Danish Agricultural Advisory Service
Danish Agricultural Advisory Service
PubMed | University of Aarhus, Natural Resources Institute Finland, Danish Agricultural Advisory Service and Swedish University of Agricultural Sciences
Type: | Journal: Genetics, selection, evolution : GSE | Year: 2016
A whole-genome association study of 4631 progeny-tested Nordic Red dairy cattle bulls using imputed next-generation sequencing data revealed a major quantitative trait locus (QTL) that affects birth index (BI) on Bos taurus autosome (BTA) 23. We analyzed this QTL to identify which of the component traits of BI are affected and understand its molecular basis.A genome-wide scan of BI in Nordic Red dairy cattle detected major QTL on BTA6, 14 and 23. The strongest associated single nucleotide polymorphism (SNP) on BTA23 was located at 13,313,896 bp with [Formula: see text]. Analyses of component traits showed that the QTL had a large effect on stillbirth. Based on the 10 most strongly associated SNPs with stillbirth, we constructed a haplotype. Among this haplotypes alleles, HAPQTL had a large negative effect on stillbirth. No animals were found to be homozygous for HAPQTL. Analysis of stillbirth records that were categorized by carrier status for HAPQTL of the sire and maternal grandsire suggested that this haplotype had a recessive mode of inheritance. Illumina BovineHD BeadChip genotypes and genotype intensity data indicated a chromosomal deletion between 12.28 and 12.81 Mbp on BTA23. An independent set of Illumina Bovine50k BeadChip genotypes identified a recessive lethal haplotype that spanned the deleted region.A deleted region of approximately 500 kb that spans three genes on BTA23 was identified and is a strong candidate QTL with a large effect on BI by increasing stillbirth.
Sun C.,University of Aarhus |
Sun C.,China Agricultural University |
Madsen P.,University of Aarhus |
Lund M.S.,University of Aarhus |
And 3 more authors.
Journal of Animal Science | Year: 2010
This study investigated the improvement in genetic evaluation of fertility traits by using production traits as secondary traits (MILK = 305-d milk yield, FAT = 305-d fat yield, and PROT = 305-d protein yield). Data including 471,742 records from first lactations of Denmark Holstein cows, covering the years of inseminations during first lactations from 1995 to 2004, were analyzed. Six fertility traits (i.e., interval in days from calving to first insemination, calving interval, days open, interval in days from first to last insemination, numbers of inseminations per conception, and nonreturn rate within 56 d after first service) were analyzed using single-and multiple-trait sire models including 1 or 3 production traits. Model stability was evaluated by correlation between EBV from 2 sub-data sets (DATAA and DATAB). Model predictive ability was assessed by the correlation between EBV from training data (DATAA or DATAB) and daughter performance (yield deviation, defined as average of daughter-records adjusted for nongenetic effects) from test data (DATAB or DATAA) in a cross-validation procedure, and correlation between EBV obtained from the whole data set (DATAT) and from a reduced data set (DATAC1, which only contained the first crop daughters) for proven bulls. In addition, the superiority of the models was evaluated by expected reliability of EBV, calculated from the prediction error variance of EBV. Based on these criteria, the models combining milk production traits showed better model stability and predictive ability than single-trait models for all the fertility traits, except for nonreturn rate within 56 d after first service. The stability and predictive ability for the model including MILK or PROT were similar to the model including all 3 milk production traits and better than the model including FAT. In addition, it was found that single-trait models underestimated genetic trend of fertility traits. These results suggested that genetic evaluation of fertility traits would be improved using a multiple-trait model including MILK or PROT. © 2010 American Society of Animal Science.
Su G.,University of Aarhus |
Madsen P.,University of Aarhus |
Nielsen U.S.,Danish Agricultural Advisory Service |
Mantysaari E.A.,Mtt Agrifood Research Finland |
And 3 more authors.
