American Angus Association

Saint Joseph, MO, United States

American Angus Association

Saint Joseph, MO, United States
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Rolf M.M.,University of Missouri | Taylor J.F.,University of Missouri | Schnabel R.D.,University of Missouri | McKay S.D.,University of Missouri | And 4 more authors.
BMC Genetics | Year: 2010

Background: Molecular estimates of breeding value are expected to increase selection response due to improvements in the accuracy of selection and a reduction in generation interval, particularly for traits that are difficult or expensive to record or are measured late in life. Several statistical methods for incorporating molecular data into breeding value estimation have been proposed, however, most studies have utilized simulated data in which the generated linkage disequilibrium may not represent the targeted livestock population. A genomic relationship matrix was developed for 698 Angus steers and 1,707 Angus sires using 41,028 single nucleotide polymorphisms and breeding values were estimated using feed efficiency phenotypes (average daily feed intake, residual feed intake, and average daily gain) recorded on the steers. The number of SNPs needed to accurately estimate a genomic relationship matrix was evaluated in this population.Results: Results were compared to estimates produced from pedigree-based mixed model analysis of 862 Angus steers with 34,864 identified paternal relatives but no female ancestors. Estimates of additive genetic variance and breeding value accuracies were similar for AFI and RFI using the numerator and genomic relationship matrices despite fewer animals in the genomic analysis. Bootstrap analyses indicated that 2,500-10,000 markers are required for robust estimation of genomic relationship matrices in cattle.Conclusions: This research shows that breeding values and their accuracies may be estimated for commercially important sires for traits recorded in experimental populations without the need for pedigree data to establish identity by descent between members of the commercial and experimental populations when at least 2,500 SNPs are available for the generation of a genomic relationship matrix. © 2010 Rolf et al; licensee BioMed Central Ltd.

Boddhireddy P.,Zoetis Inc. | Kelly M.J.,University of Queensland | Northcutt S.,American Angus Association | Prayaga K.C.,Zoetis Inc. | And 2 more authors.
Journal of Animal Science | Year: 2014

Advances in genomics, molecular biology, and statistical genetics have created a paradigm shift in the way livestock producers pursue genetic improvement in their herds. The nexus of these technologies has resulted in combining genotypic and phenotypic information to compute genomically enhanced measures of genetic merit of individual animals. However, large numbers of genotyped and phenotyped animals are required to produce robust estimates of the effects of SNP that are summed together to generate direct genomic breeding values (DGV). Data on 11,756 Angus animals genotyped with the Illumina BovineSNP50 Beadchip were used to develop genomic predictions for 17 traits reported by the American Angus Association through Angus Genetics Inc. in their National Cattle Evaluation program. Marker effects were computed using a 5-fold crossvalidation approach and a Bayesian model averaging algorithm. The accuracies were examined with EBV and deregressed EBV (DEBV) response variables and with K-means and identical by state (IBS)-based cross-validation methodologies. The cross-validation accuracies obtained using EBV response variables were consistently greater than those obtained using DEBV (average correlations were 0.64 vs. 0.57). The accuracies obtained using K-means cross-validation were consistently smaller than accuracies obtained with the IBS-based cross-validation approach (average correlations were 0.58 vs. 0.64 with EBV used as a response variable). Comparing the results from the current study with the results from a similar study consisting of only 2,253 records indicated that larger training population size resulted in higher accuracies in validation animals and explained on average 18% (69% improvement) additional genetic variance across all traits. © 2014 American Society of Animal Science. All rights reserved.

Decker J.E.,University of Missouri | Vasco D.A.,University of Missouri | Vasco D.A.,Duke University | McKay S.D.,University of Missouri | And 11 more authors.
BMC Genomics | Year: 2012

