Tsuzuki, Y. | bioRxiv Science

bioRxiv2022

Which life history strategy can maintain high genetic diversity in plants?

Classifying a variety of plant life histories is an important step to understand ecological and evolutionary background of life history diversification in plants. Principal component analysis (PCA) of life history traits, as well as elasticity analysis using a ternary diagram, successfully categorized the diverse life histories and clarified their link to various ecological characteristics, such as population dynamics, functional traits, and conservation status. However, the relationships with population genetic properties, including genetic diversity, have not been explored very much. In this study, we overlaid annual change rate of expected heterozygosity{eta} on life history spectrum obtained by PCA and elasticity analysis to examine which life history strategy can maintain high genetic diversity over time. We found that{eta} gradually changed along the fast-slow continuum and that slow-paced life histories maintained high genetic diversity, probably due to generation overlap. Elasticity analysis showed that life histories that highly depend on stasis also maintained genetic diversity. As genetic diversity reflects adaptive potential to environmental changes, our study provides a new genetic perspective on adaptative evolution and population viability to life history study.

ecology↗

bioRxiv2021

Potential effects of life history on demographic genetic structure in stage-structured plant populations

O_LIPredicting temporal dynamics of genetic diversity is important for assessing long-term population persistence. In stage-structured populations, especially in perennial plant species, genetic diversity is often compared among life history stages, such as seedlings, juveniles, and flowerings, using neutral genetic markers. Because individuals in mature stages will die and be replaced by those in more immature stages over the course of time, the comparison among stages (sometimes referred to as demographic genetic structure) has been regarded as a proxy of potential genetic changes that accompany the turnover of constituent individuals. However, because demographic genetic structure had not been theoretically examined, the basic property and the validity of demographic genetic structure remained unclear. C_LIO_LIWe developed a matrix model which was made up of difference equations of expected heterozygosity, a common proxy of genetic diversity, of each life history stage at a neutral locus in stage-structured plant populations. Based on the model, we formulated demographic genetic structure as well as the annual change rate of expected heterozygosity (denoted as{eta} ). We obtained theoretical expectation of demographic genetic structure and{eta} from our model and compared them with computational results of stochastic simulation for randomly generated 3,000 life histories for model validation. We then examined the relationships of demographic genetic structure with effective population size Ne, which is the determinants of diversity loss per generation time, as well as with{eta} . C_LIO_LITheoretical expectations on{eta} and demographic genetic structure fitted well to the results of stochastic simulation, supporting the validity of our model. Demographic genetic structure varied independently of Ne and{eta} , while having a strong correlation with stable stage distribution: expected heterozygosity was lower in stages with fewer individuals. C_LIO_LIOur results indicate that demographic genetic structure strongly reflects stable stage distribution, rather than temporal genetic dynamics, and that inferring future genetic diversity solely from demographic genetic structure would be misleading. Instead of demographic genetic structure, the newly-defined statistics{eta} will be an useful tool to predict genetic diversity at the same time scale as population dynamics, facilitating evaluation on population viability from a genetic point of view. C_LI

genetics↗