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.

Genetic evaluation including intermediate omics features

Genetics ◽  
2021 ◽  
Author(s):  
Ole F Christensen ◽  
Vinzent Börner ◽  
Luis Varona ◽  
Andres Legarra
Keyword(s):  
Evaluation System ◽  
Mixed Model ◽  
Simulated Data ◽  
Genetic Evaluation ◽  
Omics Data ◽  
Estimation Of Parameters ◽  
Data Set ◽  
Breeding Values ◽  
Mixed Model Equation ◽  
Estimated Breeding Values

Abstract In animal and plant breeding and genetics there has been an increasing interest in intermediate omics traits, such as metabolomics and transcriptomics, that mediate the effect of genetics on the phenotype of interest. For inclusion of such intermediate traits into a genetic evaluation system, there is a need for a statistical model that integrates phenotypes, genotypes, pedigree and omics traits, and a need for associated computational methods that provide estimated breeding values. In this paper, a joint model for phenotypes and omics data is presented, and a formula for the breeding values on individuals is derived. For complete omics data, three equivalent methods for best linear unbiased prediction of breeding values are presented. In all three cases, this requires solving two mixed model equation systems. Estimation of parameters using restricted maximum likelihood is also presented. For incomplete omics data, extensions of two of these methods are presented, where in both cases the extension consists of extending an omics related similarity matrix to incorporate individuals without omics data. The methods are illustrated using a simulated data set.

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.

scholarly journals Test-day or 305-day milk yield for genetic evaluation of Gir cattle

2019 ◽  
Vol 54 ◽  
Author(s):  
Rodrigo Junqueira Pereira ◽  
Denise Rocha Ayres ◽  
Mário Luiz Santana Junior ◽  
Lenira El Faro ◽  
Aníbal Eugênio Vercesi Filho ◽  
...  
Keyword(s):  
Regression Model ◽  
Milk Yield ◽  
Genetic Evaluation ◽  
Random Regression ◽  
Breeding Values ◽  
Random Regression Model ◽  
The Mean ◽  
Yield Record ◽  
Genetic Evaluations ◽  
Dairy Breed

Abstract: The objective of this work was to compare genetic evaluations of milk yield in the Gir breed, in terms of breeding values and their accuracy, using a random regression model applied to test-day records or the traditional model (TM) applied to estimates of 305-day milk yield, as well as to predict genetic trends for parameters of interest. A total of 10,576 first lactations, corresponding to 81,135 test-day (TD) records, were used. Rank correlations between the breeding values (EBVs) predicted with the two models were 0.96. The percentage of animals selected in common was 67 or 82%, respectively, when 1 or 5% of bulls were chosen, according to EBVs from random regression model (RRM) or TM genetic evaluations. Average gains in accuracy of 2.7, 3.0, and 2.6% were observed for all animals, cows with yield record, and bulls (sires of cows with yield record), respectively, when the RRM was used. The mean annual genetic gain for 305-day milk yield was 56 kg after 1993. However, lower increases in the average EBVs were observed for the second regression coefficient, related to persistency. The RRM applied to TD records is efficient for the genetic evaluation of milk yield in the Gir dairy breed.

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.

EVALUATION OF DAIRY CATTLE FOR FINAL CLASS USING ANIMAL MODELS

1988 ◽  
Vol 68 (3) ◽  
pp. 639-645 ◽  
Author(s):  
J. JAMROZIK ◽  
L. R. SCHAEFFER
Keyword(s):  
Animal Models ◽  
Dairy Cattle ◽  
Fixed Effects ◽  
Genetic Relationships ◽  
Residual Effects ◽  
Breeding Values ◽  
Stage Of Lactation ◽  
Key Words Animal ◽  
Estimated Breeding Values ◽  
Genetic Evaluations

