Evolutionary Reorganization of Transcriptomic Architecture Across a UVB Tolerance Gradient in Fish

Environmental stressors such as ultraviolet radiation impose strong selective pressures on organisms, yet how adaptation to such stressors shapes transcriptomic responses at the network level remains poorly understood. Although stratospheric ozone is recovering globally, substantial regional variation in UV exposure persists, particularly in high-altitude environments where extreme UV levels can occur. Here, we compared three fish models representing distinct biological responses to UVB exposure: wild-type zebrafish (Danio rerio), a melanin-deficient zebrafish mutant (nacre) lacking a major protective mechanism against UVB damage, and the high-altitude Andean killifish Orestias ascotanensis, a species naturally exposed to extreme UVB radiation. Together, these models define a gradient spanning physiological protection, impaired protection, and evolutionary adaptation to UVB stress. Using RNA-seq and protein-protein interaction networks, we show that transcriptomic responses differ markedly across this gradient. Wild-type and nacre zebrafish exhibited relatively limited transcriptomic changes (∼2%-2.4% of genes changing), whereas O. ascotanensis displayed a large-scale and highly coordinated response (∼21.6% of genes changing) characterized by functionally specialized networks enriched in DNA repair pathways. These differences involved not only transcriptomic magnitude but also marked reorganization of transcriptomic architecture. Integration with positive selection analyses revealed that positively selected genes were concentrated within highly interconnected regions of transcriptomic networks, consistent with adaptation involving network reorganization. Furthermore, ortholog-based analyses suggest that adaptive responses involve differential reorganization of a conserved functional background. Together, our results support a model in which adaptation to environmental stress is associated with the reorganization of conserved transcriptomic networks across physiological and evolutionary contexts, providing a systems-level perspective on the molecular basis of adaptation.