Inbred populations often suffer from increased mutational load and reduced fitness due to lower efficacy of purifying selection in groups with small effective population sizes. Genetic rescue (GR) is a conservation tool that is studied and deployed with the aim of increasing the fitness of such inbred populations by assisted migration of individuals from closely related outbred populations. The success of GR depends on several factors—such as their demographic history and distribution of dominance effects of mutations—that may vary across populations. While we understand the impact of these factors on the dynamics of GR, their impact on local adaptations remains unclear. To this end, we conduct a population genetics simulation study to evaluate the impact of trait complexity (Mendelian vs. polygenic), dominance effects, and demographic history on the efficacy of GR. We find that the impact on local adaptations depends highly on the mutational load at the time of GR, which is in turn shaped dynamically by interactions between demographic history and dominance effects of deleterious variation. Over time local adaptations are generally restored post-GR, though in the short term they are often compromised in the process of purging deleterious variation. We also show that while local adaptations are almost always fully restored, the degree to which ancestral genetic variation affecting the trait is replaced by donor variation can vary drastically and is especially high for complex traits. Our results provide insights on the impact of GR on trait evolution and considerations for the practical implementation of GR.
The Patterson F- and D-statistics are commonly used measures for quantifying population relationships and for testing hypotheses about demographic history. These statistics make use of allele frequency information across populations to infer different aspects of population history, such as population structure and introgression events. Inclusion of related or inbred individuals can bias such statistics, which may often lead to the filtering of such individuals. Here, we derive statistical properties of the F- and D-statistics, including their biases due to the inclusion of related or inbred individuals, their variances, and their corresponding mean squared errors. Moreover, for those statistics that are biased, we develop unbiased estimators and evaluate the variances of these new quantities. Comparisons of the new unbiased statistics to the originals demonstrates that our newly derived statistics often have lower error across a wide population parameter space. Furthermore, we apply these unbiased estimators using several global human populations with the inclusion of related individuals to highlight their application on an empirical dataset. Finally, we implement these unbiased estimators in open-source software package funbiased for easy application by the scientific community.
more » « less- NSF-PAR ID:
- 10361215
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Genetics
- Volume:
- 220
- Issue:
- 1
- ISSN:
- 1943-2631
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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