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ARS Home » Northeast Area » Leetown, West Virginia » Cool and Cold Water Aquaculture Research » Research » Publications at this Location » Publication #359267

Research Project: Integrated Research Approaches for Improving Production Efficiency in Salmonids

Location: Cool and Cold Water Aquaculture Research

Title: Genome-wide association analysis and accuracy of genome-enabled breeding value predictions for resistance to infectious hematopoietic necrosis virus in a commercial rainbow trout breeding population

Author
item Palti, Yniv
item Vallejo, Roger
item CHENG, HAO - University Of California, Davis
item FRAGOMENI, BRENO - University Of Connecticut
item Gao, Guangtu
item MACMILLAN, RANDY - Clear Springs Foods, Inc
item TOWNER, RICHARD - Gentec Consulting

Submitted to: Plant and Animal Genome Conference
Publication Type: Abstract Only
Publication Acceptance Date: 11/23/2018
Publication Date: 1/12/2019
Citation: Palti, Y., Vallejo, R.L., Cheng, H., Fragomeni, B., Gao, G., Macmillan, R., Towner, R. 2019. Genome-wide association analysis and accuracy of genome-enabled breeding value predictions for resistance to infectious hematopoietic necrosis virus in a commercial rainbow trout breeding population [abstract]. Plant and Animal Genome Conference. P1-298.

Interpretive Summary:

Technical Abstract: Infectious hematopoietic necrosis (IHN) is a disease of salmonids caused by the IHN virus (IHNV). Under intensive aquaculture conditions, IHNV can cause mass mortality and significant economic losses. Clear Springs Food, Inc. has been applying selective breeding to improve genetic resistance to IHNV in their rainbow trout breeding program. The goals of this study were to elucidate the genetic architecture of IHNV resistance in this commercial population using genome wide association (GWA) analyses with multiple regression single-step methods and to assess if genomic selection can improve the accuracy of genetic merit predictions over the conventional pedigree-based BLUP (PBLUP) using cross-validation analysis. A total of 10 moderate effect QTL associated with resistance to IHNV which jointly explained up to 42% of the additive genetic variance were detected in our GWA analyses. 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 breeding value predictions with wssGBLUP (0.33-0.39) was substantially better than with PBLUP (0.13-0.24). Our genome-wide scan for QTL associated with IHNV resistance revealed that the 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 genome-enabled selection models will be more effective than the traditional PBLUP method or the marker assisted selection approach for improving genetic resistance to IHNV infection in this commercial breeding population.