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ARS Home » Northeast Area » Leetown, West Virginia » Cool and Cold Water Aquaculture Research » Research » Publications at this Location » Publication #286938

Title: Identifying genes affectng stress response in rainbow trout

item Rexroad, Caird
item Liu, Sixin
item Gao, Guangtu
item Palti, Yniv
item Weber, Gregory - Greg
item Vallejo, Roger

Submitted to: Aquaculture Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 9/21/2012
Publication Date: 2/25/2013
Citation: Rexroad Iii, C.E., Liu, S., Gao, G., Palti, Y., Weber, G.M., Vallejo, R.L. 2013. Identifying genes affectng stress response in rainbow trout. Aquaculture Conference Proceedings. P0182.

Interpretive Summary:

Technical Abstract: Genomic analyses have the potential to impact aquaculture production traits by identifying markers as proxies for traits which are expensive or difficult to measure and characterizing genetic variation and biochemical mechanisms underlying phenotypic variation. One such set of traits are the responses of rainbow trout to stressors common to aquaculture production environments. Typical stressors can be categorized under handling and overcrowding, sub-optimal water quality parameters, and social interactions. These stressors may negatively impact growth, feed intake, feed efficiency, disease resistance, flesh quality, and reproductive performance. We employed genetic and functional genomic approaches towards identifying genes affecting stress response with the eventual goal of improving animal welfare and aquaculture production efficiency. A genetic study was conducted to identify QTL (quantitative trait locus) associated with stress response. Seven rainbow trout families (parents and offspring) from a single broodstock population were challenged with a 3 hour confinement stress and sampled to determine plasma cortisol concentration, a common measure for stress responsiveness in rainbow trout. A highly significant QTL explaining 40% of the phenotypic variance was detected on chromosome 16; additional suggestive QTL explaining 13-27% of the phenotypic variances were detected on chromosomes 6, 10, 12, 14, 19, 22 and sex. A third generation was similarly phenotyped and genotyped which enabled detection of significant QTL on chromosomes 9, 12 and 25 with additional suggestive QTL on chromosomes 6, 8, 13 and 15. These QTL each explained 9 to 25% of the phenotypic variance. Further validation and fine mapping these QTL may lead to the identification of genes affecting stress response and influence approaches to selection for this economically important stress response trait. A parallel functional genomic approach included employing RNA-seq, which is difficult in species for which a reference genome sequence is not available. We developed a two-step strategy that included generation of a stress reference transcriptome. Roche 454 pyrosequencing technology was used to sequence multiple tissues from fish challenged with a variety of individual stressors including high temperature (25C), low temperature (2C), high salinity (32‰), re-use water, handling/crowding and unchallenged control fish. Over 3 million reads were obtained from a pooled normalized library constructed from gill, brain, liver, spleen, kidney and muscle transcripts. These 454 sequences were assembled and annotated with Gene Ontology (GO) terms and used as a reference transcriptome. Equal amounts of total RNA extracted from livers of the fish used in the crowding challenge experiment were pooled by tank (3 treatments, 2 controls) to create 5 libraries (one per tank) which were sequenced in three runs on an Illumina HiSeq 2000. Analyses of 492 million reads have identified over 300 differentially expressed transcripts with a FDR =0.05.