Estimated breeding values for final class of 364 868 Canadian Holstein Friesian cows and 10 186 bulls from three different animal models were compared. FIRST lactation, first classifications were described by a model with fixed effects of herd-round-classifier, linear and quadratic effects of age at calving and stage of lactation at classification, and random effects of additive genetic effects of cows, and residual effects. All additive genetic relationships among animals were included. A second model used the LATEST classification on each cow rather than the first and these observations were pre-adjusted for age and stage. The third model used ALL classifications on each cow, and these were also pre-adjusted for age and stage effects. Correlations among estimated breeding values between methods ranged from 0.92 to 0.95. Estimated breeding values from LATEST were most highly correlated to sire proofs from the currently official sire model which also used the latest classification of each cow. Correlations of estimated breeding values between sires and their sons showed that results from LATEST were more accurate than results from the other two models. A model similar to that for LATEST is proposed for official genetic evaluations for conformation in the Canadian Holstein population. Key words: Animal model, conformation, dairy cattle

scholarly journals Estimation of the breeding value of sport horses in the Czech Republic

2004 ◽  
Vol 52 (1) ◽  
pp. 145-152
Author(s):  
Iva Jiskrová
Keyword(s):  
Czech Republic ◽  
Random Effects ◽  
Fixed Effects ◽  
Prediction Method ◽  
Sport Performance ◽  
Breeding Value ◽  
Progeny Testing ◽  
The Czech Republic ◽  
Breeding Values ◽  
Estimated Breeding Values

The performance of 10671 horses in 10911 sport competitions was used to estimate the breeding value of the population of the Czech warm-blooded horses using the Best Linear Unibased Prediction method. The sport performance was estimated on the basis of the number of bad points (penalties) in jumping competitions. We analysed 252781 sporting results in the period 1991 – 2002. The estimations encompassed the fixed effects of sex, age, level of the competition and random effects of the breeder, rider, competition and the permanent environment. We compared the original and innovated calculations of the estimate of the breeding value of sport horses in the Czech Republic. We then compiled a list of estimated breeding values for stallions having 30 or more offspring and we compared the estimated breeding values with the results of the official system of progeny testing for performance in the Czech Republic.

scholarly journals 60 Re-ranking of estimated breeding values using different panel densities with ssGBLUP in broiler chickens

2019 ◽  
Vol 97 (Supplement_2) ◽  
pp. 36-37
Author(s):  
Mayara Salvian ◽  
Gerson Barreto Mourão ◽  
Gabriel Costa Monteiro Moreira ◽  
Mônica Corrêa Ledur ◽  
Luiz Lehmann Coutinho ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Broiler Chickens ◽  
Reference Population ◽  
Single Step ◽  
P Value ◽  
Call Rate ◽  
Breeding Values ◽  
Heritability Estimates ◽  
Estimated Breeding Values ◽  
The Impact

Abstract The aim of this study was to compare the rank of estimated breeding values (EBV) for organs (heart, liver, lungs and gizzard) and carcass (breast, thigh and drumstick) traits using pedigree-based BLUP (PBLUP) and single-step genomic BLUP (ssGBLUP) models. A total of 1,453 chickens (703 males and 750 females) from a paternal broiler (TT) reference population belonging to the Poultry Breeding Program from Embrapa Swine and Poultry were genotyped with the Axiom® Genome-Wide Chicken Genotyping Array (Affymetrix) 600K SNP panel. Samples with a call rate lower than 90% were removed. A SNP quality control was applied for removing SNP with call rate lower than 98%, MAF lower than 2% and significant deviations from HWE (p-value < 10–7) leaving 370,608 SNP for further analysis. Estimated breeding values were predicted using the blupf90 family of programs whereby a series of bi-variate animal models that included sex and hatching as fixed effects were fitted. Heritability estimates for carcass and organ traits obtained through PBLUP varied from low (0.16) for lungs to moderate (0.34 to 0.47) for heart, liver, gizzard, breast, thigh and drumstick. The genomic heritability estimates through ssGBLUP varied from low (0.14) for lungs to moderate (0.30 to .041) for all other traits. Five subsets (5, 10, 20, 40 and 80% of SNP) were randomly selected from the full SNP set to determine the impact, in terms of EBV rank, of using reduced subsets of SNP to inform relationships among individuals. Although the 5% subset of SNP consistently had the lowest correlation with the full set of SNP, all correlations were greater than 0.995. Results suggest that a relatively limited proportion of SNP could be used to reliably predict EBV via ssGBLUP in this population.

