Genetic linkage to explain genetic variation

Abstract

Population genetics theory has been used to develop models to inform biodiversity conservation. The implementation of these models for the decision-making, monitoring and evaluating conservation efforts has improved their efficacy. Many of these models are based on neutral loci, which are assumed to not have any effect on the survival or reproduction of organisms. However, when neutral loci are linked to loci that are under selection, they do not follow the expectations predicted by theoretical neutral models. The term linked selection has been used to refer to this phenomenon. Linked selection might accelerate the rate of loss of genetic diversity, with respect expectations under neutral models. This acceleration is typically expected to occur under two different scenarios: selective sweeps and background selection. A selective sweep occurs when an advantageous allele is spread across the population along with the alleles that are linked to it. Conversely, background selection occurs when a deleterious allele is eliminated from the population along with the alleles linked to it. A third scenario of linked selection has been hypothesised to occur in small populations: associative overdominance. This scenario rather than an acceleration involves a retardation of the loss rate of genetic diversity. The proposed mechanism in operation is a type of natural selection that maintains two or more alleles in the population (i.e. balancing selection). Ultimately, linked selection will bias the conclusions obtained by neutral models. To investigate the mechanisms by which linked selection alters genetic diversity, we built a population genetics model incorporating the main factors involved in the occurrence of linked selection. We modelled the following factors: recombination/linkage disequilibrium, fitness/selection, population size and dominance. Our overall aims are twofold: • Build a model that serves as a base to develop more complex models to test competing hypotheses of linked selection. • Implement the model in a programming language and validate it against theoretical expectations The model was implemented in the programing language R and was extensively tested. The program produces outputs that are consistent with predictions from population genetics theory. By using this model as a starting point, we will be able to investigate potential mechanisms by which linked selection affects genetic diversity and its derived consequences. Our research may highlight the importance of the need to adjust neutral models.