Figure 1.
Calculation of probabilities of polymorphism and substitution under a model of balancing selection and the incorporation of these probabilities into a genome scan.
(A) Relationship among tree length , tree height
and inter-specific coalescence time
. (B) A site is polymorphic if a mutation occurred on the
length of branches until the most recent common ancestor of the ingroup sample (red region). (C) A site is a substitution if a mutation occurred on the
length of branches that represent the divergence between the outgroup species and the most recent common ancestor of the ingroup species (blue region). (D) Height and length of genealogies in relationship to their spatial proximity to a selected site and how the shapes of these genealogies affect the pattern of polymorphism around the site. The composite likelihood ratio is high near a selected site as there is an excess of polymorphisms close to the site and a deficit far from the site.
Figure 2.
Demographic models used in simulations in which a selected allele arises after the split a pair of species.
(A) Divergence model. Model parameters are a diploid effective population size , divergence time
of the ingroup and outgroup species, and the time
when the selected allele arises. (B) Divergence model with a recent bottleneck within the ingroup species. Additional model parameters are the diploid effective population size
during the bottleneck, the time
when the bottleneck began, and the time
when the bottleneck ended. (C) Divergence model with recent population growth within the ingroup species. Additional model parameters are the current diploid effective population size
after recent growth and the time
when the growth occurred.
Figure 3.
Performance of ,
, HKA, and Tajima's
under the demographic models in Figure 2 with selection parameter
and dominance parameter
.
The first column is the divergence model in Figure 2A. The second column is the divergence model in Figure 2B with a recent bottleneck within the ingroup species. The third column is the divergence model in Figure 2C with recent population growth within the ingroup species.
Figure 4.
Performance of ,
, HKA, and Tajima's
under the demographic models in Figure 2 with selection parameter
and dominance parameter
.
The first column is the divergence model in Figure 2A. The second column is the divergence model in Figure 2B with a recent bottleneck within the ingroup species. The third column is the divergence model in Figure 2C with recent population growth within the ingroup species.
Figure 5.
Performance of ,
, HKA, and Tajima's
under the bottleneck and growth demographic models in Figure 2 with selection parameter
and dominance parameter
.
The left panel is the divergence model in Figure 2B with a recent bottleneck within the ingroup species. The right panel is the divergence model in Figure 2C with recent population growth within the ingroup species. The population sizes for the bottleneck and growth demographic histories have been scaled so that they produce the same number of segregating sites as a constant size population with diploid effective size individuals.
Figure 6.
Performance of ,
, HKA, and Tajima's
under the bottleneck and growth demographic models in Figure 2 with selection parameter
and dominance parameter
.
The left panel is the divergence model in Figure 2B with a recent bottleneck within the ingroup species. The right panel is the divergence model in Figure 2C with recent population growth within the ingroup species. The population sizes for the bottleneck and growth demographic histories have been scaled so that they produce the same number of segregating sites as a constant size population with diploid effective size individuals.
Figure 7.
Signals of balancing selection within the HLA region for the CEU (blue) and YRI (orange) populations using the test statistic.
From bottom to top, the horizontal dotted gray lines indicate the ,
,
, and
empirical cutoffs, respectively.
Figure 8.
Signal of balancing selection at the FANK1 gene for the CEU (blue) and YRI (orange) populations using the test statistic.
From bottom to top, the horizontal dotted gray lines indicate the ,
,
, and
empirical cutoffs, respectively. SNPs (rsIDs) correspond to markers showing significant levels of transmission distortion within the Meyer et al. study [37].