Background: Several methods have recently been developed to identify regions of the genome that have been exposed to strong selection. However, recent theoretical and empirical work suggests that polygenic models are required to identify the genomic regions that are more moderately responding to ongoing selection on complex traits. We examine the effects of multi-trait selection on the genome of a population of US registered Angus beef cattle born over a 50-year period representing approximately 10 generations of selection. We present results from the application of a quantitative genetic model, called Birth Date Selection Mapping, to identify signatures of recent ongoing selection.Results: We show that US Angus cattle have been systematically selected to alter their mean additive genetic merit for most of the 16 production traits routinely recorded by breeders. Using Birth Date Selection Mapping, we estimate the time-dependency of allele frequency for 44,817 SNP loci using genomic best linear unbiased prediction, generalized least squares, and BayesCπ analyses. Finally, we reconstruct the primary phenotypes that have historically been exposed to selection from a genome-wide analysis of the 16 production traits and gene ontology enrichment analysis.Conclusions: We demonstrate that Birth Date Selection Mapping utilizing mixed models corrects for time-dependent pedigree sampling effects that lead to spurious SNP associations and reveals genomic signatures of ongoing selection on complex traits. Because multiple traits have historically been selected in concert and most quantitative trait loci have small effects, selection has incrementally altered allele frequencies throughout the genome. Two quantitative trait loci of large effect were not the most strongly selected of the loci due to their antagonistic pleiotropic effects on strongly selected phenotypes. Birth Date Selection Mapping may readily be extended to temporally-stratified human or model organism populations. © 2012 Decker et al.; licensee BioMed Central Ltd.

McClure M.C.,University of Missouri | Morsci N.S.,University of Wisconsin - Madison | Schnabel R.D.,University of Missouri | Kim J.W.,University of Missouri | And 8 more authors.
Animal Genetics | Year: 2010

To gain insight into the number of loci of large effect that underlie variation in cattle, a quantitative trait locus (QTL) scan for 14 economically important traits was performed in two commercial Angus populations using 390 microsatellites, 11 single nucleotide polymorphisms (SNPs) and one duplication loci. The first population comprised 1769 registered Angus bulls born between 1955 and 2003, with Expected Progeny Differences computed by the American Angus Association. The second comprised 38 half-sib families containing 1622 steers with six post-natal growth and carcass phenotypes. Linkage analysis was performed by half-sib least squares regression with gridqtl or Bayesian Markov chain Monte Carlo analysis of complex pedigrees with loki. Of the 673 detected QTL, only 118 have previously been reported, reflecting both the conservative approach to QTL reporting in the literature, and the more liberal approach taken in this study. From 33 to 71% of the genetic variance and 35 to 56% of the phenotypic variance in each trait was explained by the detected QTL. To analyse the effects of 11 SNPs and one duplication locus within candidate genes on each trait, a single marker analysis was performed by fitting an additive allele substitution model in both mapping populations. There were 53 associations detected between the SNP/duplication loci and traits with log10P nominal 4.0, where each association explained 0.92% to 4.4% of the genetic variance and 0.01% to 1.86% of the phenotypic variance. Of these associations, only six SNP/duplication loci were located within 8 cM of a QTL peak for the trait, with two being located at the QTL peak: SST-DG156121:c. 362A>G for ribeye muscle area and TG-X05380:c.422C>T for calving ease. Strong associations between several SNP/duplication loci and trait variation were obtained in the absence of any detected linked QTL. However, we reject the causality of several commercialized DNA tests, including an association between TG-X05380:c.422C>T and marbling in Angus cattle. © 2010 Stichting International Foundation for Animal Genetics.

Rolf M.M.,University of Missouri | Taylor J.F.,University of Missouri | Schnabel R.D.,University of Missouri | McKay S.D.,University of Missouri | And 4 more authors.
Animal Genetics | Year: 2012

Estimated breeding values for average daily feed intake (AFI; kg/day), residual feed intake (RFI; kg/day) and average daily gain (ADG; kg/day) were generated using a mixed linear model incorporating genomic relationships for 698 Angus steers genotyped with the Illumina BovineSNP50 assay. Association analyses of estimated breeding values (EBVs) were performed for 41 028 single nucleotide polymorphisms (SNPs), and permutation analysis was used to empirically establish the genome-wide significance threshold (P < 0.05) for each trait. SNPs significantly associated with each trait were used in a forward selection algorithm to identify genomic regions putatively harbouring genes with effects on each trait. A total of 53, 66 and 68 SNPs explained 54.12% (24.10%), 62.69% (29.85%) and 55.13% (26.54%) of the additive genetic variation (when accounting for the genomic relationships) in steer breeding values for AFI, RFI and ADG, respectively, within this population. Evaluation by pathway analysis revealed that many of these SNPs are in genomic regions that harbour genes with metabolic functions. The presence of genetic correlations between traits resulted in 13.2% of SNPs selected for AFI and 4.5% of SNPs selected for RFI also being selected for ADG in the analysis of breeding values. While our study identifies panels of SNPs significant for efficiency traits in our population, validation of all SNPs in independent populations will be necessary before commercialization. © 2011 Stichting International Foundation for Animal Genetics.

