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Waxman, D.

Publications and source records attributed to Waxman, D..

2 recordsLinked to original sources

A comprehensive representation of selection at loci with multiple alleles that allows complex forms of genotypic fitness

Genetic diversity is central to evolutionary change, with both natural selection and random genetic drift depending on variation within a population. An individual in a diploid population carries two alleles per locus, yet the population as a whole can harbour many alleles, giving rise to a rich spectrum of homozygous and heterozygous genotypes. Such multiallelic variation is common at biologically and medically important loci such as the major histocompatibility complex, the ABO blood group system, and genes underlying monogenic diseases. However, much of population genetic theory and data analysis has focussed on biallelic loci. Here, we introduce a matrix representation of the genotypic selection acting at a multiallelic locus. This exploits the common mathematical structure underlying selection and drift, and separates the effects of genetic diversity and fitness. The representation accommodates diverse selection regimes, including additive, multiplicative, frequency-dependent, and temporally varying selection, as well as heterozygote advantage. We show how, under specific assumptions, genotype-specific fitness-effects can be estimated from allele frequency trajectories over microevolutionary timescales. Applying this estimation procedure to time-series data from experimental yeast evolution illustrates how multiallelic fitness interactions, including heterozygote advantage, may be characterised from haplotype frequency data. More broadly, this work provides a practical foundation for analysing evolutionary dynamics at multiallelic loci in experimental and natural populations.

evolutionary biology↗

Detecting population continuity and ghost admixture among ancient genomes

Ancient DNA (aDNA) can prove a valuable resource when investigating the evolutionary relationships between ancient and modern populations. Performing demographic inference using datasets that include aDNA samples however, requires statistical methods that explicitly account for the differences in drift expected among a temporally distributed sample. Such drift due to temporal structure can be challenging to discriminate from admixture from an unsampled, or "ghost", population, which can give rise to very similar summary statistics and confound methods commonly used in population genetics. Sequence data from ancient individuals also have unique characteristics, including short fragments, increased sequencing-error rates, and often limited genome-coverage that poses further challenges. Here we present a novel and conceptually simple approach for assessing questions of population continuity among a temporally distributed sample. We note that conditional on heterozygote sites in an individual genome at a particular point in time, the mean proportion of derived variants at those sites in other individuals has different expectations forwards in time and backwards in time. The difference in these processes enables us to construct a statistic that can detect population continuity in a temporal sample of genomes. We show that the statistic is sensitive to historical admixture events from unsampled populations. Simulations are used to evaluate the power of this approach. We investigate a set of ancient genomes from Early Neolithic Scandinavia to assess levels of population continuity to an earlier Mesolithic individual.

genetics↗