Spatial genetic patterns and distribution dynamics of Begonia grandis (Begoniaceae), a widespread herbaceous species in China

Front Plant Sci. 2023 May 10:14:1178245. doi: 10.3389/fpls.2023.1178245. eCollection 2023.

Abstract

Introduction: Begonia L., one of the 10 largest plant genera, contains over 2,100 species, most of which have a very limited distribution range. Understanding the spatial genetic structure and distribution dynamics of a widespread species in this genus will contribute to clarifying the mechanism responsible for Begonia speciation.

Methods: In this study, we used three chloroplast DNA markers (ndhF-rpl32, atpI-atpH, and ndhA intron), coupled with species distribution modeling (SDM), to investigate the population genetic structure and distribution dynamics of Begonia grandis Dryand., the species of Begonia with the widest distribution in China.

Results: Thirty-five haplotypes from 44 populations clustered into two groups, and haplotype divergence began in the Pleistocene (1.75 Mya). High genetic diversity (H d = 0.894, H T = 0.910), strong genetic differentiation (F ST = 0.835), and significant phylogeographical structure (G ST/N ST = 0.848/0.917, P < 0.05) were observed. The distribution range of B. grandis migrated northwards after the last glacial maximum, but its core distribution area remained stable.

Discussion: Combined, the observed spatial genetic patterns and SDM results identified the Yunnan-Guizhou Plateau, the Three Gorges region, and the Daba Mountains as potential refugia of B. grandis. BEAST-derived chronogram and haplotype network analysis do not support the Flora Reipublicae Popularis Sinicae and Flora of China for subspecies classification based on morphological characteristics. Our results support the hypothesis that population-level allopatric differentiation may be an important speciation process for the Begonia genus and a key contributor to its rich diversity.

Keywords: Begonia; chloroplast DNA; glacial refugia; phylogeography; population genetic structure; species distribution modeling.

Grants and funding

This work was supported by grants from the National Natural Science Foundation of China (31570199) and the Shanghai Municipal Administration of Forestation and City Appearances (G222405 and G202401).