Pollack, J. B. | bioRxiv Science

bioRxiv2026

Variation in hypoxia tolerance is driven by evolutionary changes in gene regulation in the eastern oyster

Understanding the genomic basis of stress tolerance is crucial for predicting biological responses to environmental change. Here, we investigated the genomic basis of divergence in hypoxia tolerance between two populations of eastern oyster (Crassostrea virginica) from Louisiana and Texas, USA. We combined low-coverage whole-genome sequencing data with previously generated transcriptomic evidence to understand the mechanisms underlying population-specific variation in hypoxia tolerance. Genome-wide analyses revealed substantial population differentiation (global FST = 0.21), indicative of a clear genetic break between our study populations. We combined estimates of genomic differentiation (FST) with diversity metrics to generate a set of exploratory candidate regions showing signatures consistent with recent selection. Several candidate genes identified through this approach were associated with the maintenance of homeostasis under environmental stress. We additionally tested whether genes previously identified as differentially expressed (DE) under hypoxia exhibit elevated genomic divergence between populations. While these hypoxia DEGs did show higher than expected between-population differentiation, this pattern also holds for other environmentally responsive genes. This suggests that transcriptomically responsive genes in general may generally show elevated divergence among populations, possibly due to a weaker effect of purifying selection. Furthermore, we found that hypoxia DEGs did not show an enrichment of nonsynonymous fixed differences (p = 0.9155, as compared to the genome-wide background), suggesting that the elevated divergence seen in these genes is not driven by rapid protein-coding evolution. Together, our results support a model in which population-scale differences in hypoxia tolerance occur primarily through evolution of gene regulation acting on environmentally responsive pathways.

genomics↗

bioRxiv2021

A unicellular walker embodies a finite state machine

Cells are complex biochemical systems whose behavior emerges from interactions among myriad molecular components. Computation is often invoked as a general framework for navigating this cellular complexity. However, it is unclear how cells might embody computational processes such that theories of computation, including finite state machine models, could be productively applied. Here, we demonstrate finite state machine-like processing embodied in cells using the walking behavior of Euplotes eurystomus, a ciliate that walks across surfaces using fourteen motile appendages (cirri). We found that cellular walking entails regulated transitions between a discrete set of gait states. The set of observed transitions decomposes into a small group of high-probability, temporally irreversible transitions and a large group of low-probability time-symmetric transitions, thus revealing stereotypy in sequential patterns of state transitions. Simulations and experiments suggest that the sequential logic of the gait is functionally important. Taken together, these findings implicate a finite state machine-like process. Cirri are connected by microtubule bundles (fibers), and we found that the dynamics of cirri involved in different state transitions are associated with the structure of the fiber system. Perturbative experiments revealed that the fibers mediate gait coordination, suggesting a mechanical basis of gait control.

cell biology↗