Rainbow trout is a globally important fish species for aquaculture. However, fish for most farms ... more Rainbow trout is a globally important fish species for aquaculture. However, fish for most farms worldwide are produced by only a few breeding companies. Selection based solely on fish performance recorded at a nucleus may lead to lower-than-expected genetic gains in other production environments when genotype-by-environment (G × E) interaction exists. The aim was to quantify the magnitude of G × E interaction of growth traits (tagging weight; BWT, harvest weight; BWH, and growth rate; TGC) measured across 4 environments, located in 3 different continents, by estimating genetic correlations between environments. A total of 100 families, of at least 25 in size, were produced from the mating 58 sires and 100 dams. In total, 13,806 offspring were reared at the nucleus (selection environment) in Washington State (NUC) and in 3 other environments: a recirculating aquaculture system in Freshwater Institute (FI), West Virginia; a high-altitude farm in Peru (PE), and a cold-water farm in Germany (GER). To account for selection bias due to selective mortality, a multitrait multienvironment animal mixed model was applied to analyze the performance data in different environments as different traits. Genetic correlation (r g) of a trait measured in different environments and r g of different traits measured in different environments were estimated. The results show that heterogeneity of additive genetic variances was mainly found for BWH measured in FI and PE. Additive genetic coefficient of variation for BWH in NUC, FI, PE, and GER were 7.63, 8.36, 8.64, and 9.75, respectively. Genetic correlations between the same trait in different environments were low, indicating strong reranking (BWT: r g = 0.15 to 0.37, BWH: r g = 0.19 to 0.48, TGC: r g = 0.31 to 0.36) across environments. The r g between BWT in NUC and BWH in both FI (0.31) and GER (0.36) were positive, which was also found between BWT in NUC and TGC in both FI (0.10) and GER (0.20). However, r g were negative between BWT in NUC and both BWH (-0.06) and TGC (-0.20) in PE. Correction for selection bias resulted in higher additive genetic variances. In conclusion, strong G × E interaction was found for BWT, BWH, and TGC. Accounting for G × E interaction in the breeding program, either by using sib information from testing stations or environment-specific breeding programs, would increase genetic gains for environments that differ significantly from NUC.
Additional file 2: Table S1. Cross-validation based on sire-dam DHGLM. The data provided represen... more Additional file 2: Table S1. Cross-validation based on sire-dam DHGLM. The data provided represent the results from 10-fold cross-validations based on sire-dam DHGLM.
The international symposium will explore how the application of science and technology, particula... more The international symposium will explore how the application of science and technology, particularly agricultural biotechnologies, can benefit smallholders in developing sustainable food systems and improving nutrition in the context of climate change. The symposium takes a multisectoral approach, covering the crop, livestock, forestry and fishery sectors. It also aims to cover the wide spectrum of available biotechnologies, including microbial food fermentation, tissue culture in plants, reproductive technologies in livestock, use of molecular markers, genetic modification and other technologies. The symposium takes place over two and a half days, with keynote speakers addressing the opening plenary session on 15 February. A high-level ministerial segment will take place on 16 February. Three parallel sessions will also be held each day and the symposium will close on 17 February 2016 with a final plenary session where outcomes from the parallel sessions will be reported. All parallel session speakers and opening plenary speakers have been asked to provide a 2 page summary (1000 words) of their presentation. This document provides these summaries. The agenda for the keynote speeches and parallel sessions is provided below with hyperlinks to each speaker's summary. If a summary is available, the name of the speaker will be in blue text. CTRL+ Click on the author's name to go directly to their summary. At the end of each summary there is another hyperlink to return to the top of the document.
