Estimation of species divergence times in presence of cross-species gene flow

Cross-species introgression can have significant impacts on phylogenomic
reconstruction of species divergence events. Here, we used simulations to
show how the presence of even a small amount of introgression can bias
divergence time estimates when gene flow is ignored in the analysis. Using
advances in analytical methods under the multispecies coalescent (MSC)
model, we demonstrate that by accounting for incomplete lineage sorting
and introgression using large phylogenomic data sets this problem can be
avoided. The multispecies-coalescent with-introgression (MSci) model is
capable of accurately estimating both divergence times and ancestral
effective population sizes, even when only a single diploid individual per
species is sampled. We characterize some general expectations for biases
in divergence time estimation under three different scenarios: 1)
introgression between sister species, 2) introgression between non-sister
species, and 3) introgression from an unsampled (i.e., ghost) outgroup
lineage. We also conducted simulations under the isolation-with-migration
(IM) model, and found that the MSci model assuming episodic gene flow was
able to accurately estimate species divergence times despite high levels
of continuous gene flow. We estimated divergence times under the MSC and
MSci models from two published empirical datasets with previous evidence
of introgression, one of 372 target enrichment loci from baobabs
(Adansonia), and another of 1,000 transcriptome loci from fourteen species
of the tomato relative, Jaltomata. The empirical analyses not only confirm
our findings from simulations, demonstrating that the MSci model can
reliably estimate divergence times, but also show that divergence time
estimation under the MSC can be robust to the presence of small amounts of
introgression in empirical datasets with extensive taxon sampling.