C. Fuerst

Short communication: Genomic selection using a multi-breed, across-country reference population

Three breeds (Fleckvieh, Holstein, and Jersey) were included in a reference population, separately and together, to assess the accuracy of prediction of genomic breeding values in single-breed validation populations. The accuracy of genomic selection was defined as the correlation between estimated breeding values, calculated using phenotypic data, and genomic breeding values. The Holstein and Jersey populations were from Australia, whereas the Fleckvieh population (dual-purpose Simmental) was from Austria and Germany. Both a BLUP with a multi-breed genomic relationship matrix (GBLUP) and a Bayesian method (BayesA) were used to derive the prediction equations. The hypothesis tested was that having a multi-breed reference population increased the accuracy of genomic selection. Minimal advantage existed of either GBLUP or BayesA multi-breed genomic evaluations over single-breed evaluations. However, when the goal was to predict genomic breeding values for a breed with no individuals in the reference population, using 2 other breeds in the reference was generally better than only 1 breed.

Genetic analysis of clinical mastitis and somatic cell count traits in Austrian Fleckvieh cows

The objectives of this study were to investigate genetic associations between clinical mastitis (CM) and different somatic cell count traits, and to examine their relationships, in terms of estimated breeding values, with other traits that are routinely evaluated in Austrian Fleckvieh dual-purpose cows. Records on veterinary treatments of CM were available from the Austrian health-monitoring project. For CM, 3 intervals in early lactation were considered: -10 to 50 d, 51 to 150 d, and -10 to 150 d after calving. Within each interval, absence or presence of CM was scored as 1 or 0 based on whether or not the cow had recorded at least one veterinary treatment of CM. The average somatic cell score of the first 2 test-days after calving was defined as early lactation average somatic cell score, and lactation mean somatic cell score was the average of all test-day somatic cell scores from 8 to 305 d after calving. Subclinical mastitis was expressed as a binary trait based on prolonged elevated somatic cell counts. If somatic cell counts on 3 consecutive test-days in the interval from 8 to 305 d after calving were above 200,000 cells/mL, the binary variable subclinical mastitis was defined as 1 and otherwise 0. Records of Austrian Fleckvieh cows, with calving from January 1, 2007, to February 28, 2009, were analyzed using univariate and bivariate sire models. Threshold liability models were applied for binary traits, and Gaussian models were used for early lactation average somatic cell score and lactation mean somatic cell score. A Bayesian approach using Gibbs sampling was applied for genetic analyses. Posterior means of heritability of liability to CM were 0.06 and 0.02 in the first and second interval, respectively, and 0.05 in the full period (-10 to 150 d). Heritability estimates of somatic cell count traits were higher (0.09 to 0.13). The posterior mean of the genetic correlation between CM in lactation period 1 (-10 to 50 d after calving) and 2 (51 to 150 d after calving) was close to unity. Posterior means of genetic correlations between CM and somatic cell count traits ranged from 0.64 to 0.77. Because CM and somatic cell count describe different aspects of udder health, information on both traits should be considered for selection of bulls. Correlations of sire breeding values revealed that especially the udder conformation trait udder depth may be useful as additional information to reduce both CM and somatic cell count.

Genetic analysis of reproductive disorders and their relationship to fertility and milk yield in Austrian Fleckvieh dual-purpose cows

