Search

Motivation Biology students often struggle with the fundamental concepts of evolutionary genetics, including genetic drift, mutation and selection. To address this problem, 1LocusSim was developed to simulate the interaction of different factors, such as population size, mutation, selection and dominance, to study their effect on allelic frequency during evolution. With 1LocusSim, students can compare theoretical results with simulation outputs and solve and analyze different problems of population genetics. The 1LocusSim web has a responsive design which means that it has been specifically designed to be used on smartphones. Results To demonstrate its use, I review the classical overdominance model of population genetics and highlight a characteristic that is often not explicitly stated. Specifically, it is emphasized that the equilibrium of the model does not depend on the homozygous selection coefficients but rather on the ratio of the selection coefficients. This is already clear from the classical formula but maybe not so much for students. Also it implies that the equilibrium can be expressed solely in terms of the dominance coefficient h. To verify this theoretical prediction, I utilize the simulator and calculate the equilibrium for the well-known case of sickle cell anemia. By utilizing this tool, students can learn at their own pace and convenience, anywhere and anytime. Availability and implementation 1LocusSim if freely available at https://1LocusSim-biosdev.pythonanywhere.com/. Website implemented under the Bottle micro web-framework for Python, with all major browsers supported. Supplementary information Supplementary data are available at Bioinformatics Advances online. [ABSTRACT FROM AUTHOR]

The mode in which sexual organisms choose mates is a key evolutionary process, as it can have a profound impact on fitness and speciation. One way to study mate choice in the wild is by measuring trait correlation between mates. Positive assortative mating is inferred when individuals of a mating pair display traits that are more similar than those expected under random mating while negative assortative mating is the opposite. A recent review of 1134 trait correlations found that positive estimates of assortative mating were more frequent and larger in magnitude than negative estimates. Here, we describe the scale-of-choice effect (SCE), which occurs when mate choice exists at a smaller scale than that of the investigator's sampling, while simultaneously the trait is heterogeneously distributed at the true scale-of-choice. We demonstrate the SCE by Monte Carlo simulations and estimate it in two organisms showing positive ( Littorina saxatilis) and negative ( L. fabalis) assortative mating. Our results show that both positive and negative estimates are biased by the SCE by different magnitudes, typically toward positive values. Therefore, the low frequency of negative assortative mating observed in the literature may be due to the SCE's impact on correlation estimates, which demands new experimental evaluation. [ABSTRACT FROM AUTHOR]