Preliminary genetic analysis of beef carcass data

2009 ◽  
Vol 2009 ◽  
pp. 58-58
Author(s):  
M P Coffey ◽  
E Wall ◽  
G Banos ◽  
R Roehe
Keyword(s):  
Genetic Analysis ◽  
Beef Cattle ◽  
Genetic Improvement ◽  
Selective Breeding ◽  
Cost Effective ◽  
Genetic Evaluation ◽  
Carcass Weight ◽  
Breeding Values ◽  
Estimated Breeding Values ◽  
Farm Livestock

Selective breeding of farm livestock is one of the most cost-effective ways of improving the performance and efficiency of livestock enterprises. Genetic improvement of British beef cattle over a ten year period was recently estimated to be worth approximately £23, and the benefits continue to rise (Amer et al., 2007). While these returns are impressive, they could be improved by increasing the rate of improvement in the purebred population, for example by increasing the relevance of estimated breeding values (EBVs) to beef production by using final carcass weight and grading information. This study will examine the feasibility carcass weights and classifications from UK commercial abattoirs for the genetic evaluation of cattle for carcass weight, carcass fatness class, and carcass conformation class.

scholarly journals Prediction of breeding values for group-recorded traits including genomic information and an individually recorded correlated trait

Heredity ◽  
2020 ◽  
Vol 126 (1) ◽  
pp. 206-217
Author(s):  
Xiang Ma ◽  
Ole F. Christensen ◽  
Hongding Gao ◽  
Ruihua Huang ◽  
Bjarne Nielsen ◽  
...  
Keyword(s):  
Egg Production ◽  
Quantitative Traits ◽  
Group Structure ◽  
Genetic Evaluation ◽  
Genomic Information ◽  
Bivariate Model ◽  
Breeding Values ◽  
Lower Accuracy ◽  
Small Group Size ◽  
Estimated Breeding Values

AbstractRecords on groups of individuals could be valuable for predicting breeding values when a trait is difficult or costly to measure on single individuals, such as feed intake and egg production. Adding genomic information has shown improvement in the accuracy of genetic evaluation of quantitative traits with individual records. Here, we investigated the value of genomic information for traits with group records. Besides, we investigated the improvement in accuracy of genetic evaluation for group-recorded traits when including information on a correlated trait with individual records. The study was based on a simulated pig population, including three scenarios of group structure and size. The results showed that both the genomic information and a correlated trait increased the accuracy of estimated breeding values (EBVs) for traits with group records. The accuracies of EBV obtained from group records with a size 24 were much lower than those with a size 12. Random assignment of animals to pens led to lower accuracy due to the weaker relationship between individuals within each group. It suggests that group records are valuable for genetic evaluation of a trait that is difficult to record on individuals, and the accuracy of genetic evaluation can be considerably increased using genomic information. Moreover, the genetic evaluation for a trait with group records can be greatly improved using a bivariate model, including correlated traits that are recorded individually. For efficient use of group records in genetic evaluation, relatively small group size and close relationships between individuals within one group are recommended.

Practical aspects of a genetic evaluation system using parentage assigned from genetic markers

2005 ◽  
Vol 45 (8) ◽  
pp. 935 ◽  
Author(s):  
K. G. Dodds ◽  
J. A. Sise ◽  
M. L. Tate
Keyword(s):  
Genetic Markers ◽  
Evaluation System ◽  
Fixed Effects ◽  
Genetic Evaluation ◽  
Diagnostic Systems ◽  
Breeding Values ◽  
Mating Group ◽  
Animal Management ◽  
The Mean ◽  
Estimated Breeding Values

Animal breeding values can be calculated when genetic markers have been used to help determine the parentage of some of the animals, but their parentage has been incompletely determined. The pedigree sampling method is 1 computing strategy for calculating these breeding values. This paper describes and discusses methods for dealing with a number of practical issues that arise when implementing such a system for industry use. In particular, diagnostic systems for detecting inadequacies or possible errors in the genotyping systems and the recording of animal management are developed. Also, characteristics of the best assigned pedigrees are calculated according to mating group and used to check for sires missing from these groups. The correlation between breeding values estimated from a single sampled pedigree (using parentage probabilities) and those estimated as the mean from many sampled pedigrees gives a diagnostic to indicate which estimated breeding values are more influenced by uncertainties in relationships. For the analysis of survival traits, a method to enumerate and assign likely parentage to dead offspring which have not been DNA sampled and genotyped is described. When embryo transfer technology is used, the genetic dam needs to be included as a possible dam when considering parentage. If some fixed effects which depend on the parent are missing, these can be sampled similarly to parentage, and this may improve the evaluation if certain assumptions are met. A method to provide a likely list of parents, the ‘fitted pedigree’, which is based on the most likely parents, but modified to reduce the occurrence of unlikely family sets (e.g. very large litters) is also presented. The use of these methods will enhance the practical application of DNA parenting when used in conjunction with genetic evaluation.

scholarly journals Genetic improvement of hip-extended scores in 3 breeds of guide dogs using estimated breeding values: Notable progress but more improvement is needed

