Swimming at Increasing Speeds in Steady and Unsteady Flows of Atlantic Salmon Salmo salar: Oxygen Consumption, Locomotory Behaviour and Overall Dynamic Body Acceleration.

The swimming performance of cultured finfish species is typically studied under steady flow conditions. However, flow conditions are mostly unsteady, for instance, as experienced in sea pens in exposed sea areas. Using a Loligo swim tunnel, we investigated the effects of swimming in steady and unsteady flows at increasing swimming speeds on post-smolt Atlantic salmon. Oxygen consumption (MO2), locomotory behaviour, and overall dynamic body acceleration (ODBA), as determined with implanted acoustic sensor tags, were compared between both flow conditions. Results were obtained for mean swimming speeds of 0.2 to 0.8 m.s-1 under both flow conditions. Sensor tags that were implanted in the abdominal cavity had no significant effects on MO2 and locomotory parameters. The MO2 of fish swimming in unsteady flows was significantly higher (15-53%) than when swimming in steady flows (p < 0.05). Significant interaction effects of ODBA with flow conditions and swimming speed were found. ODBA was strongly and positively correlated with swimming speed and MO2 in unsteady flow (R2 = 0.94 and R2 = 0.93, respectively) and in steady flow (R2 = 0.91 and R2 = 0.82, respectively). ODBA predicts MO2 well over the investigated range of swimming speeds in both flow conditions. In an unsteady flow condition, ODBA increased twice as fast with MO2 compared with steady flow conditions (p < 0.05). From these results, we can conclude that (1) swimming in unsteady flow is energetically more costly for post-smolt Atlantic salmon than swimming in steady flow, as indicated by higher MO2, and (2) ODBA can be used to estimate the oxygen consumption of post-smolt Atlantic salmon in unsteady flow in swim tunnels.

Landscape genomics reveals regions associated with adaptive phenotypic and genetic variation in Ethiopian indigenous chickens.

Climate change is a threat to sustainable livestock production and livelihoods in the tropics. It has adverse impacts on feed and water availability, disease prevalence, production, environmental temperature, and biodiversity. Unravelling the drivers of local adaptation and understanding the underlying genetic variation in random mating indigenous livestock populations informs the design of genetic improvement programmes that aim to increase productivity and resilience. In the present study, we combined environmental, genomic, and phenotypic information of Ethiopian indigenous chickens to investigate their environmental adaptability. Through a hybrid sampling strategy, we captured wide biological and ecological variabilities across the country. Our environmental dataset comprised mean values of 34 climatic, vegetation and soil variables collected over a thirty-year period for 260 geolocations. Our biological dataset included whole genome sequences and quantitative measurements (on eight traits) from 513 individuals, representing 26 chicken populations spread along 4 elevational gradients (6-7 populations per gradient). We performed signatures of selection analyses ([Formula: see text] and XP-EHH) to detect footprints of natural selection, and redundancy analyses (RDA) to determine genotype-environment and genotype-phenotype-associations. RDA identified 1909 outlier SNPs linked with six environmental predictors, which have the highest contributions as ecological drivers of adaptive phenotypic variation. The same method detected 2430 outlier SNPs that are associated with five traits. A large overlap has been observed between signatures of selection identified by[Formula: see text]and XP-EHH showing that both methods target similar selective sweep regions. Average genetic differences measured by [Formula: see text] are low between gradients, but XP-EHH signals are the strongest between agroecologies. Genes in the calcium signalling pathway, those associated with the hypoxia-inducible factor (HIF) transcription factors, and sports performance (GALNTL6) are under selection in high-altitude populations. Our study underscores the relevance of landscape genomics as a powerful interdisciplinary approach to dissect adaptive phenotypic and genetic variation in random mating indigenous livestock populations.

Genotype by Environment Interactions (G*E) of Chickens Tested in Ethiopia Using Body Weight as a Performance Trait.

