Cumulative t-link threshold models for the genetic analysis of calving ease scores

In this study, a hierarchical threshold mixed model based on a cumulative t-link specification for the analysis of ordinal data or more, specifically, calving ease scores, was developed. The validation of this model and the Markov chain Monte Carlo (MCMC) algorithm was carried out on simulated data from normally and t₄ (i.e. a t-distribution with four degrees of freedom) distributed populations using the deviance information criterion (DIC) and a pseudo Bayes factor (PBF) measure to validate recently proposed model choice criteria. The simulation study indicated that although inference on the degrees of freedom parameter is possible, MCMC mixing was problematic. Nevertheless, the DIC and PBF were validated to be satisfactory measures of model fit to data. A sire and maternal grandsire cumulative t-link model was applied to a calving ease dataset from 8847 Italian Piemontese first parity dams. The cumulative t-link model was shown to lead to posterior means of direct and maternal heritabilities (0.40 ± 0.06, 0.11 ± 0.04) and a direct maternal genetic correlation (-0.58 ± 0.15) that were not different from the corresponding posterior means of the heritabilities (0.42 ± 0.07, 0.14 ± 0.04) and the genetic correlation (-0.55 ± 0.14) inferred under the conventional cumulative probit link threshold model. Furthermore, the correlation (> 0.99) between posterior means of sire progeny merit from the two models suggested no meaningful rerankings. Nevertheless, the cumulative t-link model was decisively chosen as the better fitting model for this calving ease data using DIC and PBF.     

Genome-wide association study identifies two major loci affecting calving ease and growth-related traits in cattle

Identifying quantitative trait loci (QTL) underlying complex, low-heritability traits is notoriously difficult. Prototypical for such traits, calving ease is an important breeding objective of cattle (Bos taurus)-improving programs. To identify QTL underlying calving ease, we performed a genome-wide association study using estimated breeding values (EBVs) as highly heritable phenotypes for paternal calving ease (pCE) and related traits. The massively structured study population consisted of 1800 bulls of the German Fleckvieh (FV) breed. Two pCE-associated regions on bovine chromosomes (BTA) 14 and 21 (P = 5.72 × 10(-15) and P = 2.27 × 10(-8), respectively) were identified using principal components analysis to correct for population stratification. The two most significantly associated SNPs explain 10% of the EBV variation. Since marker alleles with negative effect on pCE have positive effects on growth-related traits, the QTL may exert their effects on the birthing process through fetal growth traits. The QTL region on BTA14 corresponds to a human chromosome (HSA) region that is associated with growth characteristics. The HSA region corresponding to the BTA21 pCE QTL is maternally imprinted and involved in the Prader-Willi and Angelman syndromes. Resequencing of positional candidate genes on BTA14 revealed a highly significantly (P = 1.96 × 10(-14)) associated polymorphism ablating a polyadenylation signal of the gene encoding ribosomal protein S20 (RPS20). Our study demonstrates the leverage potential of EBVs in unraveling the genetic architecture of lowly heritable traits.     

Multivariate analysis of factors associated with calving interval and calving rate in dairy cows

We collected data on reproductive events of cows (n = 2116) that included dates of calving, first service, last artificial insemination before pregnancy examination, pregnancy examination, abortion, diagnosis of cystic ovary, and treatment with prostaglandin. We used multivariate analysis to evaluate the relationship between the interval from insemination to pregnancy examination and the length of calving interval, adjusting for other factors affecting the calving interval. The effect of the interval from insemination to pregnancy examination on calving rate was estimated using logistic regression analysis. The calving interval was long for cows with a short interval from artificial insemination to first pregnancy examination, it was at a minimum at 55 d and increased thereafter. Other factors affecting the calving interval were cystic ovaries, prostaglandin treatment, abortion, number of artificial inseminations, and days to first service. The calving rate was low among cows with a short interval to pregnancy examination, reached a maximum at 48 d, and then declined. Other factors affecting the calving rate were abortion, number of artificial inseminations and whether the cow was bred by a clean-up bull.     