PLoS ONE ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. e0212544 ◽  
Author(s):  
Eldin A. Leighton ◽  
Dolores Holle ◽  
Darryl N. Biery ◽  
Thomas P. Gregor ◽  
Mischa B. McDonald-Lynch ◽  
...  
Keyword(s):  
Genetic Improvement ◽  
Breeding Values ◽  
Guide Dogs ◽  
Estimated Breeding Values

scholarly journals Accuracies of univariate and multivariate genomic prediction models in African Cassava

2017 ◽  
Author(s):  
Uche Godfrey Okeke ◽  
Deniz Akdemir ◽  
Ismail Rabbi ◽  
Peter Kulakow ◽  
Jean-Luc Jannink
Keyword(s):  
Genomic Selection ◽  
Mixed Model ◽  
Genetic Evaluation ◽  
Environment Interaction ◽  
Genotype By Environment Interactions ◽  
Breeding Values ◽  
Genotype By Environment ◽  
Step Model ◽  
One Step ◽  
Estimated Breeding Values

List of abbreviationsGSGenomic SelectionBLUPBest Linear Unbiased PredictionEBVsEstimated Breeding ValuesEGVsEstimated genetic ValuesGEBVsGenomic Estimated Breeding ValuesSNPsSingle Nucleotide polymorphismsGxEGenotype-by-environment interactionsGxEGenotype-by-environment interactionsGxGGene-by-gene interactionsGxGxEGene-by-gene-by-environment interactionsuTUnivariate single environment one-step modeluEUnivariate multi environment one-step modelMTMulti-trait single environment one-step modelMEMultivariate single trait multi environment modelAbstractBackgroundGenomic selection (GS) promises to accelerate genetic gain in plant breeding programs especially for long cycle crops like cassava. To practically implement GS in cassava breeding, it is useful to evaluate different GS models and to develop suitable models for an optimized breeding pipeline.MethodsWe compared prediction accuracies from a single-trait (uT) and a multi-trait (MT) mixed model for single environment genetic evaluation (Scenario 1) while for multi-environment evaluation accounting for genotype-by-environment interaction (Scenario 2) we compared accuracies from a univariate (uE) and a multivariate (ME) multi-environment mixed model. We used sixteen years of data for six target cassava traits for these analyses. All models for Scenario 1 and Scenario 2 were based on the one-step approach. A 5-fold cross validation scheme with 10-repeat cycles were used to assess model prediction accuracies.ResultsIn Scenario 1, the MT models had higher prediction accuracies than the uT models for most traits and locations analyzed amounting to 32 percent better prediction accuracy on average. However for Scenario 2, we observed that the ME model had on average (across all locations and traits) 12 percent better predictive power than the uE model.ConclusionWe recommend the use of multivariate mixed models (MT and ME) for cassava genetic evaluation. These models may be useful for other plant species.

scholarly journals 61 The impact of selective phenotyping and genotyping over generations in beef cattle

2019 ◽  
Vol 97 (Supplement_2) ◽  
pp. 37-39
Author(s):  
Andrea Plotzki Reis ◽  
Rodrigo Fagundes da Costa ◽  
Fabyano Fonseca e Silva ◽  
Fernando Flores Cardoso ◽  
Matthew L Spangler
Keyword(s):  
Beef Cattle ◽  
Prediction Accuracy ◽  
Cost Benefit ◽  
Single Step ◽  
Breeding Values ◽  
Additional Information ◽  
Economic Framework ◽  
Estimated Breeding Values ◽  
The Cost ◽  
The Impact

Abstract The aim of this study was to investigate selective phenotyping to maintain adequate prediction accuracy. A simulation was conducted, with 10 replicates, using QMSim to mimic the structure and size of a Braford population. A population with 50 generations, 500 animals per generation, was created with phenotyping and genotyping beginning in generation 11. The scenarios investigated were: 1) Randomly phenotype and genotype 10, 25, 50, 75, and 100% of individuals each generation and; 2) Randomly phenotype and genotype 10, 25, 50, 75, and 100% of individuals in every-other generation. Estimated breeding values (EBV) were obtained using single-step GBLUP and accuracy was determined as the correlation between true BV from simulation and those estimated from the blupf90 family of programs. For scenarios where phenotyping and genotyping occurred every generation, EBV accuracies in generation 11 and 50 ranged from 0.32 to 0.32, 0.42 to 0.43, 0.49 to 0.51, 0.53 to 0.56 and 0.57 to 0.59 when 10, 25, 50, 75, and 100% of animals were chosen, respectively. The highest accuracies were 0.40 and 0.50 in generation 38 for scenarios 10 and 25%; 0.56, 0.61 and 0.64 in generation 40 for scenarios 50, 75 and 100%, respectively. When animals were selected every-other generation, EBV accuracy in generation 11 and 50 ranged from 0.24 to 0.26, 0.36 to 0.36, 0.43 to 0.42, 0.48 to 0.44 and 0.53 to 0.48 for 10, 25, 50, 75 and 100% of selected animals, respectively. The highest accuracies were in generation 23 for scenario 10% (0.31), in generation 37 for scenarios 25 (0.43), 50 (0.50) and 75% (0.55) and in generation 39 for 100% (0.59). Although increasing the density of phenotyped and genotyped animals increased prediction accuracy, some gains were marginal. These differences in accuracy must be contemplated in an economic framework to determine the cost-benefit of additional information.