Aquaculture is the fastest growing food production sector and it contributes significantly to glo... more Aquaculture is the fastest growing food production sector and it contributes significantly to global food security. Based on Food and Agriculture Organization (FAO) of the United Nations, aquaculture production must increase significantly to meet the future global demand for aquatic foods in 2050. According to Intergovernmental Panel on Climate Change (IPCC) and FAO, climate change may result in global warming, sea level rise, changes of ocean productivity, freshwater shortage, and more frequent extreme climate events. Consequently, climate change may affect aquaculture to various extents depending on climatic zones, geographical areas, rearing systems, and species farmed. There are 2 major challenges for aquaculture caused by climate change. First, the current fish, adapted to the prevailing environmental conditions, may be suboptimal under future conditions. Fish species are often poikilothermic and, therefore, may be particularly vulnerable to temperature changes. This will make low sensitivity to temperature more important for fish than for livestock and other terrestrial species. Second, climate change may facilitate outbreaks of existing and new pathogens or parasites. To cope with the challenges above, 3 major adaptive strategies are identified. First, general 'robustness' will become a key trait in aquaculture, whereby fish will be less vulnerable to current and new diseases while at the same time thriving in a wider range of temperatures. Second, aquaculture activities, such as input power, transport, and feed production contribute to greenhouse gas emissions. Selection for feed efficiency as well as defining a breeding goal that minimizes greenhouse gas emissions will reduce impacts of aquaculture on climate change. Finally, the limited adoption of breeding programs in aquaculture is a major concern. This implies inefficient use of resources for feed, water, and land. Consequently, the carbon footprint per kg fish produced is greater than when fish from breeding programs would be more heavily used. Aquaculture should use genetically improved and robust organisms not suffering from inbreeding depression. This will require using fish from well-managed selective breeding programs with proper inbreeding control and breeding goals. Policymakers and breeding organizations should provide incentives to boost selective breeding programs in aquaculture for more robust fish tolerating climatic change.
Birth weight is an optimum trait where very high and very low birth weights are undesirable as th... more Birth weight is an optimum trait where very high and very low birth weights are undesirable as they may cause issues, such as dystocia, stillbirths and diminished lamb vigor. Due to economic and welfare concerns, selection for more uniform birth weight is therefore desirable at all litter sizes. If uniformity in birth weight is heritable, selection against very high and very low birth weights can be conducted. The aim of the current study was to investigate if direct and maternal genetic variances in uniformity in birth weight exist in Norwegian White Sheep (NWS). Data composed birth weights of 136,992 NWS lambs born between 2000 and 2017 and corresponding sire-maternal grand sire pedigree. The double hierarchical generalized linear mixed model (DHGLM) was fitted. The direct and maternal heritability for uniformity of birth weight were 0.08 and 0.11, respectively, and larger than for many other uniformity traits in livestock. Furthermore, the direct (57.8%) and maternal (69.4%) gene...
Background: In farmed Atlantic salmon, heritability for uniformity of body weight is low, indicat... more Background: In farmed Atlantic salmon, heritability for uniformity of body weight is low, indicating that the accuracy of estimated breeding values (EBV) may be low. The use of genomic information could be one way to increase accuracy and, hence, obtain greater response to selection. Genomic information can be merged with pedigree information to construct a combined relationship matrix (H matrix) for a single-step genomic evaluation (ssGBLUP), allowing realized relationships of the genotyped animals to be exploited, in addition to numerator pedigree relationships (A matrix). We compared the predictive ability of EBV for uniformity of body weight in Atlantic salmon, when implementing either the A or H matrix in the genetic evaluation. We used double hierarchical generalized linear models (DHGLM) based either on a sire-dam (sire-dam DHGLM) or an animal model (animal DHGLM) for both body weight and its uniformity. Results: With the animal DHGLM, the use of H instead of A significantly increased the correlation between the predicted EBV and adjusted phenotypes, which is a measure of predictive ability, for both body weight and its uniformity (41.1 to 78.1%). When log-transformed body weights were used to account for a scale effect, the use of H instead of A produced a small and non-significant increase (1.3 to 13.9%) in predictive ability. The sire-dam DHGLM had lower predictive ability for uniformity compared to the animal DHGLM. Conclusions: Use of the combined numerator and genomic relationship matrix (H) significantly increased the predictive ability of EBV for uniformity when using the animal DHGLM for untransformed body weight. The increase was only minor when using log-transformed body weights, which may be due to the lower heritability of scaled uniformity, the lower genetic correlation of transformed body weight with its uniformity compared to the untransformed traits, and the small number of genotyped animals in the reference population. This study shows that ssGB-LUP increases the accuracy of EBV for uniformity of body weight and is expected to increase response to selection in uniformity.
