Search

The European Master in Animal Breeding and Genetics (EMABG) is an international master program operating on a global scale, with the aim to train experts and future leaders for research and industry. The training and education takes place at six European universities, within four study tracks with carefully designed curricula. One of the central parts of the MSc programme is the integration of teamwork activities and training of transversal skills to increase the employability of the graduates. To achieve this goal several major events are incorporated into the study programme during the entire duration of the two years. Also, strong emphasis is placed on integration of experts from the industry in the form of talks during joint events, internships, and direct work during special courses, as well as the final thesis.

Gilthead seabream (Sparus aurata) is a key aquaculture species in the Mediterranean and surrounding regions. While many traits are of interest in seabream breeding programs, phenotypes of them cannot always be easily or accurately measured. Therefore, the objectives are to predict phenotypes of production traits by using automated measurements of body features from digital images and to obtain genetic correlations between measured and predicted phenotypes. The production traits analysed were harvest weight (HW), fillet weight (FW), and fillet percentage (F%). Each image feature was tested for prediction of phenotypes by using 10-fold cross-validation. The phenotypic and genetic correlations of measured and predicted phenotypes were 0.98 and 0.996 for HW, 0.93 and 0.99 for FW, 0.27 and 0.70 for F%, respectively. The relative efficiency of mass selection was higher for predicted phenotypes, except for HW.

Highly fecund aquaculture species provide more opportunities to optimize genotyping effort in genomic selection programs through selective genotyping and pre-selection than other livestock species. The aim of this study is to optimize pre-selection in a simulated fish breeding program to achieve the highest genetic gain per genotyped fish under restricted inbreeding. We simulated breeding programs in R with preselection among all selection candidates, between full sib families and within full sib families and several pre-selection intensities within each of the strategies. Pre-selection always reduces genetic gain. However, when genotyping costs are taken into account, genetic gain per genotyped fish can be increased with preselection. Pre-selecting 40% of the candidates from all available selection candidates produced the highest additional genetic gain per genotyped fish.

Livestock populations can have different genetic backgrounds and may vary in their capacity to respond to environmental changes. Our findings suggest that improved chicken breeds differ in growth performance and phenotypic plasticity (yield stability) when they are introduced into new tropical environments. Dual consideration of productivity and phenotypic plasticity gives opportunities to select or recommend genotypes with optimal performance and wider adaptability for smallholder farmers raising livestock in different agroecologies.

In aquaculture, high accuracy in trait measurements benefits the genetic progress from a breeding program. Breeding traits like fat percentage and visceral weight are related to feed/cost efficiency of growth and product quality, and important metabolism and health indicators. Problems concentrate on finding the proper methods to accurately measure or predict these traits, as most current approaches are invasive, labour-intensive or may disturb or damage the fish. Interior trait prediction from image analysis would allow a real-time, large-scale and non-invasive alternative for such traits. This study investigates using whole-fish images in combination with exterior traits to improve the prediction of fillet fat percentage and visceral weight. The result of including images as extra input shows improvement on the accuracy of fat percentage prediction. The neural network extracted contour-based features and brings into view several biological indicators that appear to be informative for prediction.

Critical swimming speed (Ucrit) is an important measurement of swimming performance as well as a good indicator for cardio-respiratory health. It offers a new opportunity to select fish with better fitness. Here we present results from a GWAS study on critical swimming speed and growth in Nile tilapia under conditions of recurrent hypoxia. Heritability for Ucrit was moderate (0.31±0.04). Large fish generally swim faster than smaller fish, whereas fish with better swimming performance tend to show slower growth later in life. Nine suggestive SNPs associated with swimming performance were identified under a hypoxic environment. A clear pleiotropic effect on growth traits was found for some of the SNPs associated with swimming performance, while other SNPs had only an effect on swimming performance, but not on growth. Our analyses sheds a first light on the genomic mechanisms of swimming performance and growth in Nile tilapia.

