Generation of a reference transcriptome for evaluating rainbow trout responses to various stressors

生成参考转录组以评估虹鳟对各种压力源的反应

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作者:Cecilia C Sánchez, Gregory M Weber, Guangtu Gao, Beth M Cleveland, Jianbo Yao, Caird E Rexroad 3rd

Background

Fish under intensive culture conditions are exposed to a variety of acute and chronic stressors, including high rearing densities, sub-optimal water quality, and severe thermal fluctuations. Such stressors are inherent in aquaculture production and can induce physiological responses with adverse effects on traits important to producers and consumers, including those associated with growth, nutrition, reproduction, immune response, and fillet quality. Understanding and monitoring the biological mechanisms underlying stress responses will facilitate alleviating their negative effects through selective breeding and changes in management practices, resulting in improved animal welfare and production efficiency.

Conclusion

We have generated and characterized a reference transcriptome for rainbow trout that represents multiple tissues responding to multiple stressors common to aquaculture production environments. This resource compliments existing public transcriptome data and will facilitate approaches aiming to evaluate gene expression associated with stress in this species.

Results

Physiological responses to five treatments associated with stress were characterized by measuring plasma lysozyme activity, glucose, lactate, chloride, and cortisol concentrations, in addition to stress-associated transcripts by quantitative PCR. Results indicate that the fish had significant stressor-specific changes in their physiological conditions. Sequencing of a pooled normalized transcriptome library created from gill, brain, liver, spleen, kidney and muscle RNA of control and stressed fish produced 3,160,306 expressed sequence tags which were assembled and annotated. SNP discovery resulted in identification of ~58,000 putative single nucleotide polymorphisms including 24,479 which were predicted to fall within exons. Of these, 4907 were predicted to occupy the first position of a codon and 4110 the second, increasing the probability to impact amino acid sequence variation and potentially gene function.

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