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  • 1
    Online Resource
    Online Resource
    Polymorphisms within the APOBR gene are highly associated with milk levels of prognostic ketosis biomarkers in dairy cows
    American Physiological Society ; 2015
    In:  Physiological Genomics Vol. 47, No. 4 ( 2015-04), p. 129-137
    Details
    In: Physiological Genomics, American Physiological Society, Vol. 47, No. 4 ( 2015-04), p. 129-137
    Abstract: Essentially all high-yielding dairy cows experience a negative energy balance during early lactation leading to increased lipomobilization, which is a normal physiological response. However, a severe energy deficit may lead to high levels of ketone bodies and, subsequently, to subclinical or clinical ketosis. It has previously been reported that the ratio of glycerophosphocholine to phosphocholine in milk is a prognostic biomarker for the risk of ketosis in dairy cattle. It was hypothesized that this ratio reflects the ability to break down blood phosphatidylcholine as a fatty acid resource. In the current study, 248 animals from a previous study were genotyped with Illumina BovineSNP50 BeadChip, and genome-wide association studies were carried out for the milk levels of phosphocholine, glycerophosphocholine, and the ratio of both metabolites. It was demonstrated that the latter two traits are heritable with h 2 = 0.43 and h 2 = 0.34, respectively. A major quantitative trait locus was identified on cattle chromosome 25. The APOBR gene, coding for the apolipoprotein B receptor, is located within this region and was analyzed as a candidate gene. The analysis revealed highly significant associations of polymorphisms within the gene with glycerophosphocholine as well as the metabolite ratio. These findings support the hypothesis that differences in the ability to take up blood phosphatidylcholine from low-density lipoproteins play an important role in early lactation metabolic stability of dairy cows and indicate APOBR to contain a causative variant.
    Type of Medium: Online Resource
    ISSN: 1094-8341 , 1531-2267
    URL: Article
    DOI: 10.1152/physiolgenomics.00126.2014
    Language: English
    Publisher: American Physiological Society
    Publication Date: 2015
    detail.hit.zdb_id: 2031330-5
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  • 2
    Online Resource
    Online Resource
    Efficient genetic value prediction using incomplete omics data
    Springer Science and Business Media LLC ; 2019
    In:  Theoretical and Applied Genetics Vol. 132, No. 4 ( 2019-4), p. 1211-1222
    Details
    In: Theoretical and Applied Genetics, Springer Science and Business Media LLC, Vol. 132, No. 4 ( 2019-4), p. 1211-1222
    Type of Medium: Online Resource
    ISSN: 0040-5752 , 1432-2242
    URL: Article
    DOI: 10.1007/s00122-018-03273-1
    RVK:
    WA 15000
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 1478966-8
    SSG: 12
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  • 3
    Online Resource
    Online Resource
    Omics-based hybrid prediction in maize
    Springer Science and Business Media LLC ; 2017
    In:  Theoretical and Applied Genetics Vol. 130, No. 9 ( 2017-9), p. 1927-1939
    Details
    In: Theoretical and Applied Genetics, Springer Science and Business Media LLC, Vol. 130, No. 9 ( 2017-9), p. 1927-1939
    Type of Medium: Online Resource
    ISSN: 0040-5752 , 1432-2242
    URL: Article
    DOI: 10.1007/s00122-017-2934-0
    RVK:
    WA 15000
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 1478966-8
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  • 4
    Online Resource
    Online Resource
    31 Characterization of feeding-behavior patterns and application of chemometrics to predict residual feed intake based on feeding-behavior traits in growing Holstein heifers
    Oxford University Press (OUP) ; 2019
    In:  Journal of Animal Science Vol. 97, No. Supplement_1 ( 2019-07-29), p. 23-23
    Details
    In: Journal of Animal Science, Oxford University Press (OUP), Vol. 97, No. Supplement_1 ( 2019-07-29), p. 23-23
    Abstract: Objectives of this study were to characterize feeding-behavior (FB) patterns in growing dairy heifers with divergent RFI phenotypes (±0.50 SD) and to evaluate the accuracy of partial least squares regression (PLSR) models to predict RFI based on FB traits. Performance, DMI, and FB traits were measured for 70 to 100 d in 15 trials with Holstein heifers (n = 611) fed a corn-silage based ration. Seventeen FB traits were evaluated: frequency and duration of bunk visit (BV) and meal events, head-down duration (HDD), meal length, maximum non-feeding interval, corresponding day-today variation (SD) of these traits, and ratios of HDD per BV duration and meal duration, HDD per meal duration, and BV events per meal event. Data was analyzed using a mixed model that included RFI group and trial. The PLSR model for RFI was developed using cross-validation procedures (Leave-One-Out) in JMP (SAS), with FB traits as independent variables. LowRFI heifers consumed 24% less (P 〈 0.01) DMI and had lower (P 〈 0.01) day-to-day DMI variation than high-RFI heifers. Distinct differences were observed in FB patterns between low- and high-RFI heifers (Table 1). Eight of 17 FB traits were included [selected based on variable of importance (VIP) score 〉 0.80] in the PLSR model that explained 33% of the variation in RFI. Head-down duration had the highest VIP score; accordingly, low-RFI animals had 44% lower HDD and 30 and 40% lower ratios of HDD per BV duration and meal duration, respectively. Additionally, low-RFI animals had 20 and 18% fewer BV and meal events per day, spent 21% less time eating during BV events, and had reduced day-to-day variation in HDD and meal frequency. For this study, distinctive differences were observed in the FB patterns of Holstein heifers with divergent RFI, which explained 33% of the between-animal variation in RFI.
