Genotype by environment interaction for length of productive life in Swedish Red and White dairy cattle

In this study the amount of genotype by environment interaction (G×E) for length of productive life of Swedish Red and White dairy cattle was studied. The environmental variables used were the herd-year averages of number of first parity cows, peak yield, protein yield, and productive life. Data were analysed using multi-trait models (using low and high quartile herds) and reaction norm models (using the whole continuous scale). Considerable G×E was found for the trait productive life between environments (herds) with short or long average productive life, and a genetic correlation of 0.74 was found. For productive life in relation to herd size, G×E was negligible, and the genetic correlation was 0.95. For productive life in relation to herd-year average of peak yield or protein yield some G×E was indicated by the reaction norm model, especially between extreme environments. The G×E between herds with short or long average productive life should be studied further and might need to be considered in breeding programmes for dairy cattle.     

Reaction norms for protein yield and days open in Swedish red and white dairy cattle in relation to various environmental variables

Various environmental variables were used in analysis of genotype by environment interaction (GxE) for first lactation protein yield and days open in Swedish Red and White dairy cattle. The environmental variables described the herd level of production and fertility, herd size, geographic position, and weather conditions of the herds. Fixed effects of the environmental variables were analysed using a fixed regression sire model. All studied environmental variables, except the average rainfall during summer, had significant effect on both protein yield and days open. Possible effects of GxE were evaluated using random regression of protein yield and days open on the environmental variables. GxE was indicated between protein yield and herd level of production, protein yield and herd size, and days open and herd level of fertility. Correlations between the traits expressed at average and deviating levels of the environment were high indicating that GxE did not result in reranking of sires within the range of environments found in Sweden.     

Genotype x environment interactions and genetic parameters for fecal egg count and production traits of Merino sheep

Breeding for host resistance to parasites has become an imperative in many sheep industries. Because of the widespread use of AI in sheep breeding schemes, it is important to understand how the performance of offspring from rams varies in different flock environments, both for resistance to parasites and key production traits. This study used both variance component and reaction norm models to investigate the level of genotype x environment interaction for fecal egg count (FEC) and important Merino production traits in a range of flock environments in Australia. These flocks were linked by the use of common rams in a sire-referencing scheme. Both linear and quadratic polynomial reaction norm models were used. The heritability of these traits and the genetic correlation between them and FEC also was investigated using the reaction norm model. A contemporary group (CG) was defined by a flock, year, age class, sex, and paddock combination. Each CG environment was characterized by the mean value of any given trait for that CG. The recorded data used in the study were analyzed in a standardized form. Standardization for each trait was achieved within a CG by subtracting the CG mean from each observation and dividing by the CG SD. The genotype x environment effect accounted for <0.05 of the phenotypic variance for all traits. In most traits the heritability varied little across environments. The exceptions were FEC, BW, and both greasy and clean fleece weights, which had a higher heritability at the lower end of the environmental range. Fecal egg count also had a higher heritability in high-FEC environments. Genetic correlations between FEC and several key production traits were similar in the flock environments studied. Quadratic polynomial models and models with a variable residual fitted the data better than linear models. The genotype x environment effect for FEC and the genetic correlations between FEC and production traits were effectively zero; thus, sheep breeding programs for increased parasite resistance can be run effectively by ignoring these factors. Some account should be taken of the high heritabilities of FEC and fleece and BW in different flock environments.     

Estimation of genetic parameters for functional longevity in the South African Holstein cattle using a piecewise Weibull proportional hazards model

