SUMMARY: Parasites have a major impact on global finfish and shellfish aquaculture, having significant effects on farm production, sustainability and economic viability. Parasite infections and impacts can, according to pathogen and context, be considered to be either unpredictable/sporadic or predictable/regular. Although both types of infection may result in the loss of stock and incur costs associated with the control and management of infection, predictable infections can also lead to costs associated with prophylaxis and related activities. The estimation of the economic cost of a parasite event is frequently complicated by the complex interplay of numerous factors associated with a specific incident, which may range from direct production losses to downstream socio-economic impacts on livelihoods and satellite industries associated with the primary producer. In this study, we examine the world's major marine and brackish water aquaculture production industries and provide estimates of the potential economic costs attributable to a range of key parasite pathogens using 498 specific events for the purposes of illustration and estimation of costs. This study provides a baseline resource for risk assessment and the development of more robust biosecurity practices, which can in turn help mitigate against and/or minimise the potential impacts of parasite-mediated disease in aquaculture.

Dense single nucleotide polymorphism (SNP) genotyping arrays provide extensive information on polymorphic variation across the genome of species of interest. Such information can be used in studies of the genetic architecture of quantitative traits and to improve the accuracy of selection in breeding programs. In Atlantic salmon (Salmo salar), these goals are currently hampered by the lack of a high-density SNP genotyping platform. Therefore, the aim of the study was to develop and test a dense Atlantic salmon SNP array.

Each year the salmon louse ( Lepeophtheirus salmonis Krøyer, 1838) causes multi-million dollar commercial losses to the salmon farming industry world-wide, and strict lice control regimes have been put in place to reduce the release of salmon louse larvae from aquaculture facilities into the environment. For half a century, the Lepeophtheirus life cycle has been regarded as the only copepod life cycle including 8 post-nauplius instars as confirmed in four different species, including L. salmonis. Here we prove that the accepted life cycle of the salmon louse is wrong. By observations of chalimus larvae molting in incubators and by morphometric cluster analysis, we show that there are only two chalimus instars: chalimus 1 (comprising the former chalimus I and II stages which are not separated by a molt) and chalimus 2 (the former chalimus III and IV stages which are not separated by a molt). Consequently the salmon louse life cycle has only six post-nauplius instars, as in other genera of caligid sea lice and copepods in general. These findings are of fundamental importance in experimental studies as well as for interpretation of salmon louse biology and for control and management of this economically important parasite.

Sea lice have significant negative economic and welfare impacts on marine Atlantic salmon farming. Since host resistance to sea lice has a substantial genetic component, selective breeding can contribute to control of lice. Genomic selection uses genome-wide marker information to predict breeding values, and can achieve markedly higher accuracy than pedigree-based methods. Our aim was to assess the genetic architecture of host resistance to sea lice, and test the utility of genomic prediction of breeding values. Individual lice counts were measured in challenge experiments using two large Atlantic salmon post-smolt populations from a commercial breeding programme, which had genotypes for ~33 K single nucleotide polymorphisms (SNPs). The specific objectives were to: (i) estimate the heritability of host resistance; (ii) assess its genetic architecture by performing a genome-wide association study (GWAS); (iii) assess the accuracy of predicted breeding values using varying SNP densities (0.5 to 33 K) and compare it to that of pedigree-based prediction; and (iv) evaluate the accuracy of prediction in closely and distantly related animals. Heritability of host resistance was significant (0.22 to 0.33) in both populations using either pedigree or genomic relationship matrices. The GWAS suggested that lice resistance is a polygenic trait, and no genome-wide significant quantitative trait loci were identified. Based on cross-validation analysis, genomic predictions were more accurate than pedigree-based predictions for both populations. Although prediction accuracies were highest when closely-related animals were used in the training and validation sets, the benefit of having genomic-versus pedigree-based predictions within a population increased as the relationships between training and validation sets decreased. Prediction accuracy reached an asymptote with a SNP density of ~5 K within populations, although higher SNP density was advantageous for cross-population prediction. Host resistance to sea lice in farmed Atlantic salmon has a significant genetic component. Phenotypes relating to host resistance can be predicted with moderate to high accuracy within populations, with a major advantage of genomic over pedigree-based methods, even at relatively sparse SNP densities. Prediction accuracies across populations were low, but improved with higher marker densities. Genomic selection can contribute to lice control in salmon farming.