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Yoshihara Caldeira Brandt, D.

Publications and source records attributed to Yoshihara Caldeira Brandt, D..

2 recordsLinked to original sources

Characterising the detectable and invisible fractions of genomic loci under balancing selection

Balancing selection refers to scenarios where selection maintains genetic polymorphisms affecting fitness and its components. Empirical studies have documented specific cases of balancing selection, yet the general prevalence of balanced polymorphisms within genomes remains a topic of longstanding debate. Although genome-wide scans for signals of balancing selection suggest that it is rare, current methods are notoriously conservative and may identify only a small and unrepresentative fraction of loci evolving under balancing selection. What, then, are the proportions of loci under balancing selection that are detectable versus invisible to genome scans? Here, we address this question using a combination of analytical modelling and population genetic simulations. Our results provide quantitative support for the intuition that a large fraction of loci under balancing selection will be invisible to standard tests for balancing selection, with the detectable loci representing a biased subset with large and symmetrical fitness effects on different fitness components. Quantifying power across parameters that vary between species also shows that the detectable and invisible fractions of genomic loci under balancing selection are likely to differ substantially between organisms. For example, a Drosophila melanogaster-like ratio of mutation to recombination rates ([~]0.1) reduces detection power by roughly a quarter of the power expected with a human-like ratio ([~]1). This, combined with other evidence suggesting that balancing selection could be common in D. melanogaster, showcases how our appreciation of the prevalence of balancing selection is limited by our ability to detect its genomic signals, especially in those species where it might be common.

genetics↗

Estimating population split times and migration rates from historical effective population sizes

The estimation of effective population sizes (Ne) through time is of fundamental interest in population genetics, but the interpretation of Ne as the effective number of breeding individuals in the population is challenged by the effect of population structure. In fact, variation in Ne reported in many studies may be a consequence of changes in migration rates between populations rather than changes in actual population size. We address this long-standing problem here by constructing joint models of population size changes, migration, and divergence that can adjust temporal estimates of Ne and estimate the actual Ne of a local deme connected to another population through migration. We also develop a method for estimating divergence times and migration rates taking into account complex scenarios of changing population sizes. We apply the method to previously published data from humans, and show that, when taking migration and changes in Ne into account, the estimated divergence between the San and Dinka populations is approximately 108 kya, and not 255 kya as reported in a previous study. Using simulations, we demonstrate that the previously reported and surprisingly old estimates of divergence between San and Dinka is in fact caused by a quantifiable estimation bias due to changes in Ne through time.

evolutionary biology↗