Non‐genetic factors influencing functional longevity and the heritability of the trait were estimated in South African Holsteins using a piecewise Weibull proportional hazards model. Data consisted of records of 161,222 of daughters of 2,051 sires calving between 1995 and 2013. The reference model included fixed time‐independent age at first calving and time‐dependent interactions involving lactation number, region, season and age of calving, within‐herd class of milk production, fat and protein content, class of annual variation in herd size and the random herd–year effect. Random sire and maternal grandsire effects were added to the model to estimate genetic parameters. The within‐lactation Weibull baseline hazards were assumed to change at 0, 270, 380 days and at drying date. Within‐herd milk production class had the largest contribution to the relative risk of culling. Relative culling risk increased with lower protein and fat per cent production classes and late age at first calving. Cows in large shrinking herds also had high relative risk of culling. The estimate of the sire genetic variance was 0.0472 ± 0.0017 giving a theoretical heritability estimate of 0.11 in the complete absence of censoring. Genetic trends indicated an overall decrease in functional longevity of 0.014 standard deviation from 1995 to 2007. There are opportunities for including the trait in the breeding objective for South African Holstein cattle.     

Bayesian analysis of the linear reaction norm model with unknown covariates

The reaction norm model is becoming a popular approach for the analysis of genotype x environment interactions. In a classical reaction norm model, the expression of a genotype in different environments is described as a linear function (a reaction norm) of an environmental gradient or value. An environmental value is typically defined as the mean performance of all genotypes in the environment, which is usually unknown. One approximation is to estimate the mean phenotypic performance in each environment and then treat these estimates as known covariates in the model. However, a more satisfactory alternative is to infer environmental values simultaneously with the other parameters of the model. This study describes a method and its Bayesian Markov Chain Monte Carlo implementation that makes this possible. Frequentist properties of the proposed method are tested in a simulation study. Estimates of parameters of interest agree well with the true values. Further, inferences about genetic parameters from the proposed method are similar to those derived from a reaction norm model using true environmental values. On the other hand, using phenotypic means as proxies for environmental values results in poor inferences.     

Variance and covariance components for weaning weight for Herefords in three countries

Records from the Hereford Associations of the United States (USA), Canada, and Uruguay were used to estimate genetic and phenotypic variances and covariances for weaning weight. Estimation was done using a complete animal model, relatively large data sets, and the same methodology for the three countries in order to determine whether genetic parameters for weaning weight were homogeneous across environments. Data were composed of 2,322,722, 487,661, and 102,986 edited weaning weight records for USA, Canada, and Uruguay, respectively. Ten samples were obtained from each country by eliminating data from small herds with fewer than 500 records, selecting herds at random from the entire data set after removing the small herds, and then retaining the direct-sire-connected contemporary groups within each sample. The final sample sizes ranged from 9,832 to 46,377 records. An accelerated EM-REML algorithm was used in estimating the (co)variance components in each sample. The estimates were pooled by calculating the arithmetic mean of the 10 samples from within each country. Direct and maternal (in parentheses) heritability estimates were .24 (.16), .20 (.16), and .23 (.18) for USA, Canada, and Uruguay, respectively. Maternal heritabilities reported here are nearly 50% smaller than the values currently used in national genetic evaluation for the breed, which were estimated using sire-maternal grandsire models. Covariance between direct and maternal was negative in all countries, accounting for 6, 8, and 10% of the total phenotypic variation, and the total dam effect was 32.5, 37.0, and 34.0% in USA, Canada, and Uruguay, respectively. Total heritabilities were similar among the countries, with values of .19, .19, and .17 for the three respective countries. The similarity of genetic and environmental parameters across the three countries suggests that joint genetic evaluation is feasible across environments provided that the genotype x environment interaction is negligible and can be ignored.     

GxE interactions for growth and carcass leanness: Re-ranking of boars in organic and conventional pig production

The objective of this study was to evaluate genotype by environment interactions for growth rate and carcass leanness in organic and conventional pig production environments. Organic breeding values for fattening traits were estimated for 37 Hampshire AI-boars based on slaughter records registered for 1805 crossbred offspring raised in an organic environment. The offspring were born and raised in herds certified for organic production. The statistical model included the fixed effects of sex, litter size at 2 weeks and herd. It also included the random effects of herd-year-season, birth litter and animal. Conventional breeding values for the same boars were captured from the breeding organization’s genetic evaluation. In the organic environment h² was estimated to 0.30 and 0.37 for growth rate and carcass leanness, respectively (r_g = − 0.11). Spearman rank correlations between organic and conventional breeding values, based on 29 boars with ≥ 20 progenies, were 0.48 for growth rate and 0.42 for carcass leanness. Both correlations were significantly different from 0 and 1. In conclusion, the results of the present study indicate weak genotype by environment interactions for both growth rate and carcass leanness in organic and conventional pig production environments, and there is some re-ranking of boars’ breeding values between environments.     

