Genome-wide association study and genomic prediction for resistance against Streptococcus agalactiae in hybrid red tilapia (Oreochromis spp.)

Sukhavachana, Sila, Tongyoo, Pumipat, Massault, Cecile, McMillan, Nichanun, Leungnaruemitchai, Amorn, and Poompuang, Supawadee (2020) Genome-wide association study and genomic prediction for resistance against Streptococcus agalactiae in hybrid red tilapia (Oreochromis spp.). Aquaculture, 525. 735297.

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Abstract

Streptococcosis is a major disease that causes severe mortality in tilapia aquaculture worldwide. Although the conventional BLUP family selection to enhance disease resistance in a commercial red tilapia stock was successful, the response was low due to the low heritability of the traits. An alternative strategy is the utilization of genomic information to identify the best performing candidates within families. In this study, we performed genome-wide association studies for red tilapia resistance to Streptococcus agalactiae using 11,480 SNPs within 110 families represented by 1020 fish. Nineteen SNP markers were found to explain similar to 10% of the genetic variation. We compared the accuracies of genomic prediction using the pedigree-based (PBLUP), marker-based (GBLUP), and Bayesian models. The prediction accuracy was assessed by performing ten replicates of five-fold cross-validation. In each replicate, approximately 80% of the data (n similar to 816) were sampled for the training set and the remaining data (n similar to 204) were used for the validation. The BayesB model yielded the highest accuracies (0.31 and 0.20) followed by GBLUP (0.25 and 0.15) and PBLUP (0.15 and 0.06) for days to death and binary trait.

Item ID: 63499
Item Type: Article (Research - C1)
ISSN: 1873-5622
Keywords: GWAS, GBLUP, BayesB, Genomic prediction, Hybrid red tilapia, Streptococcosis
Copyright Information: © 2020 Elsevier B.V. All rights reserved.
Funders: Kasetsart University Research and Development Institute (KURDI)
Projects and Grants: KURDI Sor-Khor (Por-Mor) 1.57
Date Deposited: 17 Jun 2020 07:47
FoR Codes: 07 AGRICULTURAL AND VETERINARY SCIENCES > 0704 Fisheries Sciences > 070401 Aquaculture @ 100%
SEO Codes: 83 ANIMAL PRODUCTION AND ANIMAL PRIMARY PRODUCTS > 8301 Fisheries - Aquaculture > 830102 Aquaculture Fin Fish (excl. Tuna) @ 100%
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