Animal Breeding and Genomics Center Wageningen Livestock Research Wageningen The Netherlands

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Animal Breeding and Genomics Center Wageningen Livestock Research Wageningen The Netherlands

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Windig J.J.,Animal Breeding and Genomics Center Wageningen Livestock Research Wageningen The Netherlands | Hoving R.A.H.,Animal Breeding and Genomics Center Wageningen Livestock Research Wageningen The Netherlands | Priem J.,Central Veterinary Institute part of Wageningen UR Lelystad The Netherlands | Bossers A.,Central Veterinary Institute part of Wageningen UR Lelystad The Netherlands | And 2 more authors.
Journal of Animal Breeding and Genetics | Year: 2016

Scrapie is a neurodegenerative disease occurring in goats and sheep. Several haplotypes of the prion protein increase resistance to scrapie infection and may be used in selective breeding to help eradicate scrapie. In this study, frequencies of the allelic variants of the PrP gene are determined for six goat breeds in the Netherlands. Overall frequencies in Dutch goats were determined from 768 brain tissue samples in 2005, 766 in 2008 and 300 in 2012, derived from random sampling for the national scrapie surveillance without knowledge of the breed. Breed specific frequencies were determined in the winter 2013/2014 by sampling 300 breeding animals from the main breeders of the different breeds. Detailed analysis of the scrapie-resistant K222 haplotype was carried out in 2014 for 220 Dutch Toggenburger goats and in 2015 for 942 goats from the Saanen derived White Goat breed. Nine haplotypes were identified in the Dutch breeds. Frequencies for non-wild type haplotypes were generally low. Exception was the K222 haplotype in the Dutch Toggenburger (29%) and the S146 haplotype in the Nubian and Boer breeds (respectively 7 and 31%). The frequency of the K222 haplotype in the Toggenburger was higher than for any other breed reported in literature, while for the White Goat breed it was with 3.1% similar to frequencies of other Saanen or Saanen derived breeds. Further evidence was found for the existence of two M142 haplotypes, M142/S240 and M142/P240. Breeds vary in haplotype frequencies but frequencies of resistant genotypes are generally low and consequently selective breeding for scrapie resistance can only be slow but will benefit from animals identified in this study. The unexpectedly high frequency of the K222 haplotype in the Dutch Toggenburger underlines the need for conservation of rare breeds in order to conserve genetic diversity rare or absent in other breeds. © 2016 Blackwell Verlag GmbH.


Hidalgo A.M.,Swedish University of Agricultural Sciences | Bastiaansen J.W.M.,Wageningen University | Lopes M.S.,Wageningen University | Calus M.P.L.,Animal Breeding and Genomics Center Wageningen Livestock Research Wageningen The Netherlands | de Koning D.J.,Swedish University of Agricultural Sciences
Journal of Animal Breeding and Genetics | Year: 2016

In pig breeding, as the final product is a cross bred (CB) animal, the goal is to increase the CB performance. This goal requires different strategies for the implementation of genomic selection from what is currently implemented in, for example dairy cattle breeding. A good strategy is to estimate marker effects on the basis of CB performance and subsequently use them to select pure bred (PB) breeding animals. The objective of our study was to assess empirically the predictive ability (accuracy) of direct genomic values of PB for CB performance across two traits using CB and PB genomic and phenotypic data. We studied three scenarios in which genetic merit was predicted within each population, and four scenarios where PB genetic merit for CB performance was predicted based on either CB or a PB training data. Accuracy of prediction of PB genetic merit for CB performance based on CB training data ranged from 0.23 to 0.27 for gestation length (GLE), whereas it ranged from 0.11 to 0.22 for total number of piglets born (TNB). When based on PB training data, it ranged from 0.35 to 0.55 for GLE and from 0.30 to 0.40 for TNB. Our results showed that it is possible to predict PB genetic merit for CB performance using CB training data, but predictive ability was lower than training using PB training data. This result is mainly due to the structure of our data, which had small-to-moderate size of the CB training data set, low relationship between the CB training and the PB validation populations, and a high genetic correlation (0.94 for GLE and 0.90 for TNB) between the studied traits in PB and CB individuals, thus favouring selection on the basis of PB data. © 2016 Blackwell Verlag GmbH.


