The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Raluca G Mateescu - One of the best experts on this subject based on the ideXlab platform.
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population structure and genomic breed composition in an angus brahman crossbred cattle population
Frontiers in Genetics, 2018Co-Authors: Mesfin Gobena, Mauricio A Elzo, Raluca G MateescuAbstract:Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus-Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying Principal Component Analysis and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. Principal Component Analysis results offered additional insight into the different hierarchies of genetic variation structuring. The first Principal Component was strongly correlated with Angus-Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage – indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals. This was most likely due to inaccuracies in the pedigree-based estimation of breed composition, which supported the case for using genomic information to complement and/or replace pedigree information when estimating breed composition. Comparison with a supervised analysis where Purebreds are used as the training set suggest that accurate predictions can be achieved even in the absence of purebred population information.
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population structure and genomic breed composition in an angus brahman crossbred cattle population
Frontiers in Genetics, 2018Co-Authors: Mesfin Gobena, Mauricio A Elzo, Raluca G MateescuAbstract:Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete, or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus-Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying principal component analysis (PCA) and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. PCA results offered additional insight into the different hierarchies of genetic variation structuring. The first principal component was strongly correlated with Angus-Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage-indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals. This was most likely due to inaccuracies in the pedigree-based estimation of breed composition, which supported the case for using genomic information to complement and/or replace pedigree information when estimating breed composition. Comparison with a supervised analysis where Purebreds are used as the training set suggest that accurate predictions can be achieved even in the absence of purebred population information.
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Population Structure and Genomic Breed Composition in an Angus–Brahman Crossbred Cattle Population
Frontiers Media S.A., 2018Co-Authors: Mesfin Gobena, Mauricio A Elzo, Raluca G MateescuAbstract:Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete, or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus–Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying principal component analysis (PCA) and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. PCA results offered additional insight into the different hierarchies of genetic variation structuring. The first principal component was strongly correlated with Angus–Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage—indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals. This was most likely due to inaccuracies in the pedigree-based estimation of breed composition, which supported the case for using genomic information to complement and/or replace pedigree information when estimating breed composition. Comparison with a supervised analysis where Purebreds are used as the training set suggest that accurate predictions can be achieved even in the absence of purebred population information
Mesfin Gobena - One of the best experts on this subject based on the ideXlab platform.
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population structure and genomic breed composition in an angus brahman crossbred cattle population
Frontiers in Genetics, 2018Co-Authors: Mesfin Gobena, Mauricio A Elzo, Raluca G MateescuAbstract:Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus-Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying Principal Component Analysis and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. Principal Component Analysis results offered additional insight into the different hierarchies of genetic variation structuring. The first Principal Component was strongly correlated with Angus-Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage – indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals. This was most likely due to inaccuracies in the pedigree-based estimation of breed composition, which supported the case for using genomic information to complement and/or replace pedigree information when estimating breed composition. Comparison with a supervised analysis where Purebreds are used as the training set suggest that accurate predictions can be achieved even in the absence of purebred population information.
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population structure and genomic breed composition in an angus brahman crossbred cattle population
Frontiers in Genetics, 2018Co-Authors: Mesfin Gobena, Mauricio A Elzo, Raluca G MateescuAbstract:Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete, or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus-Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying principal component analysis (PCA) and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. PCA results offered additional insight into the different hierarchies of genetic variation structuring. The first principal component was strongly correlated with Angus-Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage-indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals. This was most likely due to inaccuracies in the pedigree-based estimation of breed composition, which supported the case for using genomic information to complement and/or replace pedigree information when estimating breed composition. Comparison with a supervised analysis where Purebreds are used as the training set suggest that accurate predictions can be achieved even in the absence of purebred population information.
