Random Permanent Environmental Effects Research Articles

PSX-4 Exploring the impact of age and body condition score on the genetic analysis of mature cow weight in American Angus cattle

Abstract Selecting sires with optimal genetic merit for mature weight (MWT) is crucial for profitability of beef producers, ensuring cost-effective production and increased economic returns per animal. The main objective of this study was to determine how different statistical approaches [e.g., including the fixed effects (FE) of age and body condition score (BCS) in the statistical model and/or pre-adjusting the weights for these effects] affect variance components estimation and genetic parameters for MWT, and their impact in the posterior selection decisions. The dataset provided by the American Angus Association (AAA) comprised 80,296 MWT records from 37,934 cows aged 2 to 15 yr. Contemporary groups (CG) were defined by concatenating herd, year, and season of measurement. Model 1 analyzed unadjusted MWT with CG and BCS as categorical FE and age as a covariable (quadratic). Model 2 was model 1 without BCS, model 3 was model 1 without age, and model 4 considered CG as the only FE. In model 5, MWT was pre-adjusted for 6 yr of age and BCS of 6, and CG was the only FE included in the statistical model. Additive genetic and permanent environment (pe) random effects were included in all statistical models except model 5, which did not include pe (only one adjusted record per animal). Variance components were calculated using REML implemented in the BLUPf90+ family of programs. Sires with at least 10 offspring (n = 1,483) were ranked according to their breeding values (EBVs) predicted for MWT, and all and the top 10% sires were used to estimate the rank correlation across models. The heritability (± SE) estimated for MWT was 0.43 (± 0.011), 0.42 (± 0.011), 0.70 (± 0.008), 0.72 (± 0.082), and 0.37 (± 0.013) for models 1, 2, 3, 4, and 5, respectively. Repeatability values were 0.64, 0.67, 0.72, and 0.76 for models 1, 2, 3, and 4, respectively. The EBV ranks were highly correlated between models 1 and 2 (Top 10%: 0.96; All: 0.99), and models 3 and 4 (Top 10%: 0.99; All: 0.99). Inflated heritabilities in models 3 and 4 suggest that the effect of age is confounded with the additive genetic effect, which will not translate to greater genetic progress. Therefore, disregarding age in the genetic evaluation of MWT is not recommended. Similarities between models 1 and 2 suggest that BCS has a relatively small impact on MWT, probably related to the relatively low genetic correlation between these traits. Models 1 and 5 cannot be directly compared, as they use slightly different response variables (body weight vs. pre-adjusted weight) and may lead to slightly different selection decisions (correlation between Top 10%: 0.85; All: 0.95). Further investigations in this field are warranted.

Genetic parameters for mid-infrared-spectroscopy-predicted mastitis phenotypes and related traits.

Genetic improvement of udder health in dairy cows is of high relevance as mastitis is one of the most prevalent diseases. Since it is known that the heritability of mastitis is low and direct data on mastitis cases are often not available in large numbers, auxiliary traits, such as somatic cell count (SCC) are used for the genetic evaluation of udder health. In previous studies, models to predict clinical mastitis based on mid-infrared (MIR) spectral data and a somatic cell count-derived score (SCS) were developed. Those models can provide a probability of mastitis for each cow at every test-day, which is potentially useful as an additional auxiliary trait for the genetic evaluation of udder health. Furthermore, MIR spectral data were used to estimate contents of lactoferrin, a glycoprotein positively associated with immune response. The present study aimed to estimate heritabilities (h2) and genetic correlations (ra) for clinical mastitis diagnosis (CM), SCS, MIR-predicted mastitis probability (MIRprob), MIR + SCS-predicted mastitis probability (MIRSCSprob) and lactoferrin estimates (LF). Data for this study were collected within the routine milk recording and health monitoring system of Austria from 2014 to 2021 and included records of approximately 54,000 Fleckvieh cows. Analyses were performed in two datasets, including test-day records from 5 to 150 or 5 to 305 days in milk. Prediction models were applied to obtain MIR- and SCS-based phenotypes (MIRprob, MIRSCSprob, LF). To estimate heritabilities and genetic correlations bivariate linear animal models were applied for all traits. A lactation model was used for CM, defined as a binary trait, and a test-day model for all other continuous traits. In addition to the random animal genetic effect, the fixed effects year-season of calving and parity-age at calving and the random permanent environmental effect were considered in all models. For CM the random herd-year effect, for continuous traits the random herd-test day effect and the covariate days in milk (linear and quadratic) were additionally fitted. The obtained genetic parameters were similar in both datasets. The heritability found for CM was expectedly low (h2 = 0.02). For SCS and MIRSCSprob, heritability estimates ranged from 0.23 to 0.25, and for MIRprob and LF from 0.15 to 0.17. CM was highly correlated with SCS and MIRSCSprob (ra = 0.85 to 0.88). Genetic correlations of CM were moderate with MIRprob (ra = 0.26 and 0.37) during 150 and 305 days in milk, respectively and low with LF (h2 = 0.10 and 0.11). However, basic selection index calculations indicate that the added value of the new MIR-predicted phenotypes is limited for genetic evaluation of udder health.