Tick-borne fever (TBF) is stated as one of the main disease challenges in Norwegian sheep farming... more Tick-borne fever (TBF) is stated as one of the main disease challenges in Norwegian sheep farming during the grazing season. TBF is caused by the bacterium Anaplasma phagocytophilum that is transmitted by the tick Ixodes ricinus. A sustainable strategy to control tickinfestation is to breed for genetically robust animals. In order to use selection to genetically improve traits we need reliable estimates of genetic parameters. The standard procedures for estimating variance components assume a Gaussian distribution of the data. However, tick-count data is a discrete variable and, thus, standard procedures using linear models may not be appropriate. Thus, the objectives of this study were twofold: 1) to compare four alternative non-linear models: Poisson, negative binomial, zero-inflated Poisson and zeroinflated negative binomial based on their goodness of fit for quantifying genetic variation, as well as heritability for tick-count and 2) to investigate potential response to selection against tick-count based on truncation selection given the estimated genetic parameters from the best fit model. Our results showed that zero-inflated Poisson was the most parsimonious model for the analysis of tick count data. The resulting estimates of variance components and high heritability (0.32) led us to conclude that genetic determinism is relevant on tick count. A reduction of the breeding values for tick-count by one sire-dam genetic standard deviation on the liability scale will reduce the number of tick counts below an average of 1. An appropriate breeding scheme could control tick-count and, as a consequence, probably reduce TBF in sheep.
Sheep farmers in Norway experienced an increase in lamb loss on range pasture during the last dec... more Sheep farmers in Norway experienced an increase in lamb loss on range pasture during the last decades. It is proposed that one reason for this increase in lamb loss in coastal areas is due to tick-borne fever (TBF) caused by A. phagocytophilum infection transmitted by the tick Ixodes ricinus. Within breed variation in response to an Anaplasma phagocytophilum infection suggest that genetic variation is present. Here genetic parameters of tick-count on lambs are estimated using data on 555 lambs of the Norwegian White Sheep breed from 6 different farms and a 10-generation pedigree. Results suggest that heritability for tick-count among Norwegian White Sheep was moderate to high and that tick-load may be reduced by selective breeding. The heritability estimates presented in this study may however be inflated. Further, the relationship between tick-count and robustness to TBF need further investigation and verification.
Abstract Text: Variance component estimation of social interaction traits requires a large number... more Abstract Text: Variance component estimation of social interaction traits requires a large number of small groups (250 to 500) of two families, which may not be practical in aquaculture. Stochastic simulations were performed to study alternative experimental designs. Three alternative designs were compared with respect to variance component estimates and response to selection, with groups composed: at random, of two families and of three families. In each design, the number of groups approximated 100. Groups composed of two and three families with a group size of at least 30 individuals were statistically more powerful to estimate direct and social variance components than groups composed at random. Response to selection from groups of two and three families was substantially higher than the response from groups composed at random. Keywords: Experimental design Genetic parameter Response to selection Socially affected trait Stochastic Simulation
When a rainbow trout stock from a single breeding program is reared in diverse production environ... more When a rainbow trout stock from a single breeding program is reared in diverse production environments, genotype-by-environment interaction (GxE) may present itself. Growth and its uniformity are considered as two of the most important traits by trout producers worldwide. However, GxE for uniformity of growth has not been studied. Using a double hierarchical generalized linear model and data from the Finnish breeding program, we quantified the genetic variance and correlation of body weight (BW) and its uniformity, as well as the degree of GxE for uniformity of BW in a breeding (BE) and a production (PE) environment. To investigate whether scaling effects (high variance related to high mean) affect the estimated parameter, the data were also log-transformed. Although heritability for uniformity (ℎ í µí±£ 2) in the BE (0.014) and in the PE (0.012) was low and of similar magnitude, the genetic coefficient of variation for uniformity was 19 and 21%, respectively, revealing high potenti...
We used digital images of rainbow trout (lateral view) to fit an ellipse around the circumference... more We used digital images of rainbow trout (lateral view) to fit an ellipse around the circumference of the fish. The values for L and H, obtained from the ellipse, were used to calculate ellipticity as (L-H)/(L+H), and the surface area of the fish as π*1/2 L*1/2H. Heritability of ellipticity and surface area at age 8 months was 0.23 and 0.21. Surface area had near-unity genetic correlation with body weight at same age. Genetic correlations of ellipticity with body weight and surface area were-0.55 and-0.56. Genetic correlation of ellipticity with harvest weight at 14 months was-0.49. Estimates of ellipticity are comparable with those of Nile tilapia and common sole. We conclude that when shape is important, ellipticity should be included in the breeding goal, with a weight that reflects the desired direction of change in shape.
