2.6 | Estimates of the effective population size and divergence time
The pairwise sequentially Markovian coalescent (PSMC) method (Heng Li & Durbin, 2011) was used to evaluate the dynamic change of effective population size (Ne ) of each population. We used 0.17 years per generation (g ) and mutation rate (μ ) of 9×10-9 per generation per site to rescale the time to year (Cutter, 2008). More recent (within 1000 years) changes of effective population size of each population and separation time between different populations were further estimated by using the MSMC2 (Schiffels & Durbin, 2014), which can much compensate results from PSMC. However, the inference accuracy of MSMC2 largely depends on the phasing accuracy of genotypes. Switch error rates will introduce bias in the calculation. To further confirm results from multiple sequentially Markovian coalescent (MSMC2), we also used Sequentially Markovian Coalescent (SMC++) methods (Terhorst, Kamm, & Song, 2017) to do the same analysis as of MSMC2. The SMC++ used phasing-free genotype data to do the population history and separation time inference, which becomes a reliable method to support inferences from MSMC2. For SMC++, we set the upper bound for the number of generations to 10,000 to estimate size history, and calculate the lower bound based on a heuristic approach. For MSMC2, we first phased all SNPs of each individual by using beagle (v5.0) (Browning & Browning, 2007), then the calculation was performed with the following parameters: -i 20 -t 6 -p ’10*1+15*2’. The mutation rate (μ ) of Parascaris spp. for SMC++ and MSMC2 were used the same values as for PSMC.