Relations between first and second lactation characters of progeny groups and effects of tandem selection on yield improvement

1975 ◽  
Vol 21 (2) ◽  
pp. 121-125 ◽  
Author(s):  
Reuven Bar-Anan
Keyword(s):  
Standard Deviation ◽  
Genetic Improvement ◽  
Genetic Correlations ◽  
Selection Criterion ◽  
Yield Improvement ◽  
Selection Models ◽  
Breeding Values ◽  
Additional Costs ◽  
Estimated Breeding Values ◽  
Sire Selection

SUMMARYCorrelations and regressions between estimated breeding values for 122 day part-lactation, 1st and 2nd lactation yield (part, 1st, 2nd) were estimated from 106 sire progeny groups, each with at least 60 effective daughters.The genetic correlations between part, 1st and 2nd kg milk were 1·0 and 0·84 respectively, and the regressions of 1st on part and of 2nd on 1st test were 2·40 and 0·82 kg/kg milk, respectively. Selection by one standard deviation between sires on part-lactation tests would improve 1st lactation yields by an average of 204 kg milk with a standard deviation of 84 kg. Selection on 1st lactation yields by one standard deviation would increase 2nd lactation yields by an average of 183 kg milk with a standard deviation of 156 kg, indicating that some bulls so selected could have below average 2nd lactation yields.Two sire selection models were simulated differing in the selection criterion; 1 st yield in model 1, and 1 st followed by 2nd yields in model 2. The contribution of proven sires to the rate of genetic improvement in lifetime production was greater from model 2 than from model 1 by about 15% without any additional costs for bull maintenance.

Divergent breeding values for fatness or residual feed intake in Angus cattle. 6. Dam-line impacts on steer carcass compliance

2018 ◽  
Vol 58 (1) ◽  
pp. 94
Author(s):  
M. P. B. Deland ◽  
J. M. Accioly ◽  
K. J. Copping ◽  
J. F. Graham ◽  
S. J. Lee ◽  
...  
Keyword(s):  
Feed Intake ◽  
South Australia ◽  
Residual Feed Intake ◽  
Carcass Weight ◽  
Research Centre ◽  
High Fat ◽  
The South ◽  
Low Fat ◽  
Breeding Values ◽  
Estimated Breeding Values

The present study determined the impact of maternal genetics for estimated breeding values for rib fat (High-Fat, Low-Fat) or residual feed intake (RFI; High-RFI, Low-RFI) on the carcass compliance of Angus steer progeny when reared pre-weaning under High or Low-Nutrition and post-weaning under various finishing system (grazing versus short-term feedlot). The dams were joined to sires of similar genetic background (close to average estimated breeding values) and sires were rotated among all dam genotypes, with herds located at either Struan Research Centre, near Naracoorte in the south-east of South Australia, or Vasse Research Station, in the south-west of Western Australia. The breeding herd was part of the Beef CRC maternal productivity project and cows were managed under either High or Low-Nutrition, achieved by adjustments to stocking rate in rotational grazing systems and supplementary feeding, so as to maintain ~20% difference in cow liveweight. The steer progeny were weaned at ~7 months of age, with individuals from both pre-weaning nutritional treatments being treated the same from then on at each site. Steers from Struan Research Centre in South Australia born in 2008 and 2009 were sold and grown out on pasture on a local commercial property. Steer calves born in 2010 at Vasse remained on the station where they were backgrounded on hay, followed by a short period (111 days) total mixed ration containing 40% grain. In the first year, steers from Struan (n = 58) were slaughtered together at ~2 years of age, and in the second year (n = 85), consigned to six slaughter groups as their ultrasound-scanned subcutaneous P8 (rump) fat reached 7 mm and their liveweight exceeded 550 kg. Steers from Vasse (n = 101) were slaughtered at ~12 months of age, all on the same day. High-Fat-line dams produced steers with carcasses with greater P8 fat than did Low-Fat-line dams at both sites. At Struan, when the 2008-born steers were slaughtered together, more steers from Low-Fat dams failed to meet minimum fat specifications, than steers from High-Fat dams (28% vs 9% respectively). The steers born in 2009 at Struan all met processor fat specifications but steers from the Low-Fat dams took longer to reach the fat threshold, and so had greater carcass weight, but attracted more price penalties because of increased dentition. All steers from Vasse met minimum requirements for fat, with none penalised for dentition. Vasse steers from High- or Low-RFI dams performed in a manner similar to that from High- and Low-Fat dams, respectively, in that the High-RFI group produced fatter carcasses than did the Low-RFI group. Steers reared under low pre-weaning nutrition weighed less at weaning than did those on High-Nutrition, but had higher weight gains after weaning, although insufficient to result in the same carcass weight. The results showed that commercial cattle producers need to be aware of the balance and trade-off among fat breeding value, effect of pre-weaning nutrition and post-weaning growth required to ensure their cattle meet market specifications and to avoid price penalties.

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