Introduction
Rising seawater temperature as a result of climate change can have detrimental effects on aquaculture production, which is exposed to interactions with environmental factors. Seafood is the main source of animal protein for a billion people worldwide and has a key role in global food security, while such changes in production can have very negative socioeconomic impacts for local communities and national economies. Therefore, understanding the possible impacts of climate change on salmon production and exploring possibilities for mitigation, is crucial.
Previous studies in salmonids suggest that changes in seawater temperature can have negative impacts on fish health and welfare by causing stress (Anttila et al. 2013); for example, there has been observed between-family variation in thermal tolerance (Anttila et al. 2013), environment effects on sexual maturation (Wild et al. 1994), and temperature-related immune response changes associated with amoebic gill disease (Benedicenti et al. 2019). Research in salmon genetics has allowed to identify genomic variants that impact resistance to important infectious diseases (e.g. Houston et al. 2010) and growth (e.g. Tsai et al. 2015), and to optimise the use of genomic data for selective breeding in a cost-effective manner (Tsairidou et al. 2019). However, robustness to climate change effects has not been routinely included in breeding goals as yet, in part because this requires identifying suitable target traits. The aims of this pilot project were to (a) record and assess changes in major growth, survival, maturation and health traits in Atlantic salmon post-smolts, challenged with moderate and with more extreme heat-wave conditions on the west coast of Scotland; and, (b) investigate the existence of temperature-dependant genotype-by-environment interactions and the potential of selective breeding to improve temperature resilience as mitigation strategy.
Materials and Methods
This study focused on a Scottish Atlantic salmon breeding programme population of 518 salmon post-smolts, of age 13-14 months, from 54 families, which were challenged for 4 weeks in 3 tanks at (i) ambient temperature, (ii) ambient +4oC, and, (iii) ambient +8oC. Data were recorded pre- and after-treatment. Oxygen and water temperature were recorded daily reaching a maximum of 24.39oC, approximating heat-wave conditions for the west coast of Scotland. 8,978 SNP genotypes (after quality control) were available for 492 fish.
Results and Discussion
There was a significant relationship between treatment and survival (p-value <5%), while ANCOVA analyses for growth traits including body weight, Fulton’s performance index and average daily gain calculated for the duration of the trial, showed statistically significant differences between-tanks after treatment, indicating that a moderate increase of water temperature (+4oC) is beneficial for growth compared to ambient temperature, but further exceeding salmon’s optimal zone (+8oC) has a negative impact on growth, possibly due to the additional energy requirements to cope with more severe heat-stress. Using ultrasound scanning, palpation and colour observation, it was observed that higher temperature treatments induced early maturation (grilsing), and an increase of AGD scores. QPCR essay for a range of pathogens and using 10 gill swab samples selected randomly (based on AGD scores) from each tank, revealed quantifiable Ct values for Aeromonas hydrophila and total bacterial load. Aeromonas hydrophila was detected on all swabs in higher temperatures, and is an opportunistic pathogen that can lead to outbreaks associated with increased water temperatures, mainly found in warm climates.
analysis revealed the presence of three distinct clusters, hence principal components were fitted as covariates in all genetic models. Firstly, genomic heritability estimates were obtained across the entire population; growth traits provided moderate heritabilities, i.e. body weight and length before and after the trial (~0.39), and average daily gain (0.26). Binary survival estimated with both a linear and a generalised linear model, and day-of-death provided boundary small estimates (<0.05). Maturation (grilsing) provided a ~0.2 heritability, while for AGD score it was not possible to detect genetic variance as the prevalence was extremely small. Within-tanks heritability estimates, showed small differences between-tanks, however, for growth traits heritabilities remained within the range observed in the overall population. For maturation the genetic variance that could be captured within each tank was very small with large standard error, while for survival traits it was possible to capture genetic variance only in the high temperature tank. This was reflected in the bivariate analyses to estimate covariances between environments; genetic correlations between-tanks for growth traits were very close to 1, indicating no significant re-ranking between environments, and for maturation the genetic correlations were very close to 1 but with large standard errors. Although in this data there was no indication for genotype-by-environment interactions, these results should be further validated in larger populations containing larger genetic variance in the traits of interest.
References
Anttila, K., et al. 2013. Variation in temperature tolerance among families of Atlantic salmon (Salmo salar) is associated with hypoxia tolerance, ventricle size and myoglobin level. Journal of Experimental Biology 216(7): 1183-1190.
Wild, V., et al. 1994. Genetic parameters and genotype × environment interaction for early sexual maturity in Atlantic salmon (Salmo salar). Aquaculture, 128(1): 51-65.
Benedicenti, O., T. G. Pottinger, C. Collins et al. 2019. Journal of fish diseases, 42, 1241-1258.
Houston, R. D., et al. 2010. The susceptibility of Atlantic salmon fry to freshwater infectious pancreatic necrosis is largely explained by a major QTL. Heredity, 105(3): 318-327.
Tsai, H.-Y., et al. 2015. Genome wide association and genomic prediction for growth traits in juvenile farmed Atlantic salmon using a high density SNP array. BMC Genomics, 16(1): 969.
Tsairidou, S., et al. 2019. Optimizing Low-Cost Genotyping and Imputation Strategies for Genomic Selection in Atlantic Salmon. G3:Genes|Genomes|Genetics, g3.400800.402019