    Type of Medium: Online Resource
    ISSN: 0021-8812 , 1525-3163
    URL: Article
    DOI: 10.1093/jas/skz053.051
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 1490550-4
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  • 5
    Online Resource
    Online Resource
    181 Characterization of feeding-behavior patterns and application of chemometrics to predict residual feed intake based on feeding-behavior traits in growing Holstein heifers
    Oxford University Press (OUP) ; 2019
    In:  Journal of Animal Science Vol. 97, No. Supplement_1 ( 2019-07-29), p. 61-62
    Details
    In: Journal of Animal Science, Oxford University Press (OUP), Vol. 97, No. Supplement_1 ( 2019-07-29), p. 61-62
    Abstract: Objectives of this study were to characterize feeding-behavior (FB) patterns in growing dairy heifers with divergent RFI phenotypes (±0.50 SD) and to evaluate the accuracy of partial least squares regression (PLSR) models to predict RFI based on FB traits. Performance, DMI, and FB traits were measured for 70 to 100 d in 15 trials with Holstein heifers (n = 611) fed a corn-silage based ration. Seventeen FB traits were evaluated: frequency and duration of bunk visit (BV) and meal events, head-down duration (HDD), meal length, maximum non-feeding interval, corresponding day-to-day variation (SD) of these traits, and ratios of HDD per BV duration and meal duration, HDD per meal duration, and BV events per meal event. Data were analyzed using a mixed model that included RFI group and trial. The PLSR model for RFI was developed using cross-validation procedures (Leave-One-Out) in JMP (SAS), with FB traits as independent variables. Low-RFI heifers consumed 24% less (P 〈 0.01) DMI and had lower (P 〈 0.01) day-to-day DMI variation than high-RFI heifers. Distinct differences were observed in FB patterns between low- and high-RFI heifers (Table 1). Eight of 17 FB traits were included [selected based on variable of importance (VIP) score 〉 0.80] in the PLSR model that explained 33% of the variation in RFI. Head-down duration had the highest VIP score; accordingly, low-RFI animals had 44% lower HDD and 30 and 40% lower ratios of HDD per BV duration and meal duration, respectively. Additionally, low-RFI animals had 20 and 18% fewer BV and meal events per day, spent 21% less time eating during BV events, and had reduced day-to-day variation in HDD and meal frequency. For this study, distinctive differences were observed in the FB patterns of Holstein heifers with divergent RFI, which explained 33% of the between-animal variation in RFI.
