Test-day milk yield records of 11,023 first-parity Holstein cows were used to estimate genetic parameters for milk yield during different lactation periods. (Co)variance components were estimated using two random regression models, RRM1 and RRM2, and the restricted maximum likelihood method, compared by the likelihood ratio test. Additive genetic variances determined by RRM1 and additive genetic and permanent environmental variances estimated by RRM2 were described, using the Wilmink function. Residual variance was constant throughout lactation for the two models. The heritability estimates obtained by RRM1 (0.34 to 0.56) were higher than those obtained by RRM2 (0.15 to 0.31). Due to the high heritability estimates for milk yield throughout lactation and the negative genetic correlation between test-day yields during different lactation periods, the RRM1 model did not fit the data. Overall, genetic correlations between individual test days tended to decrease at the extremes of the lactation trajectory, showing values close to unity for adjacent test days. The inclusion of random regression coefficients to describe permanent environmental effects led to a more precise estimation of genetic and non-genetic effects that influence milk yield.

BackgroundThe success of genomic selection depends mainly on the extent of linkage disequilibrium (LD) between markers and quantitative trait loci (QTL), the number of animals in the training set (TS) and the heritability (h2) of the trait. The extent of LD depends on the genetic structure of the population and the density of markers. The aim of this study was to calculate accuracy of direct genomic estimated breeding values (DGEBV) using best linear unbiased genomic prediction (GBLUP) for different marker densities, heritabilities and sizes of the TS in simulated populations that mimicked previously reported extent and pattern of LD in beef cattle.ResultsThe accuracy of DGEBV increased significantly (p < 0.05) with the increase in the number of bulls in the TS (480, 960 or 1920), trait h2 (0.10, 0.25 or 0.40) and marker densities (40 k or 800 k). Increasing the number of animals in the TS by 4-fold and using their phenotypes to estimate marker effects was not sufficient to maintain or increase the accuracy of DGEBV obtained using estimated breeding values (EBVs) when the trait h2 was lower than 0.40 for both marker densities. Comparing to expected accuracies of parent average (PA), the gains by using DGEBV would be of 27%, 13% and 10% for trait h2 equal to 0.10, 0.25 and 0.40, respectively, considering the scenario with 40 k markers and 1920 bulls in TS.ConclusionsAs reported in dairy cattle, the size of the TS and the extent of LD have major impact on the accuracy of DGEBV. Based on the findings of this simulation study, large TS, as well as dense marker panels, aiming to increase the level of LD between markers and QTL, will likely be needed in beef cattle for successful implementation of genomic selection.

-Data comprising 263,390 test-day (TD) records of 32,448 first parity cows calving in 467 herds between 1991 and 2001 from the Brazilian Holstein Association were used to estimate genetic and permanent environmental variance components in a random regression animal model using Legendre polynomials (LP) of order three to five by REML. Residual variance was assumed to be constant in all or in some classes of lactation periods for each LP. Estimates of genetic and permanent environmental variances did not show any trend due to the increase in the LP order. Residual variance decreased as the order of LP increased when it was assumed constant, and it was highest at the beginning of lactation and relatively constant in mid lactation when assumed to vary between classes. The range for the estimates of heritability (0.27 -0.42) was similar for all models and was higher in mid lactation. There were only slight differences between the models in both genetic and permanent environmental correlations. Genetic correlations decreased for near unity between adjacent days to values as low as 0.24 between early and late lactation. A five parameter LP to model both genetic and permanent environmental effects and assuming a homogeneous residual variance would be a parsimonious option to fit TD yields of Holstein cows in Brazil. foi assumida como constante em todo ou em algumas classes do período de lactação para cada PL. As estimativas dos efeitos genético e permanente de ambiente não apresentaram qualquer tendência atribuída ao aumento da ordem do PL. A variância residual diminuiu com o aumento da ordem do PL quando assumida como constante e foi maior no início da lactação e relativamente constante na fase intermediária quando assumida como heterogênea entre classes do período de lactação. As estimativas de herdabilidade variaram de 0,27 a 0,42 em todos os modelos e foram maiores na fase intermediária da lactação.As diferenças entre modelos para as correlações genéticas e de ambiente permanente foram pequenas. As correlações genéticas decresceram de valores próximos à unidade entre as produções de leite de controles próximos para 0,24 entre as produções de leite dos controles do início e do final da lactação. O polinômio de Legendre de cinco parâmetros para a modelagem dos efeitos genético e de ambiente permanente com homogeneidade de variância residual é uma opção parcimoniosa para o ajuste das PC de vacas da raça Holandesa no Brasil.Palavras-chave: avaliação genética, bovinos de leite, componentes de co-variância, herdabilidade, seleção

-The objective of this study was to estimate genetic parameters for milk, fat and protein yields of Holstein cows using 56,508; 35,091 and 8,326 test-day milk records from 7,015, 4,476 and 1,114 cows, calves of 359, 246 and 90 bulls, respectively. The additive genetic and permanent environmental effects were estimated using REML. Random regression models with Legendre polynomials from order 3 to 6 were used. Residual variances were considered homogeneous over the lactation period. The estimates of variance components showed similar trends, with an increase of the polynomial order for each trait. The heritability estimates ranged from 0.14 to 0.31; 0.03 to 0.21 and 0.09 to 0.33 for milk, fat and protein yield, respectively. Genetic correlations among milk, fat and protein yields ranged from 0.02 to 1.00; 0.34 to 1.00 and 0.42 to 1.00, respectively. Models with higher order Legendre polynomials are the best suited to adjust test-day data for the three production traits studied. herdabilidade variaram, respectivamente, de 0,14 a 0,31; 0,03 a 0,21; e 0,09 a 0,33 para as produções de leite, de gordura e de proteína. As correlações genéticas entre produções de leite, gordura e proteína do leite variaram de 0,02 a 1,00; 0,34 a 1,00 e 0,42 a 1,00, respectivamente. Os modelos com polinômio de Legendre de maior ordem são os mais adequados para ajuste da produção no dia do controle das três características produtivas.Palavras-chave: dia do controle, herdabilidade, produção de gordura, produção de leite, produção de proteína Revista Brasileira de Zootecnia

