Genetic diversity of Schima superba based on physiological traits and SSR markers
Abstract
Schima superba is an ecologically and economically valuable evergreen tree that plays a key role in reforestation, firebreak establishment, and urban landscaping in subtropical China. To evaluate its adaptive diversity, this study combined physiological trait assessment with SSR-based genetic analysis across eight natural populations comprising 122 individuals. Five physiological traits, including chlorophyll, malondialdehyde, proline, soluble protein, and soluble sugar, showed significant variation among and within populations (p < 0.01), with HTHL and HBB populations exhibiting the greatest phenotypic variability. Using 20 polymorphic SSR loci, we detected high genetic diversity (He = 0.804, PIC = 0.786) and moderate differentiation (Fst = 0.111) with strong gene flow (Nm = 2.23). STRUCTURE and PCoA analyses revealed five genetic clusters, and the HBN and HTHL populations displayed distinct genotypes. Mixed linear model analysis identified 14 significant SSR-trait associations, with SS30 and SS32 strongly correlated with malondialdehyde and chlorophyll content. These results demonstrate a close relationship between genetic and physiological diversity in S. superba and provide essential molecular resources for its conservation, breeding, and adaptive improvement.