MacNeil M.D.,U.S. Department of Agriculture | Lopez-Villalobos N.,Massey University | Northcutt S.L.,American Angus Association
Journal of Animal Science | Year: 2011

Recent improvement in technologies for measuring individual feed intake has made possible the collection of data suitable for breed-wide genetic evaluation. The goals of this research were to estimate genetic parameters for components of feed efficiency and develop a prototype system for conducting a genetic evaluation of Angus cattle for feed intake. Weaning weight (WWT), postweaning BW gain (PGN), subcutaneous fat depth (SQF), and feed intake data were accumulated by the American Angus Association from a variety of cooperators and augmented with data collected for routine genetic evaluation of Angus cattle. The feed intake data were standardized (SFI, mean 0 and variance 1) within contemporary groups. Numbers of animals with observed phenotypes were 18,169, 7,107, 4,976, and 4,215 for WWT, PGN, SQF, and SFI, respectively. The 4-generation pedigree for animals with records contained 45,120 individuals. (Co) variance components were estimated with ASREML, fitting a 4-trait animal model with fixed contemporary groups for WWT, PGN, SQF, and SFI. Heritability estimates were 0.33 ± 0.03, 0.31 ± 0.04, 0.26 ± 0.04, and 0.42 ± 0.05 for direct genetic effects on WWT, PGN, SQF, and SFI, respectively. Genetic correlations of WWT and PGN with SFI were 0.40 ± 0.07 and 0.55 ± 0.10, respectively, and indicate their value as indicator traits in predicting EPD for feed intake. The genetic correlation of SQF and SFI was not different from 0. For all animals with a recorded feed intake phenotype, accuracy of their EPD for feed intake ranged from 0.16 to 0.64 with a mean of 0.26. However, 9,075 animals had an accuracy that was equal to or exceeded 0.2 for their feed intake EPD. Postanalysis calculation of measures of efficiency EPD was pursued. This work demonstrates the feasibility of conducting a national cattle evaluation for feed intake using indicator traits to reduce opportunity for selection bias, increase accuracy of the evaluation for a substantial number of animals, and ultimately facilitate calculation of selection indexes including feed intake. © 2011 American Society of Animal Science. All rights reserved.

Saatchi M.,Iowa State University | McClure M.C.,University of Missouri | McClure M.C.,U.S. Department of Agriculture | McKay S.D.,University of Missouri | And 15 more authors.
Genetics Selection Evolution | Year: 2011

Background: Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Methods. Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Results: Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. Conclusions: These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy. © 2011 Saatchi et al; licensee BioMed Central Ltd.

MacNeil M.D.,U.S. Department of Agriculture | Nkrumah J.D.,Merial Limited | Woodward B.W.,Merial Limited | Northcutt S.L.,American Angus Association
Journal of Animal Science | Year: 2010

The objectives were to estimate genetic parameters needed to elucidate the relationships of a molecular breeding value (MBV) for marbling, intra-muscular fat (IMF) of yearling bulls measured with ultrasound, and marbling score (MRB) of slaughtered steers, and to assess the utility of MBV and IMF in predicting the breeding value for MRB. Records for MRB (n = 38,296) and IMF (n = 6,594) were from the American Angus Association database used for nation-al cattle evaluation. A total of 1,006 records of MBV were used in this study. (Co)variance components were estimated with ASREML, fitting an animal model with fixed contemporary groups for MRB and IMF similar to those used in the Angus national genetic evaluation. The overall mean was the only fixed effect included in the model for MBV. Heritability estimates for carcass measures were 0.48 ± 0.03, 0.31 ± 0.03, and 0.98 ± 0.05 for MRB, IMF, and MBV, respectively. Genetic correlations of IMF and MBV with MRB were 0.56 ± 0.09 and 0.38 ± 0.10, respectively. The genetic correla-tion between IMF and MBV was 0.80 ± 0.22. These results indicate the MBV evaluated may yield a greater genetic advance of approximately 20% when used as an indicator trait for genetic prediction of MRB compared with IMF. However, neither of these indicators alone provides sufficient information to produce highly accu-rate prediction of breeding value for the economically relevant trait MRB. Given that the goal is a highly accurate prediction of true breeding value for MRB, results of this work point to the need to 1) continue progeny testing, and 2) continue increasing the genetic correlation between the MBV and MRB. © 2010 American Society of Animal Science.

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