The objective of this study was to estimate genetic parameters for various reproductive disorders based on veterinary diagnoses for Austrian Fleckvieh (Simmental) dual-purpose cattle. The health traits analyzed included retained placenta, puerperal diseases, metritis, silent heat and anestrus, and cystic ovaries. Three composite traits were also evaluated: early reproductive disorders, late reproductive disorders, and all reproductive disorders. Heritabilities were estimated with logit threshold sire, linear sire, and linear animal models. The threshold model estimates for heritability ranged from 0.01 to 0.14, whereas the linear model estimates were lower, ranging from 0.005 to 0.04. Rank correlations among random effects of sires from linear and threshold sire models were high (>0.99), whereas correlations between any sire model (linear, threshold) and the linear animal model were lower (0.88-0.92). Genetic correlations among reproductive disorders, fertility traits, and milk yield were estimated with bivariate linear animal models. Fertility traits included interval from calving to first insemination, nonreturn rate at 56 d, and interval between first and last insemination. Milk yield was calculated as the mean from test-day 1 and test-day 2 after calving. Estimated genetic correlations were 1 among metritis, retained placenta, and puerperal diseases and 0.85 between silent heat-anestrus and cystic ovaries. Low to moderate correlations (-0.01 to 0.68) were obtained among the other disorders. Genetic correlations between reproductive disorders and fertility traits were favorable, whereas antagonistic relationships were observed between milk yield in early lactation and reproductive disorders. Pearson correlations between estimated breeding values for reproductive disorders and other routinely evaluated traits were computed, which revealed noticeable favorable relationships to longevity, calving ease maternal, and stillbirth maternal. The results showed that data from the Austrian health monitoring project can be used for genetic selection against reproductive disorders in Fleckvieh cattle.

Recording of direct health traits in Austria--experience report with emphasis on aspects of availability for breeding purposes.

A project to establish an Austria-wide health-monitoring system for cattle was launched in 2006. Veterinary diagnostic data subject to documentation by law [Law on the Control of Veterinary Medicinal Products (Tierarzneimittelkontrollgesetz)] are standardized, validated, and recorded in a central database. This Austria-wide project is a collaboration among agricultural and veterinary organizations as well as universities, and is also supported by the Austrian government. In addition to providing information for herd management and preventive measures, further objectives of the project include estimating breeding values for health traits and monitoring the overall health status of Austrias cattle. To ensure a high level of participation from farmers and veterinarians, data security issues are extremely important. Valid data are the prerequisite for the efficient use of health records. The challenge hereby is to distinguish between farms with low frequencies of diseases and incomplete documentation and recording. Measures were undertaken to establish a routine monitoring system for direct health traits. A routine genetic evaluation for direct health traits as part of the joint breeding value estimation program between Germany and Austria was introduced for Fleckvieh in December 2010, based on diagnostic data from 5,428 farms with 147,764 Fleckvieh cows. In 2010 to 2011, the reporting of direct health traits as a compulsory part of performance recording and the breeding program was introduced as well. The overall challenge is the availability of sufficient valid direct health data for reliable breeding values. Practical experience gained in Austria in setting up a health registration system, focusing mainly on the availability of direct health data for breeding purposes with its successes and difficulties, is described.

Comparison of different models for genetic analysis of clinical mastitis in Austrian Fleckvieh dual-purpose cows

The performance of different models for genetic analyses of clinical mastitis in Austrian Fleckvieh dual-purpose cows was evaluated. The main objective was to compare threshold sire models (probit and logit) with linear sire and linear animal models using REML algorithm. For comparison, data were also analyzed using a Bayesian threshold sire model. The models were evaluated with respect to ranking of sires and their predictive ability in cross-validation. Only minor differences were observed in estimated variance components and heritability from Bayesian and REML probit models. Heritabilities for probit and logit models were 0.06 and 0.08, respectively, whereas heritabilities for linear sire and linear animal models were lower (0.02). Correlations among ranking of sires from threshold and linear sire models were high (>0.99), whereas correlations between any sire model (threshold or linear) and the linear animal model were slightly lower (0.96). The worst sires were ranked very similar across all models, whereas for the best sires some reranking occurred. Further, models were evaluated based on their ability to predict future data, which is one of the main concerns of animal breeders. The predictive ability of each model was determined by using 2 criteria: mean squared error and Pearson correlation between predicted and observed value. Overall, the 5 models did not differ in predictive ability. In contrast to expectations, sire models had the same predictive ability as animal models. Linear models were found to be robust toward departures from normality and performed equally well as threshold models.

