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Eikje L.S.,The Norwegian Association of Sheep and Goat Breeders | Eikje L.S.,Norwegian University of Life Sciences | Schaeffer L.R.,University of Guelph | Adnoy T.,Norwegian University of Life Sciences | And 3 more authors.
Journal of Animal Breeding and Genetics | Year: 2012

A method of approximating estimated breeding values (EBV) from a multivariate distribution of true breeding values (TBV) and EBV is proposed for use in large-scale stochastic simulation of alternative breeding schemes with a complex breeding goal. The covariance matrix of the multivariate distributions includes the additive genetic (co)variances and approximated prediction error (co)variances at different selection stages in the life of the animal. The prediction error (co)variance matrix is set up for one animal at a time, utilizing information on the selection candidate and its offspring, the parents, as well as paternal and maternal half- sibs. The EBV are a regression on TBV taking individual uncertainty into account, but with additional 'free' variation drawn at random. With the current information included in the calculation of the prediction error variance of a selection candidate, it is concluded that the method can be used to optimize progeny-testing schemes, where the progeny-tested sires are utilized with large progeny groups, e.g. through artificial insemination. © 2011 Blackwell Verlag GmbH.


Valdez-Nava Y.,Norwegian University of Life Sciences | Valdez-Nava Y.,University of Natural Resources and Life Sciences, Vienna | Steinheim G.,Norwegian University of Life Sciences | Odegard J.,Nofima As | And 3 more authors.
Acta Agriculturae Scandinavica A: Animal Sciences | Year: 2011

Genotype by environment (G×E) interaction effects influence phenotypic expressions of a trait and may be of importance for sheep breeding. Interaction effects are more likely to be present when there are large environmental differences. Norwegian sheep usually graze mountain or forest pastures during summer. In this study, we estimate G×E interactions in Norwegian White Sheep as genetic correlation between area-specific traits (autumn lamb weight) in three ram circles located in two different counties; two in Buskerud in the south and one in Troms to the north of the country. Using data from the National Sheep Recording System, a bivariate animal model was fitted and genetic correlations for each trait were obtained. None of the correlations were significantly different from unity indicating the absence of G×E interaction effect for weaning weight. To gain further insight, studies should include a breeding-goal level aggregation of all traits thought to contribute to profitability. © 2011 Copyright Taylor and Francis Group, LLC.


Vage D.I.,Norwegian University of Life Sciences | Boman I.A.,The Norwegian Association of Sheep and Goat Breeders
BMC Genetics | Year: 2010

Background: Sheep carcasses with yellow fat are sporadically observed at Norwegian slaughter houses. This phenomenon is known to be inherited as a recessive trait, and is caused by accumulation of carotenoids in adipose tissue. Two enzymes are known to be important in carotenoid degradation in mammals, and are therefore potential candidate genes for this trait. These are beta-carotene 15,15'-monooxygenase 1 (BCMO1) and the beta-carotene oxygenase 2 (BCO2).Results: In the present study the coding region of the BCMO1 and the BCO2 gene were sequenced in yellow fat individuals and compared to the corresponding sequences from control animals with white fat. In the yellow fat individuals a nonsense mutation was found in BCO2 nucleotide position 196 (c.196C>T), introducing a stop codon in amino acid position 66. The full length protein consists of 575 amino acids. In spite of a very low frequency of this mutation in the Norwegian AI-ram population, 16 out of 18 yellow fat lambs were found to be homozygous for this mutation.Conclusion: In the present study a nonsense mutation (c.196C>T) in the beta-carotene oxygenase 2 (BCO2) gene is found to strongly associate with the yellow fat phenotype in sheep. The existence of individuals lacking this mutation, but still demonstrating yellow fat, suggests that additional mutations may cause a similar phenotype in this population. The results demonstrate a quantitatively important role for BCO2 in carotenoid degradation, which might indicate a broad enzyme specificity for carotenoids. Animals homozygous for the mutation are not reported to suffer from any negative health or development traits, pointing towards a minor role of BCO2 in vitamin A formation. Genotyping AI rams for c.196C>T can now be actively used in selection against the yellow fat trait. © 2010 Våge and Boman; licensee BioMed Central Ltd.


