Stephan Peischl

On the accumulation of deleterious mutations during range expansions

We investigate the effect of spatial range expansions on the evolution of fitness when beneficial and deleterious mutations cosegregate. We perform individual-based simulations of 1D and 2D range expansions and complement them with analytical approximations for the evolution of mean fitness at the edge of the expansion. We find that deleterious mutations accumulate steadily on the wave front during range expansions, thus creating an expansion load. Reduced fitness due to the expansion load is not restricted to the wave front, but occurs over a large proportion of newly colonized habitats. The expansion load can persist and represent a major fraction of the total mutation load for thousands of generations after the expansion. The phenomenon of expansion load may explain growing evidence that populations that have recently expanded, including humans, show an excess of deleterious mutations. To test the predictions of our model, we analyse functional genetic diversity in humans and find patterns that are consistent with our model.

A genomic history of Aboriginal Australia

The population history of Aboriginal Australians remains largely uncharacterized. Here we generate high-coverage genomes for 83 Aboriginal Australians (speakers of Pama–Nyungan languages) and 25 Papuans from the New Guinea Highlands. We find that Papuan and Aboriginal Australian ancestors diversified 25–40 thousand years ago (kya), suggesting pre-Holocene population structure in the ancient continent of Sahul (Australia, New Guinea and Tasmania). However, all of the studied Aboriginal Australians descend from a single founding population that differentiated ~10–32 kya. We infer a population expansion in northeast Australia during the Holocene epoch (past 10,000 years) associated with limited gene flow from this region to the rest of Australia, consistent with the spread of the Pama–Nyungan languages. We estimate that Aboriginal Australians and Papuans diverged from Eurasians 51–72 kya, following a single out-of-Africa dispersal, and subsequently admixed with archaic populations. Finally, we report evidence of selection in Aboriginal Australians potentially associated with living in the desert.

Distance from sub-Saharan Africa predicts mutational load in diverse human genomes

Significance Human genomes carry hundreds of mutations that are predicted to be deleterious in some environments, potentially affecting the health or fitness of an individual. We characterize the distribution of deleterious mutations among diverse human populations, modeled under different selection coefficients and dominance parameters. Using a new dataset of diverse human genomes from seven different populations, we use spatially explicit simulations to reveal that classes of deleterious alleles have very different patterns across populations, reflecting the interaction between genetic drift and purifying selection. We show that there is a strong signal of purifying selection at conserved genomic positions within African populations, but most predicted deleterious mutations have evolved as if they were neutral during the expansion out of Africa. The Out-of-Africa (OOA) dispersal ∼50,000 y ago is characterized by a series of founder events as modern humans expanded into multiple continents. Population genetics theory predicts an increase of mutational load in populations undergoing serial founder effects during range expansions. To test this hypothesis, we have sequenced full genomes and high-coverage exomes from seven geographically divergent human populations from Namibia, Congo, Algeria, Pakistan, Cambodia, Siberia, and Mexico. We find that individual genomes vary modestly in the overall number of predicted deleterious alleles. We show via spatially explicit simulations that the observed distribution of deleterious allele frequencies is consistent with the OOA dispersal, particularly under a model where deleterious mutations are recessive. We conclude that there is a strong signal of purifying selection at conserved genomic positions within Africa, but that many predicted deleterious mutations have evolved as if they were neutral during the expansion out of Africa. Under a model where selection is inversely related to dominance, we show that OOA populations are likely to have a higher mutation load due to increased allele frequencies of nearly neutral variants that are recessive or partially recessive.

Expansion load: recessive mutations and the role of standing genetic variation.

Expanding populations incur a mutation burden – the so‐called expansion load. Previous studies of expansion load have focused on codominant mutations. An important consequence of this assumption is that expansion load stems exclusively from the accumulation of new mutations occurring in individuals living at the wave front. Using individual‐based simulations, we study here the dynamics of standing genetic variation at the front of expansions, and its consequences on mean fitness if mutations are recessive. We find that deleterious genetic diversity is quickly lost at the front of the expansion, but the loss of deleterious mutations at some loci is compensated by an increase of their frequencies at other loci. The frequency of deleterious homozygotes therefore increases along the expansion axis, whereas the average number of deleterious mutations per individual remains nearly constant across the species range. This reveals two important differences to codominant models: (i) mean fitness at the front of the expansion drops much faster if mutations are recessive, and (ii) mutation load can increase during the expansion even if the total number of deleterious mutations per individual remains constant. We use our model to make predictions about the shape of the site frequency spectrum at the front of range expansion, and about correlations between heterozygosity and fitness in different parts of the species range. Importantly, these predictions provide opportunities to empirically validate our theoretical results. We discuss our findings in the light of recent results on the distribution of deleterious genetic variation across human populations and link them to empirical results on the correlation of heterozygosity and fitness found in many natural range expansions.

