; Li, Chun; Huang, Hong Wen; Cannon, Charles H. (2014), Data from: Footprints of divergent selection in natural populations of Castanopsis fargesii (Fagaceae), Dryad, Dataset, https://doi.org/10.5061/dryad.hf49c

Abstract

Given predicted rapid climate change, an understanding of how environmental factors affect genetic diversity in natural populations is important. Future selection pressures are inherently unpredictable, so forest management policies should maintain both overall diversity and identify genetic markers associated with the environmental factors expected to change most rapidly, like temperature and rainfall. In this study, we genotyped 648 individuals in 28 populations of Castanopsis fargesii (Fagaceae) using 32 expressed sequence tag (EST)-derived microsatellite markers. After removing six loci that departed from Hardy–Weinberg equilibrium, we measured genetic variation, population structure and identified candidate loci putatively under selection by temperature and precipitation. We found that C. fargesii populations possessed high genetic diversity and moderate differentiation among them, indicating predominant outcrossing and few restrictions to gene flow. These patterns reduce the possible impact of stochastic effects or the influence of genetic isolation. Clear footprints of divergent selection at four loci were discovered. Frequencies of five alleles at these loci were strongly correlated with environmental factors, particularly extremes in precipitation. These alleles varied from being near fixation at one end of the gradient to being completely absent at the other. Our study species is an important forest tree in the subtropical regions of China and could have a major role in future management and reforestation plans. Our results demonstrate that the gene flow is widespread and abundant in natural populations, maintaining high diversity, while diversifying selection is acting on specific genomic regions.

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