Ethiopia is a developing nation that could highly benefit from securing food via improved smallholder poultry farming. To support farmer and breeding decisions regarding which chicken strain to use in which Ethiopian environment, G*E analyses for body weight (BW) of growing male and female chickens were conducted. Research questions were (1) if a G*E is present for BW and (2) which strain performs best in which environment in terms of predicted BW. Analyses were performed using predicted BW at four different ages (90, 120, 150, and 180 days) of five strains (Horro, Koekoek, Kuroiler, Sasso-Rhode Island Red (S-RIR), and Sasso) tested in five Ethiopian regions (Addis Ababa, Amhara, Oromia, South Region, and Tigray) that are part of three Agro-Ecological Zones (AEZ) (cool humid, cool sub-humid, and warm semi-arid). The indigenous Horro strain was used as a control group to compare four other introduced tropically adapted strains. The dataset consisted of 999 female and 989 male farm-average BW measurements. G*E was strongly present (p < 0.001) for all combinations of strain and region analyzed. In line with previous research, Sasso was shown to have the highest predicted BW, especially at an early age, followed by Kuroiler. Horro had the lowest predicted BW at most ages and in most regions, potentially due to its young breeding program. The highest predicted BW were observed in Tigray, Oromia, and Amhara regions, which are in the main part of the cool sub-humid AEZ.

The induction of oocyte maturation and ovulation in the European eel (Anguilla anguilla): in vitro and in vivo comparison of progesterone with 17α,20ß-dihydroxy-4-pregnen-3-one.

Ovulation in European eel is induced by injection of 17α,20ß-dihydroxy-4-pregnen-3-one (DHP) as the maturation-inducing hormone (MIH). Female eels need to ovulate within 18 h after injection to release good quality eggs. Progesterone (P), as an upstream precursor of DHP, may promote endogenous DHP production and improve egg quality. The purpose of this study was therefore to compare treatment of P with DHP on batch level, in vitro, to determine dose-response effects, and in vivo, at a single dose. For the in vitro experiment, ovarian tissue was extracted and placed in culture plates containing hormone-free medium and media supplemented with the treatment: DHP at 1, 10 and 100 ng mL-1, or P at 10, 100 and 1,000 ng mL-1. At the start of incubation, the folliculated oocytes were sampled for histology, microscopy and qPCR. After incubation for 12 and 18 h, the oocytes were sampled for microscopy and qPCR analysis. For the in vivo experiment, females were either injected with DHP or P at a dose of 2 mg kg-1 to assess their effects on ovulation and reproductive success. At the moment of release, eggs were sampled for RNA sequencing to compare effects of DHP and P on the expression of genes involved in egg quality aspects. Remaining eggs were fertilized and larval viability was recorded. Both DHP and P were able to induce GVBD (DHP at 10 and 100 ng mL-1, P at 100 and 1,000 ng mL-1) in vitro. Expression of genes involved in oocyte maturation and ovulation was similar in vitro for both DHP and P treatments. Regarding the in vivo results, RNAseq results reflected similar DHP and P effects on the expression of genes involved in egg quality aspects. Females injected with either DHP or P ovulated, released eggs, and were equally able to produce larvae without any differences in reproductive success. Our results support the conclusion that DHP and P work equally well in vitro and in vivo. P is more attractive to apply as the price is 3,000 times lower than the price of DHP.

Species and Phenotypic Distribution Models Reveal Population Differentiation in Ethiopian Indigenous Chickens.

Smallholder poultry production dominated by indigenous chickens is an important source of livelihoods for most rural households in Ethiopia. The long history of domestication and the presence of diverse agroecologies in Ethiopia create unique opportunities to study the effect of environmental selective pressures. Species distribution models (SDMs) and Phenotypic distribution models (PDMs) can be applied to investigate the relationship between environmental variation and phenotypic differentiation in wild animals and domestic populations. In the present study we used SDMs and PDMs to detect environmental variables related with habitat suitability and phenotypic differentiation among nondescript Ethiopian indigenous chicken populations. 34 environmental variables (climatic, soil, and vegetation) and 19 quantitative traits were analyzed for 513 adult chickens from 26 populations. To have high variation in the dataset for phenotypic and ecological parameters, animals were sampled from four spatial gradients (each represented by six to seven populations), located in different climatic zones and geographies. Three different ecotypes are proposed based on correlation test between habitat suitability maps and phenotypic clustering of sample populations. These specific ecotypes show phenotypic differentiation, likely in response to environmental selective pressures. Nine environmental variables with the highest contribution to habitat suitability are identified. The relationship between quantitative traits and a few of the environmental variables associated with habitat suitability is non-linear. Our results highlight the benefits of integrating species and phenotypic distribution modeling approaches in characterization of livestock populations, delineation of suitable habitats for specific breeds, and understanding of the relationship between ecological variables and quantitative traits, and underlying evolutionary processes.

