The discernible and hidden effects of clonality on the genotypic and genetic states of populations: Improving our estimation of clonal rates

Partial clonality is widespread across the tree of life, but most population genetic models are designed for exclusively clonal or sexual organisms. This gap hampers our understanding influence on evolutionary trajectories and interpretation data. We performed forward simulations diploid populations at increasing rates (c), analysed their relationships with genotypic (clonal richness, R, distribution sizes, Pareto ?) (FIS linkage disequilibrium) indices, tested predictions c from data through supervised machine learning. Two complementary behaviours emerged probability distributions indices c. While impact R ? was easily described by simple mathematical equations, its effects were noticeable only highest levels (c > 0.95). Consequently, allowed reliable estimates c, while descriptors led to poorer performances when < 0.95. These results provide clear baseline expectations diversity dynamics under partial clonality. Worryingly, however, use realistic sample sizes acquire empirical systematically gross underestimates (often one two orders magnitude) suggesting that many interpretations hitherto proposed in literature, mostly based should be reappraised. propose future avenues derive confidence intervals show that, although still approximate, a learning method would greatly improve estimation