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Population Structure and Genomic Breed Composition in an Angus–Brahman Crossbred Cattle Population
Frontiers Media S.A., 2018Co-Authors: Mesfin Gobena, Mauricio A Elzo, Raluca G MateescuAbstract:Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete, or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus–Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying principal component analysis (PCA) and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. PCA results offered additional insight into the different hierarchies of genetic variation structuring. The first principal component was strongly correlated with Angus–Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage—indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals. This was most likely due to inaccuracies in the pedigree-based estimation of breed composition, which supported the case for using genomic information to complement and/or replace pedigree information when estimating breed composition. Comparison with a supervised analysis where Purebreds are used as the training set suggest that accurate predictions can be achieved even in the absence of purebred population information
Robert D. Schnabel - One of the best experts on this subject based on the ideXlab platform.
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comparison of molecular breeding values based on within and across breed training in beef cattle
Genetics Selection Evolution, 2013Co-Authors: Stephen D Kachman, Mark R Thallman, Lars Alexander Kuehn, Mahdi Saatchi, Matthew L Spangler, Kathryn J Hanford, G L Bennett, Warren M. Snelling, Dorian J. Garrick, Robert D. SchnabelAbstract:Background: Although the efficacy of genomic predictors based on within-breed training looks promising, it is necessary to develop and evaluate across-breed predictors for the technology to be fully applied in the beef industry. The efficacies of genomic predictors trained in one breed and utilized to predict genetic merit in differing breeds based on simulation studies have been reported, as have the efficacies of predictors trained using data from multiple breeds to predict the genetic merit of Purebreds. However, comparable studies using beef cattle field data have not been reported. Methods: Molecular breeding values for weaning and yearling weight were derived and evaluated using a database containing BovineSNP50 genotypes for 7294 animals from 13 breeds in the training set and 2277 animals from seven breeds (Angus, Red Angus, Hereford, Charolais, Gelbvieh, Limousin, and Simmental) in the evaluation set. Six single-breed and four across-breed genomic predictors were trained using pooled data from purebred animals. Molecular breeding values were evaluated using field data, including genotypes for 2227 animals and phenotypic records of animals born in 2008 or later. Accuracies of molecular breeding values were estimated based on the genetic correlation between the molecular breeding value and trait phenotype. Results: With one exception, the estimated genetic correlations of within-breed molecular breeding values with trait phenotype were greater than 0.28 when evaluated in the breed used for training. Most estimated genetic correlations for the across-breed trained molecular breeding values were moderate (> 0.30). When molecular breeding values were evaluated in breeds that were not in the training set, estimated genetic correlations clustered around zero. Conclusions: Even for closely related breeds, within- or across-breed trained molecular breeding values have limited prediction accuracy for breeds that were not in the training set. For breeds in the training set, across- and within-breed trained molecular breeding values had similar accuracies. The benefit of adding data from other breeds to a within-breed training population is the ability to produce molecular breeding values that are more robust across breeds and these can be utilized until enough training data has been accumulated to allow for a within-breed training set.
Dorian J. Garrick - One of the best experts on this subject based on the ideXlab platform.