    Type of Medium: Online Resource
    ISSN: 0021-8812 , 1525-3163
    URL: Article
    DOI: 10.1093/jas/skz053.138
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 1490550-4
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  • 6
    Online Resource
    Online Resource
    Novel Use of Derived Genotype Probabilities to Discover Significant Dominance Effects for Milk Production Traits in Dairy Cattle
    Oxford University Press (OUP) ; 2013
    In:  Genetics Vol. 193, No. 2 ( 2013-02-01), p. 431-442
    Details
    In: Genetics, Oxford University Press (OUP), Vol. 193, No. 2 ( 2013-02-01), p. 431-442
    Abstract: The estimation of dominance effects requires the availability of direct phenotypes, i.e., genotypes and phenotypes in the same individuals. In dairy cattle, classical QTL mapping approaches are, however, relying on genotyped sires and daughter-based phenotypes like breeding values. Thus, dominance effects cannot be estimated. The number of dairy bulls genotyped for dense genome-wide marker panels is steadily increasing in the context of genomic selection schemes. The availability of genotyped cows is, however, limited. Within the current study, the genotypes of male ancestors were applied to the calculation of genotype probabilities in cows. Together with the cows’ phenotypes, these probabilities were used to estimate dominance effects on a genome-wide scale. The impact of sample size, the depth of pedigree used in deriving genotype probabilities, the linkage disequilibrium between QTL and marker, the fraction of variance explained by the QTL, and the degree of dominance on the power to detect dominance were analyzed in simulation studies. The effect of relatedness among animals on the specificity of detection was addressed. Furthermore, the approach was applied to a real data set comprising 470,000 Holstein cows. To account for relatedness between animals a mixed-model two-step approach was used to adjust phenotypes based on an additive genetic relationship matrix. Thereby, considerable dominance effects were identified for important milk production traits. The approach might serve as a powerful tool to dissect the genetic architecture of performance and functional traits in dairy cattle.
    Type of Medium: Online Resource
    ISSN: 1943-2631
    URL: Article
    DOI: 10.1534/genetics.112.144535
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2013
    detail.hit.zdb_id: 1477228-0
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  • 7
    Online Resource
    Online Resource
    Genomic prediction of unordered categorical traits: an application to subpopulation assignment in German Warmblood horses
    Springer Science and Business Media LLC ; 2016
    In:  Genetics Selection Evolution Vol. 48, No. 1 ( 2016-12)
    Details
    In: Genetics Selection Evolution, Springer Science and Business Media LLC, Vol. 48, No. 1 ( 2016-12)
    Type of Medium: Online Resource
    ISSN: 1297-9686
    URL: Article
    DOI: 10.1186/s12711-016-0192-2
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2016
    detail.hit.zdb_id: 2012369-3
    SSG: 12
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  • 8
    Online Resource
    Online Resource
    284 Genetic Selection Through Ecofeed Index Reduces Carbon Footprint in Heifers
    Oxford University Press (OUP) ; 2021
    In:  Journal of Animal Science Vol. 99, No. Supplement_3 ( 2021-10-08), p. 145-145
    Details
    In: Journal of Animal Science, Oxford University Press (OUP), Vol. 99, No. Supplement_3 ( 2021-10-08), p. 145-145
    Abstract: Efficient feed conversion by ruminants has a direct impact on the animal’s carbon footprint. The objective of this study was to determine the effect of using the EcoFeed® index by STgenetics® to reduce methane production. The EcoFeed® index is an integrated approach to genetic selection based on progeny testing of females for residual feed intake to identify animals who consume less feed while maintaining production compared to their herd mates to increase profitability and global sustainability. EcoFeed® is moderately heritable and uncorrelated with traits currently selected for in dairy cows. A dataset containing phenotypic and genomic information on 5,441 heifers was used for the analysis. Heifers were divided into low, medium and high EcoFeed® classes based on ±0.5 SD from the mean. To estimate methane emissions, 17 mathematical models were collated from the literature. All models were subjected to evaluation of performance using an independent dataset containing 458 individual-animal methane production measurements. The model recommended by Intergovernmental Panel for Climate Change had the lowest root mean square prediction error with 1% mean bias and 3.37% slope bias. This model was used to calculate emissions from low and high EcoFeed® heifers. In addition, an average of all model results was computed and used to compare different classes of heifers. Based on dietary information and feed intake, low and high EcoFeed® heifers were estimated to produce 194 and 164 g methane/d, respectively, using the selected model. Using model averages, the estimated methane production was 186 and 162 g methane/d, for low and high EcoFeed® heifers, respectively. The reduction in emission between low and high EcoFeed® classes was 12.6 to 15.4%. If savings from crop production were to be considered, there will be further reductions in the carbon footprint. Therefore, genomic selection is a powerful tool to reduce carbon footprint in ruminants.
    Type of Medium: Online Resource
    ISSN: 0021-8812 , 1525-3163
    URL: Article
    DOI: 10.1093/jas/skab235.266
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 1490550-4
    SSG: 12
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