What Goes Wrong during Early Development of Artificially Reproduced European Eel Anguilla anguilla? Clues from the Larval Transcriptome and Gene Expression Patterns.

In eels, large variations in larval mortality exist, which would impede the viable production of juvenile glass eels in captivity. The transcriptome of European eel larvae was investigated to identify physiological pathways and genes that show differential regulation between non-viable vs. viable larvae. Expression of genes involved in inflammation and host protection was higher, suggesting that non-viable larvae suffered from microbial infection. Expression of genes involved in osmoregulation was also higher, implying that non-viable larvae tried to maintain homeostasis by strong osmoregulatory adaptation. Expression of genes involved in myogenesis, neural, and sensory development was reduced in the non-viable larvae. Expression of the major histocompatibility complex class-I (mhc1) gene, M-protein (myom2), the dopamine 2B receptor (d2br), the melatonin receptor (mtr1), and heat-shock protein beta-1 (hspb1) showed strong differential regulation and was therefore studied in 1, 8, and 15 days post-hatch (dph) larvae by RT-PCR to comprehend the roles of these genes during ontogeny. Expression patterning of these genes indicated the start of active swimming (8 dph) and feed searching behavior (15 dph) and confirmed immunocompetence immediately after hatching. This study revealed useful insights for improving larval survival by microbial control and salinity reduction.

Genome-wide association analysis of adaptation to oxygen stress in Nile tilapia (Oreochromis niloticus).

BACKGROUND: Tilapia is one of the most abundant species in aquaculture. Hypoxia is known to depress growth rate, but the genetic mechanism by which this occurs is unknown. In this study, two groups consisting of 3140 fish that were raised in either aerated (normoxia) or non-aerated pond (nocturnal hypoxia). During grow out, fish were sampled five times to determine individual body weight (BW) gains. We applied a genome-wide association study to identify SNPs and genes associated with the hypoxic and normoxic environments in the 16th generation of a Genetically Improved Farmed Tilapia population. RESULTS: In the hypoxic environment, 36 SNPs associated with at least one of the five body weight measurements (BW1 till BW5), of which six, located between 19.48 Mb and 21.04 Mb on Linkage group (LG) 8, were significant for body weight in the early growth stage (BW1 to BW2). Further significant associations were found for BW in the later growth stage (BW3 to BW5), located on LG1 and LG8. Analysis of genes within the candidate genomic region suggested that MAPK and VEGF signalling were significantly involved in the later growth stage under the hypoxic environment. Well-known hypoxia-regulated genes such as igf1rb, rora, efna3 and aurk were also associated with growth in the later stage in the hypoxic environment. Conversely, 13 linkage groups containing 29 unique significant and suggestive SNPs were found across the whole growth period under the normoxic environment. A meta-analysis showed that 33 SNPs were significantly associated with BW across the two environments, indicating a shared effect independent of hypoxic or normoxic environment. Functional pathways were involved in nervous system development and organ growth in the early stage, and oocyte maturation in the later stage. CONCLUSIONS: There are clear genotype-growth associations in both normoxic and hypoxic environments, although genome architecture involved changed over the growing period, indicating a transition in metabolism along the way. The involvement of pathways important in hypoxia especially at the later growth stage indicates a genotype-by-environment interaction, in which MAPK and VEGF signalling are important components.

Heritable variation in swimming performance in Nile tilapia (Oreochromis niloticus) and negative genetic correlations with growth and harvest weight.

Nile tilapia is predominantly produced in smallholder ponds without aeration. We hypothesize that Nile tilapia with high oxygen uptake efficiency (O2UE) may perform better under these conditions than Nile tilapia with low O2UE. Critical swimming speed (Ucrit, in cm s-1) is a potential indicator for O2UE. Our objectives were to estimate variance components for Ucrit and fish size at swim testing early in life, and genetic correlations (rg) between Ucrit with harvest weight (HW) and daily growth coefficient (DGC) later after grow-out in a non-aerated pond. Substantial heritability was found for absolute Ucrit (0.48). The estimated rg between absolute Ucrit and fish size at testing were all strong and positive (range 0.72-0.83). The estimated rg between absolute Ucrit and HW, and absolute Ucrit and DGC were - 0.21 and - 0.63 respectively, indicating that fish with higher absolute Ucrit had lower growth in the non-aerated pond as compared to fish with lower absolute Ucrit. These results suggest a juvenile trade-off between swimming and growth performance where fish with high Ucrit early in life show slower growth later under conditions of limited oxygen availability. We conclude that Ucrit in Nile tilapia is heritable and can be used to predict growth performance.