Joint estimation of (co) variance components and breeding values for mean and dispersion of days from calving to first service in Holstein cow

2017 ◽  
Vol 57 (4) ◽  
pp. 760 ◽  
Author(s):  
Heydar Ghiasi ◽  
Majbritt Felleki
Keyword(s):  
Standard Deviation ◽  
Genetic Correlation ◽  
Additive Genetic Variance ◽  
Joint Estimation ◽  
Breeding Value ◽  
Genetic Trend ◽  
Breeding Values ◽  
The Mean ◽  
Estimated Breeding Values ◽  
Genetic Standard Deviation

The present study explored the possibility of selection for uniformity of days from calving to first service (DFS) in dairy cattle. A double hierarchical generalised linear model with an iterative reweighted least-squares algorithm was used to estimate covariance components for the mean and dispersion of DFS. Data included the records of 27 113 Iranian Holstein cows (parity, 1–6) in 15 herds from 1981 to 2007. The estimated additive genetic variance for the mean and dispersion were 32.25 and 0.0139; both of these values had low standard errors. The genetic standard deviation for dispersion of DFS was 0.117, indicating that decreasing the estimated breeding value of dispersion by one genetic standard deviation can increase the uniformity by 12%. A strong positive genetic correlation (0.689) was obtained between the mean and dispersion of DFS. This genetic correlation is favourable since one of the aims of breeding is to simultaneously decrease the mean and increase the uniformity of DFS. The Spearman rank correlations between estimated breeding values in the mean and dispersion for sires with a different number of daughter observations were 0.907. In the studied population, the genetic trend in the mean of DFS was significant and favourable (–0.063 days/year), but the genetic trend in the dispersion of DFS was not significantly different from zero. The results obtained in the present study indicated that the mean and uniformity of DFS can simultaneously be improved in dairy cows.

scholarly journals Responses to selection for lean growth in sheep

2002 ◽  
Vol 74 (1) ◽  
pp. 39-50 ◽  
Author(s):  
G. Simm ◽  
R.M. Lewis ◽  
B. Grundy ◽  
W.S. Dingwall
Keyword(s):  
Fixed Effects ◽  
Mixed Model ◽  
Live Weight ◽  
Control Line ◽  
Breeding Values ◽  
Breeding Goal ◽  
Lean Growth ◽  
Selection For ◽  
Estimated Breeding Values ◽  
And Control

AbstractThis paper reports the selection responses achieved, and related results, following 9 years of index selection for lean growth in Suffolk sheep. The breeding goal of the index used comprised carcass lean weight and carcass fat weight at a constant age, with relative economic values of + 3 and –1 per kg. The selection criteria were live weight (LWT), ultrasonic fat depth (UFD) and ultrasonic muscle depth (UMD) adjusted to a constant age of 150 days. By year 9, responses in LWT, UFD and UMD in both sexes, as judged by the divergence between selection and control line performance, amounted to 4·88 kg, -1·1 mm and 2·8 mm respectively; these responses are between 7 and 15% of the overall means of the traits concerned. Although selection was originally on index scores based on phenotypic records, the retrospective analyses reported here used the mixed model applications of residual maximum likelihood to estimate parameters and best linear unbiased prediction to predict breeding values. The statistical model comprised fixed effects plus random effects accounting for direct additive, maternal additive and temporary environmental variation. Estimated genetic trends obtained by regressing estimated breeding values on year of birth were similar to annual responses estimated by comparing selection and control line means. Estimates of direct heritabilities were 0·054, 0·177, 0·286, 0·561 and 0·410 for birth weight (BWT), weaning weight (WWT), LWT, UFD and UMD respectively. Corresponding estimates of maternal heritabilities were 0·287, 0·205, 0·160, 0·083 and 0·164. Phenotypic correlations between all pairs of traits were positive and usually moderately high. There were low negative direct additive correlations between BWT and WWT, and between BWT and LWT, but higher positive maternal additive correlations between all other pairs of weight traits.

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