Steinheim G.,Norwegian University of Life Sciences | Eikje L.S.,The Norwegian Association of Sheep and Goat Breeders | Klemetsdal G.,Norwegian University of Life Sciences | Adnoy T.,Norwegian University of Life Sciences | Odegard J.,Nofima
Small Ruminant Research | Year: 2012

We studied breed and breed by environment interaction effects on lamb mortality during the summer grazing period. One hundred forty-six Norwegian sheep farms that stocked the two most common breeds - Norwegian White Sheep (NWS) and Spælsau together and grazed both in the same free-range grazing areas were used. Average summer mortality of lambs on the study farms was 8.7% for NWS and 6.3% for Spælsau. For 110 of the 146 sheep flocks Spælsau had the lower lamb mortality during summer. The higher mortality observed amongst NWS lambs may suggest a higher environmental sensitivity for this breed, which coincides well with results previously obtained for lamb autumn weights of the same two breeds. Analysing genotype by environment interactions with a probit threshold model revealed that the breeds differed significantly in lamb mortality, and that they ranked their flock environments in a slightly, albeit significantly, different way, i.e., breed by environment interactions did affect lamb mortality. The consequences of the threshold model's assumptions and the constraints on interpretation of results are discussed. © 2012 Elsevier B.V.


Boman I.A.,Norwegian University of Life Sciences | Klemetsdal G.,Norwegian University of Life Sciences | Nafstad O.,Animalia Meat and Poultry Research Center | Blichfeldt T.,The Norwegian Association of Sheep and Goat Breeders | Vage D.I.,Norwegian University of Life Sciences
Journal of Animal Breeding and Genetics | Year: 2011

In this study we show that selection based on progeny testing is able to induce a rapid change in allele frequency, even when a fairly broad and balanced breeding goal is applied. The myostatin 3'-UTR mutation (c.*1232G>A) previously found to affect muscularity in Texel sheep is also present in the Norwegian White Sheep population. By genotyping the rams used for artificial insemination (born in1977-2006), a rapid increase in the c.*1232G>A allele frequency was observed, from 0.31 in 1990 to 0.82 in 2006. The major increase was observed after BLUP-based breeding values and the EUROP classification system for carcass quality was implemented in 1991 and 1996, respectively. The MSTN frameshift mutation c.960delG, recently identified in this population, did not show a similar increase in allele frequency during the same period, in spite that it has a strong desirable effect on meat and fat traits. The results also illustrate that unwanted side effects can rapidly be introduced into a population using an efficient breeding scheme. A system for monitoring changes in phenotypic traits additional to those under selection is therefore recommended to identify possible side effects at an early stage. © 2010 Blackwell Verlag GmbH.


PubMed | The Norwegian Association of Sheep and Goat Breeders
Type: Comparative Study | Journal: Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie | Year: 2012

A method of approximating estimated breeding values (EBV) from a multivariate distribution of true breeding values (TBV) and EBV is proposed for use in large-scale stochastic simulation of alternative breeding schemes with a complex breeding goal. The covariance matrix of the multivariate distributions includes the additive genetic (co)variances and approximated prediction error (co)variances at different selection stages in the life of the animal. The prediction error (co)variance matrix is set up for one animal at a time, utilizing information on the selection candidate and its offspring, the parents, as well as paternal and maternal half- sibs. The EBV are a regression on TBV taking individual uncertainty into account, but with additional free variation drawn at random. With the current information included in the calculation of the prediction error variance of a selection candidate, it is concluded that the method can be used to optimize progeny-testing schemes, where the progeny-tested sires are utilized with large progeny groups, e.g. through artificial insemination.

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