Potential accuracy of genetic evaluation for calving difficulty with incomplete data on calving difficulty and/or birth weight using a bivariate threshold-linear animal model

The purpose of this study was to evaluate the potential loss of accuracy in direct and maternal predicted breeding values (PBV) for calving difficulty (CD) with different levels of missing records of CD and/or birth weight (BW), using a bivariate threshold-linear animal model. Data obtained from the American Gelbvieh Association included 84,420 first-parity records with both CD and BW available. The final pedigree file included 178,858 animals. The model included fixed calf-sex-dam-age, random herd-year-season, and animal direct and maternal effects. Different levels of missing observations for CD and BW were obtained by randomly deleting 0, 25, 50, 75, and 100% of records for both traits in various combinations. Correlation estimates between PBV for CD obtained with complete and incomplete data were used to measure the changes in PBV for different levels of missing records. Reported correlations are means of three replicates. The results suggest that the information on direct and maternal PBV provided by CD records is more reliable than the information provided by BW records. The difference was especially large when a high proportion of CD records were missing. Correlations above 0.96 and 0.95 for direct and maternal PBV, respectively, when missing 25% or 0% of the CD or BW records suggest that small changes would be predicted with a low proportion incomplete data. For genetic prediction of popular sires (with > 100 pogeny), a higher proportion of missing records could be tolerated. The results suggest that the bivariate threshold-linear animal model is useful for routine genetic evaluation of CD with incomplete field data.     

A partial explanation of superior birth weights among foreign-born women

This study of 766 black women reexamined the issue of advantage in birthweight and length of gestation in foreign-born women and confirms the reported higher birthweights among that group. Subjects were new registrants for prenatal care at a public clinic in Harlem, New York City, 1971-73, and were part of a randomized trial of nutritional supplementation during pregnancy. 3 nativity groups were represented: New York City, southern United States, and foreign countries. Despite the standard selection of all subjects for high risk for low birthweight, foreign-born women had only 3.8% of births under 2500 grams in contrast to 15.6% among the southern women, and 18% among New York City natives. 6 sets of variables were examined in relation to birthweight outcome. An average birthweight advantage of 218 grams for the foreign-born was found to be associated with higher childhood social status and more positive health behaviors.     

Transfer of fresh and cryopreserved IVP bovine embryos: normal calving, birth weight and gestation lengths

In vitro and in vivo developmental competence of fresh and cryopreserved in vitro produced (IVP) bovine embryos was evaluated up to birth. Three experiments were done. The objective in the first experiment was to develop an optimal vitrification procedure for IVP bovine embryos by determining effects of exposure time (2, 5, 10, 20 min) and temperature (4, 22, 27 degrees C) in cryoprotective agents prior to vitrification on their post-thaw viability. The best combination was used in Experiments 2 and 3. In the second experiment, the importance of post-thaw morphologic selection on pregnancy rates was determined by transferring either selected or unselected single embryos. In the third experiment, pregnancy initiation, maintenance and calving results of vitrified embryos were compared with fresh and conventionally frozen embryos. Fetal losses, birth weights, gestation lengths and frequency of dystocia in the third experiment were monitored. The interaction of exposure time and temperature on both post-thaw re-expansion and hatching rates was significant (P < 0.01). Five minute exposure at 27 degrees C was optimal. In the second experiment, post-thaw selected vitrified embryos had higher pregnancy rates than unselected embryos (P < 0.05). In the third experiment, the pregnancy rate of vitrified embryos did not differ from that of fresh embryos (P > 0.05). However, pregnancy rate of conventionally frozen embryos was lower than that of fresh or vitrified embryos (P < 0.05). Of 92 calves born, 53 were male and 39 were female. Birth weights and dystocia scores of single-born calves did not differ between sexes (P > 0.05). Twin-born calves were lighter than single-born calves (P < 0.05). Overall, the data demonstrate that the transfer of vitrified IVP bovine embryos can result in healthy, apparently normal calves similar to those derived from transfer of fresh and conventionally frozen IVP bovine embryos.     

Exploring biological relationships between calving traits in primiparous cattle with a Bayesian recursive model

Structural equation models (SEMs) of a recursive type with heterogeneous structural coefficients were used to explore biological relationships between gestation length (GL), calving difficulty (CD), and perinatal mortality, also known as stillbirth (SB), in cattle, with the last two traits having categorical expression. An acyclic model was assumed, where recursive effects existed from the GL phenotype to the liabilities (latent variables) to CD and SB and from the liability to CD to that of SB considering four periods regarding GL. The data contained GL, CD, and SB records from 90,393 primiparous cows, sired by 1122 bulls, distributed over 935 herd-calving year classes. Low genetic correlations between GL and the other calving traits were found, whereas the liabilities to CD and SB were high and positively correlated, genetically. The model indicated that gestations of approximately 274 days of length (3 days shorter than the average) would lead to the lowest CD and SB and confirmed the existence of an intermediate optimum of GL with respect to these traits.     

