Browsing by Author "Bapst, Beat"

Prediction of genomic breeding values is of major practical relevance in dairy cattle breeding. Deterministic equations have been suggested to predict the accuracy of genomic breeding values in a given design which are based on training set size, reliability of phenotypes, and the number of independent chromosome segments (Me). The aim of our study was to find a general deterministic equation for the average accuracy of genomic breeding values that also accounts for marker density and can be fitted empirically. Two data sets of similar to 698 Holstein Friesian bulls genotyped with 50 K SNPs and 19332 Brown Swiss bulls genotyped with 50 K SNPs and imputed to,600 K SNPs were available. Different k-fold (k = 2-10, 15, 20) cross-validation scenarios (50 replicates, random assignment) were performed using a genomic BLUP approach. A maximum likelihood approach was used to estimate the parameters of different prediction equations. The highest likelihood was obtained when using a modified form of the deterministic equation of Daetwyler et al. (2010), augmented by a weighting factor (w) based on the assumption that the maximum achievable accuracy is w < 1. The proportion of genetic variance captured by the complete SNP sets (w(2)) was 0.76 to 0.82 for Holstein Friesian and 0.72 to 0.75 for Brown Swiss. When modifying the number of SNPs, w was found to be proportional to the log of the marker density up to a limit which is population and trait specific and was found to be reached with,209000 SNPs in the Brown Swiss population studied.

In this study, direct genomic values for the functional traits general temperament, milking temperament, aggressiveness, rank order in herd, milking speed, udder depth, position of labia, and days to first heat in Brown Swiss dairy cattle were estimated based on similar to 777,000 (777K) single nucleotide polymorphism (SNP) information from 1,126 animals Accuracy of direct genomic values was assessed by a 5-fold cross-validation with 10 replicates. Correlations between deregressed proofs and direct genomic values were 0.63 for general temperament, 0.73 for milking temperament, 0.69 for aggressiveness, 0.65 for rank order in herd, 0.69 for milking speed, 0.71 for udder depth, 0.66 for position of labia, and 0.74 for days to first heat. Using the information of similar to 54,000 (54K) SNP led to only marginal deviations in the observed accuracy. Trying to predict the 20% youngest bulls led to correlations of 0.55, 0.77, 0.73, 0.55, 0.64, 0.59, 0.67, and 0.77, respectively, for the traits listed above. Using a novel method to estimate the accuracy of a direct genomic value (defined as correlation between direct genomic value and true breeding value and accounting for the correlation between direct genomic values and conventional breeding values) revealed accuracies of 0.37, 0.20, 0.19, 0.27, 0.48, 0.45, 0.36, and 0.12, respectively, for the traits listed above. These values are much smaller but probably also more realistic than accuracies based on correlations, given the heritabilities and samples sizes in this study. Annotation of the largest estimated SNP effects revealed 2 candidate genes affecting the traits general temperament and days to first heat.

The aim of this study was to estimate genetic parameters and accuracies of breeding values for milk content traits of individual udder quarters in Brown Swiss cattle. Data of 1,799 phenotyped cows from 40 Swiss dairy herds were analyzed, taking the complete pedigree into account. Fat, protein, lactose, and urea contents, somatic cell score (S CS), and information about hyperkeratosis were available for each udder quarter. The milk of rear udder quarters was found to have significantly higher lactose content and significantly lower fat content than milk of the front udder quarters. The same trend found for fat content was observed for protein content, whereas no differences between the udder quarters were observed for urea content, SCS, or hyperkeratosis. Heritabilities for each udder quarter were in the following ranges: fat content 0.09 +/- 0.06 to 0.14 +/- 0.06, protein content 0.20 +/- 0.09 to 0.33 +/- 0.07, lactose content 0.04 +/- 0.03 to 0.16 +/- 0.07, urea content 0.13 +/- 0.07 to 0.22 +/- 0.08, SCS 0.18 +/- 0.06 to 0.32 +/- 0.07, and hyperkeratosis 0.12 +/- 0.04 to 0.26 +/- 0.05. In our study, hyperkeratosis, protein content, and SCS showed higher heritabilities in the front udder quarters, fat content had higher heritabilities in the rear udder quarters, and no systematic pattern in heritability was observed for lactose content or urea content. Additive genetic correlations between all udder quarters were >0.90 for protein and urea contents, whereas they were remarkably low (<0.60) for SCS. For fat and lactose contents, the genetic correlations between the 2 front or between the 2 rear quarters, respectively, were notably higher than correlations between 1 front and 1 rear quarter, suggesting that the front and the rear udders could be considered as partly genetically different organs. The variability within the udder as such was found to be of low heritability (<0.10) in general, but repeatability was moderate to high for some traits (lactose content: 0.33 +/- 0.05, protein content: 0.53 +/- 0.05). Some of these findings can be explained by differences in the physiological background of the traits.

