Genetic analysis of ventricular arrhythmia in young German Shepherd Dogs.

BACKGROUND: Ventricular arrhythmias (VA) and sudden death are inherited in German Shepherd Dogs (GSDs). OBJECTIVES: To estimate the genetic parameters (heritabilities and correlations) of 3 traits of VA (single premature ventricular complexes (PVCs), 2 consecutive PVCs (couplets), and 3 or more consecutive PVCs-ventricular tachycardia [VT]). ANIMALS: Three hundred and ninety-eight GSDs. METHODS: Prospective, observational, case control study. Dogs were phenotyped by 24-hour ambulatory ECG from 6 to 45 weeks of age. Edited ECG records included the number of incidents of (1) single PVCs, (2) couplets, and (3) VT. RESULTS: A data set of 1,239 Holter records from 398 GSDs was used to estimate genetic variables. Phenotypic correlations for affectedness (binarily coded 0/1) of the 3 traits ranged from 0.55 to 0.74, whereas correlations for severity (continuous values of 24-hour VA counts) ranged from 0.26 to 0.39. Estimates of genetic correlation among the severity traits were 0.06 to 0.27. Estimated heritabilities were 0.54, 0.54, and 0.46 for affectedness and 0.33, 0.69, and 0.69 for severity of PVCs, couplets, and VT, respectively. Month and year of birth and age at ECG recording had significant effects on all 3 traits. Season of ECG recording had a significant effect on the number of single PVCs, but not couplets or incidents of VT. Age of onset differed, with single PVCs appearing an average of 4 days earlier than couplets and VT. CONCLUSION: These results imply a strong genetic component for this disease but suggest that differences in the 3 traits should be taken into consideration in studies to identify the underlying genes.

DNA-based paternity analysis and genetic evaluation in a large, commercial cattle ranch setting.

Deoxyribonucleic acid-based tests were used to assign paternity to 625 calves from a multiple-sire breeding pasture. There was a large variability in calf output and a large proportion of young bulls that did not sire any offspring. Five of 27 herd sires produced over 50% of the calves, whereas 10 sires produced no progeny and 9 of these were yearling bulls. A comparison was made between the paternity results obtained when using a DNA marker panel with a high (0.999), cumulative parentage exclusion probability (P(E)) and those obtained when using a marker panel with a lower P(E) (0.956). A large percentage (67%) of the calves had multiple qualifying sires when using the lower resolution panel. Assignment of the most probable sire using a likelihood-based method based on genotypic information resolved this problem in approximately 80% of the cases, resulting in 75% agreement between the 2 marker panels. The correlation between weaning weight, on-farm EPD based on pedigrees inferred from the 2 marker panels was 0.94 for the 24 bulls that sired progeny. Partial progeny assignments inferred from the lower resolution panel resulted in the generation of EPD for bulls that actually sired no progeny according to the high-P(E) panel, although the Beef Improvement Federation accuracies of EPD for these bulls were never greater than 0.14. Simulations were performed to model the effect of loci number, minor allele frequency, and the number of offspring per bull on the accuracy of genetic evaluations based on parentage determinations derived from SNP marker panels. The SNP marker panels of 36 and 40 loci produced EPD with accuracies nearly identical to those EPD resulting from use of the true pedigree. However, in field situations where factors including variable calf output per sire, large sire cohorts, relatedness among sires, low minor allele frequencies, and missing data can occur concurrently, the use of marker panels with a larger number of SNP loci will be required to obtain accurate on-farm EPD.

Genetic evaluation of beef carcass data using different endpoint adjustments.