Journal of Dairy Science | Year: 2012
This study investigated the accuracy of direct genomic breeding values (DGV) using a genomic BLUP model, genomic enhanced breeding values (GEBV) using a one-step blending approach, and GEBV using a selection index blending approach for 15 traits of Nordic Red Cattle. The data comprised 6,631 bulls of which 4,408 bulls were genotyped using Illumina Bovine SNP50 BeadChip (Illumina, San Diego, CA). To validate reliability of genomic predictions, about 20% of the youngest genotyped bulls were taken as test data set. Deregressed proofs (DRP) were used as response variables for genomic predictions. Reliabilities of genomic predictions in the validation analyses were measured as squared correlations between DRP and genomic predictions corrected for reliability of DRP, based on the bulls in the test data sets. A set of weighting (scaling) factors was used to construct the combined relationship matrix among genotyped and nongenotyped bulls for one-step blending, and to scale DGV and its expected reliability in the selection index blending. Weighting (scaling) factors had a small influence on reliabilities of GEBV, but a large influence on the variation of GEBV. Based on the validation analyses, averaged over the 15 traits, the reliability of DGV for bulls without daughter records was 11.0 percentage points higher than the reliability of conventional pedigree index. Further gain of 0.9 percentage points was achieved by combining information from conventional pedigree index using the selection index blending, and gain of 1.3 percentage points was achieved by combining information of genotyped and nongenotyped bulls simultaneously applying the one-step blending. These results indicate that genomic selection can greatly improve the accuracy of preselection for young bulls in Nordic Red population, and the one-step blending approach is a good alternative to predict GEBV in practical genetic evaluation program. © 2012 American Dairy Science Association.
Gao H.,University of Aarhus |
Gao H.,China Agricultural University |
Christensen O.F.,University of Aarhus |
Madsen P.,University of Aarhus |
And 4 more authors.
Genetics Selection Evolution | Year: 2012
Background: A single-step blending approach allows genomic prediction using information of genotyped and non-genotyped animals simultaneously. However, the combined relationship matrix in a single-step method may need to be adjusted because marker-based and pedigree-based relationship matrices may not be on the same scale. The same may apply when a GBLUP model includes both genomic breeding values and residual polygenic effects. The objective of this study was to compare single-step blending methods and GBLUP methods with and without adjustment of the genomic relationship matrix for genomic prediction of 16 traits in the Nordic Holstein population. Methods: The data consisted of de-regressed proofs (DRP) for 5 214 genotyped and 9 374 non-genotyped bulls. The bulls were divided into a training and a validation population by birth date, October 1, 2001. Five approaches for genomic prediction were used: 1) a simple GBLUP method, 2) a GBLUP method with a polygenic effect, 3) an adjusted GBLUP method with a polygenic effect, 4) a single-step blending method, and 5) an adjusted single-step blending method. In the adjusted GBLUP and single-step methods, the genomic relationship matrix was adjusted for the difference of scale between the genomic and the pedigree relationship matrices. A set of weights on the pedigree relationship matrix (ranging from 0.05 to 0.40) was used to build the combined relationship matrix in the single-step blending method and the GBLUP method with a polygenetic effect. Results: Averaged over the 16 traits, reliabilities of genomic breeding values predicted using the GBLUP method with a polygenic effect (relative weight of 0.20) were 0.3% higher than reliabilities from the simple GBLUP method (without a polygenic effect). The adjusted single-step blending and original single-step blending methods (relative weight of 0.20) had average reliabilities that were 2.1% and 1.8% higher than the simple GBLUP method, respectively. In addition, the GBLUP method with a polygenic effect led to less bias of genomic predictions than the simple GBLUP method, and both single-step blending methods yielded less bias of predictions than all GBLUP methods. Conclusions: The single-step blending method is an appealing approach for practical genomic prediction in dairy cattle. Genomic prediction from the single-step blending method can be improved by adjusting the scale of the genomic relationship matrix.© 2012 Gao et al; licensee BioMed Central Ltd.
Kadri N.K.,University of Aarhus |
Sahana G.,University of Aarhus |
Charlier C.,University of Liège |
Iso-Touru T.,Mtt Agrifood Research Finland |
And 10 more authors.
PLoS Genetics | Year: 2014
In dairy cattle, the widespread use of artificial insemination has resulted in increased selection intensity, which has led to spectacular increase in productivity. However, cow fertility has concomitantly severely declined. It is generally assumed that this reduction is primarily due to the negative energy balance of high-producing cows at the peak of lactation. We herein describe the fine-mapping of a major fertility QTL in Nordic Red cattle, and identify a 660-kb deletion encompassing four genes as the causative variant. We show that the deletion is a recessive embryonically lethal mutation. This probably results from the loss of RNASEH2B, which is known to cause embryonic death in mice. Despite its dramatic effect on fertility, 13%, 23% and 32% of the animals carry the deletion in Danish, Swedish and Finnish Red Cattle, respectively. To explain this, we searched for favorable effects on other traits and found that the deletion has strong positive effects on milk yield. This study demonstrates that embryonic lethal mutations account for a non-negligible fraction of the decline in fertility of domestic cattle, and that associated positive effects on milk yield may account for part of the negative genetic correlation. Our study adds to the evidence that structural variants contribute to animal phenotypic variation, and that balancing selection might be more common in livestock species than previously appreciated. © 2014 Kadri et al.