Genetic parameter estimates for preweaning traits of beef cattle in a stressful environment

Data collected from 1957 through 1985 from a Hereford herd located in the Southwest were analyzed separately for each sex to evaluate the heritabilities of and genetic correlations among preweaning growth traits within groups of environmentally similar years. Data were grouped into years with poor, moderate and good environments based on contemporary group means for male calves' weaning weight. A total of 7,690 records were analyzed for birth weight, weaning weight and preweaning daily gain with a model that included year of birth, sire within year of birth, age of dam and a covariate of day of birth for birth weight or age at weaning for the weaning traits. Year of birth was a significant source of variation in all environments for all traits, accounting for more of the variation in the good and poor years than in moderate years. Heritability estimates for all traits were greater in good and moderate years than in poor years for bull calves. For heifers, however, estimates for weaning weight and preweaning daily gain were greater in the poor environment. Genetic correlations among birth weight and preweaning gain increased from the good environment to the poor environment (-.49 +/- .26 to .82 +/- .56 for male calves and -.09 +/- 2.6 to .46 +/- .25 for female calves) but phenotypic correlations were near zero in all environments.(ABSTRACT TRUNCATED AT 250 WORDS)     

Feed efficiency of rainbow trout can be improved through selection: different genetic potential on alternative diets

To assess the genetic potential for selection of increased feed efficiency in rainbow trout (Oncorhynchus mykiss), we estimated the heritabilities and correlations for BW, daily weight gain (DG), and daily feed intake (DFI). Body weight was recorded 5 times, and DG and DFI 3 times during a feeding trial lasting 22 mo. To test the hypothesis that phenotypic and genetic parameters were influenced by a nutritional environment, fish were fed either a modern normal protein diet (NP, 40 to 45% protein and 30 to 33% lipid) or an alternative high protein diet (HP, 50 to 56% protein, 20 to 24% lipid) in a split-family design. Results showed that there were no large differences in heritabilities between the diets. Average heritability for DFI over both diets and different fish ages was low (average h2 = 0.10), indicating that modest genetic changes in response to selection can be obtained. Average heritabilities for BW and DG over both diets and different fish ages were 0.28 and 0.33, respectively. The NP diet enabled fish to express a wide range of BW, as shown by the increased coefficients of phenotypic variation for BW. Fish fed the HP diet showed increased phenotypic variation for DFI in > 750-g fish. On the NP diet, genetic correlations of DFI with DG and BW were very strong for 750- to 2,000-g fish. In contrast, on the HP diet, the respective correlations were moderate to low, revealing more genetic potential to change growth and feed intake simultaneously in opposite directions. An analysis of the predicted selection responses showed that selection solely for high DG improved feed efficiency as a correlated genetic response. Simultaneous selection for high DG and reduced DFI, in turn, may increase genetic gain in feed efficiency by a factor of 1.2 compared with selection solely for DG. However, variation for growth and feed intake and the relationships between these traits were different in different nutritional environments, leading to divergent genetic responses on the alternative diets.     

Genotype–environment interaction for age at first calving in buffaloes,using the reaction norm model

The objective of this study was to evaluate the genotype–environment interaction effect on age at first calving in buffaloes. The records were analysed using two approaches: (a) standard animal model and (b) reaction norm model. For the reaction norm analysis, two environmental gradients were formed, using age of first calving or milk yield group contemporary average. The results showed differences in the heritability estimates when using the two approaches. The reaction norm model indicated high heritability in more favourable environments and low magnitude genetic correlations between extreme environments. Based on our findings, we verified the significance of the genotype–environment interaction effect on age at first calving in buffaloes.     