Abstract Text: We studied how much the size of a breeding nucleus must be increased to compensate... more Abstract Text: We studied how much the size of a breeding nucleus must be increased to compensate for the loss in genetic gain due to genotype environment interaction (GxE). With truncation selection at a predefined rate of inbreeding for a trait recorded on candidates in the nucleus only, the number of families must increase substantially even with low GxE. When the trait can also be recorded on sibs in the commercial grow-out environment, increases in number of families are less. If the trait cannot be recorded on the selection candidates, preliminary results indicate that the increase in size of the breeding nucleus is marginal. The type of traits in the breeding objective may therefore have a large impact on whether the cost of increasing the size of the breeding nucleus become higher than establishment of a second breeding nucleus in an important market. Keywords: Aquaculture Genotype by environment interaction Breeding program
ABSTRACT Generating breeding programmes that effectively improve farmed fish performance across m... more ABSTRACT Generating breeding programmes that effectively improve farmed fish performance across multiple environments and make fish more uniform within production environments would aid farmers to produce food under diverse environments. We review genotype-by-environment interaction leading to re-ranking of genotypes across environments, that is non-unity genetic correlation between traits measured in different environments, and micro-environmental sensitivity leading to a change in environmental variance of a trait. A quantitative review across 38 species showed that (i) genotype-by-environment interaction studies are lacking for many economically important traits. (ii) Re-ranking is moderate for growth (average genetic correlation = 0.72) and survival (average genetic correlation = 0.54). Significant re-ranking is of concern because selection in a nucleus leads to lower genetic responses in commercial environments compared to a case when re-ranking does not exist. (iii) Re-ranking is weak for age-at-sexual-maturity and fish appearance (average genetic correlation = 0.86), implying that genetic improvement in one environment is expected to be effective in the other environments. Future research should provide guidelines for how to account for genotype-by-environment interaction when collecting data, estimating breeding values and optimising the structure of the breeding programme. (iv) Coefficient of genetic variation for sensitivity against unknown micro-environmental factors within a single environment for body weight is high. Hence, genetic improvement towards less sensitive fish, resulting in more uniform production, is possible, but a large number of relatives with phenotypes is needed for obtaining moderate accuracy of selection. This review elucidates needs for further research on genotype-by-environment interaction and micro-environmental sensitivity in economically important traits and species.
Rainbow trout is a globally important fish species for aquaculture. However, fish for most farms ... more Rainbow trout is a globally important fish species for aquaculture. However, fish for most farms worldwide are produced by only a few breeding companies. Selection based solely on fish performance recorded at a nucleus may lead to lower-than-expected genetic gains in other production environments when genotype-by-environment (G × E) interaction exists. The aim was to quantify the magnitude of G × E interaction of growth traits (tagging weight; BWT, harvest weight; BWH, and growth rate; TGC) measured across 4 environments, located in 3 different continents, by estimating genetic correlations between environments. A total of 100 families, of at least 25 in size, were produced from the mating 58 sires and 100 dams. In total, 13,806 offspring were reared at the nucleus (selection environment) in Washington State (NUC) and in 3 other environments: a recirculating aquaculture system in Freshwater Institute (FI), West Virginia; a high-altitude farm in Peru (PE), and a cold-water farm in Germany (GER). To account for selection bias due to selective mortality, a multitrait multienvironment animal mixed model was applied to analyze the performance data in different environments as different traits. Genetic correlation (r g) of a trait measured in different environments and r g of different traits measured in different environments were estimated. The results show that heterogeneity of additive genetic variances was mainly found for BWH measured in FI and PE. Additive genetic coefficient of variation for BWH in NUC, FI, PE, and GER were 7.63, 8.36, 8.64, and 9.75, respectively. Genetic correlations between the same trait in different environments were low, indicating strong reranking (BWT: r g = 0.15 to 0.37, BWH: r g = 0.19 to 0.48, TGC: r g = 0.31 to 0.36) across environments. The r g between BWT in NUC and BWH in both FI (0.31) and GER (0.36) were positive, which was also found between BWT in NUC and TGC in both FI (0.10) and GER (0.20). However, r g were negative between BWT in NUC and both BWH (-0.06) and TGC (-0.20) in PE. Correction for selection bias resulted in higher additive genetic variances. In conclusion, strong G × E interaction was found for BWT, BWH, and TGC. Accounting for G × E interaction in the breeding program, either by using sib information from testing stations or environment-specific breeding programs, would increase genetic gains for environments that differ significantly from NUC.