Carcass data from 6,795 Simmental-sired animals born from 1992 to 2001 were used to determine whether adjustment to a constant age, back-fat, HCW, or marbling score would result in differences in heritability of the carcass traits and, correspondingly, if EPD calculated using those variance components and adjustments would result in sire reranking. The endpoints were age (EPA), backfat (EPF), HCW (EPC), or marbling (EPM). The traits analyzed were 12th-rib backfat (FAT), HCW, marbling (MRB), LM area (LMA), and percentage retail cuts (PRC). The data were analyzed using an animal model, where contemporary group was included as a fixed effect and was composed of slaughter date, sex, and herd. Random effects included in the model were direct genetic and residual. Estimates of heritability ranged from 0.12 to 0.14, 0.32 to 0.34, and 0.26 to 0.27 for FAT, HCW, and LMA, respectively, for the corresponding endpoints. Heritability for MRB was estimated to be 0.27 at all endpoints. For PRC, estimates of heritability were more variable, with estimates of 0.23 +/- 0.05, 0.32 +/- 0.05, 0.21 +/- 0.05, and 0.20 +/- 0.04 for EPA, EPF, EPC, and EPM, respectively. However, because the EPF and EPC adjustments adjust for a component trait of PRC (FAT and HCW, respectively), they may be altering the trait to one different from PRC. Spearman rank correlations between EPD within a trait using EPA compared with the other endpoints were >0.90 (P < 0.01) for FAT, HCW, MRB, and LMA. For PRC, Spearman rank correlations with EPA EPD were 0.73 (P < 0.01), 0.93 (P < 0.01), and 0.95 (P < 0.01) for EPF, EPC, and EPM, respectively. For most traits and endpoints, there was little reranking among sires when alternative endpoints were used. However, adjusting PRC to EPF appears to result in a greater heritability and substantial re-ranking of sires, potentially due to the adjustment changing the trait to one other than PRC.

Validation of commercial DNA tests for quantitative beef quality traits.

Associations between 3 commercially available genetic marker panels (GeneSTAR Quality Grade, GeneSTAR Tenderness, and Igenity Tender-GENE) and quantitative beef traits were validated by the US National Beef Cattle Evaluation Consortium. Validation was interpreted to be the independent confirmation of the associations between genetic tests and phenotypes, as claimed by the commercial genotyping companies. Validation of the quality grade test (GeneSTAR Quality Grade) was carried out on 400 Charolais x Angus crossbred cattle, and validation of the tenderness tests (GeneSTAR Tenderness and Igenity Tender-GENE) was carried out on over 1,000 Bos taurus and Bos indicus cattle. The GeneSTAR Quality Grade marker panel is composed of 2 markers (TG5, a SNP upstream from the start of the first exon of thyroglobulin, and QG2, an anonymous SNP) and is being marketed as a test associated with marbling and quality grade. In this validation study, the genotype results from this test were not associated with marbling score; however, the association of substituting favorable alleles of the marker panel with increased quality grade (percentage of cattle grading Choice or Prime) approached significance (P < or = 0.06), mainly due to the effect of 1 of the 2 markers. The GeneSTAR Tenderness and Igenity TenderGENE marker panels are being marketed as tests associated with meat tenderness, as assessed by Warner-Bratzler shear force. These marker panels share 2 common mu-calpain SNP, but each has a different calpastatin SNP. In both panels, there were highly significant (P < 0.001) associations of the calpastatin marker and the mu-calpain haplotype with tenderness. The genotypic effects of the 2 tenderness panels were similar to each other, with a 1 kg difference in Warner-Bratzler shear force being observed between the most and least tender genotypes. Unbiased and independent validation studies are important to help build confidence in marker technology and also as a potential source of data required to enable the integration of marker data into genetic evaluations. As DNA tests associated with more beef production traits enter the marketplace, it will become increasingly important, and likely more difficult, to find independent populations with suitable phenotypes for validation studies.

Bayesian reanalysis of a quantitative trait locus accounting for multiple environments by scaling in broilers.

A Bayesian method was developed to handle QTL analyses of multiple experimental data of outbred populations with heterogeneity of variance between sexes for all random effects. The method employed a scaled reduced animal model with random polygenic and QTL allelic effects. A parsimonious model specification was applied by choosing assumptions regarding the covariance structure to limit the number of parameters to estimate. Markov chain Monte Carlo algorithms were applied to obtain marginal posterior densities. Simulation demonstrated that joint analysis of multiple environments is more powerful than separate single trait analyses of each environment. Measurements on broiler BW obtained from 2 experiments concerning growth efficiency and carcass traits were used to illustrate the method. The population consisted of 10 full-sib families from a cross between 2 broiler lines. Microsatellite genotypes were determined on generations 1 and 2, and phenotypes were collected on groups of generation 3 animals. The model included a polygenic correlation, which had a posterior mean of 0.70 in the analyses. The reanalysis agreed on the presence of a QTL in marker bracket MCW0058-LEI0071 accounting for 34% of the genetic variation in males and 24% in females in the growth efficiency experiment. In the carcass experiment, this QTL accounted for 19% of the genetic variation in males and 6% in females.