Impact of dominance and epistasis on the genetic make-up of simulated populations under selection: a model development

SUMMARY A two-locus genetic model was used to simulate different levels of additive, dominance, and additive-by-additive genetic effects. The character under phenotypic selection was controlled by 30 pairs of diallelic loci, located on different chromosomes. Initial gene frequencies were set to 0.5 for all loci and the recombination probability was 0.20 between adjacent loci. The broad-sense heritability was varied at levels of 0.03, 0.30, and 0.60. After building up a random mating population with 200 males and 400 females, the phenotypic best individuals per year were selected over 200 years (approx. 35 overlapping generations), keeping the population size constant. The results of the simulations showed extreme differences between eight models with the same initial heritability, but different amounts of additive, dominance, and additive-by-additive variance components. A model with additive, dominance, and additive-by-additive variance at the same initial magnitude, and negative dominance and positive additive-by-additive effect, led to the highest genetic response in the long term for all heritabilities simulated. The additive model showed the best selection advance in the short term. Some of the initial dominance and additive-by-additive variance was converted to additive genetic variance during the selection period, which in turn contributed to the selection response. ZUSAMMENFASSUNG: Auswirkungen von Dominanz and Epistasie auf den genetischen Aufbau von simulierten Populationen unter Selektion: Eine Modellentwicklung Ein 2-Locus-Genmodell wurde zur Simulation verschiedener Ausprägungen von additiven, Dominanz und additiv mal additiv genetischen Effekten verwendet. Das Merkmal under phänotypischer Selektion wurde von 30 diallelen Locuspaaren auf verschiedenen Chromosomen kontrolliert. Die Anfangsgenfrequenz wurde für alle Loci mit 0.5 angenommen und die Rekombinationsrate betrug 0.20 zwischen benachbarten Loci. Die Heritabilität im weiteren Sinn wurde zwischen 0.03, 0.30 und 0.60 variiert. Nach dem Aufbau einer Population durch Zufallspaarung von 200 männlichen und 400 weiblichen Individuen wurden die phänotypisch besten Individuen pro Jahr unter Konstanthaltung der Populationsgröße über einen Zeitraum von 200 Jahren (ca. 35 überlappende Generationen) selektiert. Die Ergebnisse der Simulationen zeigten extreme Unterschiede zwischen den acht Modellen mit der gleichen Anfangsheritabilität aber verschiedenen Anteilen von additiven, Dominanz und additiv mal additiven Varianzkomponenten. Ein Modell mit zu Beginn gleich hoher additiver, Dominanz und additiv mal additiver Varianz und negativem Dominanz- und positivem additiv mal additiven Effekt führte bei allen simulierten Heritabilitäten langfristig zum höchsten Selektionserfolg. Kurzfristig zeigte das additive Modell den höchsten Selektionsfortschritt. Ein Teil der Anfangs-Dominanz- und -Additiv mal additiv-Varianz wurde während der Selektionsperiode in additive Varianz umgewandelt, die wiederum zum Selektionserfolg beitrug.

Effect of inbreeding depression on survival of Austrian Brown Swiss calves and heifers

The aim of this study was to estimate inbreeding depression for juvenile mortality in Austrian Brown Swiss replacement heifers born in the years 2001 to 2007. After data editing, records of 69,571 animals were investigated. In total, the pedigree consisted of 203,894 animals. Mean and median inbreeding coefficients were 0.0514 and 0.0475, respectively. The following periods were defined for analyses of juvenile mortality: P1=48 h to 30 d, P2=31 to 180 d, P3=181 to the day before first calving or a maximum age of 1,200 d if no calving was reported, P4=48 h to the day before age at first calving or a maximum age of 1,200 d if no calving was reported. Mortality during the first 30 d of life was 3.2%; in the total rearing period, 9.3% of the heifers died (excluding slaughtered and exported animals). For the estimation of the effect of inbreeding and of genetic parameters a linear animal model with the random effects herd-year of birth and animal as well as the fixed effects year of birth-month of birth and dam parity, and the continuous effect of inbreeding coefficient (linear and quadratic) was applied. The model was reduced to the linear effect of inbreeding as the quadratic term was not found to have a significant effect. Inbreeding significantly affected all traits unfavorably. In the full rearing period (P4), heifer calves with an inbreeding coefficient of 0.10 had a 4.9% higher mortality rate than heifer calves with no inbreeding.

