Data from: Bayesian estimation of genomic clines

We developed a Bayesian genomic cline model to study the genetic
architecture of adaptive divergence and reproductive isolation between
hybridizing lineages. This model quantifies locus-specific patterns of
introgression with two cline parameters that describe the probability of
locus-specific ancestry as a function of genome-wide admixture.
"Outlier" loci with extreme patterns of introgression relative
to most of the genome can be identified. These loci are potentially
associated with adaptive divergence or reproductive isolation. We
simulated genetic data for admixed populations that included neutral
introgression, as well as loci that were subject to directional, epistatic
or underdominant selection, and analyzed these data using the Bayesian
genomic cline model. Under many demographic conditions, underdominance or
directional selection had detectable and predictable effects on cline
parameters and "outlier" loci were greatly enriched for genetic
regions affected by selection. We also analyzed previously published
genetic data from two transects through a hybrid zone between Mus
domesticus and M. musculus. We found considerable variation in rates of
introgression across the genome and particularly low rates of
introgression for two X-linked markers. There were similarities and
differences in patterns of introgression between the two transects, which
likely reflects a combination of stochastic variability due to genetic
drift and geographic variation in the genetic architecture of reproductive
isolation. By providing a robust framework to quantify and compare
patterns of introgression among genetic regions and populations, the
Bayesian genomic cline model will advance our understanding of the
genetics of reproductive isolation and the speciation process.