Expansion Load and the Evolutionary Dynamics of a Species Range

Expanding populations incur a mutation burden, the so-called expansion load. Using a mixture of individual-based simulations and analytical modeling, we study the expansion load process in models where population growth depends on the population’s fitness (i.e., hard selection). We show that expansion load can severely slow down expansions and limit a species’ range, even in the absence of environmental variation. We also study the effect of recombination on the dynamics of a species range and on the evolution of mean fitness on the wave front. If recombination is strong, mean fitness on front approaches an equilibrium value at which the effects of fixed mutations cancel each other out. The equilibrium rate at which new demes are colonized is similar to the rate at which beneficial mutations spread through the core. Without recombination, the dynamics is more complex, and beneficial mutations from the core of the range can invade the front of the expansion, which results in irregular and episodic expansion. Although the rate of adaptation is generally higher in recombining organisms, the mean fitness on the front may be larger in the absence of recombination because high-fitness individuals from the core have a higher chance to invade the front. Our findings have important consequences for the evolutionary dynamics of species ranges as well as on the role and the evolution of recombination during range expansions.

Evolutionary rescue by beneficial mutations in environments that change in space and time

A factor that may limit the ability of many populations to adapt to changing conditions is the rate at which beneficial mutations can become established. We study the probability that mutations become established in changing environments by extending the classic theory for branching processes. When environments change in time, under quite general conditions, the establishment probability is approximately twice the ‘effective selection coefficient’, whose value is an average that gives most weight to a mutants fitness in the generations immediately after it appears. When fitness varies along a gradient in a continuous habitat, increased dispersal generally decreases the chance a mutation establishes because mutations move out of areas where they are most adapted. When there is a patch of favourable habitat that moves in time, there is a maximum speed of movement above which mutations cannot become established, regardless of when and where they first appear. This critical speed limit, which is proportional to the mutations maximum selective advantage, represents an absolute constraint on the potential of locally adapted mutations to contribute to evolutionary rescue.

Establishment of New Mutations in Changing Environments

Understanding adaptation in changing environments is an important topic in evolutionary genetics, especially in the light of climatic and environmental change. In this work, we study one of the most fundamental aspects of the genetics of adaptation in changing environments: the establishment of new beneficial mutations. We use the framework of time-dependent branching processes to derive simple approximations for the establishment probability of new mutations assuming that temporal changes in the offspring distribution are small. This approach allows us to generalize Haldane’s classic result for the fixation probability in a constant environment to arbitrary patterns of temporal change in selection coefficients. Under weak selection, the only aspect of temporal variation that enters the probability of establishment is a weighted average of selection coefficients. These weights quantify how much earlier generations contribute to determining the establishment probability compared to later generations. We apply our results to several biologically interesting cases such as selection coefficients that change in consistent, periodic, and random ways and to changing population sizes. Comparison with exact results shows that the approximation is very accurate.

Impact of range expansions on current human genomic diversity

The patterns of population genetic diversity depend to a large extent on past demographic history. Most human populations are known to have gone recently through a series of range expansions within and out of Africa, but these spatial expansions are rarely taken into account when interpreting observed genomic diversity, possibly because they are difficult to model. Here we review available evidence in favour of range expansions out of Africa, and we discuss several of their consequences on neutral and selected diversity, including some recent observations on an excess of rare neutral and selected variants in large samples. We further show that in spatially subdivided populations, the sampling strategy can severely impact the resulting genetic diversity and be confounded by past demography. We conclude that ignoring the spatial structure of human population can lead to some misinterpretations of extant genetic diversity.

Evolution of dominance under frequency-dependent intraspecific competition.

A population-genetic analysis is performed of a two-locus two-allele model, in which the primary locus has a major effect on a quantitative trait that is under frequency-dependent disruptive selection caused by intraspecific competition for a continuum of resources. The modifier locus determines the degree of dominance at the trait level. We establish the conditions when a modifier allele can invade and when it becomes fixed if sufficiently frequent. In general, these are not equivalent because an unstable internal equilibrium may exist and the condition for successful invasion of the modifier is more restrictive than that for eventual fixation from already high frequency. However, successful invasion implies global fixation, i.e., fixation from any initial condition. Modifiers of large effect can become fixed, and also invade, in a wider parameter range than modifiers of small effect. We also study modifiers with a direct, frequency-independent deleterious fitness effect. We show that they can invade if they induce a sufficiently high level of dominance and if disruptive selection on the ecological trait is strong enough. For deleterious modifiers, successful invasion no longer implies global fixation because they can become stuck at an intermediate frequency due to a stable internal equilibrium. Although the conditions for invasion and for fixation if sufficiently frequent are independent of the linkage relation between the two loci, the rate of spread depends strongly on it. The present study provides further support to the view that evolution of dominance may be an efficient mechanism to remove unfit heterozygotes that are maintained by balancing selection. It also demonstrates that an invasion analysis of mutants of very small effect is insufficient to obtain a full understanding of the evolutionary dynamics under frequency-dependent selection.

A sequential coalescent algorithm for chromosomal inversions

Chromosomal inversions are common in natural populations and are believed to be involved in many important evolutionary phenomena, including speciation, the evolution of sex chromosomes and local adaptation. While recent advances in sequencing and genotyping methods are leading to rapidly increasing amounts of genome-wide sequence data that reveal interesting patterns of genetic variation within inverted regions, efficient simulation methods to study these patterns are largely missing. In this work, we extend the sequential Markovian coalescent, an approximation to the coalescent with recombination, to include the effects of polymorphic inversions on patterns of recombination. Results show that our algorithm is fast, memory-efficient and accurate, making it feasible to simulate large inversions in large populations for the first time. The SMC algorithm enables studies of patterns of genetic variation (for example, linkage disequilibria) and tests of hypotheses (using simulation-based approaches) that were previously intractable.