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comparison of molecular breeding values based on within and across breed training in beef cattle
Genetics Selection Evolution, 2013Co-Authors: Stephen D Kachman, Mark R Thallman, Lars Alexander Kuehn, Mahdi Saatchi, Matthew L Spangler, Kathryn J Hanford, G L Bennett, Warren M. Snelling, Dorian J. Garrick, Robert D. SchnabelAbstract:Background: Although the efficacy of genomic predictors based on within-breed training looks promising, it is necessary to develop and evaluate across-breed predictors for the technology to be fully applied in the beef industry. The efficacies of genomic predictors trained in one breed and utilized to predict genetic merit in differing breeds based on simulation studies have been reported, as have the efficacies of predictors trained using data from multiple breeds to predict the genetic merit of Purebreds. However, comparable studies using beef cattle field data have not been reported. Methods: Molecular breeding values for weaning and yearling weight were derived and evaluated using a database containing BovineSNP50 genotypes for 7294 animals from 13 breeds in the training set and 2277 animals from seven breeds (Angus, Red Angus, Hereford, Charolais, Gelbvieh, Limousin, and Simmental) in the evaluation set. Six single-breed and four across-breed genomic predictors were trained using pooled data from purebred animals. Molecular breeding values were evaluated using field data, including genotypes for 2227 animals and phenotypic records of animals born in 2008 or later. Accuracies of molecular breeding values were estimated based on the genetic correlation between the molecular breeding value and trait phenotype. Results: With one exception, the estimated genetic correlations of within-breed molecular breeding values with trait phenotype were greater than 0.28 when evaluated in the breed used for training. Most estimated genetic correlations for the across-breed trained molecular breeding values were moderate (> 0.30). When molecular breeding values were evaluated in breeds that were not in the training set, estimated genetic correlations clustered around zero. Conclusions: Even for closely related breeds, within- or across-breed trained molecular breeding values have limited prediction accuracy for breeds that were not in the training set. For breeds in the training set, across- and within-breed trained molecular breeding values had similar accuracies. The benefit of adding data from other breeds to a within-breed training population is the ability to produce molecular breeding values that are more robust across breeds and these can be utilized until enough training data has been accumulated to allow for a within-breed training set.
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genomic selection of purebred animals for crossbred performance in the presence of dominant gene action
Genetics Selection Evolution, 2013Co-Authors: Jian Zeng, Ali Toosi, Rohan L. Fernando, Jack C M Dekkers, Dorian J. GarrickAbstract:Genomic selection is an appealing method to select Purebreds for crossbred performance. In the case of crossbred records, single nucleotide polymorphism (SNP) effects can be estimated using an additive model or a breed-specific allele model. In most studies, additive gene action is assumed. However, dominance is the likely genetic basis of heterosis. Advantages of incorporating dominance in genomic selection were investigated in a two-way crossbreeding program for a trait with different magnitudes of dominance. Training was carried out only once in the simulation. When the dominance variance and heterosis were large and overdominance was present, a dominance model including both additive and dominance SNP effects gave substantially greater cumulative response to selection than the additive model. Extra response was the result of an increase in heterosis but at a cost of reduced purebred performance. When the dominance variance and heterosis were realistic but with overdominance, the advantage of the dominance model decreased but was still significant. When overdominance was absent, the dominance model was slightly favored over the additive model, but the difference in response between the models increased as the number of quantitative trait loci increased. This reveals the importance of exploiting dominance even in the absence of overdominance. When there was no dominance, response to selection for the dominance model was as high as for the additive model, indicating robustness of the dominance model. The breed-specific allele model was inferior to the dominance model in all cases and to the additive model except when the dominance variance and heterosis were large and with overdominance. However, the advantage of the dominance model over the breed-specific allele model may decrease as differences in linkage disequilibrium between the breeds increase. Retraining is expected to reduce the advantage of the dominance model over the alternatives, because in general, the advantage becomes important only after five or six generations post-training. Under dominance and without retraining, genomic selection based on the dominance model is superior to the additive model and the breed-specific allele model to maximize crossbred performance through purebred selection.
D P Berry - One of the best experts on this subject based on the ideXlab platform.
