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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.

AFLP Genome Scanning Reveals Divergent Selection in Natural Populations of Liriodendron chinense (Magnoliaceae) along a Latitudinal Transect