Production and related variables in bovine leukaemia virus-infected cows

A newly developed milk dot blot test was used to detect anti-bovine leukaemia virus (BLV) antibody in milk samples from 2079 lactating adult cows from among 61 herds. The milk dot blot test was highly repeatable; the concordance rate, compared with the agar gel immunodiffusion test performed on serum, was 83.5%. All herds contained BLV-positive cows; the prevalence rate was 36%. BLV-positive cows tended to come from larger herds and were older and more often later in lactation. Fourteen production and related variables (herd size, age, days open, days in milk, milk somatic cell count, milk, fat, and protein produced in the current lactation, projected production of milk, fat, and protein, and breed class average deviations for milk, fat, and protein) were compared between BLV-positive and BLV-negative cows. Although somatic cell count, milk produced, and projected production of milk and protein were related significantly to BLV status using simple tests of association, once the variables herd size, age and days in milk were controlled, these differences were removed. Further analyses using logistic (outcome: individual cow BLV status) and least-squares regression (outcome:herd proportion of BLV-positive cows) failed to show an association between any of the measured production or related variables and BLV-positivity. We concluded that the effect of BLV on production and related variables in dairy cows was below the sensitivity of our analytical techniques or was non-existent.Abbreviations ABCA herd average breed class average for milk, fat, and protein production - AVGAGE average age of the herd - ADIM herd average for days in milk - AGID agar gel immunodiffusion - AVGSCC herd average milk somatic cell count - BCA breed class average, a milk, fat and protein production index calculated by comparing a cow's actual 305-day lactation production to the corresponding BCA standard for the same breed, age, and month of calving - BLV bovine leukaemia virus - CALVINT calving interval - COWAGE cow age - DBCA breed class average deviation for milk, fat, and protein production, the difference between an individual cow's BCA and the herd average - DIM days in milk - HS herd size corresponding to the number of lactating cows in a herd - LACT actual amount of milk, fat, and protein produced in a cow's lactation - ODHIC Ontario Dairy Herd Improvement Corporation - PCTPOS percentage of herd that is BLV-positive - PROJ projected 305-day production for milk, fat, and protein by fitting to a standard lactation curve adjusted for days in milk and age at calving - RHBCA rolling herd average for breed class average for milk, fat, and protein production, the average for all cows that completed a lactation (cows must have completed a 305-day lactation) during the previous 12 months - SCC milk somatic cell count     

The effect of sire selection on cow mortality and early lactation culling in adverse and favorable cow survival environments

The objective of this study was to determine the extent that genetic selection can help reduce dairy cow mortality and early lactation culling in adverse cow survival environments. Two datasets were constructed. The first contained 100,911 mortality records and 171,178 sixty-day culling records from 1467 herds. Cows that left the herd (culled or died) from 21 days prior to a due date through 60 days in milk were considered a 60-day cull. Cows were classified as belonging to herds with adverse cow survival environments (≥ 4.4% mortality rate and ≥ 7.1% 60-day cull rate) or favorable cow survival environments (<4.4% mortality rate and <7.1% 60-day cull rate). The second dataset included 20,438 mortality records and 34,942 sixty-day culling records from 314 herds with a known herd management system. Cows from both datasets were stratified into quartiles based on their sire's predicted transmitting ability (PTA) for productive life and other traits. Cows in the first dataset were also stratified into high (>50th percentile) and low (≤ 50th percentile) groups based on their sire's PTA for daughter calving ease and daughter stillbirth rates. Mortality and 60-day culling in the first dataset were evaluated with logistic regression models with the independent effects of sire PTA quartile, cow survival environment (adverse or favorable), the interaction of sire PTA quartile with cow survival environment, lactation number, age within lactation number, and herd-calving-cluster. The second dataset was analyzed in the same manner, but with cow survival environment replaced by herd management system. The estimated proportion of lactations that ended in death declined from 9.0% to 6.8% and 60-day culling incidence from 7.6% to 4.9% as sire productive life PTA went from the lowest to highest quartile in adverse cow survival environments. The corresponding reduction in mortality (0.7%) and 60-day culling (0.9%) were also significant in favorable cow survival environments. Mortality and 60-day culling both declined by 2.0% from low to high sire productive life PTA quartile in complete confinement free-stalls, which was the most unfavorable herd management system for cow survival. Daughters of bulls with high somatic cell score PTA and low daughter pregnancy rate PTA had higher incidences of mortality and 60-day culling, and 60-day culling was higher for daughters of sires with high milk and protein yield PTA. Selection to reduce stillbirth risk was associated with less mortality and 60-day culling, whereas mortality risk was reduced in favorable cow survival environments with selection to lower the incidence of stillbirths and calving difficulty. In conclusion, this study provides evidence that sire selection can play an important role in reducing the incidence of mortality and early lactation culling, particularly in herds with adverse cow survival environments.     

