Location: Cool and Cold Water Aquaculture ResearchTitle: Genome-wide mapping of quantitative trait loci and accuracy of genomic selection for resistance to infectious hematopoietic necrosis virus in rainbow trout using multiple regression single-step methods
|CHENG, HAO - University Of California, Davis|
|FRAGOMENI, BRENO - University Of California, Davis|
|MACMILLAN, JOHN - University Of California, Davis|
|TOWNER, RICHARD - Gentec Consulting|
Submitted to: Gordon Research Conferences
Publication Type: Abstract Only
Publication Acceptance Date: 2/1/2019
Publication Date: 2/9/2019
Citation: Vallejo, R.L., Cheng, H., Fragomeni, B.O., Shewbridge, K., Gao, G., Macmillan, J.R., Towner, R., Palti, Y. 2019. Genome-wide mapping of quantitative trait loci and accuracy of genomic selection for resistance to infectious hematopoietic necrosis virus in rainbow trout using multiple regression single-step methods [abstract]. Gordon Research Conferences. P29107.
Technical Abstract: Infectious hematopoietic necrosis (IHN) is a disease of salmonid fish that is caused by the IHN virus (IHNV). Under commercial aquaculture conditions, IHNV can cause significant mortality and economic losses. At present, there is no proven and cost-effective method for IHNV control. Clear Springs Foods, Inc. has been applying selective breeding to improve genetic resistance to IHNV in their rainbow trout breeding program. The goals of this study were: (1) to elucidate the genetic architecture of IHNV resistance in this commercial population performing genome-wide association studies (GWAS) with multiple regression single-step methods, and (2) to assess if whole genome-enabled selection methods can improve the accuracy of genetic merit predictions over conventional pedigree-based best linear unbiased prediction (PBLUP) method using cross-validation analysis. A total of 10 moderate effect quantitative trait loci (QTL) associated with resistance to IHNV and jointly explaining up to 42% of the additive genetic variance were discovered in our GWAS. Only three of the 10 QTL were detected by both the single-step Bayesian multiple regression (ssBMR) and the weighted single-step GBLUP (wssGBLUP) methods. The accuracy of animal breeding value predictions with wssGBLUP (0.33-0.39) was substantially better than with PBLUP (0.13-0.24). Our comprehensive genome-wide scan for QTL associated with IHNV resistance revealed that genetic resistance to IHNV is controlled by the oligogenic inheritance of up to 10 moderate effect QTL and many small-effect loci in this commercial rainbow trout breeding population. Taken together, the results of this study suggest that whole genome-enabled selection methods will be more effective than the traditional pedigree-based PBLUP method or the marker-assisted selection approach for improving the genetic resistance of rainbow trout to IHNV in this commercial breeding population.