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1.
J Dairy Sci ; 88(3): 1199-207, 2005 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-15738253

RESUMO

Health data collected from 1996 to 1999 from 177 herds in Minnesota and Wisconsin were analyzed to establish genetic basis for infectious and noninfectious diseases. Three types of health traits were targeted. First, available infectious conditions were used to identify animals that are superior in their general immunity (including innate immunity) for infectious diseases. Generalized immunity may be thought of as a combination of immune responses to a variety of immune system challenges. Second, single infectious and noninfectious diseases were analyzed separately. Third, infectious reproductive diseases as one category of related conditions, and cystic ovary disease as one category of 3 related noninfectious ovary disorders were studied. Data were analyzed using a threshold model that included herd, calving year, season of calving, and parity as cross-classified fixed factors; and sire and cow within sires as random effects. Days at risk and days in milk at the beginning of a record were included by fitting the days as continuous covariates in the model. A heritability value of 0.202 +/- 0.083 was estimated for generalized immunity. Heritability values of 0.141 and 0.161 were estimated for uterine infection and mastitis, respectively. Heritability of single noninfectious disorders ranged from 0.087 to 0.349. The amount of additive genetic variance recovered in the underlying scale of noninfectious disorders tended to zero when combining multiple conditions. The study supports combining infectious diseases into categories of interest but we do not recommend the same approach for noninfectious disorders.


Assuntos
Doenças dos Bovinos/epidemiologia , Doenças dos Bovinos/genética , Doenças Transmissíveis/veterinária , Predisposição Genética para Doença , Transtornos da Lactação/veterinária , Abomaso , Animais , Bovinos , Doenças dos Bovinos/imunologia , Doenças Transmissíveis/epidemiologia , Doenças Transmissíveis/genética , Feminino , Nível de Saúde , Lactação/genética , Lactação/fisiologia , Transtornos da Lactação/epidemiologia , Transtornos da Lactação/genética , Modelos Lineares , Masculino , Mastite Bovina/epidemiologia , Mastite Bovina/genética , Minnesota/epidemiologia , Cistos Ovarianos/epidemiologia , Cistos Ovarianos/genética , Cistos Ovarianos/veterinária , Paresia Puerperal/epidemiologia , Paresia Puerperal/genética , Gravidez , Característica Quantitativa Herdável , Fatores de Risco , Gastropatias/epidemiologia , Gastropatias/genética , Gastropatias/veterinária , Wisconsin/epidemiologia
2.
J Anim Sci ; 77(3): 582-90, 1999 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-10229353

RESUMO

Estimation of genetic parameters and accuracy of threshold model genetic predictions were investigated. Data were simulated for different population structures by using Monte Carlo techniques. Variance components were estimated by using threshold models and linear sire models applied to untransformed data, logarithmically transformed data, and transformation to Snell scores. Effects of number of categories (2, 5, and 10), incidence of categories (extreme, moderate, and normal), heritability in the underlying scale (.04, .20, and .50), and data structure (unbalanced and balanced) on accuracy of genetic prediction were investigated. The real importance of using a threshold model was to estimate genetic parameters. An expected heritability of .20 was estimated to be .22 and .10 by a threshold model and a linear model, respectively. Accuracy increased significantly with a larger number of categories, a more normal distribution of incidences, increased heritability, and more balanced data. Even threshold models were shown to be more efficient with more than two categories (e.g., binomial). Transformation of scale did not accomplish the purpose intended.


Assuntos
Criação de Animais Domésticos/estatística & dados numéricos , Modelos Estatísticos , Seleção Genética , Criação de Animais Domésticos/métodos , Animais , Cruzamento/métodos , Cruzamento/estatística & dados numéricos , Método de Monte Carlo
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