Effects of pedigree errors on the efficiency of conservation decisions

Conservation schemes often aim at increasing genetic diversity by minimizing kinship, and the best method to achieve this goal, when pedigree data is available, is to apply optimal contributions. Optimal contributions calculate contributions per animal so that the weighted average mean kinship among candidate parents is minimized. This approach assumes that pedigree data is correct and complete. However, in practice, pedigrees often contain errors: parents are recorded incorrectly or even missing. We used simulations to investigate the effect of these two types of errors on minimizing kinship. Our findings show that a low percentage of wrong parent information reduces the effect of optimal contributions. When the percentage of wrong parent information is above 15%, the population structure and type of errors, should be taken into account before applying optimal contributions. Optimal contributions based on pedigrees with missing parent information hampers conservation of genetic diversity; however, missing parent information can be corrected. It is crucial to know which animals are founders. We strongly recommend that pedigree registration include whether missing parents are either true founders or non-founders

Sociale scharrelaars of schadelijke schurken?

In dit essay betogen de auteursj dat de combinatie van een verbeterde opfok en houderij en een nieuwe sociale fokkerijstrategie veelbelovend is om sociaal gedrag, en daarmee dierenwelzijn, te verbeteren

Optimal mass selection policies for schemes with overlapping generations and restricted inbreeding

<p>Abstract</p> <p>Optimum breeding schemes for maximising the rate of genetic progress with a restriction on the rate of inbreeding (per year or per generation) are investigated for populations with overlapping generations undergoing mass selection. The optimisation is for the numbers of males and females to be selected and for their distribution over age classes. Expected rates of genetic progress (Δ<it>G</it>) are combined with expected rates of inbreeding (Δ<it>F</it>) in a linear objective function (Φ = Δ<it>G </it>- λΔ<it>F</it>) which is maximised. A simulated annealing algorithm is used to obtain the solutions. The restriction on inbreeding is achieved by increasing the number of parents and, in small schemes with severe restrictions, by increasing the generation interval. In the latter case the optimum strategy for obtaining the maximum genetic gain is far from truncation selection across age classes. In most situations, the optimum mating ratio is one but the differences in genetic gain obtained with different mating ratios are small. Optimisation of schemes when restricting the rate of inbreeding per generation leads to shorter generation intervals than optimisation when restricting the rate of inbreeding per year.</p

Long-term genetic contributions : prediction of rates of inbreeding and genetic gain in selected populations

This dissertation focuses on the prediction of long-term genetic contributions, rates of inbreeding and rates of gain in artificially selected populations. The long-term genetic contribution ( r i ) of ancestor i born at time t 1 , is defined as the proportion of genes from i that are present in individuals in generation t 2 deriving by descent from i , where ( t 2 - t 1 )→∞.The long-term genetic contribution of an individual was predicted by linear regression on the selective advantage of the individual. With overlapping generations, long-term genetic contributions were predicted using a modified gene flow approach. A novel definition of generation interval was introduced, which states that the generation interval is the length of time in which long-term genetic contributions sum to unity. It was shown that the rate of inbreeding is proportional to the sum of squared of expected long-term genetic contributions and that the rate of genetic gain is proportional to the sum of cross products of long-term genetic contributions and Mendelian sampling terms. Accurate predictions of rates of inbreeding were obtained for populations with discrete or overlapping generations undergoing either mass selection or selection on Best Linear Unbiased Prediction of breeding values. The method was applied to crossbreeding systems, which showed that the use of crossbred information may increase the rate of genetic gain, but measures to restrict the rate of inbreeding are required.</p

Genetic gain of pure line selection and combined crossbred purebred selection with constrained inbreeding

Using deterministic methods, rates of genetic gain (ýG) and inbreeding (ýF) were compared between pure line selection (PLS) and combined crossbred purebred selection (CCPS), for the sire line of a three-way crossbreeding scheme. Purebred performance and crossbred performance were treated as genetically correlated traits assuming the infinitesimal model. Breeding schemes were compared at a fixed total number of purebred selection candidates, i.e. including crossbred information did not affect the size of the purebred nucleus. Selection was by truncation on estimated breeding values for crossbred performance. Rates of genetic gain were predicted using a pseudo-BLUP selection index. Rates of inbreeding were predicted using recently developed methods based on long-term genetic contributions. Results showed that changing from PLS to CCPS may increase ýF by a factor of 2·14. In particular with high heritabilities and low purebred-crossbred genetic correlations, CCPS requires a larger number of parents than PLS, to avoid excessive ýF. The superiority of CCPS over PLS was judged by comparing ýG from both selection strategies at the same ýF. At the same ýF, CCPS was superior to PLS and the superiority of CCPS was only moderately reduced compared with the situation without a restriction on ýF. This paper shows that the long-term genetic contribution theory can be used to balance ýF and ýG in animal breeding schemes within very limited computing time

On the relation between gene flow theory and genetic gain

In conventional gene flow theory the rate of genetic gain is calculated as the summed products of genetic selection differential and asymptotic proportion of genes deriving from sex-age groups. Recent studies have shown that asymptotic proportions of genes predicted from conventional gene flow theory may deviate considerably from true proportions. However, the rate of genetic gain predicted from conventional gene flow theory was accurate. The current note shows that the connection between asymptotic proportions of genes and rate of genetic gain that is embodied in conventional gene flow theory is invalid, even though genetic gain may be predicted correctly from it.Note sur la relation entre le calcul de flux des gènes et le progrès génétique. Dans la méthode classique de calcul de la transmission des gènes, le taux de progrès génétique est calculé comme la somme des produits de la différentielle de sélection génétique et de la proportion asymptotique des gènes provenant des groupes âge-sexe. Des études récentes ont montré que les proportions asymptotiques de gènes prédites à partir de la méthode classique de calcul des flux de gènes peuvent dévier considérablement des proportions réelles. Par contre, le progrès génétique est prédit à partir de cette même méthode avec une bonne précision. La présente note montre que le lien entre le flux des gènes et le progrès génétique, tel qu'il apparaît dans la méthode classique de calcul des flux des gènes n'est donc pas correct, même si le progrès génétique peut être correctement prédit à partir de ladite méthode