Modeling linkage disequilibrium in natural populations: the example of the Soay sheep population of St. Kilda, Scotland - PubMed (original) (raw)

Modeling linkage disequilibrium in natural populations: the example of the Soay sheep population of St. Kilda, Scotland

Allan F McRae et al. Genetics. 2005 Sep.

Abstract

The use of linkage disequilibrium to localize the genes underlying quantitative traits has received considerable attention in the livestock genetics community over the past few years. This has resulted in the investigation of linkage disequilibrium structures of several domestic livestock populations to assess their potential use in fine-mapping efforts. However, the linkage disequilibrium structure of free-living populations has been less well investigated. As the direct evaluation of linkage disequilibrium can be both time consuming and expensive the use of simulations that include as many aspects of population history as possible is advocated as an alternative. A simulation of the linkage disequilibrium structure of the Soay sheep population of St. Kilda, Scotland, is provided as an example. The simulated population showed significant decline of linkage disequilibrium with genetic distance and low levels of background linkage disequilibrium, indicating that the Soay sheep population is a viable resource for linkage disequilibrium fine mapping of quantitative trait loci.

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Figures

Figure 1.

Figure 1.

Outline map of part of the St. Kilda archipelago. The Soay sheep were restricted to the island of Soay until 1932 when a small group was moved to Hirta, which now holds the majority of the population. The Village Bay study area is shaded.

Figure 2.

Figure 2.

Census population size of the Soay sheep population on Hirta for the years 1955–2001. The population size is characterized by its frequent crashes when population size decreases by up to 60% in 1 year. The weak upward trend in population size with time is shown (dashed line).

Figure 3.

Figure 3.

Comparison between Village Bay and Hirta population data. (a) Plot of census population sizes of Hirta (solid line) and the Village Bay population (dashed line). (b) Scatter plot showing the strong correlation between the census population sizes of Hirta and the Village Bay (r = 0.962, P < 0.0001). (c) Comparison of the proportion of lambs observed in Hirta and the Village Bay. The dashed line indicates a perfect relationship. (d) Comparison of the adult sex ratio (male/female) in the two populations.

Figure 4.

Figure 4.

Simulated linkage disequilibrium structure of the Soay sheep population. Each point is the absolute value of Lewontin's formula image-statistic from a random pair of loci from one simulation (1000 replicates). The mean formula image-value over successive intervals of 2.5 cM is given by a horizontal line.

Figure 5.

Figure 5.

Analysis of the stability of simulated linkage disequilibrium structure to variation in population parameters. Each plot shows the linkage disequilibrium structure as given by 1000 simulated replicates using altered parameter values: (a) decreasing the effective population size used to simulate the initial haplotypes, (b) increasing the initial effective population size by a factor of two, (c) using population dynamics parameters at the “low” end of their 95% confidence interval, (d) using population dynamics parameters at the “high” end of their confidence interval, (e) decreasing the coefficient of variation of male reproductive success by a factor of two, and (f) increasing the variation of male reproductive success by a factor of two. Horizontal bars give the mean formula image-value over successive intervals of 2.5 cM.

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References

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