Salmonid gene expression biomarkers indicative of physiological responses to changes in salinity and temperature, but
Aimee Lee S Houde1,2, Arash Akbarzadeh2,3, Oliver P Günther4
1Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC, Canada, V6T 1Z4.
Abstract:
An organism's ability to respond effectively to environmental change is critical to its survival. Yet, life stage and overall condition can dictate tolerance thresholds to heightened environmental stressors, such that stress may not be equally felt across individuals and at all times. Also, the transcriptional responses induced by environmental changes can reflect both generalized responses as well as others that are highly specific to the type of change being experienced. Thus, if transcriptional biomarkers specific to a stressor, even under multi-stressor conditions, can be identified, the biomarkers could then be applied in natural environments to determine when and where an individual experiences such a stressor. Here, we experimentally challenged juvenile Chinook salmon (Oncorhynchus tshawytscha) to validate candidate gill gene expression biomarkers. A sophisticated experimental design manipulated salinity (freshwater, brackish water and seawater), temperature (10, 14 and 18°C) and dissolved oxygen (normoxia and hypoxia) in all 18 possible combinations for 6 days using separate trials for three smolt statuses (pre-smolt, smolt and de-smolt). In addition, changes in juvenile behaviour, plasma variables, gill Na+/K+-ATPase activity, body size, body morphology and skin pigmentation supplemented the gene expression responses. We identified biomarkers specific to salinity and temperature that transcended the multiple stressors, smolt status and mortality (live, dead and moribund). Similar biomarkers for dissolved oxygen were not identified. This work demonstrates the unique power of gene expression biomarkers to identify a specific stressor even under multi-stressor conditions, and we discuss our next steps for hypoxia biomarkers using an RNA-seq study.
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