Swimming Performance and Oxygen Consumption as Non-lethal Indicators of Production Traits in Atlantic Salmon and Gilthead Seabream.

The aim of this study was to investigate swimming performance and oxygen consumption as non-lethal indicator traits of production parameters in Atlantic salmon Salmo salar L. and Gilthead seabream Sparus aurata L. A total of 34 individual fish of each species were subjected to a series of experiments: (1) a critical swimming speed (Ucrit) test in a swim-gutter, followed by (2) two starvation-refeeding periods of 42 days, and (3) swimming performance experiments coupled to respirometry in swim-tunnels. Ucrit was assessed first to test it as a predictor trait. Starvation-refeeding traits included body weight; feed conversion ratio based on dry matter; residual feed intake; average daily weight gain and loss. Swim-tunnel respirometry provided oxygen consumption in rest and while swimming at the different speeds, optimal swim speed and minimal cost of transport (COT). After experiments, fish were dissected and measured for tissue weights and body composition in terms of dry matter, ash, fat, protein and moist, and energy content. The Ucrit test design was able to provide individual Ucrit values in high throughput manner. The residual Ucrit (RUcrit) should be considered in order to remove the size dependency of swimming performance. Most importantly, RUcrit predicted filet yield in both species. The minimal COT, the oxygen consumption when swimming at Uopt, added predictive value to the seabream model for feed intake.

Optimizing design to estimate genetic correlations between environments with common environmental effects.

Breeding programs for different species aim to improve performance by testing members of full-sib (FS) and half-sib (HS) families in different environments. When genotypes respond differently to changes in the environment, this is defined as genotype by environment (G × E) interaction. The presence of common environmental effects within families generates covariance between siblings, and these effects should be taken into account when estimating a genetic correlation. Therefore, an optimal design should be established to accurately estimate the genetic correlation between environments in the presence of common environmental effects. We used stochastic simulation to find the optimal population structure using a combination of FS and HS groups with different levels of common environmental effects. Results show that in a population with a constant population size of 2,000 individuals per environment, ignoring common environmental effects when they are present in the population will lead to an upward bias in the estimated genetic correlation of on average 0.3 when the true genetic correlation is 0.5. When no common environmental effects are present in the population, the lowest standard error (SE) of the estimated genetic correlation was observed with a mating ratio of one dam per sire, and 10 offspring per sire per environment. When common environmental effects are present in the population and are included in the model, the lowest SE is obtained with mating ratios of at least 5 dams per sire and with a minimum number of 10 offspring per sire per environment. We recommend that studies that aim to estimate the magnitude of G × E in pigs, chicken, and fish should acknowledge the potential presence of common environmental effects and adjust the mating ratio accordingly.

The genetic correlation between feed conversion ratio and growth rate affects the design of a breeding program for more sustainable fish production.

BACKGROUND: Most fish breeding programs aim at improving growth rate and include feed conversion ratio (FCR) neither in the breeding goal nor in the selection index, although decreasing FCR is known to increase farm profit and decrease environmental impacts. This is because FCR is difficult to measure in fish that live in groups and FCR is assumed to have a favourable (negative) genetic correlation with growth, although the magnitude of this correlation is unknown. We investigated the effect of the genetic correlation between growth and FCR on the economic and environmental responses of a two-trait breeding goal (growth and FCR), compared to a single-trait breeding goal (growth only). Next, we evaluated the weights to assign to growth and FCR in a two-trait breeding goal to maximize sustainability of fish production. METHODS: We used pseudo-best linear unbiased prediction (BLUP) index calculations to simulate a breeding program for sea bass. For the single-trait breeding goal, the trait in the breeding goal and in the index was thermal growth coefficient (TGC) and for the two-trait breeding goal, the traits in the breeding goal were TGC and FCR and the traits in the index were TGC and percentage of fat in the dorsal muscle (an indirect measure of FCR). We simulated responses to selection for genetic and phenotypic correlations between TGC and FCR ranging from 0 to - 0.8. Then, in the two-trait breeding goal, we calculated the economic return and the change in eutrophication when using economic values (EV) or environmental values (ENV). RESULTS: When the genetic correlation between TGC and FCR was lower than - 0.45, we found major differences in economic returns and in eutrophication between single and two-trait breeding programs. At a correlation of - 0.25, the two-trait breeding goal based on EV increased economic return by 25% compared to the single-trait breeding goal, while using ENV decreased eutrophication by 1.34% per ton of fish produced after one generation of selection. CONCLUSIONS: The genetic correlation between TGC and FCR affects the magnitude of economic losses due to omitting FCR in the breeding program. In addition, the genetic correlation affects the importance of choosing EV or ENV to reduce eutrophication and increase profit.

