bioRxivEvolutionary BiologyPreprint
Development shapes molecular responses to thermal extremes in a desert bird
Lea HuberiD, Charlie Kinahan CornwallisiD, Molatelo Rosina KekanaiD, Neleke Lotz, Zanell Brand, Schalk CloeteiD, Anel EngelbrechtiD, Mads F. SchouiD
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Abstract
Thermal extremes are among the most immediate environmental challenges faced by animals. Coping with these conditions across life is complex because growth changes body size, heat exchange and thermoregulatory demands. Consequently, adaptive responses in young, small individuals may be maladaptive, or require adjustment, later in life. However, in endotherms we know very little about how thermoregulatory responses to hot and cold temperatures change during development, or about the molecular mechanisms regulating responses. We examined the molecular responses to acute heat (40{degrees}C), cold (12{degrees}C) and benign (23{degrees}C) conditions in 1- and 8-week-old ostrich chicks (Struthio camelus), a rapidly growing species exposed to strong daily and seasonal temperature variation. We found that in 1-week-old chicks, 44% of temperature-related genes were involved in both heat and cold responses, indicating that responses to opposing temperatures involve overlapping molecular pathways. However, the response of 76% of these genes changed during development. For example, some genes that increased with heat exposure when young decreased with heat exposure later in development, and vice versa. Such opposing selection pressures may maintain genetic variation in thermoregulatory pathways. Consistent with this prediction, comparisons between ostrich subspecies adapted to different thermal environments revealed patterns of genomic variation compatible with balancing selection in differentially expressed genes. Our results show that hot and cold temperatures trigger overlapping molecular responses that change during development, which shape genetic variation in the thermoregulatory system.
- organism: chicken / avian
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
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