Location: Cool and Cold Water Aquaculture ResearchTitle: Genome-wide association studies reveal similar genetic architecture with shared and unique QTL for Bacterial Cold Water Disease resistance in two rainbow trout (Oncorhynchus mykiss) 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: bioRxiv
Publication Type: Other
Publication Acceptance Date: 7/16/2017
Publication Date: 7/17/2017
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. Genome-wide association studies reveal similar genetic architecture with shared and unique QTL for Bacterial Cold Water Disease resistance in two rainbow trout (Oncorhynchus mykiss) breeding populations. bioRxiv. doi: 10.1101/163964.
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 (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.