Chronic simultaneous exposure of common carp (Cyprinus carpio) from embryonic to juvenile stage to drospirenone and gestodene at low ng/L level caused intersex.

Synthetic progestins are emerging contaminants of the aquatic environment with endocrine disrupting potential. The main aim of the present study was to investigate the effects of the synthetic progestins gestodene, and drospirenone on sex differentiation in common carp (Cyprinus carpio) by histological analysis. To gain insights into the mechanisms behind the observations from the in vivo experiment on sex differentiation, we analyzed expression of genes involved in hypothalamus-pituitary-gonad (HPG) and hypothalamus-pituitary-thyroid (HPT) axes, histology of hepatopancreas, and in vitro bioassays. Carp were continuously exposed to concentrations of 2 ng/L of single progestins (gestodene or drospirenone) or to their mixture at concentration 2 ng/L of each. The exposure started 24 h after fertilization of eggs and concluded 160 days post-hatching. Our results showed that exposure of common carp to a binary mixture of drospirenone and gestodene caused increased incidence of intersex (32%) when compared to clean water and solvent control groups (both 3%). Intersex most probably was induced by a combination of multiple modes of action of the studied substances, namely anti-gonadotropic activity, interference with androgen receptor, and potentially also with HPT axis or estrogen receptor.

Optimized grouping to increase accuracy of prediction of breeding values based on group records in genomic selection breeding programs.

BACKGROUND: Phenotypic records of group means or group sums are a good alternative to individual records for some difficult to measure, but economically important traits such as feed efficiency or egg production. Accuracy of predicted breeding values based on group records increases with increasing relationships between group members. The classical way to form groups with more closely-related animals is based on pedigree information. When genotyping information is available before phenotyping, its use to form groups may further increase the accuracy of prediction from group records. This study analyzed two grouping methods based on genomic information: (1) unsupervised clustering implemented in the STRUCTURE software and (2) supervised clustering that models genomic relationships. RESULTS: Using genomic best linear unbiased prediction (GBLUP) models, estimates of the genetic variance based on group records were consistent with those based on individual records. When genomic information was available to constitute the groups, genomic relationship coefficients between group members were higher than when random grouping of paternal half-sibs and of full-sibs was applied. Grouping methods that are based on genomic information resulted in higher accuracy of genomic estimated breeding values (GEBV) prediction compared to random grouping. The increase was ~ 1.5% for full-sibs and ~ 11.5% for paternal half-sibs. In addition, grouping methods that are based on genomic information led to lower coancestry coefficients between the top animals ranked by GEBV. Of the two proposed methods, supervised clustering was superior in terms of accuracy, computation requirements and applicability. By adding surplus genotyped offspring (more genotyped offspring than required to fill the groups), the advantage of supervised clustering increased by up to 4.5% compared to random grouping of full-sibs, and by 14.7% compared to random grouping of paternal half-sibs. This advantage also increased with increasing family sizes or decreasing genome sizes. CONCLUSIONS: The use of genotyping information for grouping animals increases the accuracy of selection when phenotypic group records are used in genomic selection breeding programs.

Economic optimization of full-sib test group size and genotyping effort in a breeding program for Atlantic salmon.