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carcass characteristics of cattle differing in jersey proportion
Journal of Dairy Science, 2018Co-Authors: D P Berry, Maria Judge, R D Evans, F Buckley, A R CromieAbstract:ABSTRACT Comparison of alternative dairy (cross-)breeding programs requires full appraisals of all revenues and costs, including beef merit. Few studies exist on carcass characteristics of crossbred dairy progeny originating from dairy herds as well as their dams. The objective of the present study was to quantify, using a national database, the carcass characteristics of young animals and cows differing in their fraction of Jersey. The data set consisted of 117,593 young animals and 42,799 cows. The associations between a combination of sire and dam breed proportion (just animal breed proportion when the dependent variable was on cows) with age at slaughter (just for young animals), carcass weight, conformation, fat score, price per kilogram, and total carcass value were estimated using mixed models that accounted for covariances among herdmates of the same sex slaughtered in close proximity in time; we also accounted for age at slaughter in young animals (which was substituted with carcass weight and carcass fat score when the dependent variable was age at slaughter), animal sex, parity of the cow or dam (where relevant), and temporal effects represented by a year-by-month 2-way interaction. For young animals, the heaviest of the dairy carcasses were from the mating of a Holstein-Friesian dam and a Holstein-Friesian sire (323.34 kg), whereas the lightest carcasses were from the mating of a purebred Jersey dam to a purebred Jersey sire which were 46.31 kg lighter (standard error of the difference = 1.21 kg). The young animal carcass weight of an F1 Holstein-Friesian × Jersey cross was 20.4 to 27.0 kg less than that of a purebred Holstein-Friesian animal. The carcass conformation of a Holstein-Friesian young animal was 26% superior to that of a purebred Jersey, translating to a difference of 0.78 conformation units on a scale of 1 to 15. Purebred Holstein-Friesians produced carcasses with less fat than their purebred Jersey counterparts. The difference in carcass price per kilogram among the alternative sire-dam breed combinations investigated was minimal, although large differences existed among the different breed types for overall carcass value; the carcass value of a Holstein-Friesian animal was 20% greater than that of a Jersey animal. Purebred Jersey animals required, on average, 21 d longer to reach a given carcass weight and fat score relative to a purebred Holstein-Friesian. The difference in age at slaughter between a purebred Holstein-Friesian animal and the mating between a Holstein-Friesian sire with a Jersey dam, and vice versa, was between 7.0 and 8.9 d. A 75.8-kg difference in carcass weight existed between the carcass of a purebred Jersey cow and that of a Holstein-Friesian cow; a 50% Holstein–Friesian-50% Jersey cow had a carcass 42.0 kg lighter than that of a purebred Holstein-Friesian cow. Carcass conformation was superior in purebred Holstein-Friesian compared with purebred Jersey cows. Results from this study represent useful input parameters to populate simulation models of alternative breeding programs on dairy farms, and to help beef farmers evaluate the cost-benefit of rearing, for slaughter, animals differing in Jersey fraction.
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milk production and fertility performance of holstein friesian and jersey purebred cows and their respective crosses in seasonal calving commercial farms
Journal of Dairy Science, 2016Co-Authors: E L Coffey, R D Evans, B Horan, D P BerryAbstract:There is renewed interest in dairy cow crossbreeding in Ireland as a means to further augment productivity and profitability. The objective of the present study was to compare milk production and fertility performance for Holstein, Friesian, and Jersey purebred cows, and their respective crosses in 40 Irish spring-calving commercial dairy herds from the years 2008 to 2012. Data on 24,279 lactations from 11,808 cows were available. The relationship between breed proportion, as well as heterosis and recombination coefficients with performance, was quantified within a mixed model framework that also contained the fixed effects of parity; cow and contemporary group of herd-year-season of calving were both included as random effects in the mixed model. Breed proportion was associated with all milk production parameters investigated. Milk yield was greatest for Holstein (5,217kg), intermediate for Friesian (4,591kg), and least for Jersey (4,230kg), whereas milk constituents (i.e., fat and protein concentration) were greatest for Jersey (9.38%), intermediate for Friesian (7.91%), and least for Holstein (7.75%). Yield of milk solids in crossbred cows exceeded their respective parental average performance; greatest milk solids yield (i.e., fat kg + protein kg) was observed in the Holstein × Jersey first-cross, yielding 25kg more than the mid-parent mean. There was no consistent breed effect on the reproductive traits investigated. Relative to the mid-parent mean, Holstein × Jersey cows calved younger as heifers and had a shorter calving interval. Friesian × Jersey first-cross cows also had a shorter calving interval relative to their mid-parent mean. Results were consistent with findings from smaller-scale controlled experiments. Breed complementarity and heterosis attainable from crossbreeding resulted in superior animal performance and, consequently, greater expected profitability in crossbred cows compared with their respective Purebreds.
