Inference of demographic history
The software DIYABC v2.1.0 (Cornuet et al., 2014) was implemented to
investigate demographic history based on Approximated Bayesian
Computation (ABC) using nuclear SSR markers. The three previously
defined geographic groups were employed in the DIYABC analysis. We
simulated and tested five potential scenarios of demographic history
among the three groups that could have generated the current genetic
variation (Fig. 3): s1, southward migration; s2, northward migration;
s3-4, central origin; and s5: hybridization origin. We adopted a
generalized stepwise mutation (GSM) model for repeat number mutation,
and single nucleotide indels (SNI) were allowed. One million simulations
were performed for each scenario. The strength of support for our
scenarios was evaluated by comparing posterior probabilities via
logistic regression using the top 1% of the simulated datasets
according to the similarity of summary statistics to the observed data
(Table S1). The methods for performing DIYABC and model evaluation were
described in detail in the SMM.
We used VarEff (Nikolic & Chevalet, 2014) to test for changes in
effective population size over the past 500 years, encompassing the
increase in anthropogenic activities in Taiwan (i.e., when a large
number of Han Chinese immigrated to Taiwan). We set a generic mutation
rate prior of 0.000048 and adopted a
GSM
model with p = 0.4, as estimated by DIYABC (see Results).
Additional parameters for each population are provided in Table S2.
After 10,000 burn-in iterations, we ran 10,000 steps with 100 steps per
batch and 100 steps between sampled steps to avoid autocorrelation, and
a total of 10,000,000 MCMC iterations were employed.