-Data from 26,558 Holstein cows in 802 herds were used to estimate genetic, residual and phenotypic parameters for 22 type traits. The model included the fixed effects of herd-year, period of classification, classifier, stage of lactation and age of cows at calving (covariate) and random genetic and residual effects. Heritability for type traits ranged from 0.10 to 0.39. The genetic variability in these traits suggested the possibility for moderate genetic gains through selection. The phenotypic correlations were moderated, mainly in the section conformation. Genetic correlations between type traits ranged from -0.44 to 0.85. High genetic correlations indicated that breeding programs could be successful without including all type traits. The selection for the final score at the expense of other traits must be performed with restraint, because in the long term, this may promote undesirable changes in some type traits.

Longevity is a desirable trait in the dairy industry because of its relationship to profitability. The aim of this study was to estimate genetic parameters for longevity measurements related to productive life, or life in the herd, and linear type traits of Brazilian Holstein cows born between the years 1990 and 2008. The (co) variance components were estimated by the restricted maximum likelihood method. The heritability for measurements of longevity and linear type traits ranged from 0.05 to 0.07 and 0.08 to 0.39, respectively. The genetic correlations between measurements of longevity and linear type traits ranged from -0.39 to 0.31. Direct selection for longevity does not necessarily lead to long-lived cows, due to low heritability. Indirect genetic selection for udder depth, bone quality, udder height, rear teat placement and conformation traits showed the highest genetic correlations with measurements of time between birth and last milk record and time from first calving to last milk record.

-Records of test-day milk yields of the first three lactations of 25,500 Holstein cows were used to estimate genetic parameters for milk yield by using two alternatives of definition of fixed regression of the random regression models (RRM). Legendre polynomials of fourth and fifth orders were used to model regression of fixed curve (defined based on averages of the populations or multiple sub-populations formed by grouping animals which calved at the same age and in the same season of the year) or random lactation curves (additive genetic and permanent enviroment). Akaike information criterion (AIC) and Bayesian information criterion (BIC) indicated that the models which used multiple regression of fixed lactation curves of lactation multiple regression model with fixed lactation curves had the best fit for the first lactation test-day milk yields and the models which used a single regression of fixed curve had the best fit for the second and third lactations. Heritability for milk yield during lactation estimates did not vary among models but ranged from 0.22 to 0.34, from 0.11 to 0.21, and from 0.10 to 0.20, respectively, in the first three lactations. Similarly to heridability estimates of genetic correlations did not vary among models. The use of single or multiple fixed regressions for fixed lactation curves by RRM does not influence the estimates of genetic parameters for test-day milk yield across lactations.Key Words: test-day milk yield, genetic correlation, heritability, Legendre polynomial, selection Parâmetros genéticos para produção de leite usando modelos de regressão aleatória com diferentes alternativas de modelagem da regressão fixa RESUMO -Os registros de produção de leite no dia do controle das três primeiras lactações de 25,5 mil vacas da raça Holandesa foram utilizados para estimar parâmetros genéticos para produção de leite usando duas alternativas de definição da regressão fixa dos modelos de regressão aleatória (MRA). Os polinômios de Legendre de ordens 4 e 5 foram usados para modelar as regressões das curvas fixas (definidas com base nas médias das produções de leite no dia do controle da população ou de múltiplas sub-populações formadas pelo agrupamento de animais que pariram na mesma idade e estação do ano) e aleatórias (genética aditiva e de ambiente permanente) de lactação. Os critérios de informação de Akaike (AIC) e Bayesiano (BIC) indicaram os modelos que consideraram múltiplas regressões das curvas fixas de lactação como os que melhor se ajustaram aos registros de produção de leite da primeira lactação e os modelos que utilizaram uma única regressão da curva fixa, como os melhores para ajuste das segunda e terceira lactações. As herdabilidades para produção de leite ao longo da lactação não variaram entre modelos, entretanto variaram de 0,22 a 0,34; 0,11 a 0,21 e 0,10 a 0,20, respectivamente, para as três primeiras lactações. Semelhantemente às estimativas de herdabilidade os valores das estimativas de correlações genéticas não variaram entre modelos. O uso de uma ou de...

A model for analyzing test day records including both fixed and random coefficients was applied to the genetic evaluation of first lactation data for Holstein cows. Data comprising 87045 test-day milk yield records from calving between 1997 and 2001 from Holstein herds in 10 regions of the Brazilian state of Minas Gerais. Six persistency of lactation measures were evaluated using breeding values obtained by random regression analyses. The Wilmink function was used to model the additive genetic and permanent environmental effects. Residual variance was constant throughout lactation. Ranking for animals did not change among criteria for persistency measurements, but ranking changes were observed when the estimated breeding value (EBV) for persistency of lactation was contrasted with those estimated for 305-day milk yield (305MY). The rank correlation estimates for persistency of lactation and 305MY were practically the same for sire and cows, and ranged from -0.45 to 0.69. The EBVs for milk yield during lactation for sires producing daughters with superior 305MY indicate genetic differences between sires regarding their ability to transmit desirable persistency of lactation traits. This suggests that selection for total lactation milk yield does not identify sires or cows that are genetically superior in regard to persistency of lactation. Genetic evaluation for persistency of lactation is important for improving the efficiency of the milk production capacity of Holstein cows.