scholarly journals Comparison of BLUP and Bayesian methods for different sizes of training population in genomic selection

2020 ◽  
Vol 44 (5) ◽  
pp. 994-1002
Author(s):  
Samet Hasan ABACI ◽  
Hasan ÖNDER
Keyword(s):  
Genomic Selection ◽  
Milk Yield ◽  
Predictive Ability ◽  
Breeding Value ◽  
Training Population ◽  
Breeding Values ◽  
Value Prediction ◽  
The Usa ◽  
Population Sizes ◽  
Estimated Breeding Values

This study aims to compare the accuracy of pedigree-based and genomic-based breeding value prediction for different training population sizes. In this study, Bayes (A, B, C, Cpi) and GBLUP methods for genomic selection and BLUP method for pedigree-based selection were used. Genomic and pedigree-based breeding values were estimated for partial milk yield (158 days) of Holstein cows (400 individuals) from a private enterprise in the USA. For this aim, populations were created for indirect breeding value estimates as training (322–360) and test (78–40) populations. In animals genotyped with a 54k SNP, the marker file was encoded as –10, 0, and 10 for AA, AB, and BB marker genotypes, respectively. Bayes and GBLUP methods were performed using GenSel 4.55 software. A total of 50,000 iterations were used, with the first 5000 excluded as the burn-in. Pedigree-based breeding values were estimated by REML using MTDFREML software employing an animal model. Correlations between partial milk yield and estimated breeding values were used to assess the predictive ability for methods. Bayes B method gave the highest accuracy for the indirect estimate of breeding value.

scholarly journals Training Population Optimization for Genomic Selection in Miscanthus

2020 ◽  
Vol 10 (7) ◽  
pp. 2465-2476
Author(s):  
Marcus O. Olatoye ◽  
Lindsay V. Clark ◽  
Nicholas R. Labonte ◽  
Hongxu Dong ◽  
Maria S. Dwiyanti ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Perennial Grass ◽  
Substantial Contribution ◽  
Lignocellulosic Ethanol ◽  
Training Population ◽  
Training Set ◽  
Breeding Values ◽  
Single Clone ◽  
Estimated Breeding Values ◽  
The Ideal

Miscanthus is a perennial grass with potential for lignocellulosic ethanol production. To ensure its utility for this purpose, breeding efforts should focus on increasing genetic diversity of the nothospecies Miscanthus × giganteus (M×g) beyond the single clone used in many programs. Germplasm from the corresponding parental species M. sinensis (Msi) and M. sacchariflorus (Msa) could theoretically be used as training sets for genomic prediction of M×g clones with optimal genomic estimated breeding values for biofuel traits. To this end, we first showed that subpopulation structure makes a substantial contribution to the genomic selection (GS) prediction accuracies within a 538-member diversity panel of predominately Msi individuals and a 598-member diversity panels of Msa individuals. We then assessed the ability of these two diversity panels to train GS models that predict breeding values in an interspecific diploid 216-member M×g F2 panel. Low and negative prediction accuracies were observed when various subsets of the two diversity panels were used to train these GS models. To overcome the drawback of having only one interspecific M×g F2 panel available, we also evaluated prediction accuracies for traits simulated in 50 simulated interspecific M×g F2 panels derived from different sets of Msi and diploid Msa parents. The results revealed that genetic architectures with common causal mutations across Msi and Msa yielded the highest prediction accuracies. Ultimately, these results suggest that the ideal training set should contain the same causal mutations segregating within interspecific M×g populations, and thus efforts should be undertaken to ensure that individuals in the training and validation sets are as closely related as possible.

scholarly journals Implementation of an Economic Lifetime Net Merit for the Dual-Purpose German Black Pied Cattle Breed

Agriculture ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 41
Author(s):  
Saskia Meier ◽  
Danny Arends ◽  
Paula Korkuć ◽  
Sandra Kipp ◽  
Dierck Segelke ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Dairy Cattle ◽  
Milk Yield ◽  
Cattle Breed ◽  
Breeding Value ◽  
Dual Purpose ◽  
Breeding Values ◽  
Fitness Traits ◽  
Milk Performance ◽  
Estimated Breeding Values

Recently, a Total Merit Index (RZ€) has been developed for German Holstein dairy cattle on the basis of margin in Euro. Our aim was to adjust this lifetime net merit for the dual-purpose German Black Pied cattle breed (DSN) accounting for beef production in addition to milk performance and fitness traits. We used the estimated breeding values of DSN sires and developed a breeding value for carcass weight and quality. Furthermore, we adjusted the German Holstein marginal profits per standard deviation, which are used to calculate the estimated breeding values, to DSN-specific values. The DSN Net Merit is the sum of the three sub-indices DSN Net Milk, DSN Net Fitness, and DSN Net Beef, which contribute to the DSN Net Merit with 52.84%, 43.43%, and 3.73%, respectively. The DSN Net Merit that was calculated for 33 DSN sires ranged between EUR −1114 and +709. The DSN Net Merit strongly correlates with the Total Merit Index. The implementation of the DSN Net Merit is useful for selection and mating decisions. Especially, the sub-index DSN Net Beef, which does not correlate with existing breeding values, can be used to maintain the dual-purpose character of DSN while modestly improving milk yield. The approach can be easily adapted to other dual-purpose breeds.