Additional file 2: Table S1. Cross-validation based on sire-dam DHGLM. The data provided represen... more Additional file 2: Table S1. Cross-validation based on sire-dam DHGLM. The data provided represent the results from 10-fold cross-validations based on sire-dam DHGLM.
The international symposium will explore how the application of science and technology, particula... more The international symposium will explore how the application of science and technology, particularly agricultural biotechnologies, can benefit smallholders in developing sustainable food systems and improving nutrition in the context of climate change. The symposium takes a multisectoral approach, covering the crop, livestock, forestry and fishery sectors. It also aims to cover the wide spectrum of available biotechnologies, including microbial food fermentation, tissue culture in plants, reproductive technologies in livestock, use of molecular markers, genetic modification and other technologies. The symposium takes place over two and a half days, with keynote speakers addressing the opening plenary session on 15 February. A high-level ministerial segment will take place on 16 February. Three parallel sessions will also be held each day and the symposium will close on 17 February 2016 with a final plenary session where outcomes from the parallel sessions will be reported. All parallel session speakers and opening plenary speakers have been asked to provide a 2 page summary (1000 words) of their presentation. This document provides these summaries. The agenda for the keynote speeches and parallel sessions is provided below with hyperlinks to each speaker's summary. If a summary is available, the name of the speaker will be in blue text. CTRL+ Click on the author's name to go directly to their summary. At the end of each summary there is another hyperlink to return to the top of the document.
Aquaculture is the fastest growing food production sector and it contributes significantly to glo... more Aquaculture is the fastest growing food production sector and it contributes significantly to global food security. Based on Food and Agriculture Organization (FAO) of the United Nations, aquaculture production must increase significantly to meet the future global demand for aquatic foods in 2050. According to Intergovernmental Panel on Climate Change (IPCC) and FAO, climate change may result in global warming, sea level rise, changes of ocean productivity, freshwater shortage, and more frequent extreme climate events. Consequently, climate change may affect aquaculture to various extents depending on climatic zones, geographical areas, rearing systems, and species farmed. There are 2 major challenges for aquaculture caused by climate change. First, the current fish, adapted to the prevailing environmental conditions, may be suboptimal under future conditions. Fish species are often poikilothermic and, therefore, may be particularly vulnerable to temperature changes. This will make low sensitivity to temperature more important for fish than for livestock and other terrestrial species. Second, climate change may facilitate outbreaks of existing and new pathogens or parasites. To cope with the challenges above, 3 major adaptive strategies are identified. First, general 'robustness' will become a key trait in aquaculture, whereby fish will be less vulnerable to current and new diseases while at the same time thriving in a wider range of temperatures. Second, aquaculture activities, such as input power, transport, and feed production contribute to greenhouse gas emissions. Selection for feed efficiency as well as defining a breeding goal that minimizes greenhouse gas emissions will reduce impacts of aquaculture on climate change. Finally, the limited adoption of breeding programs in aquaculture is a major concern. This implies inefficient use of resources for feed, water, and land. Consequently, the carbon footprint per kg fish produced is greater than when fish from breeding programs would be more heavily used. Aquaculture should use genetically improved and robust organisms not suffering from inbreeding depression. This will require using fish from well-managed selective breeding programs with proper inbreeding control and breeding goals. Policymakers and breeding organizations should provide incentives to boost selective breeding programs in aquaculture for more robust fish tolerating climatic change.
Birth weight is an optimum trait where very high and very low birth weights are undesirable as th... more Birth weight is an optimum trait where very high and very low birth weights are undesirable as they may cause issues, such as dystocia, stillbirths and diminished lamb vigor. Due to economic and welfare concerns, selection for more uniform birth weight is therefore desirable at all litter sizes. If uniformity in birth weight is heritable, selection against very high and very low birth weights can be conducted. The aim of the current study was to investigate if direct and maternal genetic variances in uniformity in birth weight exist in Norwegian White Sheep (NWS). Data composed birth weights of 136,992 NWS lambs born between 2000 and 2017 and corresponding sire-maternal grand sire pedigree. The double hierarchical generalized linear mixed model (DHGLM) was fitted. The direct and maternal heritability for uniformity of birth weight were 0.08 and 0.11, respectively, and larger than for many other uniformity traits in livestock. Furthermore, the direct (57.8%) and maternal (69.4%) gene...
