Genome-Wide Association and Genomic Selection for Resistance to Amoebic Gill Disease in Atlantic Salmon

Abstract

Amoebic gill disease (AGD) is one of the largest threats to salmon aquaculture, causing serious economic and animal welfare burden. Treatments can be expensive and environmentally damaging, hence the need for alternative strategies. Breeding for disease resistance can contribute to prevention and control of AGD, providing long-term cumulative benefits in selected stocks. The use of genomic selection can expedite selection for disease resistance due to improved accuracy compared to pedigree-based approaches. The aim of this work was to quantify and characterize genetic variation in AGD resistance in salmon, the genetic architecture of the trait, and the potential of genomic selection to contribute to disease control. An AGD challenge was performed in ∼1,500 Atlantic salmon, using gill damage and amoebic load as indicator traits for host resistance. Both traits are heritable (h2 ∼0.25-0.30) and show high positive correlation, indicating they may be good measurements of host resistance to AGD. While the genetic architecture of resistance appeared to be largely polygenic in nature, two regions on chromosome 18 showed suggestive association with both AGD resistance traits. Using a cross-validation approach, genomic prediction accuracy was up to 18% higher than that obtained using pedigree, and a reduction in marker density to ∼2,000 SNPs was sufficient to obtain accuracies similar to those obtained using the whole dataset. This study indicates that resistance to AGD is a suitable trait for genomic selection, and the addition of this trait to Atlantic salmon breeding programs can lead to more resistant stocks.

Potential of genomic selection for improvement of resistance to Ostreid Herpes virus in Pacific oyster (Crassostrea gigas)

“…The prediction accuracy values ranged from 0.678 to 0.758 for GBLUP (with SNP densities ranging from 500 to 18K), while PBLUP only reached an accuracy of 0.637. This result has been mirrored in other studies of genomic versus pedigree-based prediction of disease resistance breeding values for other important farmed fish species, e.g Atlantic salmon (Tsai et al 2015; Yoshida et al 2017; Ødegård et al 2014; Robledo et al 2018), rainbow trout (Vallejo et al 2017; Yoshida et al 2018), sea bream (Palaiokostas et al 2016) and sea bass (Palaiokostas et al 2018a). Further, in shellfish similar findings have been observed for prediction of breeding values for growth traits in scallop (Dou et al 2016) and Pacific oyster (Gutierrez et al 2018b).…”

“…Moreover, a high density linkage map containing ∼20K SNPs has recently been created and aligned with the physical reference genome assembly (Gutierrez et al 2018a; Zhang et al 2012). Using such arrays, several studies have demonstrated that genomic selection for aquaculture species results in improved accuracy compared to traditional pedigree-based approaches; for example in Atlantic salmon (Robledo et al 2018), coho salmon (Barría et al 2018), rainbow trout (Vallejo et al 2018), common carp (Palaiokostas et al 2018b), and Pacific oyster (Gutierrez et al 2018b).…”

Potential of genomic selection for improvement of resistance to ostreid herpesvirus in Pacific oyster (Crassostrea gigas)

“…This result has been mirrored in other studies of genomic vs. pedigree‐based prediction of disease resistance breeding values for other important farmed fish species, e.g. Atlantic salmon (Ødegård et al ; Tsai et al ; Yoshida et al ; Robledo et al ), rainbow trout (Vallejo et al ; Yoshida et al ), sea bream (Palaiokostas et al ) and sea bass (Palaiokostas et al ). Further, in shellfish similar findings have been observed for prediction of breeding values for growth traits in scallop (Dou et al ) and Pacific oyster (Gutierrez et al ).…”

“…Moreover, a high-density linkage map containing 20 000 SNPs has recently been created and aligned with the physical reference genome assembly (Zhang et al 2012;Gutierrez et al 2018a). Using such arrays, several studies have demonstrated that genomic selection for aquaculture species results in improved accuracy compared with traditional pedigree-based approaches; for example in Atlantic salmon (Robledo et al 2018), coho salmon (Barr ıa et al 2018), rainbow trout (Vallejo et al 2018), common carp (Palaiokostas et al 2018b) and Pacific oyster (Gutierrez et al 2018b).…”

Optimizing genomic prediction of host resistance to koi herpesvirus disease in carp

“…Genomic prediction models were applied using datasets of varying SNP density using either 157 MAF or linkage disequilibrium (LD) values as thresholds for filtering. In particular, to obtain 158 the reduced density SNP panels for genomic prediction, a strategy of retaining SNPs surpassing 159 a sequentially increased MAF threshold was applied, as described in Robledo et al (2018). Four different scenarios were tested for evaluating the impact of genetic relationships between 178 training and validation sets.…”