scholarly journals Single and multitrait estimates of breeding values for survival using sire and animal models

2002 ◽  
Vol 75 (1) ◽  
pp. 15-24 ◽  
Author(s):  
T. H. E. Meuwissen ◽  
R. F. Veerkamp ◽  
B. Engel ◽  
S. Brotherstone
Keyword(s):  
Linear Model ◽  
Milk Yield ◽  
Survival Data ◽  
Weibull Model ◽  
Breeding Value ◽  
Breeding Values ◽  
Time Period ◽  
True Breeding ◽  
Estimated Breeding Values ◽  
Genetic Regression

AbstractSurvival data were simulated under the Weibull model in a half-sib family design, and about 50% of the records were censored. The data were analysed using the proportional hazard model (PHM) and, after transformation to survival scores, using a linear and a binary (logit) model (LIN and BIN, respectively), where the survival scores are indicators of survival during time period t given survival up to period t – 1. Correlations between estimated and true breeding values of sires (accuracies of selection) were very similar for all three models (differences were smaller than 0·3%). Daughter effects were however less accurately predicted by the LIN model, i.e.taking proper account of the distribution of the survival data yields more accurate predictions of daughter effects. The estimated variance components and regressions of true on estimated breeding values were difficult to compare for the LIN models, because estimated breeding values were expressed as additive effects on survival scores while the simulated true breeding values were expressed on the underlying scale. Also the differences in accuracy of selection between sire and animal model breeding value estimates were small, probably due to the half-sib family design of the data. To estimate breeding values for functional survival, i.e. the component of survival that is genetically independent of production (here milk yield), two methods were compared: (i) breeding values were predicted by a single-trait linear model with a phenotypic regression on milk yield; and (ii) breeding values were predicted by a two-trait linear model for survival and milk yield, and breeding values for survival corrected for milk yield were obtained by a genetic regression on the milk yield breeding value estimates. Both methods yielded very similar accuracies of selection for functional survival, and are expected to be equivalent.

scholarly journals A note on genetic parameters and accuracy of estimated breeding values in honey bees

2019 ◽  
Vol 51 (1) ◽  
Author(s):  
Evert W. Brascamp ◽  
Piter Bijma
Keyword(s):  
Honey Bees ◽  
Variance Components ◽  
Genetic Parameters ◽  
Additive Genetic Variance ◽  
Breeding Value ◽  
Phenotypic Variance ◽  
Breeding Values ◽  
Estimated Breeding Values ◽  
Additive Genetic Relationship ◽  
The Relationship

Abstract Background In honey bees, observations are usually made on colonies. The phenotype of a colony is affected by the average breeding value for the worker effect of the thousands of workers in the colony (the worker group) and by the breeding value for the queen effect of the queen of the colony. Because the worker group consists of multiple individuals, interpretation of the variance components and heritabilities of phenotypes observed on the colony and of the accuracy of selection is not straightforward. The additive genetic variance among worker groups depends on the additive genetic relationship between the drone-producing queens (DPQ) that produce the drones that mate with the queen. Results Here, we clarify how the relatedness between DPQ affects phenotypic variance, heritability and accuracy of the estimated breeding values of replacement queens. Second, we use simulation to investigate the effect of assumptions about the relatedness between DPQ in the base population on estimates of genetic parameters. Relatedness between DPQ in the base generation may differ considerably between populations because of their history. Conclusions Our results show that estimates of (co)variance components and derived genetic parameters were seriously biased (25% too high or too low) when assumptions on the relationship between DPQ in the statistical analysis did not agree with reality.

scholarly journals Genomic selection for white spot syndrome virus resistance in whiteleg shrimp boosts survival under an experimental challenge test

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Marie Lillehammer ◽  
Rama Bangera ◽  
Marcela Salazar ◽  
Sergio Vela ◽  
Edna C. Erazo ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Genetic Improvement ◽  
White Spot Syndrome Virus ◽  
Random Mating ◽  
Challenge Test ◽  
White Spot ◽  
Breeding Value ◽  
Genomic Breeding ◽  
Breeding Values ◽  
White Spot Syndrome

AbstractWhite spot syndrome virus (WSSV) causes major worldwide losses in shrimp aquaculture. The development of resistant shrimp populations is an attractive option for management of the disease. However, heritability for WSSV resistance is generally low and genetic improvement by conventional selection has been slow. This study was designed to determine the power and accuracy of genomic selection to improve WSSV resistance in Litopenaeus vannamei. Shrimp were experimentally challenged with WSSV and resistance was evaluated as dead or alive (DOA) 23 days after infestation. All shrimp in the challenge test were genotyped for 18,643 single nucleotide polymorphisms. Breeding candidates (G0) were ranked on genomic breeding values for WSSV resistance. Two G1 populations were produced, one from G0 breeders with high and the other with low estimated breeding values. A third population was produced from “random” mating of parent stock. The average survival was 25% in the low, 38% in the random and 51% in the high-genomic breeding value groups. Genomic heritability for DOA (0.41 in G1) was high for this type of trait. The realised genetic gain and high heritability clearly demonstrates large potential for further genetic improvement of WSSV resistance in the evaluated L. vannamei population using genomic selection.