Hot topic: Effect of breeding strategies using genomic information on fitness and health

A complex deterministic approach was used to model the breeding goal and breeding structure for the Austrian Fleckvieh (dual-purpose Simmental) breed. The reference breeding goal corresponded to the current total merit index (TMI-R), where dairy traits have a relative weight of 37.9% and fitness traits of 43.7% (beef traits 16.5%; milkability 2%). The breeding program was characterized by 280,000 cows under performance recording, 3,200 bull dams, 100 test bulls with a test capacity of 25%, and 15 proven bulls and 8 bull sires per year. The annual monetary genetic gain (AMGG) was generated mainly by increases in milk fat and milk protein yield (80.6%) and only to a small extent by fitness traits (6.6%). The inclusion of direct health traits (early reproductive disorders, cystic ovaries, and mastitis) with their economic weights increased the relative AMGG for fitness traits from 6.6 to 11.2%. The presently slightly negative AMGG for fertility index and udder health changed in a positive direction. Increasing the weight on the direct health traits by 50% resulted in a further shift toward fitness and health. The effect of strategies using genomic information in a total merit index (TMI) with varying weights on fitness and health traits was also analyzed. The conventional progeny-testing scheme was defined as the reference breeding program. A breeding program was considered to be genomically enhanced (GS50) when 50% of inseminations of herdbook cows and of bull dams were from young bulls with a genomic TMI, and a second program (GS100) did not rely on progeny-tested bulls at all. For GS50, a clear shift of the relative gain in AMGG toward fitness and health traits was observed for all 3 TMI scenarios, as a result of larger progeny groups and a shorter generation interval. For GS100, where no gene flow from progeny-tested bulls was assumed, the genetic gain per generation was lower for the fertility and udder health index but higher per year. The results based on natural genetic gain per year showed that no positive genetic response for fertility and udder health index were achieved for TMI-R (without the inclusion of direct health traits) in GS50 and GS100. The direction of the genetic trend was determined by the weights given to fertility and udder health indices within the TMI. When appropriate weights generated a clear positive trend, GS50 and GS100 reinforced this trend.

Farmer-observed health data around calving—Genetic parameters and association with veterinarian diagnoses in Austrian Fleckvieh cows

The objective of this study was to investigate if farmer-observed health data around calving can be used together with veterinarian diagnoses for genetic evaluations. Four diseases are recorded by farmers: retained placenta, downer cow syndrome, mastitis, and lameness. Mean disease frequencies were 4.7, 3.8, and 1.8% for retained placenta, downer cow syndrome, and mastitis, respectively. Lameness had a very low frequency (0.7%) and a preliminary analysis revealed a heritability close to zero for this trait. Therefore, lameness was not considered in the analysis. For genetic analyses, univariate and bivariate linear animal models were fitted. Heritabilities for retained placenta, downer cow syndrome, and mastitis were 0.01, 0.03, and 0.003, respectively. Genetic correlations among the investigated disease traits were low to moderate and not significantly different from zero. Pearson correlations between estimated breeding values for disease traits and other routinely evaluated traits were computed, which revealed mostly favorable relationships to fertility, maternal calving ease, muscling, and longevity. In addition, a moderate favorable association was found between mastitis and somatic cell score. Heritability estimates of farmer-observed health traits were comparable to estimates based on veterinarian diagnoses. Genetic correlations between the investigated diseases based on farmer observations and veterinarian diagnoses were almost 1, with estimates ranging from 0.98 to 0.99. These results suggest that farmer recorded health data could be used together with veterinarian diagnoses for genetic evaluations.