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Möbius, W.

Publications and source records attributed to Möbius, W..

2 recordsLinked to original sources

Evolution of populations expanding on curved surfaces

The expansion of a population into new habitat is a transient process that leaves its footprints in the genetic composition of the expanding population. How the structure: of the environment shapes the population front and the evolutionary dynamics during such a range expansion is little understood. Here, we investigate the evolutionary dynamics of populations consisting of many selectively neutral genotypes expanding on curved surfaces. Using a combination of individual-based off-lattice simulations, geometrical arguments, and lattice-based stepping-stone simulations, we characterise the effect of individual bumps on an otherwise flat surface. Compared to the case of a range expansion on a flat surface:, we observe a transient relative increase, followed by a decrease, in neutral genetic diversity at the population front. Ill addition, we find that individuals at the sides of the bump have a dramatically increased expected number of descendants, while their neighbours closer to the bumps centre are far less lucky. Both observations can be explained using an analytical description of straight paths (geodesics) on the curved surface, Complementing previous studies of heterogeneous flat environments, the findings here build our understanding of how complex environments shape the evolutionary dynamics of expanding populations.

evolutionary biology

Genetic Drift and Selection in Many-Allele Range Expansions

We experimentally and numerically investigate the evolutionary dynamics of four competing strains of E. coli with differing expansion velocities in radially expanding colonies. We compare experimental measurements of the average fraction, correlation functions between strains, and the relative rates of genetic domain wall annihilations and coalescences to simulations modeling the population as a one-dimensional ring of annihilating and coalescing random walkers with deterministic biases due to selection. The simulations reveal that the evolutionary dynamics can be collapsed onto master curves governed by three essential parameters: (1) an expansion length beyond which selection dominates over genetic drift; (2) a characteristic angular correlation describing the size of genetic domains; and (3) a dimensionless constant quantifying the interplay between a colonys curvature at the frontier and its selection length scale. We measure these parameters with a new technique that precisely measures small selective differences between spatially competing strains and show that our simulations accurately predict the dynamics with no additional fitting. Our results suggest that that the random walk model can act as a useful predictive tool when describing the evolutionary dynamics of range expansions composed of an arbitrary number of competing alleles with different fitnesses.\n\nAuthor summaryPopulation expansions occur naturally during the spread of invasive species and have played a role in our evolutionary history when many of our ancestors expanded out of Africa. We use a colony of bacteria expanding into unoccupied, nutrient-rich territory on an agar plate as a model system to explore how an expanding populations spatial structure impacts its evolutionary dynamics. Spatial structure is present in expanding microbial colonies because daughter cells migrate only a small distance away from their mothers each generation. Generally, the constituents of expansions occurring in nature and in the lab have different genetic compositions (genotypes, or alleles if a single gene differs), each instilling different fitnesses, which compete to proliferate at the frontier. Here, we show that a random-walk model can accurately predict the dynamics of four expanding strains of E. coli with different fitnesses; each strain represents a competing allele. Our results can be extended to describe any number of competing genotypes with different fitnesses in a naturally occurring expansions. Our model can also be used to precisely measure small selective differences between spatially competing genotypes in controlled laboratory settings.

evolutionary biology