Tungsten electrode contamination caused by metal vapour from a base metal during a tungsten inert gas welding was investigated. The metal ions transported from the weld pool surface were deposited on the tungsten electrode surface during welding. The tungsten fraction of the electrode surface layer was decreased because the deposited metal vapour diffused inside the tungsten electrode. The melting point of the electrode surface layer was lowered, decreasing to the electrode operating temperature. Results show that the electrode melted and deformed. This electrode contamination was promoted when a larger amount of metal ions was transported to the electrode surface., Tungsten electrode contamination caused by metal vapour from a base metal during a tungsten inert gas welding was investigated. The metal ions transported from the weld pool surface were deposited on the tungsten electrode surface during welding. The tungsten fraction of the electrode surface layer was decreased because the deposited metal vapour diffused inside the tungsten electrode. The melting point of the electrode surface layer was lowered, decreasing to the electrode operating temperature. Results show that the electrode melted and deformed. This electrode contamination was promoted when a larger amount of metal ions was transported to the electrode surface.

Environmental differences between the breeding (B) and commercial production (C) environments may lead to genotype-by-environment interactions (GxE) i.e. re-ranking of breeding values of animals in the two environments. A substantial re-ranking implies genetic progress achieved in breeding programs is not realized in performance of production animals. The issues of GxE are not new and several solutions exist, however, there has not been much focus on solutions for breeding programs for poultry. This PhD-project investigated GxE interactions in breeding programs for poultry and solutions to improve genetic progress in these breeding programs. A strong GxE interaction for body weight (BW) traits was found in broilers that were raised in B and C environments. Indications of GxE were significant re-ranking of breeding values, heterogeneous variances and different heritability for BW under B and C conditions. The genetic correlations between BW traits measured in B and C environments were in the range 0.48-0.54. Genetic variances of C traits were more than 2 times higher than those of B traits. Heritability of C traits (0.31-0.37) were higher than those of B traits (0.27-0.30). In this thesis, several approaches to improve genetic gains of the poultry breeding programs in the presence of GxE have been investigated: phenotyping strategies, optimal modelling of traits, use of group records, and the use of genomic information. Different phenotyping strategies were compared in a breeding program for broilers that used genomic selection. It was found that when the genetic correlations between traits measured in B and C were 0.5 and 0.7, allocation of 70% and 30% hatched birds to B and C environments, respectively, for phenotype testing led to the highest genetic gains among the compared phenotyping strategies. When the genetic correlation was 0.9, moving birds to C did not improve genetic gains of the breeding scheme due to reduced selection intensity. Increasing proportion o

Predicting breed-specific environmental suitability has been problematic in livestock production. Native breeds have low productivity but are thought to be more robust to perform under local conditions than exotic breeds. Attempts to introduce genetically improved exotic breeds are generally unsuccessful, mainly due to the antagonistic environmental conditions. Knowledge of the environmental conditions that are shaping the breed would be needed to determine its suitability to different locations. Here, we present a methodology to predict the suitability of breeds for different agro-ecological zones using Geographic Information Systems tools and predictive habitat distribution models. This methodology was tested on the current distribution of two introduced chicken breeds in Ethiopia: the Koekoek, originally from South Africa, and the Fayoumi, originally from Egypt. Cross-validation results show this methodology to be effective in predicting breed suitability for specific environmental conditions. Furthermore, the model predicts suitable areas of the country where the breeds could be introduced. The specific climatic parameters that explained the potential distribution of each of the breeds were similar to the environment from which the breeds originated. This novel methodology finds application in livestock programs, allowing for a more informed decision when designing breeding programs and introduction programs, and increases our understanding of the role of the environment in livestock productivity.

Social interactions are common for all living organisms. In animal breeding, these interactions are of interest as they are often a source of indirect genetic effects (IGEs). An IGE is a heritable effect of an individual on the trait value of another individual. In aquaculture populations and some plants, social interactions have an additional consequence – interactions in the form of competition inflate variability of trait values among individuals. The phenotypic variability of a genotype has been studied as a quantitative trait in itself, and is often referred to as inherited variability. The main objective of this thesis was to study the genetics of inherited variability, with a focus on the relationship between competition (i.e., IGEs) and variability.In the thesis, we used Nile tilapia as a model species. We found that variability of body weight and body size traits in Nile tilapia is heritable, and shows a large genetic coefficient of variation, which offers good opportunities for improvement of uniformity by means of genetic selection.To study the genetic relationship between social interactions and variability, we developed a quantitative genetic model that integrates both phenomena. In this model, interactions between social partners lead to divergence (competition) or convergence (cooperation) of their phenotypes (e.g., body weight) over their life time. The effects of social interaction in the model are heritable and can evolve. These effects comprise direct genetic effect of the focal individual and IGE of its social partner. With a simulation study we showed that the model yields increased variability of body weight with increase of competition, similar to what is observed in real aquaculture populations. Selection for cooperation will therefore lead to decreased variability. These findings suggest that IGEs may be creating an entire level of genetic variation in variability, that has so far been overlooked. Using existing statistical models, we show t