Genetic parameter estimates indicate the possibility of genetic gain by selecting for reproductive traits of females from a commercial tilapia population (Oreochromis niloticus)

This study aimed to verify the possibility of obtaining genetic gain by selecting breeders based on genetic parameter estimates for reproductive performance traits of female tilapia (Oreochromis sp.) from a commercial population. The study was conducted using a database containing information on reproductive traits collected from 2009 to 2021. During the breeding period, the animals were stocked in tanks in a 1:3 male: female ratio. Eggs were collected from the mouth of the females every five days, and the collected eggs were measured in 100 mL beakers to estimate the egg volume. To estimate the variance components and genetic parameters (heritability, correlation, and repeatability), a mixed animal model was used with the fixed effects of the production cycle and breeding tanks, in addition to the additive direct genetic and permanent environmental random effects. The heritability values were 0.26 ± 0.14, 0.18 ± 0.10, 0.15 ± 0.09, and 0.13 ± 0.08 for total egg volume, average egg volume, spawning frequency, and average spawning interval, respectively, with repeatability above 0.43 for all analyzed variables, demonstrating the ability of the evaluated breeds to maintain the same production level during the different cycles. The genetic correlations among the variables were high, with a correlation of −0.99 between the total egg volume and the average spawning interval. Thus, selecting for total egg volume, which had the highest heritability, would result in animals that produce a large volume of eggs and have short spawning intervals.

140 Targhee Sire Benchmarking at the U.S. Sheep Experiment Station

Abstract The Targhee breed was developed at the U.S. Sheep Experiment Station (USSES) starting in 1926, and has become an established range breed used commercially in the Western U.S. Our objective was to benchmark the performance of industry-based (external) Targhee sires with those currently in use at USSES. Nineteen Targhee sires from 12 flocks were incorporated into the USSES breeding flock starting with the 2015 breeding season. Data were measured through 2022 for 3 production and 12 wool traits with a range of 180 to 1,967 records per trait. Externally sourced sires averaged 38.3 progeny (7 to 78), with 0 to 4 ram lambs (15 total) and 0 to 15 (106 total) ewe lambs retained per sire in the flock. They were ancestors of 984 grand-progeny. USSES sires averaged 25.0 progeny (5 to 52), with 0 to 1 ram lambs (2 total) and 0 to 8 (53 total) ewe lambs retained per sire. They had 275 grand-progeny. Pedigree data was used to compute the marginal genetic contributions for each sire to the current flock using ENDOG. External sires had a cumulative contribution of 31.9 percent (0.4 to 3.9) while the USSES sires contributed 1.4 percent (0.0 to 0.9). Using R, fixed effects examined were age of dam, lamb sex, lamb birth year, grazing group, and type of birth/rearing. Significant variation explained in a trait by main effects (P < 0.005), and their two-way interactions (P < 0.001), were included in the final linear mixed models fitted. Externally sourced and USSES sires were assigned to separate genetic groups to account for the anticipated differences in genetic base. Using WOMBAT, a univariate animal model was fitted to estimate variance components and predict estimated breeding values for each lamb trait. Selection of random effects was based on log-likelihood ratio tests. Final models fitted and estimated heritabilities are summarized in Table 1. Total litter weight at 120 days per ewe lambing (TW120) was evaluated using a repeated measures model with direct additive and permanent environmental random effects of the ewe. Genetic group solutions were not significantly different (P > 0.05) for any traits evaluated. Since both sire groups originated from the same population, this suggests significant selection divergence had not occurred between industry and USSES flocks. Incorporation of external Targhee sires increased the genetic diversity of the USSES flock. It also strengthened industry ties to the USSES flock, which will benefit the commercial genetic evaluation conducted by the National Sheep Improvement Program. USDA is an equal opportunity provider and employer.

Estimates of genetic parameters, principal components and cluster analysis for milk yield and body weight in Guzera cattle

Context The estimation of genetic parameters for traits related to the production of milk, beef or both may assist in defining the selection criteria and objectives of the breeding program, as well as in the identification and selection of genetically superior animals. Aims The objectives of this study were to estimate genetic parameters for body weight and 305-day milk yield of Guzera cattle and to perform cluster analysis on the basis of estimated breeding values for these traits, to identify groups of animals that could be selected for the production of beef, milk or dual purpose. Methods Body weights (N = 253 012) of males and females were ecorded at 120 days of age (BW120), at weaning (WW), at 365 days (BW365), at yearling stage (YW) and at 24 months (BW24), and 6237 complete lactations (MY305) of 4723 cows were used to estimate the genetic parameters. The bi-trait animal models included direct additive genetic, maternal permanent environmental and temporary random effects for body weights and additive genetic, permanent environmental and temporary environmental random effects for MY305. The fixed effects for all the traits were contemporary group and age of cow at calving. Key results The estimates of heritability ranged from 0.14 ± 0.01 for WW to 0.23 ± 0.01 for MY305. The genetic correlations between body weights at different ages and milk yield were positive and ranged from 0.27 ± 0.11 to 0.38 ± 0.19. Two principal components explained 86.74% of the total genetic variance among the traits. Conclusions Cluster analysis identified four different clusters and showed that the Guzera breed had bulls with different genetic patterns that permits genetic selection for beef, milk or dual purpose. Implications The genetic correlations of the present study suggest that selection to increase milk yield will lead to a slight genetic gain in the same direction for body weight at different ages, in contrast to reports from some other studies.

