Genetic variation of traits measured  in several environments. I. Estimation and testing of homogeneous genetic and intra-class correlations between environments

Robert, C.; Foulley, JL; Ducrocq, V.

doi:10.1051/gse:19950202

Cited by 3 publications

(4 citation statements)

References 3 publications

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“…Bivariate analyses provided estimates of the variance of the simplex value (−2 log likelihood) for testing genetic correlation coefficients against zero using the likelihood ratio test (Robert et al, 1995). The maximum likelihood function was obtained for 2 models, one without constraint (full model) and a reduced model with genetic correlation set to zero.…”

Section: Estimation Of Genetic Parametersmentioning

confidence: 99%

Fertility Responses of Mexican Holstein Cows to US Sire Selection

Cienfuegos-Rivas

Blake

Oltenacu

et al. 2006

Journal of Dairy Science

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Genetic relationships between 2 fertility traits and milk production were investigated using mature-equivalent lactation records of 55,162 daughters of 1,339 Holstein sires in Mexico and 499,401 daughters of 663 Holstein sires in the northeastern United States. Data sets contained yields in first and second lactation, age at first calving (AFC), and calving interval (CI). There were 474 US sires in common between countries. A herd-year standard deviation criterion defined nonoverlapping low- (< or = 1,300 kg) and high- (> or = 1,600 kg) opportunity Mexican herd environments and a low-opportunity (< or = 1,024 kg) US environment. Genetic variances for the average Mexican herd (all data) for AFC and CI were 65 and 85% as large as those obtained from half-sisters in the average US herd. Genetic correlations for first-lactation milk in the average US herd and AFC and CI in the average Mexican environment were unfavorable (0.18 and 0.10). Regression coefficients of AFC in Mexican environments on US genetic gain in milk ranged from 2 to 7 d/1,000 kg. However, the favorable predicted response in AFC from genetic gain in milk in Mexican environments, like those in average US herds, ranged from -4 to -7 d/1,000 kg (r(g) = - 0.20). This unequal AFC response may indicate genotype by environment interaction in fitness performance or differential breeding management of high and low yielding Mexican cows. The potential effects of age at first service of breeding females need to be disentangled to accurately assess genetic improvement needs for Mexican Holstein herds.

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Section: Estimation Of Genetic Parametersmentioning

confidence: 99%

Fertility Responses of Mexican Holstein Cows to US Sire Selection

Cienfuegos-Rivas

Blake

Oltenacu

et al. 2006

Journal of Dairy Science

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“…Memory requirements, low convergence speed and CPU time prevented fitting a bivariate animal model considering each country's records as a different trait with a diagonal residual variance matrix across traits. Thus, a singletrait Animal Model accounting for Across-Country Interactions (AMACI) with fixed or genetic effects was fitted to the data and was mathematically equivalent to a bi-trait model [21]:…”

Section: Across-country Evaluation Models 2221 Across-country Evamentioning

confidence: 99%

Investigation of three strategies for an international genetic evaluation of beef cattle weaning weight