Genetic Parameters for the Piglet Mortality Traits Crushing,Stillbirth and Total Mortality,and their Relation to Birth Weight

The aim of this study was to estimate genetic and phenotypic parameters for the three mortality traits crushing, stillbirth and total mortality in piglets, and their respective correlations with birth weight. Records were available from 11 016 Yorkshire piglets from 1046 first parity litters in a Swedish experimental herd. Each mortality trait was analysed jointly with birth weight, using bivariate models. Both mixed linear models and threshold models were used. The threshold models took environmental and maternal genetic effects into account, whereas the linear models also included a direct genetic effect of the piglet on its birth weight. The estimated heritabilities were low for all mortality traits (0.01-0.15), with the lowest estimate for crushing and the highest for stillbirth. The estimated environmental correlations between the different mortality traits and birth weight were negative. The estimated genetic correlations between crushing and birth weight (both direct and maternal effect) were also negative in both models, indicating that sows with low-weight piglets are more likely to crush piglets. However, the genetic correlations between stillbirth and birth weight (both direct and maternal effect) were positive. These results suggest that stillbirth and crushing are traits with different genetic backgrounds, and that genetically increasing the birth weight of the piglets may result in more stillborn piglets.     

Analysis of genotype by environment interaction for milk yield traits in first lactation of Simmental cattle

The breeding goal for Simmental cattle is derived for intensively managed dairy farms. Its suitability for extensive farms was addressed by analysing possible genotype by environment interaction (G × E) between the management levels for first lactation milk yield traits. A first analysis was performed with the data collected from 300 000 purebred daughters of 278 second crop bulls born in Bavaria in 1993 and 1994. The farms were classified by herd‐year‐effect, using the sum of fat and protein yields into two levels of management, either with 33 or 10% quantiles, corresponding to approximately 100 000 cows and 30 000 cows, respectively. The comparison was based on ‘daughter yield’ deviations (DYD). Correlations between DYD of extensive and intensive environments were 0.90, 0.91 and 0.87 for milk, fat and protein yield (kg) for 33% quantiles, respectively. Corresponding correlations for 10% quantiles were 0.85, 0.83 and 0.77. Despite high correlations, 50 out of 149 sires showed significant differences between DYD in different environments. Bulls with higher DYD for milk yield on intensive farms were superior in all environments. For the second analysis extensive and intensive farms in northern and southern Bavaria were chosen at random. Approximately 20 000 cows in each management class were used for the estimation of genetic parameters. In both regions phenotypic and additive‐genetic variances were higher in the intensively managed herds. Likewise heritabilities were higher for fat and protein yield, but not for milk where higher heritabilities were observed in 33% quantiles. Genetic correlations between extensive and intensive environments were 0.97 and above (33% quantiles). Ten per cent quantiles led to lower genetic correlations (0.90–0.95). Although no serious re‐ranking effects of sires were evident, the scale effect and the differences in genetic parameters should be taken into consideration in practical breeding.     

