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Hamar, Norway

Ferencakovic M.,University of Zagreb | Hamzic E.,University of Natural Resources and Life Sciences, Vienna | Hamzic E.,Norwegian University of Life Sciences | Gredler B.,Qualitas AG | And 4 more authors.
Journal of Animal Breeding and Genetics | Year: 2013

Using genome-wide SNP data, we calculated genomic inbreeding coefficients (FROH > 1 Mb, FROH > 2 Mb, FROH > 8 Mb and FROH > 16 Mb) derived from runs of homozygosity (ROH) of different lengths (>1, >2, >8 and > 16 Mb) as well as from levels of homozygosity (FHOM). We compared these values of inbreeding coefficients with those calculated from pedigrees (FPED) of 1422 bulls comprising Brown Swiss (304), Fleckvieh (502), Norwegian Red (499) and Tyrol Grey (117) cattle breeds. For all four breeds, population inbreeding levels estimated by the genomic inbreeding coefficients FROH > 8 Mb and FROH > 16 Mb were similar to the levels estimated from pedigrees. The lowest values were obtained for Fleckvieh (FPED = 0.014, FROH > 8 Mb = 0.019 and FROH > 16 Mb = 0.008); the highest, for Brown Swiss (FPED = 0.048, FROH > 8 Mb = 0.074 and FROH > 16 Mb = 0.037). In contrast, inbreeding estimates based on the genomic coefficients FROH > 1 Mb and FROH > 2 Mb were considerably higher than pedigree-derived estimates. Standard deviations of genomic inbreeding coefficients were, on average, 1.3-1.7-fold higher than those obtained from pedigrees. Pearson correlations between genomic and pedigree inbreeding coefficients ranged from 0.50 to 0.62 in Norwegian Red (lowest correlations) and from 0.64 to 0.72 in Tyrol Grey (highest correlations). We conclude that the proportion of the genome present in ROH provides a good indication of inbreeding levels and that analysis based on ROH length can indicate the relative amounts of autozygosity due to recent and remote ancestors. © 2012 Blackwell Verlag GmbH. Source


Grant
Agency: Cordis | Branch: FP7 | Program: BSG-SME | Phase: KBBE.2011.1.3-06 | Award Amount: 3.94M | Year: 2012

The Gene2Farm project will address the needs of the cattle industry, in particular of the SMEs and end users, for an accessible, adaptable and reliable system to apply the new genomic knowledge to underpin sustainability and profitability of European cattle farming. Gene2Farm will undertake a comprehensive programme of work from statistical theory development, through genome sequencing, to address new phenotyping approaches and the construction of tools, that will be validated in conjunction with SMEs and industry partners. Advanced statistical theory and applications will use the genomic and phenotypic information to optimise and customise genomic selection, breeding and population management and between breed predictions. The project will sequence key animals and exchange data with other international projects to create the most comprehensive bovine genome sequence database. Detailed analysis of these genome sequences will define genome structure, shared alleles, frequencies and historic haplotypes, within and between populations. This information will be used to optimise the informativeness of SNP panels and select SNPs to tag haplotypes, and hence ensure that genotype information can be used within and between breeds. The project will explore the opportunities for extended phenotypic collection, including the use of automated on farm systems and will develop standardisation protocols that, in consultation with ICAR, could be used by the industry for data collection and management. Developed tools will be tested and validated by demonstration in collaboration with dairy, dual purpose, beef and minority breed organisations. Finally a dissemination programme will ensure that training needs of the industry are served from an entry level training programme for farmers to advanced summer schools for the SMEs and expert user community.