The aim of this study was to estimate genetic parameters and accuracies of breeding values for a set of functional, behavior, and conformation traits in Brown Swiss cattle. These traits were milking speed, udder depth, position of labia, rank order in herd, general temperament, aggressiveness, milking temperament, and days to first heat. Data of 1,799 phenotyped Brown Swiss cows from 40 Swiss dairy herds were analyzed taking the complete pedigree into account. Estimated heritabilities were within the ranges reported in literature, with results at the high end of the reported values for some traits (e.g., milking speed: 0.42 +/- 0.06, udder depth: 0.42 +/- 0.06), whereas other traits were of low heritability and heritability estimates were of low accuracy (e.g., milking temperament: 0.04 +/- 0.04, days to first heat: 0.02 +/- 0.04). For most behavior traits, we found relatively high heritabilities (general temperament: 0.38 +/- 0.07, aggressiveness: 0.12 +/- 0.08, and rank order in herd: 0.16 +/- 0.06). Position of labia, arguably an indicator trait for pathological urovagina, was genetically analyzed in this study for the first time, and a moderate heritability (0.28 +/- 0.06) was estimated.

Genetic parameters were inferred for the health traits mastitis, metritis, retained placenta, ovarian cysts and acetonemia from 1247 Brown Swiss cows in first parity kept in 53 organic and low input farms in Switzerland. For genetic analyses, univariate animal and sire models, repeatability animal and sire models, and random regression sire models (RRM) in a "generalized linear mixed model (GLMM) context" were applied. The five health traits were defined as binary data, count data, and longitudinal binary data in the interval between -1 and 120 d in milk (DIM). Firstly, binary data were analyzed by applying linear animal and sire models, and threshold animal and sire models with a probit link function. Secondly, data of total number of disease cases recorded within the defined time span were analyzed by using GLMM animal and sire models with a log link function for Poisson distributed count data. Thirdly, for longitudinal health data, linear repeatability animal and sire models, linear sire RRM, threshold animal and sire repeatability models, and threshold sire RRM with a probit link function were applied. Disease incidences of the five health disorders in organic farms were on a generally low level, with a highest incidence of 5.78% for mastitis within the time span of 120 d. With regard to mastitis, moderate heritabilities with an average value of 0.15 were realized from univariate models and binary data, and from GLMM with the log link function and count data. Heritabilities for mastitis were smaller ( < 0.10) when using the longitudinal data structure in combination with repeatability models and RRM. Repeatabilities and heritabilities for longitudinal data as realized from repeatability models were on a quite similar level. Only for longitudinal ovarian cysts, heritabilities substantially differed from repeatabilities. Heritability was 0.02 from the animal model and 0.01 from the sire model, but repeatabilities were 0.14, which indicates a substantial permanent environmental effect. Daily heritabilities for all health traits from linear and threshold RRM at the beginning of lactation and at the end of the defined interval were three times higher than corresponding heritabilities in the middle of lactation. Bayesian information criterion (BIC) and heritabilities themselves favored threshold models over linear models. However, linear models converged more easily than threshold models, and genetic parameter estimates had smaller standard errors. Similar BIC values were found when comparing animal with sire models, although generally higher heritabilities were realized from sire models. For RRIVI applications, BIC was smaller and heritabilities were higher for linear sire compared to threshold sire models. (C) 2014 Elsevier B.V. All rights reserved.

Organic and low input farming differ substantially from conventional farming, suggesting the need for separate breeding programs. This requires knowledge of (co)variance components of important traits in low input or organic production systems. Test-day data for production and data for reproduction traits from 1283 Brown Swiss cows kept in 54 small, low input farms across Switzerland were available. Production traits milk yield (MY), fat percentage (Fat%), protein percentage (Pro%), lactose percentage (Lac%), somatic cell score (SCS), and milk urea nitrogen (MUN), were analyzed with a multi-trait random regression animal model with days in milk (DIM) as a time covariate. Female fertility traits of number of inseminations (NI), stillbirth (SB), calving ease (CE), calving to first service (CTFS), days open (DO), and gestation length (CL) were analyzed with parity as a time covariate, with threshold methodology applied for the first three traits. A threshold-linear sire model was applied to estimate daily correlations between MY, Fat%, Pro%, SCS, MUN and the binary distributed fertility trait conception rate (CR). In general, daily heritabilities for production traits followed the pattern as found for high input production systems. Expected genetic antagonisms were found between my and Pro%, and between MY and Fat% for all DIM. An antagonistic relationship between MY and SCS was only found directly after calving in parity 1. In parities 2 to 7, heritabilities for an interval trait describing the cows' ability to recover after calving, e.g. CTFS, were lower than estimates for traits associated with a successful insemination, e.g. NI and DO. Pronounced antagonistic relationships between MY and CR were in the range of -0.40 to -0.80 from DIM 20 to DIM 200. In this study, we showed the variety and flexibility of random regression methodology which can be applied to data from small herds, and for a limited number of repeated measurements of a categorical trait per cow. Estimated genetic parameters for reproduction traits were partly different from those estimated in high input production systems. In particular, these differences underline the necessity to implement an own organic breeding program using estimates from the current study which are based on data obtained only from cows in organic or low input herds. (C) 2012 Elsevier B.V. All rights reserved.