Genetic aspects of longevity in Angus and Hereford cows

Thirty years and 23 yr of life history data from a Hereford herd in Arizona and an Angus herd in Wyoming, respectively, were analyzed. Longevity averaged 4.21 +/- .06 for years from first calving to disposal (FST), 7.40 +/- .06 for years from birth to disposal (AGE) and 3.46 +/- .06 for lifetime number of calves weaned (NUM) in Herefords and 4.49 +/- .13 (FST), 6.68 +/- .12 (AGE) and 3.66 +/- .11 (NUM) in Angus. In the Hereford herd, heritability estimates for traits measuring longevity, estimated from daughter-dam regression and paternal half-sib analyses, ranged from .16 to .26. In the Angus herd, heritability estimates from daughter-dam regression ranged from .03 to .05. In the Hereford herd, genetic correlations of birth weight and weaning weight with longevity, from daughter-dam regression, were negative and generally of low magnitude, whereas genetic correlations between weaning condition score and longevity were positive and moderate. Analogous estimates from paternal half-sib analyses all were positive and moderate to high. Phenotypic correlations between early life traits and longevity traits in Herefords all were near zero. In the Angus herd, curves for age-specific survivorship and age-specific survival rate varied markedly among sires. This study suggested the existence of moderate genetic variation for longevity traits in beef cattle. None of the traits expressed early in life that were examined would, however, be reliable predictors of genetic or phenotypic merit for longevity.     

Estimation of the economic value of herd‐life length based on simulated changes in survival rate

Functional traits are an important aspect of long‐term breeding strategies for dairy cattle. In this regard, it is necessary to develop simple methods for estimating the economic value of herd life. In this study, the economic daily value of herd life was estimated when survival rate varied between ?0.05 and 0.05 from the basal survival rate. The extension days per survival rate were 26.5 days in Hokkaido and 20.3 days in other regions. The increases in values of annual income per day of herd life were 95.18 yen in Hokkaido and 101.80 yen in other regions. The relative economic weights of milk yield to herd life per genetic standard deviation were 0.668 in Hokkaido and 1.03 in other regions. Estimated increments in yearly profits based on young sire selection for herd life were 963 yen in Hokkaido and 1,030 yen in other regions. The estimated increments in annual profits based on young sire selection for milk yield were 1,268 yen in Hokkaido and 2,097 yen in other regions. Given that economic value was linearly correlated with herd‐life length, the linear regression coefficients between these factors could be used to estimate the economic value of herd‐life length.     

Autoregressive model for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle

Reproductive efficiency is major determinant of the dairy herd profitability. Thus, reproductive traits have been widely used as selection objectives in the current dairy cattle breeding programs. We aimed to evaluate strategies to model days open (DO), calving interval (CI) and daughter pregnancy rate (DPR) in Brazilian Holstein cattle. These reproductive traits were analysed by the autoregressive (AR) model and compared with classical repeatability (REP) model using 127,280, 173,092 and 127,280 phenotypic records, respectively. The first three calving orders of cows from 1,469 Holstein herds were used here. The AR model reported lower values for Akaike Information Criteria and Mean Square Errors, as well as larger model probabilities, for all evaluated traits. Similarly, larger additive genetic and lower residual variances were estimated from AR model. Heritability and repeatability estimates were similar for both models. Heritabilities for DO, CI and DPR were 0.04, 0.07 and 0.04; and 0.05, 0.06 and 0.04 for AR and REP models, respectively. Individual EBV reliabilities estimated from AR for DO, CI and DPR were, in average, 0.29, 0.30 and 0.29 units higher than those obtained from REP model. Rank correlation between EBVs obtained from AR and REP models considering the top 10 bulls ranged from 0.72 to 0.76; and increased from 0.98 to 0.99 for the top 100 bulls. The percentage of coincidence between selected bulls from both methods increased over the number of bulls included in the top groups. Overall, the results of model-fitting criteria, genetic parameters estimates and EBV predictions were favourable to the AR model, indicating that it may be applied for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle.