Genome-wide association and genomic prediction of resistance to Flavobacterium columnare in a farmed rainbow trout population

Abstract

Columnaris disease is an emerging disease affecting farmed rainbow trout (Oncorhynchus mykiss) globally. In aquaculture breeding, genomic selection has been increasingly used to improve traits that are difficult to measure on candidate fish (such as disease resistance traits). Following a natural outbreak of columnaris disease, 3,054 exposed fish and their 81 parents (33 dams and 48 sires) were genotyped with the 57K SNP Axiom ™ trout genotyping array. Genetic parameters of host resistance (measured as a binary survival trait) were estimated, a genome wide association study was performed, and the accuracy of pedigree-based and genomic prediction was estimated. After quality controls, 2,874 challenged fish (1,403 dead fish and 1,471 alive fish) and 78 parents genotyped for 27,907 SNPs remained. Pedigree based heritability was estimated to be 0.18 and 0.35 on the observed and underlying scale, respectively. Genomic heritability was estimated to be 0.21 and 0.43 on the observed and underlying scale, respectively. A quantitative trait loci (QTL) was detected on chromosome Omy3, significant at the genome-wide level, along with several suggestive QTLs on two other chromosomes. The additive effect on mortality proportion of the peak SNP from Omy3 was estimated to be 0.11 (0.018; se). Pedigree-based prediction accuracy was 0.59, and the use of genomic evaluation increased the prediction accuracy by at least 13.6%. Using the second iteration of a weighted genomic-based evaluation increased the prediction accuracy by 18.6% compared to the pedigree-based model. These results suggest that resistance is a suitable target trait for genetic improvement by selective breeding, and genomic selection may be a useful approach to speed up this process.

Insight into selective breeding for robustness based on field survival records: New genetic evaluation of survival traits in pacific white shrimp (Penaeus vannamei) breeding line

“…Moreover, survival data recorded from commercial lines when special events arise e.g., disease outbreaks can also be applied effectively to developing disease resistant strains, and these type of data are also valuable for avoiding potential G-by-E effects compared with survival data from controlled (artificial) challenge experiments (Bangera et al, 2014;Dégremont et al, 2015;Barría et al, 2020;Fraslin et al, 2022). Additionally, despite of low heritability of survival traits at the early grow-out testing stage, routine genetic evaluation of survival data in breeding lines provides a vital assessment of the relative health status of a stock under the general husbandry management practices employed in the breeding lines.…”

“…Currently, disease resistance strains have been developed successfully via this approach for a number of aquatic species, including farmed salmonid species (Correa et al, 2015;Vallejo et al, 2017;Barría et al, 2019), Pacific oyster (Gutierrez et al, 2018), and European sea bass (Palaiokostas et al, 2018). A second approach is to use selection based on survival data records in the field and this can provide another important data source for selecting robustness by improving overall individual survival rate (Gjedrem and Rye, 2018) and for developing specific disease resistance strains (Barría et al, 2020;Fraslin et al, 2022). This approach allows direct collection of data under real commercial farm conditions, and thereby avoids potential for genotype-by-environment (G-by-E) problems as seen in controlled challenge experiments between challenge test environments and production conditions on farm.…”