Location: Cool and Cold Water Aquaculture ResearchTitle: Similar genetic architecture with shared and unique quantitative trait loci for bacterial cold water disease resistance in two rainbow trout breeding populations
|FRAGOMENI, BRENO - University Of Georgia|
|HERNANDEZ, ALVARO - University Of Illinois|
|Leeds, Timothy - Tim|
|PARSONS, JAMES - Troutlodge, Inc|
|MARTIN, KYLE - Troutlodge, Inc|
|Welch, Timothy - Tim|
|Wiens, Gregory - Greg|
Submitted to: Frontiers in Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/4/2017
Publication Date: 10/23/2017
Publication URL: https://handle.nal.usda.gov/10113/5859841
Citation: Vallejo, R.L., Liu, S., Gao, G., Fragomeni, B.O., Hernandez, A.G., Leeds, T.D., Parsons, J.E., Martin, K.E., Evenhuis, J., Welch, T.J., Wiens, G.D., Palti, Y. 2017. Similar genetic architecture with shared and unique quantitative trait loci for bacterial cold water disease resistance in two rainbow trout breeding populations. Frontiers in Genetics. 8:156. https://doi.org/10.3389/fgene.2017.00156.
Interpretive Summary: Using genome-enabled approaches for selective breeding for traits that cannot be measured directly in potential breeders, like disease resistance, holds great promise as it provides individual genetic merit estimates for potential breeders compared to family-average estimates in traditional selective breeding. Previously we have shown that bacterial cold water disease (BCWD) resistance in rainbow trout can be improved using traditional family-based selection, but progress has been limited to exploiting only between-family genetic variation. We then evaluated whole-genome enabled selection for BCWD resistance in a commercial rainbow trout population, and found that whole-genome selection can substantially improve the genetic gain. In the current study we conducted whole genome association studies and identified the major chromosome regions harboring genes that affect BCWD resistance in two important rainbow trout populations. Although some of the largest-effect chromosome regions were shared between the two populations, we also detected major differences in the impact of other regions. The results of this study will enable us to develop more cost-effective genome-enabled approaches for improving resistance to BCWD in rainbow trout aquaculture, but they also show that some of the genes involved in resistance to this disease may vary between breeding populations. This means that those new and more cost-effective genome-based methods for improved disease resistance will have to be tested and refined for breeding populations that were not included in this study. In addition, the results of this study can be used to further investigate the causative genes affecting BCWD resistance or susceptibility in rainbow trout, which is important for better understanding of the fish immune system and can lead to further improvement of disease prevention and treatment methods in the aquaculture industry.
Technical Abstract: Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect QTL for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57K SNP array and a genome physical map have enabled us to conduct genome-wide association studies (GWAS) that overcome several experimental limitations from our previous work. In the current study, we conducted GWAS for BCWD resistance in two rainbow trout breeding populations using two genotyping platforms, the 57K Affymetrix SNP array and restriction-associated DNA (RAD) sequencing. Overall, we identified 14 moderate-large effect QTL that explained up to 60.8% of the genetic variance in one of the two populations and 27.7% in the other. Four of these QTL were found in both populations explaining a substantial proportion of the variance, although major differences were also detected between the two populations. Our results confirm that BCWD resistance is controlled by the oligogenic inheritance of few moderate-large effect loci and a large-unknown number of loci each having a small effect on BCWD resistance. We detected differences in QTL number and genome location between two GWAS models (weighted single-step GBLUP and Bayes B), which highlights the utility of using different models to uncover QTL. The RAD-SNPs detected a greater number of QTL than the 57K SNP array in one population, suggesting that the RAD-SNPs may uncover polymorphisms that are more unique and informative for the specific population in which they were discovered.