Meuwissen T.H.E.,Norwegian University of Life Sciences | Svendsen M.,GENO SA | Solberg T.,GENO SA | Odegard Jo.,Aqua Gen AS
Genetics Selection Evolution | Year: 2015

Background: In dairy cattle, current genomic predictions are largely based on sire models that analyze daughter yield deviations of bulls, which are derived from pedigree-based animal model evaluations (in a two-step approach). Extension to animal model genomic predictions (AMGP) is not straightforward, because most of the animals that are involved in the genetic evaluation are not genotyped. In single-step genomic best linear unbiased prediction (SSGBLUP), the pedigree-based relationship matrix A and the genomic relationship matrix G are combined in a matrix H, which allows for AMGP. However, as the number of genotyped animals increases, imputation of the genotypes for all animals in the pedigree may be considered. Our aim was to impute genotypes for all animals in the pedigree, construct alternative relationship matrices based on the imputation results, and evaluate the accuracy of the resulting AMGP by cross-validation in the national Norwegian Red dairy cattle population. Results: A large-scale national dataset was effectively handled by splitting it into two sets: (1) genotyped animals and their ancestors (i.e. GA set with 20,918 animals) and (2) the descendants of the genotyped animals (i.e. D set with 4,022,179 animals). This allowed restricting genomic computations to a relatively small set of animals (GA set), whereas the majority of the animals (D set) were added to the animal model equations using Henderson's rules, in order to make optimal use of the D set information. Genotypes were imputed by segregation analysis of a large pedigree with relatively few genotyped animals (3285 out of 20,918). Among the AMGP models, the linkage and linkage disequilibrium based G matrix (G LDLA0 ) yielded the highest accuracy, which on average was 0.06 higher than with SSGBLUP and 0.07 higher than with two-step sire genomic evaluations. Conclusions: AMGP methods based on genotype imputation on a national scale were developed, and the most accurate method, GLDLA0BLUP, combined linkage and linkage disequilibrium information. The advantage of AMGP over a sire model based on two-step genomic predictions is expected to increase as the number of genotyped cows increases and for species, with smaller sire families and more dam relationships. © 2015 Meuwissen et al. Source


Standerholen F.B.,Norwegian University of Life Sciences | Standerholen F.B.,Hedmark University College | Waterhouse K.E.,SpermVital AS | Larsgard A.G.,GENO SA | And 9 more authors.
Theriogenology | Year: 2015

To make timing of artificial insemination (AI) relative to ovulation less critical, methods for prolonging shelf life of spermatozoa in vivo after AI have been attempted to be developed. Encapsulation of sperm cells is a documented technology, and recently, a technology inwhich sperm cells are embedded in alginate gel has been introduced and commercialized. In this study, standard processed semen with the Biladyl extender (control) was compared with semen processed by sperm immobilization technology developed by SpermVital AS in a blind field trial. Moreover, in vitro acrosome and plasma membrane integrity was assessed and comparedwith AI fertility data for possible correlation. Semen from 16 Norwegian Red young bulls with unknown fertility was collected and processed after splitting the semen in two aliquots. These aliquotswere processed with the standard Biladyl extender or the SpermVital extender to a final number of 12 × 106 and 25 × 106 spermatozoa/dose, respectively. In total, 2000 semen doses were produced from each bull, divided equally by treatment. Artificial insemination doses were set up to design a blinded AI regime; 5 + 5 straws from each extender within ejaculates in ten-straw goblets were distributed to AI technicians and veterinarians all over Norway. Outcomes of the inseminations were measured as 56-day nonreturn rate (NRR). Postthaw sperm quality was assessed by flow cytometry using propidium iodide and Alexa 488-conjugated peanut agglutinin to assess the proportion of plasma membrane and acrosome-intact sperm cells, respectively. In total, data from 14,125 first inseminations performed over a 12-month period, 7081 with Biladyl and 7044 with SpermVital semen,were used in the statistical analyses. Therewas no significant difference in 56-day NRR for the two semen categories, overall NRR being 72.5% and 72.7% for Biladyl and SpermVital, respectively. The flow cytometric results revealed a significant higher level of acrosome-intact live spermatozoa in Biladyl-processed semen compared to SpermVital semen. The results indicate that the level of acrosome-intact live spermatozoa in the AI dose did not affect the 56-day NRR for the two semen processingmethods. In conclusion, this study has showed that immobilized spermatozoa provide equal fertility results as standard processed semen when AI is performed in a blinded field trial, although the immobilization procedure caused increased sperm damage evaluated in vitro compared to standard semen processing procedure. © 2015 The Authors. Source

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