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

Isolation by spatial distance (IBD), environment (IBE), and historical
climatic stability (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 differ 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 set (cpDNA and nSSR), and for different regions (the
overall species range, and northern and southern sub-regions of the
range). We found a significant IBI pattern in nSSRs 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 sub-regions. 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.