BACKGROUND: Breeding companies may want to maximize the rate of genetic gain from their breeding program within a limited budget. In salmon breeding programs, full-sibs of selection candidates are subjected to performance tests for traits that cannot be recorded on selection candidates. While marginal gains in the aggregate genotype from phenotyping and genotyping more full-sibs per candidate decrease, costs increase linearly, which suggests that there is an optimum in the allocation of the budget among these activities. Here, we studied how allocation of the fixed budget to numbers of phenotyped and genotyped test individuals in performance tests can be optimized. METHODS: Gain in the aggregate genotype was a function of the numbers of full-sibs of selection candidates that were (1) phenotyped in a challenge test for sea lice resistance (2) phenotyped in a slaughter test (3) genotyped in the challenge test, and (4) genotyped in the slaughter test. Each of these activities was subject to budget constraints. Using a grid search, we optimized allocation of the budget among activities to maximize gain in the aggregate genotype. We performed sensitivity analyses on the maximum gain in the aggregate genotype and on the relative allocation of the budget among activities at the optimum. RESULTS: Maximum gain in the aggregate genotype was €386/ton per generation. The response surface for gain in the aggregate genotype was rather flat around the optimum, but it curved strongly near the extremes. Maximum gain was sensitive to the size of the budget and the relative emphasis on breeding goal traits, but less sensitive to the accuracy of genomic prediction and costs of phenotyping and genotyping. The relative allocation of budget among activities at the optimum was sensitive to costs of phenotyping and genotyping and the relative emphasis on breeding goal traits, but was less sensitive to the accuracy of genomic prediction and the size of the budget. CONCLUSIONS: There is an optimum allocation of budget to the numbers of full-sibs of selection candidates that are phenotyped and genotyped in performance tests that maximizes gain in the aggregate genotype. Although potential gains from optimizing group sizes and genotyping effort may be small, they come at no extra cost.

Genetic correlations between growth performance and carcass traits of purebred and crossbred pigs raised in tropical and temperate climates1.

In pig breeding, selection commonly takes place in purebred (PB) pigs raised mainly in temperate climates (TEMP) under optimal environmental conditions in nucleus farms. However, pork production typically makes use of crossbred (CB) animals raised in nonstandardized commercial farms, which are located not only in TEMP regions but also in tropical and subtropical regions (TROP). Besides the differences in the genetic background of PB and CB, differences in climate conditions, and differences between nucleus and commercial farms can lower the genetic correlation between the performance of PB in the TEMP (PBTEMP) and CB in the TROP (CBTROP). Genetic correlations (rg) between the performance of PB and CB growing-finishing pigs in TROP and TEMP environments have not been reported yet, due to the scarcity of data in both CB and TROP. Therefore, the present study aimed 1) to verify the presence of genotype × environment interaction (G × E) and 2) to estimate the rg for carcass and growth performance traits when PB and 3-way CB pigs are raised in 2 different climatic environments (TROP and TEMP). Phenotypic records of 217,332 PB and 195,978 CB, representing 2 climatic environments: TROP (Brazil) and TEMP (Canada, France, and the Netherlands) were available for this study. The PB population consisted of 2 sire lines, and the CB population consisted of terminal 3-way cross progeny generated by crossing sires from one of the PB sire lines with commercially available 2-way maternal sow crosses. G × E appears to be present for average daily gain, protein deposition, and muscle depth given the rg estimates between PB in both environments (0.64 to 0.79). With the presence of G × E, phenotypes should be collected in TROP when the objective is to improve the performance of CB in the TROP. Also, based on the rg estimates between PBTEMP and CBTROP (0.22 to 0.25), and on the expected responses to selection, selecting based only on the performance of PBTEMP would give limited genetic progress in the CBTROP. The rg estimates between PBTROP and CBTROP are high (0.80 to 0.99), suggesting that combined crossbred-purebred selection schemes would probably not be necessary to increase genetic progress in CBTROP. However, the calculated responses to selection show that when the objective is the improvement of CBTROP, direct selection based on the performance of CBTROP has the potential to lead to the higher genetic progress compared with indirect selection on the performance of PBTROP.

Derivation of the economic value of R0 for macroparasitic diseases and application to sea lice in salmon.

