Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

Genetic parameters for production traits of dairy Gyr (Bos indicus) x Holstein cattle estimated with a random regression model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comparison of factor-analytic and reduced rank models for test-day milk yield in Gyr dairy cattle (Bos indicus)

We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.

Effect of pregnancy on the genetic evaluation of dairy cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modelos genéticos para a produção no dia do controle em bovinos Gir Leiteiro (Bos indicus)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Strategies for single nucleotide polymorphism (SNP) genotyping to enhance genotype imputation in Gyr (Bos indicus) dairy cattle: Comparison of commercially available SNP chips

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Milk yield persistency in Brazilian Gyr cattle based on a random regression model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Influence of sire and sire breed (Gyr versus Holstein) on establishment of pregnancy and embryonic loss in lactating Holstein cows during summer heat stress

Heat stress has negative effects on pregnancy rates of lactating dairy cattle. There are genetic differences in tolerance to heat stress; Bos taurus indicus (B. t. indicus) cattle and embryos are more thermotolerant than Bos taurus taurus (B. t. taurus). In the present study, the effects of sire and sire breed on conception and embryonic/fetal loss rates of lactating Holstein cows during the Brazilian summer were determined. In Experiment 1, cows (n = 302) were AI after estrus detection or at a fixed-time with semen from one Gyr (B. t. indicus) or one Holstein sire (B. t. taurus). Pregnancy was diagnosed 80 days after AI. In Experiment 2, cows (n = 811) were AI with semen from three Gyr and two Holstein sires. Pregnancy was diagnosed at 30-40 and at 60-80 days after AI. Cows diagnosed pregnant at the first examination but non-pregnant at the second were considered as having lost their embryo or fetus. Data were analyzed by logistic regression. The model considered the effect of sire within breed, sire breed, days postpartum, period of lactation, and AI type (AI after estrus versus fixed-time). There was no effect of the AI type, days postpartum or milk production on conception or embryonic loss rates. The use of Gyr bulls increased pregnancy rate when compared to Holstein bulls [9.1% (60/657) versus 5.0% (23/456), respectively, P = 0.008; data from Experiments 1 and 2 combined]. Additionally, in Experiment 2, cows inseminated using semen from sire #4 (Gyr) had lower embryonic loss (10%) when compared with other B. t. indicus (35.3% and 40%) or B. t. taurus sires (18.2% and 38.5%, P = 0.03). In conclusion, the use of B. t. indicus sires may result in higher conception rates in lactating Holstein cows during summer heat stress. Moreover, sire can affect embryonic loss and selection of bulls according to this criterion may result in higher parturition rates in lactating Holstein cows. (c) 2006 Elsevier B.V. All rights reserved.

Detecting Loci under Recent Positive Selection in Dairy and Beef Cattle by Combining Different Genome-Wide Scan Methods

As the methodologies available for the detection of positive selection from genomic data vary in terms of assumptions and execution, weak correlations are expected among them. However, if there is any given signal that is consistently supported across different methodologies, it is strong evidence that the locus has been under past selection. In this paper, a straightforward frequentist approach based on the Stouffer Method to combine P-values across different tests for evidence of recent positive selection in common variations, as well as strategies for extracting biological information from the detected signals, were described and applied to high density single nucleotide polymorphism (SNP) data generated from dairy and beef cattle (taurine and indicine). The ancestral Bovinae allele state of over 440,000 SNP is also reported. Using this combination of methods, highly significant (P<3.17×10-7) population-specific sweeps pointing out to candidate genes and pathways that may be involved in beef and dairy production were identified. The most significant signal was found in the Cornichon homolog 3 gene (CNIH3) in Brown Swiss (P = 3.82×10-12), and may be involved in the regulation of pre-ovulatory luteinizing hormone surge. Other putative pathways under selection are the glucolysis/gluconeogenesis, transcription machinery and chemokine/cytokine activity in Angus; calpain-calpastatin system and ribosome biogenesis in Brown Swiss; and gangliosides deposition in milk fat globules in Gyr. The composite method, combined with the strategies applied to retrieve functional information, may be a useful tool for surveying genome-wide selective sweeps and providing insights in to the source of selection.

Effect of somatic cell count and mastitis pathogens on milk composition in Gyr cows

Abstract Background Gyr cows are well adapted to tropical conditions, resistant to some tropical diseases and have satisfactory milk production. However, Gyr dairy herds have a high prevalence of subclinical mastitis, which negatively affects their milk yield and composition. The objectives of this study were (i) to evaluate the effects of seasonality, mammary quarter location (rear x front), mastitis-causing pathogen species, and somatic cell count (SCC) on milk composition in Gyr cows with mammary quarters as the experimental units and (ii) to evaluate the effects of seasonality and somatic cell count (SCC) on milk composition in Gyr cows with cows as the experimental units. A total of 221 lactating Gyr cows from three commercial dairy farms were selected for this study. Individual foremilk quarter samples and composite milk samples were collected once a month over one year from all lactating cows for analysis of SCC, milk composition, and bacteriological culture. Results Subclinical mastitis reduced lactose, nonfat solids and total solids content, but no difference was found in the protein and fat content between infected and uninfected quarters. Seasonality influenced milk composition both in mammary quarters and composite milk samples. Nevertheless, there was no effect of mammary quarter position on milk composition. Mastitis-causing pathogens affected protein, lactose, nonfat solids, and total solids content, but not milk fat content. Somatic cell count levels affected milk composition in both mammary quarters and composite samples of milk. Conclusions Intramammary infections in Gyr cows alter milk composition; however, the degree of change depends on the mastitis-causing pathogen. Somatic cell count is negatively associated with reduced lactose and nonfat solids content in milk. Seasonality significantly affects milk composition, in which the concentration of lactose, fat, protein, nonfat solids and total solids differs between dry and wet seasons in Gyr cows.

A note on inbreeding in dairy cattle breeding

Starting from the study at the beginning of the East German "Heterosisfeldversuch", where PANICKE et al. (1975) considered the possibilities of a targeted use of inbreeding and heterotic effects, we show and discuss results of inbreeding studies in the USA dairy cattle breeding. Several research groups worldwide presented effective tools for managing inbreeding in dairy cattle. Their efforts underline the need of inbreeding studies. Contemplating inbreeding is necessary for any breeding decision to avoid inbreeding depression and for improved genetic analyses, e.g. in QTL- estimation. A novel methodology (HERNANDEZ-SANCHEZ et al., 2004a and b) is suggested for estimating inbreeding at the three levels of population, individual and locus.