Location: Cool and Cold Water Aquaculture ResearchTitle: Genomic predictions for fillet yield and firmness in rainbow trout using reduced-density SNP panels
|AL-TOBASEI, RAFET - Middle Tennessee State University|
|ALI, ALI - University Of Maryland|
|GARCIA, ANDRE - University Of Georgia|
|LOURENCO, DANIELA - University Of Georgia|
|Leeds, Timothy - Tim|
|SALEM, MOHAMED - University Of Maryland|
Submitted to: BMC Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/22/2021
Publication Date: 1/30/2021
Citation: Al-Tobasei, R., Ali, A., Garcia, A.L., Lourenco, D., Leeds, T.D., Salem, M. 2021. Genomic predictions for fillet yield and firmness in rainbow trout using reduced-density SNP panels. BMC Genomics. 22:92. https://doi.org/10.1186/s12864-021-07404-9.
Interpretive Summary: Fillet yield and quality are economically-important traits for rainbow trout producers. Compared to traditional selective breeding approaches to improve these traits, the use of genomic selection - where an animal's breeding value is estimated by genotyping thousands or tens of thousands of DNA markers - has been shown to improve the accuracy of estimated breeding values and thus is expected to improve the rate by which these traits can be improved through selective breeding. However, the current cost of genotyping individual animals for several thousands of DNA markers may be impractical for some producers. This study evaluated the accuracy of genomic selection strategies for fillet yield and quality using as many as 35,000 DNA markers to less than 200 DNA markers in a resource rainbow trout population developed by ARS scientists. The use of as few as 500-800 DNA markers resulted in estimated breeding values that had similar, or better, accuracy compared to those estimated using a traditional selective breeding approach. This study identifies effective genomic selection strategies that can be implemented while reducing the costs associated with genotyping.
Technical Abstract: One of the most important goals for the rainbow trout aquaculture industry is to improve muscle yield and fillet quality. Previously, we showed that a 50K transcribed-SNP chip can be used to detect quantitative trait loci (QTL) associated with muscle yield and fillet firmness. In this study, data from 1,568 fish genotyped for the 50K transcribed-SNP chip and approximately 774 fish phenotyped for muscle yield and fillet firmness were used in a single-step genomic BLUP (ssGBLUP) model to compute the genomic estimated breeding values (GEBV). In addition, pedigree-based best linear unbiased prediction (PBLUP) was used to calculate traditional, family-based estimated breeding values (EBV). The genomic predictions outperformed the traditional EBV by 35 percent for muscle yield and 42 percent for fillet firmness. The predictive ability for muscle yield and fillet firmness was 0.19 - 0.20 with PBLUP, and 0.27 with ssGBLUP. Additionally, reducing SNP panel densities indicated that using 500 - 800 SNPs in genomic predictions still provides predictive abilities higher than PBLUP. These results suggest that genomic evaluation is a feasible strategy to identify and select fish with superior genetic merit within rainbow trout families, even with low-density SNP panels.