Abildgaard L.,University of Aarhus |
Hojberg O.,University of Aarhus |
Schramm A.,University of Aarhus |
Balle K.M.,Danish Agricultural Advisory Service |
Engberg R.M.,University of Aarhus
Animal Feed Science and Technology | Year: 2010
Proliferation of Clostridium perfringens type A in the broiler intestinal tract is related to poor growth and litter quality, and can under certain conditions lead to the development of necrotic enteritis (NE), a severe gastrointestinal disease in broilers. The aim of the present study was to investigate the influence of a commercial essential oil blend, CRINA® Poultry, on the intestinal C. perfringens population in broilers vaccinated against coccidiosis. The observed C. perfringens levels were relatively high in general and peaked at 27 days of bird age with numbers ranging from 7 to 8 log cells per g of ileal and caecal content; these numbers correspond to those typically found in birds suffering from NE. No C. perfringens-related pathological changes were observed, however, indicating low levels of virulent strains among the C. perfringens or lack of other predisposing factors. Dietary concentrations of 100 and 200 mg/kg feed of the essential oil blend did not reduce the intestinal numbers of C. perfringens compared to a non-supplemented control group (P>0.05). Further, the essential oil blend failed to improve (P>0.05) both the growth and feed conversion ratio of the broilers. For rapid quantification of C. perfringens type A in broilers, a real-time PCR assay, targeting the α-toxin-encoding plc gene, was developed for use in ileal and caecal samples and was shown to be a fast and reliable alternative to conventional plate counting. © 2010 Elsevier B.V. All rights reserved.
Kristensen N.B.,University of Aarhus |
Sloth K.H.,Agro Technology A S |
Hojberg O.,University of Aarhus |
Spliid N.H.,University of Aarhus |
And 2 more authors.
Journal of Dairy Science | Year: 2010
The present study aimed to investigate the effects of 2 corn silage inoculation strategies (homofermentative vs. heterofermentative inoculation) under field conditions and to monitor responses in silage variables over the feeding season from January to August. Thirty-nine commercial dairy farms participated in the study. Farms were randomly assigned to 1 of 3 treatments: control (nonactive carrier; Chr. Hansen A/S, Hørsholm, Denmark), Lactisil (inoculation with 1 × 105 Lactobacillus pentosus and 2.5 × 104 Pediococcus pentosaceus per gram of fresh matter; Chr. Hansen A/S), and Lalsil Fresh (inoculation with 3 × 105 Lactobacillus buchneri NCIMB 40788 per gram of fresh matter; Lallemand Animal Nutrition, Blagnac, France). Inoculation with Lactisil had no effects on fermentation variables and aerobic stability. On the contrary, inoculation with Lalsil Fresh doubled the aerobic stability: 37, 38, and 80±8h for control, Lactisil, and Lalsil Fresh, respectively. The effect of Lalsil Fresh on aerobic stability tended to differ between sampling times, indicating a reduced difference between treatments in samples collected in April. Lalsil Fresh inoculation increased silage pH and contents of acetic acid, propionic acid, propanol, propyl acetate, 2-butanol, propylene glycol, ammonia, and free AA. The contents and ratios of dl-lactic acid, l-lactic acid relative to dl-lactic acid, free glucose, and dl-lactic acid relative to acetic acid decreased with Lalsil Fresh inoculation. Lalsil Fresh inoculation increased the silage counts of total lactic acid bacteria and reduced yeast counts. The Fusarium toxins deoxynivalenol, nivalenol, and zearalenone were detected in all silages at all collections, but the contents were not affected by ensiling time or by inoculation treatment. The effect of inoculation treatments on milk production was assessed by collecting test-day results from the involved farms and comparing the actual milk production with predicted milk production within farm based on test-day results from 2007 and 2008. The average milk production of lactating cows at test days during the study (January to September 2009) was 30.7±0.5kg of energy-corrected milk/d. Milk production was 104.6±0.7% of the predicted yield and did not differ among treatments. In conclusion, the present study showed that homofermentative inoculants might not compete efficiently or might not deviate sufficiently from the epiphytic flora on whole-crop corn to affect fermentation in standard qualities of corn silage. Heterofermentative inoculation increased aerobic stability and numerous fermentation variables. None of the treatments affected milk production, and more-stable corn silage seemed to have a similar production value as compared with less-stable homofermented silage. Heterofermented silage can be evaluated for its properties to limit aerobic silage deterioration in the feed chain. © 2010 American Dairy Science Association.