Bayesian estimates of genetic parameters for pre-conception traits, gestation length and calving interval in beef cattle

A total of 5253 records obtained from 2081 Rubia Gallega beef cows managed using artificial insemination as the only reproduction system were analysed to estimate genetic parameters for days to first insemination (DFI), days from first insemination to conception (FIC), number of inseminations per conception (IN), days open (DO), gestation length (GL) and calving interval (CI) via multitrait Bayesian procedures. Estimates of the mean of posterior distribution of the heritability of DFI, FIC, IN, DO, GL and CI were, respectively, 0.050, 0.078, 0.071, 0.053, 0.037 and 0.085 and the corresponding estimates for repeatability of these traits were 0.116, 0.129, 0.147, 0.138, 0.082 and 0.132, respectively. No significant genetic correlations associated to DFI or GL were found. However, genetic correlations between the other four analysed traits were high and significant. Genetic correlations between FIC and IN, DO and CI were similar and higher than 0.85. Genetic correlations of IN-DO and IN-CI were over 0.65. The highest genetic correlation was estimated for the pair DO-CI (0.992) that can be considered the same trait in genetic terms. Results indicated that DFI can be highly affected by non-genetic factors thus limiting its usefulness to be used as an earlier indicator of reproductive performance in beef cattle. Moreover, GL could not be associated to the reproductive performance of the cow before conception. The other four analysed traits, FIC, IN, DO and CI, have close genetic relationships. The inclusion of IN as an earlier indicator of fertility in beef cattle improvement programs using artificial insemination as the main reproductive system can be advisable due to the low additional recording effort needed.     

Effect of swine lymphocyte antigen haplotypes on birth and weaning weights in pigs

Birth weights of 708 live piglets and weaning weights of 566 piglets were used to investigate the effect of the swine lymphocyte antigen (SLA) complex on these traits in Large White pigs. Piglets were from litters of a long-term selection experiment to measure response for selection to increase litter size. SLA haplotypes were determined using conventional class I antisera. A total of 14 haplotypes were detected. The effect of SLA haplotype on birth and weaning weights was investigated using a statistical model that included the effects of experimental group, sire, dam, sex and SLA haplotype. Results indicated that SLA class I haplotype 13.1.3 increased birth weights (P less than 0.10) and significantly increased weaning weights (P less than 0.01). This effect of haplotype 13.1.3 on weaning weight was 605 +/- 215 g (0.3 standard deviations). SLA class I homozygosity did not appear to affect birth and weaning weights. These results suggest that the SLA complex plays an important role in early growth in the pig and that further study of SLA effects on growth and reproduction are warranted.     

Seasonal variation in pre- and postpartum maternal body measurements and infant birth weights

A sample of 225 rural Taiwanese women were followed longitudinally through two successive pregnancy and lactation periods. Maternal pre- and postpartum weight and skinfold thicknesses and infant birth weights showed considerable seasonal variation. The lowest mean maternal weights, irrespective of pregnancy or lactation status, occurred in the summer months of June, July, and August, when temperatures and rainfall reach their yearly maxima. The lowest mean birth weights were also recorded for the warm, rainy summer months. Furthermore, a disproportionate number of infants weighing less than one standard deviation below the mean birth weight were born between May and October. The observed seasonal variations most probably reflect annual cycles of agricultural activities and food availability.     

Bayesian inference in genetic parameter estimation of visual scores in Nellore beef-cattle

The aim of this study was to estimate the components of variance and genetic parameters for the visual scores which constitute the Morphological Evaluation System (MES), such as body structure (S), precocity (P) and musculature (M) in Nellore beef-cattle at the weaning and yearling stages, by using threshold Bayesian models. The information used for this was gleaned from visual scores of 5,407 animals evaluated at the weaning and 2,649 at the yearling stages. The genetic parameters for visual score traits were estimated through two-trait analysis, using the threshold animal model, with Bayesian statistics methodology and MTGSAM (Multiple Trait Gibbs Sampler for Animal Models) threshold software. Heritability estimates for S, P and M were 0.68, 0.65 and 0.62 (at weaning) and 0.44, 0.38 and 0.32 (at the yearling stage), respectively. Heritability estimates for S, P and M were found to be high, and so it is expected that these traits should respond favorably to direct selection. The visual scores evaluated at the weaning and yearling stages might be used in the composition of new selection indexes, as they presented sufficient genetic variability to promote genetic progress in such morphological traits.     