BACKGROUND: Macroparasites, such as ticks, lice, and helminths, are a concern in livestock and aquaculture production, and can be controlled by genetic improvement of the host population. Genetic improvement should aim at reducing the rate at which parasites spread across the farmed population. This rate is determined by the basic reproduction ratio, i.e. [Formula: see text], which is the appropriate breeding goal trait. This study aims at providing a method to derive the economic value of [Formula: see text]. METHODS: Costs of a disease are the sum of production losses and expenditures on disease control. Genetic improvement of [Formula: see text] lowers the loss-expenditure frontier. Its economic effect depends on whether the management strategy is optimized or not. The economic value may be derived either from the reduction in losses with constant expenditures or from the reduction in expenditures with constant losses. RESULTS: When [Formula: see text] ≤ 1, the economic value of a further reduction is zero because there is no risk of a major epidemic. When [Formula: see text] > 1 and management is optimized, the economic value increases with decreasing values of [Formula: see text], because both the mean number of parasites per host and frequency of treatments decrease at an increasing rate when [Formula: see text] decreases. When [Formula: see text] > 1 and management is not optimized, the economic value depends on whether genetic improvement is used for reducing expenditures or losses. For sea lice in salmon, the economic value depends on a reduction in expenditures with constant losses, and is estimated to be 0.065€/unit [Formula: see text]/kg production. DISCUSSION: Response to selection for measures of disease prevalence cannot be predicted from quantitative genetic theory alone. Moreover, many studies fail to address the issue of whether genetic improvement results in reduced losses or expenditures. Using [Formula: see text] as the breeding goal trait, weighed by its appropriate economic value, avoids these issues. CONCLUSION: When management is optimized, the economic value increases with decreasing values of [Formula: see text] (until the threshold of [Formula: see text], where it drops to zero). When management is not optimized, the economic value depends on whether genetic improvement is used for reduced expenditures or production losses. For sea lice in salmon, the economic value is estimated to be 0.065 €/unit [Formula: see text]/kg production.

Cost-benefit analysis of aquaculture breeding programs.

BACKGROUND: Profitability of breeding programs is a key determinant in the adoption of selective breeding, and can be evaluated using cost-benefit analysis. There are many options to design breeding programs, with or without a multiplier tier. Our objectives were to evaluate different breeding program designs for aquaculture and to optimize the number of selection candidates for these programs. METHODS: The baseline was based on an existing breeding program for gilthead seabream, where improvement of the nucleus had priority over improvement of the multiplier tier, which was partly replaced once every 3 years. Alternative breeding programs considered were annual multiplier tier replacement, annual multiplier tier replacement with priority on improvement of the multiplier tier, and a program without a multiplier tier. Cost-benefit analyses were performed to compare breeding programs. The outcomes were used to describe relationships between profitability and the number of selection candidates, length of the time horizon, and production output, and to estimate the optimum numbers of selection candidates. RESULTS: The baseline breeding program was profitable after 5 years and reached a net present value of 2.9 million euro in year 10. All alternative programs were more profitable up to year 17. The program without a multiplier tier was the most profitable one up to year 22, followed by the program with annual multiplier tier replacement and nucleus priority. The optimum number of selection candidates increased with the length of the time horizon and production output. CONCLUSIONS: The baseline breeding program was profitable after 5 years. For a short time horizon, putting priority on improvement of the multiplier tier over the nucleus is more profitable than putting priority on nucleus improvement, and vice versa for a long time horizon. Use of a multiplier tier increases the delay between costs made for selection and resulting benefits. Thus, avoiding the use of a multiplier tier will increase the profitability of the breeding program in the short term. The optimum number of selection candidates increases with the length of the time horizon and production output. Using too many selection candidates relative to the optimum leads to less reduction in profitability than using too few selection candidates.

Derivation of economic values for production traits in aquaculture species.

BACKGROUND: In breeding programs for aquaculture species, breeding goal traits are often weighted based on the desired gains but economic gain would be higher if economic values were used instead. The objectives of this study were: (1) to develop a bio-economic model to derive economic values for aquaculture species, (2) to apply the model to determine the economic importance and economic values of traits in a case-study on gilthead seabream, and (3) to validate the model by comparison with a profit equation for a simplified production system. METHODS: A bio-economic model was developed to simulate a grow-out farm for gilthead seabream, and then used to simulate gross margin at the current levels of the traits and after one genetic standard deviation change in each trait with the other traits remaining unchanged. Economic values were derived for the traits included in the breeding goal: thermal growth coefficient (TGC), thermal feed intake coefficient (TFC), mortality rate (M), and standard deviation of harvest weight ([Formula: see text]). For a simplified production system, improvement in TGC was assumed to affect harvest weight instead of growing period. Using the bio-economic model and a profit equation, economic values were derived for harvest weight, cumulative feed intake at harvest, and overall survival. RESULTS: Changes in gross margin showed that the order of economic importance of the traits was: TGC, TFC, M, and [Formula: see text]. Economic values in € (kg production)-1 (trait unit)-1 were: 0.40 for TGC, -0.45 for TFC, -7.7 for M, and -0.0011 to -0.0010 for [Formula: see text]. For the simplified production system, similar economic values were obtained with the bio-economic model and the profit equation. The advantage of the profit equation is its simplicity, while that of the bio-economic model is that it can be applied to any aquaculture species, because it can include any limiting factor and/or environmental condition that affects production. CONCLUSIONS: We confirmed the validity of the bio-economic model. TGC is the most important trait to improve, followed by TFC and M, and the effect of [Formula: see text] on gross margin is small.