Concern about the status of livestock breeds and their conservation has increased as selection and small population sizes caused loss of genetic diversity. Meanwhile, dense SNP chips and whole genome sequences (WGS) became available, providing opportunities to accurately quantify the impact of selection on genetic diversity and develop tools to better preserve such genetic diversity for long-term perspectives. This thesis aimed to infer the impact of selection and mitigate its effects on genetic diversity using genomic information. One of the advantages of WGS information, compared to pedigree and SNP chip information, is that it provides information on all variants, including rare ones, and ‘true’ relationships between individuals may be estimated thus being useful for evaluating genetic diversity. Taking into account rare variants had significant effects on estimated relationships. Moreover, optimal contribution (OC) strategy was used to perform selection either in a breeding program, maximising genetic merit while minimising loss of genetic diversity, or to build a gene bank, only maximising the conserved genetic diversity, with the aim to quantify loss of genetic diversity due to selection decisions. More genetic diversity was conserved when genomic information was used for selection decisions instead of pedigree and WGS information revealed a high loss of genetic diversity due to losing rare variants. Ways to reduce the loss of genetic diversity during a genomic selection program were investigated. The choice of individuals to update the reference population was proposed as a promising way to better conserve genetic diversity in a breeding population. In fact, changes in the reference population will lead to changes in prediction equations and thus ultimately to a shift in long-term selection decisions. Differences between reference population design using either random, truncation or OC selection of individuals, on the breeding population were modest but OC ac

In this course, you will learn how an animal breeder balances the need for improving the desirable qualities of the animals with the need for genetic diversity and long-term sustainability of the breeding program. You will learn about the scientific concepts in genetics that are applied in animal breeding, as well as how to apply the models and computational methods that are used in animal breeding.

In sea cage fish farming, production quotas aim to constrain the impact of fish farming on the surrounding ecosystem. It is unknown how these quotas affect economic profitability and environmental impact of genetic improvement. We combined bioeconomic modelling with life cycle assessment (LCA) to calculate the economic (EV) and environmental (ENV) values of thermal growth coefficient (TGC) and feed conversion ratio (FCR) of sea bass reared in sea cages, given four types of quota commonly used in Europe: annual production (Qprod), annual feed distributed (Qannual_ feed), standing stock (Qstock), and daily feed distributed (Qdaily_ feed). ENV were calculated for LCA impact categories climate change, eutrophication and acidification. ENV were expressed per ton of fish produced per year (ENV(fish)) and per farm per year (ENV(farm)). Results show that irrespective of quota used, EV of FCR as well as ENV(fish) and ENV(farm) were always positive, meaning that improving FCR increased profit and decreased environmental impacts. However, the EV and the ENV(fish) of TGC were positive only when quota was Qstock or Qdaily_ feed. Moreover, the ENV(farm) of TGC was negative in Qstock and Qdaily_ feed quotas, meaning that improving TGC increased the environmental impact of the farm. We conclude that Qstock quota and Qdaily_ feed quota are economically favorable to a genetic improvement of TGC, a major trait for farmers. However, improving TGC increases the environmental impact of the farm. Improving FCR represents a good opportunity to balance out this increase but more information on its genetic background is needed to develop breeding programs improving FCR.