Genetic associations between weight at maturity and maturation rate with ages and weights at first and second calving in Canchim beef cattle

Genetic parameters for weight at maturity (WM), maturation rate (MR), age and weight at first calving (AFC and WFC) and second calving (ASC and WSC) were estimated for females of the Canchim breed. The number of records per trait ranged from 1440 to 1923. The restricted maximum likelihood method was used and the statistical model included the fixed effect of contemporary group and the additive genetic and residual as random effects. The mean heritability estimate and respective standard errors were 0.34±0.05 (WM), 0.13±0.04 (MR), 0.14±0.04 (AFC), 0.44±0.06 (WFC), 0.16±0.06 (ASC) and 0.39±0.06 (WSC). The heritability estimate for WM and MR suggested that it would be possible to achieve changes in the animals' growth curve through selection, but the genetic correlation between these two traits suggested that there would be antagonism between them. Selection for WM would result in animals with later growth and would also affect individuals' sexual precocity. This was also seen from the genetic correlations between WM and the other traits, which ranged from 0.37 to 0.98; and between MR and the other traits, which ranged from -0.83 to -0.25. Selection to modify WM would be expected to result in correlated responses in AFC, WFC and WSC and a moderate response in ASC. Although the heritability estimate for MR was low, selection aimed for its increase might cause a large decrease in AFC, ASC and WFC and a moderate change in WSC, and this could be an alternative for improving the progeny's overall performance.     

Bayesian subset analysis.

As a means of assessing the importance of variation in treatment effect among patient subsets, we derived posterior distributions for subset-specific treatment effects. The effects are represented by combinations of terms for treatment and treatment-by-covariate interaction effects in familiar regression models. Exchange-ability among the interactions is a key assumption; thus, the results are of interest primarily in the context of examining a collection of subsets with no definite a priori distinction relative to treatment effect. Exchangeability leads to a shrinking of the posterior distributions of the interaction terms toward the natural origin of 0, offsetting the tendency of the estimated effects to disperse. The method is applied to parameter estimates from a proportional hazards regression analysis of survival data from a clinical trial, invoking the approximate multivariate normal distribution of the estimates. No subjective prior distributions are required. Vague priors are used for all of the regression coefficients except the treatment-by-covariate interactions, which are assumed to follow a normal distribution.     

Bayesian isotonic regression and trend analysis

In many applications, the mean of a response variable can be assumed to be a nondecreasing function of a continuous predictor, controlling for covariates. In such cases, interest often focuses on estimating the regression function, while also assessing evidence of an association. This article proposes a new framework for Bayesian isotonic regression and order-restricted inference. Approximating the regression function with a high-dimensional piecewise linear model, the nondecreasing constraint is incorporated through a prior distribution for the slopes consisting of a product mixture of point masses (accounting for flat regions) and truncated normal densities. To borrow information across the intervals and smooth the curve, the prior is formulated as a latent autoregressive normal process. This structure facilitates efficient posterior computation, since the full conditional distributions of the parameters have simple conjugate forms. Point and interval estimates of the regression function and posterior probabilities of an association for different regions of the predictor can be estimated from a single MCMC run. Generalizations to categorical outcomes and multiple predictors are described, and the approach is applied to an epidemiology application.     

Bayesian analysis of mutational spectra

Studies that examine both the frequency of gene mutation and the pattern or spectrum of mutational changes can be used to identify chemical mutagens and to explore the molecular mechanisms of mutagenesis. In this article, we propose a Bayesian hierarchical modeling approach for the analysis of mutational spectra. We assume that the total number of independent mutations and the numbers of mutations falling into different response categories, defined by location within a gene and/or type of alteration, follow binomial and multinomial sampling distributions, respectively. We use prior distributions to summarize past information about the overall mutation frequency and the probabilities corresponding to the different mutational categories. These priors can be chosen on the basis of data from previous studies using an approach that accounts for heterogeneity among studies. Inferences about the overall mutation frequency, the proportions of mutations in each response category, and the category-specific mutation frequencies can be based on posterior distributions, which incorporate past and current data on the mutant frequency and on DNA sequence alterations. Methods are described for comparing groups and for assessing dose-related trends. We illustrate our approach using data from the literature.