A genetic linkage map of sole (Solea solea): a tool for evolutionary and comparative analyses of exploited (flat)fishes.

Linkage maps based on markers derived from genes are essential evolutionary tools for commercial marine fish to help identify genomic regions associated with complex traits and subject to selective forces at play during exploitation or selective breeding. Additionally, they allow the use of genomic information from other related species for which more detailed information is available. Sole (solea solea L.) is a commercially important flatfish species in the North Sea, subject to overexploitation and showing evidence of fisheries-induced evolutionary changes in growth- and maturation-related traits. Sole would definitely benefit from a linkage map to better understand how evolution has shaped its genome structure. This study presents a linkage map of sole based on 423 single nucleotide polymorphisms derived from expressed sequence tags and 8 neutral microsatellite markers. The total map length is 1233.8 cM and consists of 38 linkage groups with a size varying between 0 to 92.1 cM. Being derived from expressed sequence tags allowed us to align the map with the genome of four model fish species, namely medaka (Oryzias latipes), Nile tilapia (Oreochromis niloticus), three-spined stickleback (Gasterosteus aculeatus) and green spotted pufferfish (Tetraodon nigroviridis). This comparison revealed multiple conserved syntenic regions with all four species, and suggested that the linkage groups represent 21 putative sole chromosomes. The map was also compared to the linkage map of turbot (Scophthalmus maximus), another commercially important flatfish species and closely related to sole. For all putative sole chromosomes (except one) a turbot homolog was detected, confirming the even higher degree of synteny between these two flatfish species.

Identifying environmental variables explaining genotype-by-environment interaction for body weight of rainbow trout (Onchorynchus mykiss): reaction norm and factor analytic models.

BACKGROUND: Identifying the relevant environmental variables that cause GxE interaction is often difficult when they cannot be experimentally manipulated. Two statistical approaches can be applied to address this question. When data on candidate environmental variables are available, GxE interaction can be quantified as a function of specific environmental variables using a reaction norm model. Alternatively, a factor analytic model can be used to identify the latent common factor that explains GxE interaction. This factor can be correlated with known environmental variables to identify those that are relevant. Previously, we reported a significant GxE interaction for body weight at harvest in rainbow trout reared on three continents. Here we explore their possible causes. METHODS: Reaction norm and factor analytic models were used to identify which environmental variables (age at harvest, water temperature, oxygen, and photoperiod) may have caused the observed GxE interaction. Data on body weight at harvest was recorded on 8976 offspring reared in various locations: (1) a breeding environment in the USA (nucleus), (2) a recirculating aquaculture system in the Freshwater Institute in West Virginia, USA, (3) a high-altitude farm in Peru, and (4) a low-water temperature farm in Germany. Akaike and Bayesian information criteria were used to compare models. RESULTS: The combination of days to harvest multiplied with daily temperature (Day*Degree) and photoperiod were identified by the reaction norm model as the environmental variables responsible for the GxE interaction. The latent common factor that was identified by the factor analytic model showed the highest correlation with Day*Degree. Day*Degree and photoperiod were the environmental variables that differed most between Peru and other environments. Akaike and Bayesian information criteria indicated that the factor analytical model was more parsimonious than the reaction norm model. CONCLUSIONS: Day*Degree and photoperiod were identified as environmental variables responsible for the strong GxE interaction for body weight at harvest in rainbow trout across four environments. Both the reaction norm and the factor analytic models can help identify the environmental variables responsible for GxE interaction. A factor analytic model is preferred over a reaction norm model when limited information on differences in environmental variables between farms is available.