Seno, F. | bioRxiv Science

bioRxiv2023

Sperm length evolution in relation to body mass is shaped by multiple trade-offs in tetrapods

Sperm size is highly variable across species and is influenced by various factors including fertilization mode, female reproductive traits and sperm competition. Despite considerable efforts, many questions about sperm size variation remain open. Variation in body size may affect sperm size evolution through its influence on these factors, but the extent to which sperm size variation is linked to body mass remains elusive. In this study, we use the general theory of Pareto Optimality to investigate the relationship between sperm size and body mass across tetrapods. We find that tetrapods fall within a triangular-shaped Pareto front in the trait space of body mass and sperm length suggesting that the evolution of sperm size in relation to body size is shaped by trade-offs. We then explore the three main factors predicted to influence sperm size evolution, namely sperm competition, clutch size and genome size. Our results demonstrate that body mass optimally shapes sperm size evolution in tetrapods mainly through its association with sperm competition and clutch size. Finally, we show that the triangular-shaped Pareto front is maintained when tested separately within mammals, birds, endothermic species and internal fertilizers, suggesting that similar evolutionary trade-offs characterize the evolution of sperm size in relation to body size within taxonomic/phylogenetic and functional subgroups of tetrapods. This study provides insights into the evolutionary mechanisms driving interspecific sperm size variation and highlights the importance of considering multiple trade-offs in optimizing reproductive traits.

evolutionary biology↗

bioRxiv2021

Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules

Knowledge-based approaches use the statistics collected from protein data-bank structures to estimate effective interaction potentials between amino acid pairs. Empirical relations are typically employed that are based on the crucial choice of a reference state associated to the null interaction case. Despite their significant effectiveness, the physical interpretation of knowledge-based potentials has been repeatedly questioned, with no consensus on the choice of the reference state. Here we use the fact that the Flory theorem, originally derived for chains in a dense polymer melt, holds also for chain fragments within the core of globular proteins, if the average over buried fragments collected from different non-redundant native structures is considered. After verifying that the ensuing Gaussian statistics, a hallmark of effectively non-interacting polymer chains, holds for a wide range of fragment lengths, we use it to define a bona fide reference state. Notably, despite the latter does depend on fragment length, deviations from it do not. This allows to estimate an effective interaction potential which is not biased by the presence of correlations due to the connectivity of the protein chain. We show how different sequence-independent effective statistical potentials can be derived using this approach by coarse-graining the protein representation at varying levels. The possibility of defining sequence-dependent potentials is explored.

biophysics↗