1. Estimating contemporary effective population size in non-model species using linkage disequilibrium across thousands of loci
- Author
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Wesley A. Larson, Robin S. Waples, and Ryan K. Waples
- Subjects
0106 biological sciences ,0301 basic medicine ,Linkage disequilibrium ,Salmo salar ,Genomics ,Biology ,010603 evolutionary biology ,01 natural sciences ,Chromosomes ,Linkage Disequilibrium ,Coalescent theory ,03 medical and health sciences ,Genome Size ,Effective population size ,Human population genetics ,Genetics ,Animals ,Computer Simulation ,Genome size ,Genetics (clinical) ,Population Density ,Linkage (software) ,Models, Genetic ,Genetics, Population ,030104 developmental biology ,Genetic Loci ,Evolutionary biology ,Original Article ,Recombination - Abstract
Contemporary effective population size (Ne) can be estimated using linkage disequilibrium (LD) observed across pairs of loci presumed to be selectively neutral and unlinked. This method has been commonly applied to data sets containing 10-100 loci to inform conservation and study population demography. Performance of these Ne estimates could be improved by incorporating data from thousands of loci. However, these thousands of loci exist on a limited number of chromosomes, ensuring that some fraction will be physically linked. Linked loci have elevated LD due to limited recombination, which if not accounted for can cause Ne estimates to be downwardly biased. Here, we present results from coalescent and forward simulations designed to evaluate the bias of LD-based Ne estimates ([Ncirc ]e). Contrary to common perceptions, increasing the number of loci does not increase the magnitude of linkage. Although we show it is possible to identify some pairs of loci that produce unusually large r(2) values, simply removing large r(2) values is not a reliable way to eliminate bias. Fortunately, the magnitude of bias in [Ncirc ]e is strongly and negatively correlated with the process of recombination, including the number of chromosomes and their length, and this relationship provides a general way to adjust for bias. Additionally, we show that with thousands of loci, precision of [Ncirc ]e is much lower than expected based on the assumption that each pair of loci provides completely independent information.
- Published
- 2016
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