2005

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Abstract

Weaning weights from 83 389 Limousin calves born between 1993 and 2002 in France and the Trans-Tasman block (Australia/New Zealand) were analysed to compare different strategies for running an international genetic evaluation for the breed. These records were a subset of the complete data for both countries and comprised a sample of herds that had recorded progeny of sires used across both countries. Genetic and phenotypic parameters for weaning weight were estimated within the countries. The estimates of direct genetic heritabilities were higher in France than in the Trans-Tasman block (0.31 vs. 0.22), while direct-maternal genetic correlations were less negative in the Trans-Tasman block (-0.10) than in France (-0.21). Different strategies for an international evaluation were studied, and the correlations between the estimated breeding values (EBV) of national evaluations and these strategies were derived. The international evaluation strategies were a) an animal model on raw performance data with non unity genetic correlations and heterogeneous residual and genetic variances across countries; b) the same animal model applied to pre-corrected (for fixed effects) performance data; and c) a sire model on de-regressed proofs (MACE). Estimates of the genetic correlations between weaning weight in both countries were 0.86 (0.80) for direct (maternal) genetic effects for the first strategy. Estimation of variance components by MACE appeared to be very sensitive to the sample of bulls and their reliability approximations. Variance component estimates obtained using pre-corrected data were inconsistent with estimates on raw data. However, the EBV predicted using pre-corrected data and parameters estimated from the raw data were similar to those predicted from raw data. Correlations between national and international EBV were always high (> 0.90) for sires, whichever genetic effect (direct or maternal) or international evaluation model was considered. The ranking of the bulls in the top 100 is of primary interest in terms of international genetic evaluation. In this study, some re-ranking of sires was observed for the top 100 bulls between countries and between the three international evaluation models. Thus, the origin of top sires may vary according to the implemented international evaluation strategy.

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“…Statistical procedures based on the theory of the generalized likelihood ratio, previously proposed by , Shaw (1991) and Visscher (1992), have been applied to test the homogeneity of genetic and phenotypic parameters against Falconer's (1952) saturated model. In particular, Robert et al (1995) have described a procedure for estimating components of variance and covariance between environments and for testing the homogeneity of the following parameters:…”

Section: Introductionmentioning

confidence: 99%

“…The problem of testing homogeneity of intra-class correlations between environments was finally solved under 3 different assumptions about the genetic correlations between environments: equal to one (Visscher, 1992); constant and positive (Robert et al, 1995); and just positive (this work).…”

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confidence: 99%

Genetic variation of traits measured in several environments. II. Inference on between-environment homogeneity of intra-class correlations

Robert¹,

Foulley²,

Ducrocq³

1995

Genet Sel Evol

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This paper describes a further contribution to the problem of testing homogeneity of intra-class correlations among environments in the case of univariate linear models, without making any assumption about the genetic correlation between environments. An iterative generalized expectation-maximization (EM) algorithm, as described in Foulley and Quaas (1994), is presented for computing restricted maximum likelihood (REML) estimates of the residual and between-family components of variance and covariance. Three different parameterizations (cartesian, polar and spherical coordinates) are proposed to compute EM-REML estimators under the reduced (constant intra-class correlation between environments) model. This procedure is illustrated with the analysis of simulated data. heteroskedasticity / parameterization / intra-class correlation / expectationmaximization / restricted maximum likelihood Résumé-Variation génétique de caractères mesurés dans plusieurs milieux. II. Inférence relative à des corrélations intra-classe constantes entre milieux. Cet article décrit une approche permettant d'estimer les composantes de variance-covariance entre milieux dans le cas de corrélation intra-classe homogènes entre milieux, sans faire d'hypothèse sur les corrélations génétiques entre milieux pris 2 à 2. Un algorithme itératif d'espérancemaximisation (EM), comparable à celui décrit par Foulley et Quaas (1994), est proposé pour calculer les estimations du maximum de vraisemblance restreinte (REML) des composantes résiduelles et familiales de variance covariance. Trois paramétrisations différentes (coordonnées cartésiennes, polaires et sphériques) sont proposées pour calculer les estimateurs EM-REML sous le modèle réduit (les corrélations intra-classe sont supposées toutes égales à une même constante). Cette procédure est illustrée par l'analyse de données simulées.

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Genetic variation of traits measured in several environments. I. Estimation and testing of homogeneous genetic and intra-class correlations between environments

Cited by 3 publications

References 3 publications

Fertility Responses of Mexican Holstein Cows to US Sire Selection

Fertility Responses of Mexican Holstein Cows to US Sire Selection

Investigation of three strategies for an international genetic evaluation of beef cattle weaning weight

Genetic variation of traits measured in several environments. II. Inference on between-environment homogeneity of intra-class correlations

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