Different processes shape the patterns of divergence in the nuclear and chloroplast genomes of a relict tree species in East Asia.

Abstract

Isolation by spatial distance (IBD), environment (IBE), and historical climatic instability (IBI) are three common processes assessed in phylogeographic and/or landscape genetic studies. However, the relative contributions of these three processes with respect to spatial genetic patterns have seldom been compared. Moreover, whether the relative contribution differs in different regions or when assessed using different genetic markers has rarely been reported. Lindera obtusiloba has been found to have two sister genetic clades of chloroplast (cpDNA) and nuclear microsatellite (nSSR), both of which show discontinuous distribution in northern and southern East Asia. In this study, we used the Mantel test and multiple matrix regression with randomization (MMRR) to determine the relative contributions of IBD, IBE, and IBI with respect to L. obtusiloba populations. Independent Mantel tests and MMRR calculations were conducted for two genetic data sets (cpDNA and nSSR) and for different regions (the overall species range, and northern and southern subregions of the range). We found a significant IBI pattern in nSSR divergence for all assessed regions, whereas no clear IBI pattern was detected with respect to cpDNA. In contrast, significant (or marginal) divergent IBD patterns were detected for cpDNA in all regions, whereas although a significant IBE was apparent with respect to the overall range, the effect was not detected in the two subregions. The differences identified in nSSR and cpDNA population divergence may be related to differences in the heredity and ploidy of the markers. Compared with the southern region, the northern region showed less significant correlation patterns, which may be related to the shorter population history and restricted population range. The findings of this study serve to illustrate that comparing between markers or regions can contribute to gaining a better understanding the population histories of different genomes or within different regions of a species' range.