In developing countries minimal and erratic performance and pedigree recording impede implementation of large-sized breeding programs. Small-sized nucleus programs offer an alternative but rely on their economic performance for their viability. We investigated the economic performance of 2 alternative small-sized dairy nucleus programs [i.e., progeny testing (PT) and genomic selection (GS)] over a 20-yr investment period. The nucleus was made up of 453 male and 360 female animals distributed in 8 non-overlapping age classes. Each year 10 active sires and 100 elite dams were selected. Populations of commercial recorded cows (CRC) of sizes 12,592 and 25,184 were used to produce test daughters in PT or to create a reference population in GS, respectively. Economic performance was defined as gross margins, calculated as discounted revenues minus discounted costs following a single generation of selection. Revenues were calculated as cumulative discounted expressions (CDE, kg) × 0.32 (€/kg of milk) × 100,000 (size commercial population). Genetic superiorities, deterministically simulated using pseudo-BLUP index and CDE, were determined using gene flow. Costs were for one generation of selection. Results show that GS schemes had higher cumulated genetic gain in the commercial cow population and higher gross margins compared with PT schemes. Gross margins were between 3.2- and 5.2-fold higher for GS, depending on size of the CRC population. The increase in gross margin was mostly due to a decreased generation interval and lower running costs in GS schemes. In PT schemes many bulls are culled before selection. We therefore also compared 2 schemes in which semen was stored instead of keeping live bulls. As expected, semen storage resulted in an increase in gross margins in PT schemes, but gross margins remained lower than those of GS schemes. We conclude that implementation of small-sized GS breeding schemes can be economically viable for developing countries.

In sea cage fish farming, production quotas aim to constrain the impact of fish farming on the surrounding ecosystem. It is unknown how these quotas affect economic profitability and environmental impact of genetic improvement. We combined bioeconomic modelling with life cycle assessment (LCA) to calculate the economic (EV) and environmental (ENV) values of thermal growth coefficient (TGC) and feed conversion ratio (FCR) of sea bass reared in sea cages, given four types of quota commonly used in Europe: annual production (Qprod), annual feed distributed (Qannual-feed), standing stock (Qstock), and daily feed distributed (Qdaily-feed). ENV were calculated for LCA impact categories climate change, eutrophication and acidification. ENV were expressed per ton of fish produced per year (ENV(fish)) and per farm per year (ENV(farm)). Results show that irrespective of quota used, EV of FCR as well as ENV(fish) and ENV(farm) were always positive, meaning that improving FCR increased profit and decreased environmental impacts. However, the EV and the ENV(fish) of TGC were positive only when quota was Qstock or Qdaily-feed. Moreover, the ENV(farm) of TGC was negative in Qstock and Qdaily-feed quotas, meaning that improving TGC increased the environmental impact of the farm. We conclude that Qstock quota and Qdaily-feed quota are economically favorable to a genetic improvement of TGC, a major trait for farmers. However, improving TGC increases the environmental impact of the farm. Improving FCR represents a good opportunity to balance out this increase but more information on its genetic background is needed to develop breeding programs improving FCR.

In sea cage farming, fish are exposed to seasonal variations of water temperature, and these variations can differ from one location to another. A small increase in water temperature does not only stimulate growth of the fish (until an optimal level) but also lowers dissolved oxygen concentration in water. Dissolved oxygen may then become a rearing constraint during the production cycle if the oxygen requirement of fish is higher than the supply. The impact of this constraint on production parameters (stocking density of cages and/or batch rotation) and thus on economic profit of a farm will depend on both local thermal regime and growth potential of the fish. Increased growth is one of the most important traits in a breeding objective to increase production capacity and profitability. We used a bioeconomic model of seabass reared in cages to calculate the economic value (EV) of increasing thermal growth coefficient (TGC) by selection in different conditions of average temperature (Tm) and amplitude of temperature variation (Ta). Tm and Ta values were taken from different locations in the eastern and western Mediterranean. Results show that increasing TGC has two consequences: (i) fast growing fish reach harvest weight earlier, which increases the number of batches that can be produced per year, and (ii) fast growing fish have higher daily feed intake and, consequently, higher daily oxygen consumption. To balance the oxygen demand and availability in a cage, a farmer might have to reduce the average stocking density, resulting in fewer fish produced per batch. Consequently, EV of TGC is positive when Tm is 19.5 °C or 21 °C, when an increase in number of batches produced compensates for the decrease in stocking density. EV of TGC is negative or null in areas where Tm is closer to 18 °C because the increase in number of batches produced cannot compensate for the decrease in stocking density. Our results show, for the first time, the importance of variation in ambient