Genetic line × concentrate level interactions for milk production and feed efficiency in dairy cattle

1992 ◽  
Vol 72 (2) ◽  
pp. 227-236 ◽  
Author(s):  
S. Wang ◽  
G. L. Roy ◽  
A. J. Lee ◽  
A. J. McAllister ◽  
T. R. Batra ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Milk Yield ◽  
Feed Efficiency ◽  
Production Efficiency ◽  
Breeding Value ◽  
Environment Interaction ◽  
Genetic Line ◽  
Breeding Values ◽  
Concentrate Level

Early first lactation data from 2230 cows of five research herds of Agriculture Canada were used to study the interactions of genetic line by concentrate level, and sire by concentrate level and to estimate breeding values of sires. The genetic lines were defined as Holstein (H), Ayrshire (A), and H × A or A × H (C). The interactions of sire by concentrate level were studied separately using progeny of five different mating groups: G1, H sires mated to H cows; G2, H sires mated to H, A and C cows; G3, A sires mated to A cows; G4, A sires mated to H, A and C cows; and G5, C sires mated to C cows. The interactions of genetic line by concentrate were significant (P < 0.05) for 56- to 112-d milk yield (MY112), corrected 56-to 112-d milk yield (CMY112) and feed efficiency (EFMY112 = MY112/TDN consumption). H and C cows produced more milk and were more efficient than A cows when fed high levels of concentrate. The H cattle possess a greater capacity to convert the concentrate into milk, while A cattle reach maximum milk production earlier than H cattle. The interactions of sire by concentrate were statistically significant for MY112, EFMY112 and CMY112 in G1 (P < 0.01), and G2 (P < 0.01). The breeding values of sires for MY112 were estimated using BLUP for all of the H line (BLUP-T), for half of the population consuming low amounts of concentrate (BLUP-L) and for the other half consuming high amounts (BLUP-H). A significant reranking of sires was found among the three groups. Key words: Genotype × environment interaction, milk production, efficiency, breeding value, dairy cattle

scholarly journals Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations

2016 ◽  
Vol 73 (3) ◽  
pp. 243-251 ◽  
Author(s):  
José Marcelo Soriano Viana ◽  
Hans-Peter Piepho ◽  
Fabyano Fonseca e Silva
Keyword(s):  
Genomic Selection ◽  
Quantitative Genetics ◽  
Breeding Value ◽  
Value Prediction

A comparison of genomic selection methods for breeding value prediction

2015 ◽  
Vol 60 (10) ◽  
pp. 925-935 ◽  
Author(s):  
Xin Wang ◽  
Zefeng Yang ◽  
Chenwu Xu
Keyword(s):  
Genomic Selection ◽  
Breeding Value ◽  
Selection Methods ◽  
Value Prediction

Repeatability and bias of estimated breeding values for dairy bulls and bull dams calculated from animal model evaluations

1993 ◽  
Vol 57 (2) ◽  
pp. 175-182 ◽  
Author(s):  
P. Uimari ◽  
E. A. Mäntysaari
Keyword(s):  
Animal Model ◽  
Dairy Cow ◽  
Relative Weight ◽  
Breeding Value ◽  
Potential Bias ◽  
Data Set ◽  
Breeding Values ◽  
Dairy Bulls ◽  
Estimated Breeding Values ◽  
Genetic Standard Deviation

AbstractAn animal model and an approximative method for calculating repeatabilities of estimated breeding values are used in Finnish dairy cow evaluation. Changes in estimated breeding values over time as daughters accumulate were studied. Special emphasis was given to the accuracy and potential bias in the pedigree indices of young sires. The data set used was the same as in the national evaluation and the traits investigated were protein yield and somatic cell count. The average repeatability in evaluation of bulls without daughters was 0·37. The empirical repeatability defined as a squared correlation between the pedigree index and the final sire proof was only 0·15. The reduction in the repeatability was attributed to the selection on pedigree index. The upward bias observed in pedigree indices was 5 kg (approx. 0·3 of genetic standard deviation). The bias was caused by the overestimation of bull dams' breeding value. Also the proofs of bull sires increased after the second crop of daughters. The correlation between the evaluations of the same sire calculated from two separate equal size daughter groups was 0·91 when the bull had 10 to 50 daughters and 0·87 with over 100 daughters. This illustrates how the relative weight of the pedigree decreases while more progeny information is accumulated in the evaluation.

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