Association of markers in the bovine CAPN1 gene with meat tenderness in large crossbred populations that sample influential industry sires.

Two previously identified single-nucleotide polymorphism markers located within the micromolar calcium-activated neutral protease gene (CAPN1) were evaluated for their association with variation in meat tenderness using one commercial sample of Simmental x Angus crossbred calves and one multibreed, crossbred research herd. The commercial sample included 362 animals sired by 23 registered Simmental bulls bred to unregistered Angus cows and represented current industry animals in which to test the predictive merit of the markers. The second sample was a research herd including 564 steers from the Germplasm Evaluation Cycle VII population at the U.S. Meat Animal Research Center, produced with semen from popular sires of the seven Bos taurus beef breeds with the most registrations in the United States (Angus, Charolais, Gelbvieh, Hereford, Limousin, Red Angus, and Simmental) on Angus, Hereford, and MARC III cows. These animals form a relatively outbred population that constituted a stringent test of the predictive merit of the genetic markers, although small groups were half-sibs. Warner-Bratzler shear force measurements were used to determine tenderness phenotypes for all animals. The populations were genotyped for two markers that predict variation at amino acid positions 316 and 530 of the mu-calpain polypeptide, produced by the CAPN1 gene. Minor allele frequencies for markers 316 and 530 in the commercial sample were 0.17 and 0.37, respectively, and in the Cycle VII animals, were 0.20 and 0.28, respectively. Both markers showed association with shear force in the commercial sample (P = 0.04) and the Cycle VII population (P = 0.02), supporting the hypothesis that they represent potential markers to aid selection for improved meat tenderness in commercial populations of beef cattle in the United States.

Evaluation of Simmental carcass EPD estimated using live and carcass data.

This study was conducted to compare carcass EPD predicted using yearling live animal data and/or progeny carcass data, and to quantify the association between the carcass phenotype of progeny and the sire EPD. The live data model (L) included scan weight, ultrasound fat thickness, longissimus muscle area, and percentage of intramuscular fat from yearling (369 d of age) Simmental bulls and heifers. The carcass data model (C) included hot carcass weight, fat thickness, longissimus muscle area, and marbling score from Simmental-sired steers and cull heifers (453 d of age). The combined data model (F) included live animal and carcass data as separate but correlated traits. All data and pedigree information on 39,566 animals were obtained from the American Simmental Association, and all EPD were predicted using animal model procedures. The genetic model included fixed effects of contemporary group and a linear covariate for age at measurement, and a random animal genetic effect. The EPD from L had smaller variance and range than those from either C or F. Further, EPD from F had highest average accuracy. Correlations indicated that evaluations from C and F were most similar, and L would significantly (P < 0.05) re-rank sires compared with models including carcass data. Progeny (n = 824) with carcass data collected subsequent to evaluation were used to quantify the association between progeny phenotype and sire EPD using a model including contemporary group, and linear regressions for age at slaughter and the appropriate sire EPD. The regression coefficient was generally improved for sire EPD from L when genetic regression was used to scale EPD to the appropriate carcass trait basis. The EPD from C and F had similar linear associations with progeny phenotype, although EPD from F may be considered optimal because of increased accuracy. These data suggest that carcass EPD based on a combination of live and carcass data predict differences in progeny phenotype at or near theoretical expectation.

Genetic parameters for carcass traits and their live animal indicators in Simmental cattle.