Background: In farmed Atlantic salmon, heritability for uniformity of body weight is low, indicat... more Background: In farmed Atlantic salmon, heritability for uniformity of body weight is low, indicating that the accuracy of estimated breeding values (EBV) may be low. The use of genomic information could be one way to increase accuracy and, hence, obtain greater response to selection. Genomic information can be merged with pedigree information to construct a combined relationship matrix (H matrix) for a single-step genomic evaluation (ssGBLUP), allowing realized relationships of the genotyped animals to be exploited, in addition to numerator pedigree relationships (A matrix). We compared the predictive ability of EBV for uniformity of body weight in Atlantic salmon, when implementing either the A or H matrix in the genetic evaluation. We used double hierarchical generalized linear models (DHGLM) based either on a sire-dam (sire-dam DHGLM) or an animal model (animal DHGLM) for both body weight and its uniformity. Results: With the animal DHGLM, the use of H instead of A significantly increased the correlation between the predicted EBV and adjusted phenotypes, which is a measure of predictive ability, for both body weight and its uniformity (41.1 to 78.1%). When log-transformed body weights were used to account for a scale effect, the use of H instead of A produced a small and non-significant increase (1.3 to 13.9%) in predictive ability. The sire-dam DHGLM had lower predictive ability for uniformity compared to the animal DHGLM. Conclusions: Use of the combined numerator and genomic relationship matrix (H) significantly increased the predictive ability of EBV for uniformity when using the animal DHGLM for untransformed body weight. The increase was only minor when using log-transformed body weights, which may be due to the lower heritability of scaled uniformity, the lower genetic correlation of transformed body weight with its uniformity compared to the untransformed traits, and the small number of genotyped animals in the reference population. This study shows that ssGB-LUP increases the accuracy of EBV for uniformity of body weight and is expected to increase response to selection in uniformity.
Tick-borne fever (TBF) is stated as one of the main disease challenges in Norwegian sheep farming... more Tick-borne fever (TBF) is stated as one of the main disease challenges in Norwegian sheep farming during the grazing season. TBF is caused by the bacterium Anaplasma phagocytophilum that is transmitted by the tick Ixodes ricinus. A sustainable strategy to control tickinfestation is to breed for genetically robust animals. In order to use selection to genetically improve traits we need reliable estimates of genetic parameters. The standard procedures for estimating variance components assume a Gaussian distribution of the data. However, tick-count data is a discrete variable and, thus, standard procedures using linear models may not be appropriate. Thus, the objectives of this study were twofold: 1) to compare four alternative non-linear models: Poisson, negative binomial, zero-inflated Poisson and zeroinflated negative binomial based on their goodness of fit for quantifying genetic variation, as well as heritability for tick-count and 2) to investigate potential response to selection against tick-count based on truncation selection given the estimated genetic parameters from the best fit model. Our results showed that zero-inflated Poisson was the most parsimonious model for the analysis of tick count data. The resulting estimates of variance components and high heritability (0.32) led us to conclude that genetic determinism is relevant on tick count. A reduction of the breeding values for tick-count by one sire-dam genetic standard deviation on the liability scale will reduce the number of tick counts below an average of 1. An appropriate breeding scheme could control tick-count and, as a consequence, probably reduce TBF in sheep.
Sheep farmers in Norway experienced an increase in lamb loss on range pasture during the last dec... more Sheep farmers in Norway experienced an increase in lamb loss on range pasture during the last decades. It is proposed that one reason for this increase in lamb loss in coastal areas is due to tick-borne fever (TBF) caused by A. phagocytophilum infection transmitted by the tick Ixodes ricinus. Within breed variation in response to an Anaplasma phagocytophilum infection suggest that genetic variation is present. Here genetic parameters of tick-count on lambs are estimated using data on 555 lambs of the Norwegian White Sheep breed from 6 different farms and a 10-generation pedigree. Results suggest that heritability for tick-count among Norwegian White Sheep was moderate to high and that tick-load may be reduced by selective breeding. The heritability estimates presented in this study may however be inflated. Further, the relationship between tick-count and robustness to TBF need further investigation and verification.
Abstract Text: Variance component estimation of social interaction traits requires a large number... more Abstract Text: Variance component estimation of social interaction traits requires a large number of small groups (250 to 500) of two families, which may not be practical in aquaculture. Stochastic simulations were performed to study alternative experimental designs. Three alternative designs were compared with respect to variance component estimates and response to selection, with groups composed: at random, of two families and of three families. In each design, the number of groups approximated 100. Groups composed of two and three families with a group size of at least 30 individuals were statistically more powerful to estimate direct and social variance components than groups composed at random. Response to selection from groups of two and three families was substantially higher than the response from groups composed at random. Keywords: Experimental design Genetic parameter Response to selection Socially affected trait Stochastic Simulation
When a rainbow trout stock from a single breeding program is reared in diverse production environ... more When a rainbow trout stock from a single breeding program is reared in diverse production environments, genotype-by-environment interaction (GxE) may present itself. Growth and its uniformity are considered as two of the most important traits by trout producers worldwide. However, GxE for uniformity of growth has not been studied. Using a double hierarchical generalized linear model and data from the Finnish breeding program, we quantified the genetic variance and correlation of body weight (BW) and its uniformity, as well as the degree of GxE for uniformity of BW in a breeding (BE) and a production (PE) environment. To investigate whether scaling effects (high variance related to high mean) affect the estimated parameter, the data were also log-transformed. Although heritability for uniformity (ℎ í µí±£ 2) in the BE (0.014) and in the PE (0.012) was low and of similar magnitude, the genetic coefficient of variation for uniformity was 19 and 21%, respectively, revealing high potenti...
We used digital images of rainbow trout (lateral view) to fit an ellipse around the circumference... more We used digital images of rainbow trout (lateral view) to fit an ellipse around the circumference of the fish. The values for L and H, obtained from the ellipse, were used to calculate ellipticity as (L-H)/(L+H), and the surface area of the fish as π*1/2 L*1/2H. Heritability of ellipticity and surface area at age 8 months was 0.23 and 0.21. Surface area had near-unity genetic correlation with body weight at same age. Genetic correlations of ellipticity with body weight and surface area were-0.55 and-0.56. Genetic correlation of ellipticity with harvest weight at 14 months was-0.49. Estimates of ellipticity are comparable with those of Nile tilapia and common sole. We conclude that when shape is important, ellipticity should be included in the breeding goal, with a weight that reflects the desired direction of change in shape.
Abstract Text: We studied how much the size of a breeding nucleus must be increased to compensate... more Abstract Text: We studied how much the size of a breeding nucleus must be increased to compensate for the loss in genetic gain due to genotype environment interaction (GxE). With truncation selection at a predefined rate of inbreeding for a trait recorded on candidates in the nucleus only, the number of families must increase substantially even with low GxE. When the trait can also be recorded on sibs in the commercial grow-out environment, increases in number of families are less. If the trait cannot be recorded on the selection candidates, preliminary results indicate that the increase in size of the breeding nucleus is marginal. The type of traits in the breeding objective may therefore have a large impact on whether the cost of increasing the size of the breeding nucleus become higher than establishment of a second breeding nucleus in an important market. Keywords: Aquaculture Genotype by environment interaction Breeding program
ABSTRACT Generating breeding programmes that effectively improve farmed fish performance across m... more ABSTRACT Generating breeding programmes that effectively improve farmed fish performance across multiple environments and make fish more uniform within production environments would aid farmers to produce food under diverse environments. We review genotype-by-environment interaction leading to re-ranking of genotypes across environments, that is non-unity genetic correlation between traits measured in different environments, and micro-environmental sensitivity leading to a change in environmental variance of a trait. A quantitative review across 38 species showed that (i) genotype-by-environment interaction studies are lacking for many economically important traits. (ii) Re-ranking is moderate for growth (average genetic correlation = 0.72) and survival (average genetic correlation = 0.54). Significant re-ranking is of concern because selection in a nucleus leads to lower genetic responses in commercial environments compared to a case when re-ranking does not exist. (iii) Re-ranking is weak for age-at-sexual-maturity and fish appearance (average genetic correlation = 0.86), implying that genetic improvement in one environment is expected to be effective in the other environments. Future research should provide guidelines for how to account for genotype-by-environment interaction when collecting data, estimating breeding values and optimising the structure of the breeding programme. (iv) Coefficient of genetic variation for sensitivity against unknown micro-environmental factors within a single environment for body weight is high. Hence, genetic improvement towards less sensitive fish, resulting in more uniform production, is possible, but a large number of relatives with phenotypes is needed for obtaining moderate accuracy of selection. This review elucidates needs for further research on genotype-by-environment interaction and micro-environmental sensitivity in economically important traits and species.
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