Abstract
Understanding adaptive genetic variation and its relation to environmental factors are important for understanding how plants adapt to climate change and for managing genetic resources. Genome scans for the loci exhibiting either notably high or low levels of population differentiation (outlier loci) provide one means of identifying genomic regions possibly associated with convergent or divergent selection. In this study, we combined Amplified Fragment Length Polymorphism (AFLP) genome scan and environmental association analysis to test for signals of natural selection in natural populations of Liriodendron chinense (Chinese Tulip Tree; Magnoliaceae) along a latitudinal transect. We genotyped 276 individuals from 11 populations of L. chinense using 987 AFLP markers. Both frequency-based (Dfdist and BayeScan) and correlation-based (MLM) methods were applied to detect outlier loci. Our analyses recovered both neutral and potentially adaptive genetic differentiation among populations of L. chinense. We found moderate genetic diversity within populations and high genetic differentiation among populations with reduced genetic diversity toward the periphery of the species ranges. Nine AFLP marker loci showed evidence of being outliers for population differentiation for both detection methods. Of these, six were strongly associated with at least one climate factor. Temperature, precipitation, and radiation were found to be three important factors influencing local adaptation of L. chinense. The outlier AFLP loci are likely not the target of natural selection, but the neighboring genes of these loci might be involved in local adaptation. Hence, these candidates should be validated by further studies.
Highlights
Climate change has become a major threat to global biodiversity (Davis and Shaw, 2001; Parmesan, 2006)
Documenting the genetic basis of local adaptation governed by natural selection is important for understanding how plants adapt to their environment and respond to climatic changes
When applying GLM analysis to the Amplified Fragment Length Polymorphism (AFLP) data set and taking population structure into account, we found that six out of the nine loci identified by both Dfdist and BayeScan were found to be correlated with the climatic factors
Summary
Climate change has become a major threat to global biodiversity (Davis and Shaw, 2001; Parmesan, 2006). For forest species, reciprocal transplant experiments and QTL mapping are not suitable for analysis of the adaptive genetic responses to climatic change due to their longer juvenile phase (Savolainen et al, 2007). Estimating population differentiation for all loci allows identification of ‘outlier loci’ whose level of differentiation among populations is either much greater or much less than that expected under neutral expectations (Lewontin and Krakauer, 1973; Storz, 2005; Foll and Gaggiotti, 2008; Nosil et al, 2009; Fischer et al, 2011) These outlier loci are assumed to be in linkage disequilibrium with genes involved in adaptive evolution due to genetic hitchhiking (Luikart et al, 2003; Schlötterer, 2003). AFLP genome scans have been extensively used in studies of plant populations, e.g., Howea (Palmae; Savolainen et al, 2006), Silene (Caryophyllaceae; Minder and Widmer, 2008), Mikania (Asteraceae; Wang et al, 2012), and Themeda (Poaceae; Dell’Acqua et al, 2014)
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