Heidaritabar M.,Wageningen University | Calus M.P.L.,Animal Breeding and Genomics Center Wageningen Livestock Research Wageningen the Netherlands | Megens H.-J.,Wageningen University | Vereijken A.,Hendrix Genetics Research | And 2 more authors.
Journal of Animal Breeding and Genetics | Year: 2016

There is an increasing interest in using whole-genome sequence data in genomic selection breeding programmes. Prediction of breeding values is expected to be more accurate when whole-genome sequence is used, because the causal mutations are assumed to be in the data. We performed genomic prediction for the number of eggs in white layers using imputed whole-genome resequence data including ~4.6 million SNPs. The prediction accuracies based on sequence data were compared with the accuracies from the 60 K SNP panel. Predictions were based on genomic best linear unbiased prediction (GBLUP) as well as a Bayesian variable selection model (BayesC). Moreover, the prediction accuracy from using different types of variants (synonymous, non-synonymous and non-coding SNPs) was evaluated. Genomic prediction using the 60 K SNP panel resulted in a prediction accuracy of 0.74 when GBLUP was applied. With sequence data, there was a small increase (~1%) in prediction accuracy over the 60 K genotypes. With both 60 K SNP panel and sequence data, GBLUP slightly outperformed BayesC in predicting the breeding values. Selection of SNPs more likely to affect the phenotype (i.e. non-synonymous SNPs) did not improve the accuracy of genomic prediction. The fact that sequence data were based on imputation from a small number of sequenced animals may have limited the potential to improve the prediction accuracy. A small reference population (n = 1004) and possible exclusion of many causal SNPs during quality control can be other possible reasons for limited benefit of sequence data. We expect, however, that the limited improvement is because the 60 K SNP panel was already sufficiently dense to accurately determine the relationships between animals in our data. © 2016 Blackwell Verlag GmbH.


Windig J.J.,Animal Breeding and Genomics Center Wageningen Livestock Research Wageningen The Netherlands | Oldenbroek K.,Center for Genetic Resources the Netherlands Wageningen Wageningen The Netherlands
Journal of Animal Breeding and Genetics | Year: 2015

Excessive inbreeding rates and small effective population sizes are an important problem in many populations of dogs. Proper genetic management of these populations can decrease the problem, and several measures are available. However, the effectiveness of these measures is not clear beforehand. Therefore, a simulation model was developed to test measures that aim to decrease the rate of inbreeding. The simulation program was used to evaluate inbreeding restriction measures in the Dutch golden retriever dog population. This population consisted of approximately 600 dams and 150 sires that produce 300 litters each year. The five most popular sires sire approximately 25% of the litters in a year. Simulations show that the small number of popular sires and their high contribution to the next generation are the main determinants of the inbreeding rates. Restricting breeding to animals with a low average relatedness to all other animals in the population was the most effective measure and decreased the rate of inbreeding per generation from 0.41 to 0.12%. Minimizing co-ancestry of parents was not effective in the long run, but decreased variation in inbreeding rates. Restricting the number of litters per sire generally decreased the generation interval because sires were replaced more quickly, once they met their restriction. In some instances, this lead to an increase in inbreeding rates because the next generations were more related. The simulation tool proved to be a powerful and educational tool for deciding which breeding restrictions to apply, and can be effective in different breeds and species as well. © 2015 Blackwell Verlag GmbH.


Hulsegge B.,Animal Breeding and Genomics Center Wageningen Livestock Research Wageningen The Netherlands | Calus M.P.L.,Animal Breeding and Genomics Center Wageningen Livestock Research Wageningen The Netherlands | Oldenbroek J.K.,Center for Genetic Resources The Netherlands Wageningen The Netherlands | Windig J.J.,Animal Breeding and Genomics Center Wageningen Livestock Research Wageningen The Netherlands
Journal of Animal Breeding and Genetics | Year: 2016

From a genetic point of view, the selection of breeds and animals within breeds for conservation in a national gene pool can be based on a maximum diversity strategy. This implies that priority is given to conservation of breeds and animals that diverge most and overlap of conserved diversity is minimized. This study investigated the genetic diversity in the Dutch Red and White Friesian (DFR) cattle breed and its contribution to the total genetic diversity in the pool of the Dutch dairy breeds. All Dutch cattle breeds are clearly distinct, except for Dutch Friesian breed (DF) and DFR and have their own specific genetic identity. DFR has a small but unique contribution to the total genetic diversity of Dutch cattle breeds and is closely related to the Dutch Friesian breed. Seven different lines are distinguished within the DFR breed and all contribute to the diversity of the DFR breed. Two lines show the largest contributions to the genetic diversity in DFR. One of these lines comprises unique diversity both within the breed and across all cattle breeds. The other line comprises unique diversity for the DFR but overlaps with the Holstein Friesian breed. There seems to be no necessity to conserve the other five lines separately, because their level of differentiation is very low. This study illustrates that, when taking conservation decisions for a breed, it is worthwhile to take into account the population structure of the breed itself and the relationships with other breeds. © 2016 Blackwell Verlag GmbH.

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