Lavrentovich, M. O. | Search bioRxiv

bioRxiv2018

Pollen Patterns Form from Modulated Phases

Pollen grains are known for their impressive variety of species-specific, microscale surface patterning. Despite having similar biological developmental steps, pollen grain surface features are remarkably geometrically varied. Previous work suggests that a physical process may drive this pattern formation and that the observed diversity of patterns can be explained by viewing pollen pattern development as a phase transition to a spatially modulated phase. Several studies have shown that the polysaccharide material of plant cell walls undergoes phase separation in the absence of cross-linking stabilizers of the mixed phase. Here we show experimental evidence that phase separation of the extracellular polysaccharide material (primexine) during pollen cell development leads to a spatially modulated phase. The spatial pattern of this phase-separated primexine is also mechanically coupled to the undulation of the pollen cell membrane. The resulting patterned pools of denser primexine form the negative template of the ultimate sites of sporopollenin deposition, leading to the final micropattern observed in the mature pollen. We then present a general physical model of pattern formation via modulated phases. Using analytical and numerical techniques, we find that most of the pollen micropatterns observed in biological evolution could result from a physical process of modulated phases. However, an analysis of the relative rates of transitions from states that are equilibrated to or from states that are not equilibrated suggests that while equilibrium states of this process have occurred throughout evolutionary history, there has been no particular evolutionary selection for symmetric, equilibrated states.

biophysics↗

bioRxiv2017

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↗