Selective sweep mapping of genes with large phenotypic effects - PubMed (original) (raw)

Selective sweep mapping of genes with large phenotypic effects

John P Pollinger et al. Genome Res. 2005 Dec.

Abstract

Many domestic dog breeds have originated through fixation of discrete mutations by intense artificial selection. As a result of this process, markers in the proximity of genes influencing breed-defining traits will have reduced variation (a selective sweep) and will show divergence in allele frequency. Consequently, low-resolution genomic scans can potentially be used to identify regions containing genes that have a major influence on breed-defining traits. We model the process of breed formation and show that the probability of two or three adjacent marker loci showing a spurious signal of selection within at least one breed (i.e., Type I error or false-positive rate) is low if highly variable and moderately spaced markers are utilized. We also use simulations with selection to demonstrate that even a moderately spaced set of highly polymorphic markers (e.g., one every 0.8 cM) has high power to detect regions targeted by strong artificial selection in dogs. Further, we show that a gene responsible for black coat color in the Large Munsterlander has a 40-Mb region surrounding the gene that is very low in heterozygosity for microsatellite markers. Similarly, we survey 302 microsatellite markers in the Dachshund and find three linked monomorphic microsatellite markers all within a 10-Mb region on chromosome 3. This region contains the FGFR3 gene, which is responsible for achondroplasia in humans, but not in dogs. Consequently, our results suggest that the causative mutation is a gene or regulatory region closely linked to FGFR3.

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Figures

Figure 1.

Figure 1.

Effects of time since breed formation on FST and observed marker heterozygosity. Expected levels of marker heterozygosity under the infinite-alleles model (E(H) = θ/(1 + θ)); (gray lines). Observed heterozygosity after conditioning on markers showing variability among breeds (black lines).

Figure 2.

Figure 2.

Effect of heterozygosity on Type I error of all statistics considered in this study across 500,000 simulated replicate data sets. Simulations simultaneously varied time since breed formation, number of breeds compared, number of chromosomes sampled per breed, extent of bottleneck, duration of bottleneck, marker variability and density, and size of ancestral population.

Figure 3.

Figure 3.

Simulation results summarizing the effect of selection on the average heterozygosity and FST among 200 replicate data sets per parameter combination (selection ranging from 10%-50% for marker density of 0.8 cM and 3.2 cM spacing between markers).

Figure 4.

Figure 4.

Summary of the power of the homozygosity statistics with varying values of recombination, selection, and mutation.

Figure 5.

Figure 5.

Microsatellite marker heterozygosity (A,B) and FST (C) values for the Large Munsterlander (Black), German Longhair (Brown), and control breeds. (A) Heterozygosity for markers on chromosome 11, the location of the TYRP1 gene, (B) heterozygosity for markers on control chromosome 5, (C) FST values for markers on chromosome 11.

Figure 6.

Figure 6.

Heterozygosity for markers on chromosome 3 for Dachshunds and control breeds. A low heterozygosity sweep region unique to Dachshunds and including the FGFR3 gene is found.

Figure 7.

Figure 7.

Heterozygosity frequency distribution for 302 microsatellite markers in Dachshunds (top) and control breeds (bottom).

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References

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