PubMed | University of Aarhus, Danish Agricultural Advisory Service, Nordic Cattle Genetic Evaluation, Mtt Agrifood Research Finland and University of Liège
Type: Journal Article | Journal: PLoS genetics | Year: 2014
In dairy cattle, the widespread use of artificial insemination has resulted in increased selection intensity, which has led to spectacular increase in productivity. However, cow fertility has concomitantly severely declined. It is generally assumed that this reduction is primarily due to the negative energy balance of high-producing cows at the peak of lactation. We herein describe the fine-mapping of a major fertility QTL in Nordic Red cattle, and identify a 660-kb deletion encompassing four genes as the causative variant. We show that the deletion is a recessive embryonically lethal mutation. This probably results from the loss of RNASEH2B, which is known to cause embryonic death in mice. Despite its dramatic effect on fertility, 13%, 23% and 32% of the animals carry the deletion in Danish, Swedish and Finnish Red Cattle, respectively. To explain this, we searched for favorable effects on other traits and found that the deletion has strong positive effects on milk yield. This study demonstrates that embryonic lethal mutations account for a non-negligible fraction of the decline in fertility of domestic cattle, and that associated positive effects on milk yield may account for part of the negative genetic correlation. Our study adds to the evidence that structural variants contribute to animal phenotypic variation, and that balancing selection might be more common in livestock species than previously appreciated.
Makgahlela M.L.,University of Helsinki |
Makgahlela M.L.,Mtt Agrifood Research Finland |
Mantysaari E.A.,Mtt Agrifood Research Finland |
Stranden I.,Mtt Agrifood Research Finland |
And 5 more authors.
Journal of Animal Breeding and Genetics | Year: 2013
The current study evaluates reliability of genomic predictions in selection candidates using multi-trait random regression model, which accounts for interactions between marker effects and breed of origin in the Nordic Red dairy cattle (RDC). The population structure of the RDC is admixed. Data consisted of individual animal breed proportions calculated from the full pedigree, deregressed proofs (DRP) of published estimated breeding values (EBV) for yield traits and genotypic data for 37 595 single nucleotide polymorphic markers. The analysed data included 3330 bulls in the reference population and 812 bulls that were used for validation. Direct genomic breeding values (DGV) were estimated using the model under study, which accounts for breed effects and also with GBLUP, which assume uniform population. Validation reliability was calculated as a coefficient of determination from weighted regression of DRP on DGV (rDRP,DGV 2), scaled by the mean reliability of DRP. Using the breed-specific model increased the reliability of DGV by 2 and 3% for milk and protein, respectively, when compared to homogeneous population GBLUP. The exception was for fat, where there was no gain in reliability. Estimated validation reliabilities were low for milk (0.32) and protein (0.32) and slightly higher (0.42) for fat. © 2012 Blackwell Verlag GmbH.
PubMed | University of Oulu, Danish Agricultural Advisory Service and Mtt Agrifood Research Finland
Type: Journal Article | Journal: Journal of dairy science | Year: 2014
The observed low accuracy of genomic selection in multibreed and admixed populations results from insufficient linkage disequilibrium between markers and trait loci. Failure to remove variation due to the population structure may also hamper the prediction accuracy. We verified if accounting for breed origin of alleles in the calculation of genomic relationships would improve the prediction accuracy in an admixed population. Individual breed proportions derived from the pedigree were used to estimate breed-wise allele frequencies (AF). Breed-wise and across-breed AF were estimated from the currently genotyped population and also in the base population. Genomic relationship matrices (G) were subsequently calculated using across-breed (GAB) and breed-wise (GBW) AF estimated in the currently genotyped and also in the base population. Unified relationship matrices were derived by combining different G with pedigree relationships in the evaluation of genomic estimated breeding values (GEBV) for genotyped and ungenotyped animals. The validation reliabilities and inflation of GEBV were assessed by a linear regression of deregressed breeding value (deregressed proofs) on GEBV, weighted by the reliability of deregressed proofs. The regression coefficients (b1) from GAB ranged from 0.76 for milk to 0.90 for protein. Corresponding b1 terms from GBW ranged from 0.72 to 0.88. The validation reliabilities across 4 evaluations with different G were generally 36, 40, and 46% for milk, protein, and fat, respectively. Unexpectedly, validation reliabilities were generally similar across different evaluations, irrespective of AF used to compute G. Thus, although accounting for the population structure in GBW tends to simplify the blending of genomic- and pedigree-based relationships, it appeared to have little effect on the validation reliabilities.