The objective of this study was to estimate parameters required for genetic evaluation of Simmental carcass merit using carcass and live animal data. Carcass weight, fat thickness, longissimus muscle area, and marbling score were available from 5,750 steers and 1,504 heifers sired by Simmental bulls. Additionally, yearling ultrasound measurements of fat thickness, longissimus muscle area, and estimated percentage of intramuscular fat were available on Simmental bulls (n = 3,409) and heifers (n = 1,503). An extended pedigree was used to construct the relationship matrix (n = 23,968) linking bulls and heifers with ultrasound data to steers and heifers with carcass data. All data were obtained from the American Simmental Association. No animal had both ultrasound and carcass data. Using an animal model and treating corresponding ultrasound and carcass traits separately, genetic parameters were estimated using restricted maximum likelihood. Heritability estimates for carcass traits were 0.48 +/- 0.06, 0.35 +/- 0.05, 0.46 +/- 0.05, and 0.54 +/- 0.05 for carcass weight, fat thickness, longissimus muscle area, and marbling score, respectively. Heritability estimates for bull (heifer) ultrasound traits were 0.53 +/- 0.07 (0.69 +/- 0.09), 0.37 +/- 0.06 (0.51 +/- 0.09), and 0.47 +/- 0.06 (0.52 +/- 0.09) for fat thickness, longissimus muscle area, and intramuscular fat percentage, respectively. Heritability of weight at scan was 0.47 +/- 0.05. Using a bivariate weight model including scan weight of bulls and heifers with carcass weight of slaughter animals, a genetic correlation of 0.77 +/- 0.10 was obtained. Models for fat thickness, longissimus muscle area, and marbling score were each trivariate, including ultrasound measurements on yearling bulls and heifers, and corresponding carcass traits of slaughter animals. Genetic correlations of carcass fat thickness with bull and heifer ultrasound fat were 0.79 +/- 0.13 and 0.83 +/- 0.12, respectively. Genetic correlations of carcass longissimus muscle area with bull and heifer ultrasound longissimus muscle area were 0.80 +/- 0.11 and 0.54 +/- 0.12, respectively. Genetic correlations of carcass marbling score with bull and heifer ultrasound intramuscular fat percentage were 0.74 +/- 0.11 and 0.69 +/- 0.13, respectively. These results provide the parameter estimates necessary for genetic evaluation of Simmental carcass merit using both data from steer and heifer carcasses, and their ultrasound indicators on yearling bulls and heifers.

An autoregressive repeatability animal model for test-day records in multiple lactations.

Test-day (TD) models are becoming a standard for genetic evaluation of production traits in dairy cattle. Various approaches to model covariances between TD records include random regression, autoregressive repeatability, orthogonal polynomials, and models based on character processing. The applicability of these models is mainly associated with the number of parameters to estimate, incorporation of multiple lactations, and the accuracy of correlations generated by the cow's repeated expression of milking performance (TD yields) within and across lactations. We define and evaluate a multiple-lactation, autoregressive-repeatability model that disentangles environmental effects due to cow within and between lactations. Simulated records either included or ignored a long-term environmental effect between lactations. Our autoregressive TD animal model correctly detected presence and the absence of this effect and accurately recovered the assumed variance components and correlations underlying the data (10 parameters for three lactations). Estimates of variance components and autocorrelation coefficients were obtained using DFREML-simplex methodology. Given the value of this approach to reduce the size of residual variance components, autoregressive animal models are a preferable alternative to classical methods based on cumulative lactation yield to improve milk production in dairy cattle.

Trajetória de crescimento e efeito da idade da vaca nos modelos de regressäo aleatória de bovinos jovens da raça Tabapuä / Growth trajectory and age-of-dam effect for random regression models of young Tabapuä beef cattle

Para estabelecer a melhor forma de considerar os efeitos fixos dos modelos de regressäo aleatória, avaliou-se a utilizaçäo de funçöes polinomiais na descriçäo de curvas de crescimento e no efeito da idade da vaca sobre pesos corporais de 41.415 bovinos jovens da raça Tabapuä, criados em regime de pasto. A idade da vaca ao parto e o sexo do animal influenciaram os pesos nos primeiros dois anos de vida, e o efeito da idade da mäe sobre o desenvolvimento dos animais mostrou-se dependente da idade dos filhos. Altos coeficientes de determinaçäo (R²>0,98) foram alcançados utilizando-se o efeito da idade da vaca no dia da pesagem do animal (i.e., a idade da vaca ao parto mais a idade do animal no dia de sua pesagem) em polinômios de, no mínimo, segundo grau, e curvas de crescimentos médios, diferenciadas para machos e fêmeas, descritas por meio de polinômios de, no mínimo, terceiro grau