ABSTRACT The objective of this work is to estimate genetic parameters and breeding values to improve embryo and oocyte production, using repeatability and random regression models (RRM) for Gir dairy cattle. We used 11,398 records of ovum pick-up from 1,747 dairy Gir donors and evaluated sixteen different models: the traditional repeatability model and fifteen RRM, each of which considered a different combination of Legendre polynomial regressors to describe the additive genetic and permanent environment effects. The 4G1P model (four regressors for the genetic effect and one regressor for the permanent environment effect) is the most suitable model to analyze the number of viable and total oocytes, while the 3G1P is the best model to analyze the number of cleaved and viable embryos, according to the values of the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). The heritability estimated with the RRM was higher than that estimated with the repeatability model. The high repeatability reported for oocyte and embryo count traits indicates that donors, which had high oocyte and embryo counts in the first ovum pick-up, should maintain this result in the next ovum pick-up. Genetic correlations between adjacent ages were high and positive, while genetic correlations between extreme ages were weak. We observed a reranking of the top sires and females (heifers and cows) over the period evaluated. The reliability of the estimated breeding values by RRM showed changes across age, and the expected genetic gains by RRM are larger. This shows that RRM is most suitable alternative for the evaluation and selection of oocyte and embryo count traits.

ABSTRACT The objective of this work was to estimate genetic parameters and evaluate genetic trends over 26 years for morphometric traits in Mangalarga Marchador horses. Twelve morphometric traits were evaluated (withers and croup heights; length of head, body, shoulder, croup, neck, back, and loins; width of head and croup, and cannon bone and thorax perimeters). These traits were evaluated in 38,341 animals born between 1987 and 2012 and with a relationship matrix of 77,719 animals. Gibbs sampler was used to obtain samples of the posterior distributions of genetic parameters under animal models. Genetic trends were estimated by regression of estimated breeding values in function of birth year. The heritabilities of all traits were moderate to high and ranged from 0.27 to 0.48. However, the additive genetic coefficients of variation were low, ranging from 1.23 to 3.82%. The genetic trends of all the studied traits were significant, but of low magnitude. Negative genetic trend was observed for body length, while positive genetic trends were estimated for the other 11 traits. Although additive genetic differences accounted for a significant part of the phenotypic differences, genetic gains in the population were limited by low phenotypic variability. Therefore, it is necessary to develop data collection strategies to increase phenotypic and genetic variability in the population, such as the inclusion of animals that do not meet breed standard, but which have parents registered in the breeders’ association, in the database.

Resumo: O objetivo deste trabalho foi verificar se o modelo de regressão aleatória com polinômios lineares do tipo spline (MRAPLS) é adequado para estimar os parâmetros genéticos de características produtivas e reprodutivas em uma população multirracial de bovinos leiteiros, bem como investigar o efeito do grupo genético da progênie sobre o mérito genético do touro. Foram utilizados o modelo multicaracterístico (Mult) e o MRAPLS com nós ajustados aos grupos genéticos, para obtenção dos parâmetros genéticos. Foram considerados os registros de vacas 1/2 Holandesa + 1/2 Gir (1/2HG), 5/8 Holandesa + 3/8 Gir (5/8HG) e 3/4 Holandesa + 1/4 Gir (3/4HG). O MRAPLS apresentou os melhores ajustes. As variâncias aditivas e residuais estimadas por Mult e MRAPLS foram semelhantes. As herdabilidades variaram de 0,20 a 0,33 para idade ao primeiro parto, de 0,09 a 0,22 para duração da primeira lactação e de 0,15 a 0,35 para produção de leite em até 305 dias na primeira lactação, de acordo com a composição genética das vacas. O MRAPLS é adequado para estimar parâmetros genéticos de características produtivas e reprodutivas em populações multirraciais de bovinos leiteiros. O mérito genético do touro é influenciado pelo grupo genético da progênie por meio do qual ele é avaliado.

Abstract: The objective of this work was to determine whether the random regression model using linear splines (RRMLS) is suitable to estimate the genetic parameters for productive and reproductive traits of a multiple-breed dairy cattle population, as well as to investigate the effect of the genetic group of the progeny on the genetic merit of the sire. The multiple-trait model (MTM) and the RRMLS with one knot fitted for every genetic group were used to obtain the genetic parameters. Records of 1/2 Holstein + 1/2 Gyr (1/2HG), 5/8 Holstein + 3/8 Gyr (5/8HG), and 3/4 Holstein + 1/4 Gyr (3/4HG) crossbreed dams were considered. The RRMLS showed better fitting. The additive and residual variances estimated by the MTM and the RRMLS were similar. Heritability varied from 0.20 to 0.33 for age at first calving, from 0.09 to 0.22 for first lactation length, and from 0.15 to 0.35 for first lactation 305-day milk yield, according to the genetic composition of the dams. The RRMLS is suitable to estimate the genetic parameters for productive and reproductive traits of multiple-breed dairy cattle populations. The genetic merit of the sires is affected by the genetic group of the progeny by which they are evaluated.

O objetivo deste trabalho foi avaliar componentes de covariância e valores genéticos para produção de leite acumulada em até 305 dias, a partir dos dados das três primeiras lactações de vacas Gir. Foram analisados dados de 14.659 lactações, de 9.079 vacas, por meio dos modelos de repetibilidade, multicaracterístico (Mult) e de regressão aleatória com variância residual homogênea (MRAHo) ou heterogênea (MRAHe). A produção de leite foi considerada como característica distinta em cada lactação, no modelo Mult. Polinômios lineares foram utilizados nos modelos de regressão aleatória para ajuste das trajetórias médias e dos efeitos genético aditivo e de ambiente permanente individuais, de acordo com a ordem de parto. As médias a posteriori da herdabilidade foram semelhantes entre os diferentes modelos e lactações, e variaram entre 0,24 e 0,29. Os modelos Mult e MRAHe ajustaram-se melhor aos dados, uma vez que observou-se heterogeneidade de variâncias genéticas e residuais entre lactações. As correlações genéticas da produção acumulada de leite em até 305 dias nas três primeiras lactações foram próximas de 1,0; portanto, a seleção de reprodutores já pode ser feita a partir dos resultados da primeira lactação. Modelos de regressão aleatória com variâncias genéticas e residuais heterogêneas permitem modelar adequadamente as covariâncias das produções de leite acumuladas em múltiplas lactações e obter valores genéticos para seleção de reprodutores com base nos dados já da primeira lactação.

The objective of this work was to evaluate covariance components and breeding values for 305-day cumulative milk yield with data from the first three lactations of Gyr cows. A total of 14,659 lactations of 9,079 cows were evaluated, using the models of repeatability, multiple-trait (MT), and random regression with residual homoscedasticity (RRMHo) or heteroscedasticity (RRMHe). Milk yield was considered as a different trait in each lactation, in the MT model. Linear polynomials were used in random regression models to fit the mean trajectories and the additive genetic and permanent environment individual effects, according to calving order. Posteriori means for heritability were similar among different models and lactations, and varied from 0.24 to 0.29. The MT and RRMHe models had a better fit to the data, since heterogeneity was observed for genetic and residual variances between lactations. The genetic correlations of cumulative milk yield up to 305 days in the first three lactations were close to 1.0; therefore, the selection of reproducers can be made with data already from the first lactation. Random regression models with heterogenous genetic and residual variances allow for proper modeling of the covariances in cumulative milk yields in multiple lactations and for obtaining the genetic values to be used in the selection of reproducers, based on data already from the first lactation.