PSVIII-5 Genetic parameters of thrombin as a proxy for horn fly abundance in beef cattle

Abstract Horn flies (Haematobia irritans) are a major nuisance to cattle, especially in warm, humid regions, and are estimated to cause economic losses in excess of $1 billion annually to the U.S. beef cattle industry. Variation in horn fly tolerance has been reported within and across breeds, and heritability estimates ranging between 10 and 80% show a clear genetic basis. However, collecting fly abundance phenotypes is costly and logistically demanding, which precludes large-scale implementation. Consequently, finding correlated phenotypes and endo-phenotypes that are heritable and relatively easy to measure would facilitate implementation of horn fly tolerance genetic improvement programs. Thrombin (TH), a blood coagulation precursor, has a reported association with horn fly count variation within and across cattle breeds. In this study, the genetic basis of thrombin in beef cattle was investigated. Blood samples and horn fly count were collected on 360 cows and heifers twice during the summer of 2019 (June and August). Due to uncertainty associated with assessment of horn fly abundance and thrombin and the fact that economic losses occur only when fly abundance exceeds a certain threshold, thrombin was categorized into 4 classes (1=TH > 500 ng/ml; 2=250< TH< 500 ng/ml; 3=100< TH< 250 ng/ml; and 4=TH< 100 ng/ml). The trait was analyzed using linear (continuous) and threshold (discrete) mixed models. Both models included farm, pregnancy status, and cow age as fixed effects and additive and permanent environment random effects. The pedigree included 642 animals. Estimates of heritability were 0.24 and 0.29 using linear and threshold models, respectively. Estimates of repeatability were slightly higher using the threshold model (0.21 vs 0.19). Despite the small data size, all estimates were non-zero based on their respective highest posterior density intervals. These results indicate reasonable genetic variation for thrombin that could be harnessed for improvement of horn fly tolerance in cattle.

Genetic parameters of somatic cell scores using random regression test-day models with Legendre polynomials in Tunisian dairy cattle

The aim of this study was to analyse the genetic parameters of test-day somatic cell scores (TDSCS) in Tunisian dairy cattle using random regression models (RRM) with homogeneous residual variances. Data included 43,647 test-day somatic cell count (TDSCC) records collected on 4825 Holstein-Friesian cows with parities up to the fifth, and calving dates between 2000 and 2014. Records of the same animal belonging to different lactations were treated as repeated records. Additive genetic (AG) and permanent environmental (PE) random effects were fitted using Legendre polynomials functions (LP) up to the fifth-order. The models included fixed regressions on days-in-milk (DIM), modelling the average phenotypic curve using Ali-Schaeffer's lactation function. Overall, three models (LP3, LP4 and LP5) where compared using the -2log marginal density for Bayes factor (-2logp) and the deviance information criterion (DIC). Models were also compared by similarities between the estimated breeding values and genetic trends. For all models, the total variances tended to decrease during the first month of the lactation, then they maintained a nearly constant trend. All models showed the largest AG and PE variances at the beginning and at the end of lactation with an oscillating pattern in the middle. The heritability estimates of from the three models ranged from 0.01 to 0.08 with the lowest heritability estimates being in the mid-lactation period. Genetic correlations between adjacent DIM were high and then decreased as the intervals widened. All the best statistical criteria were obtained with the LP5 model, however, no differences were observed between the estimated 305 average breeding values (EBV305) from the three models. This assumes that the LP3 model can be selected as a parsimonious model since it contains the smallest number of parameters. This RRM study provided a good insight into the changes in genetic merit of the somatic cell score trait in Tunisian dairy cattle and that an EBV for the SCS should be included in the selection programs. It also showed the benefits given of using RRMs to perform national genetic evaluations of dairy cattle for milk production traits in Tunisia.

Estimation of genetic parameters and breeding values for feed intake and energy balance using pedigree relationships or single-step genomic evaluation in Holstein Friesian cows

At the beginning of lactation, high-performing dairy cows often experience a severe energy deficit, which in turn is associated with metabolic stress. Increasing feed intake (FI) or reducing the energy deficit during this period could improve the metabolic stability and thus the health of the animals. Genomic selection for the first time enables the inclusion of this hard-to-measure trait in breeding programs. The objective of the current study was the estimation of genetic parameters and genomic breeding values for FI and energy balance (EB). For this purpose, 1,374 Holstein Friesian (HF) dairy cows from 8 German research farms were phenotyped with standardized FI data protocols. After data editing, phenotypic data of HF comprised a total of 40,012 average weekly FI records with a mean of 21.8 ± 4.3 kg/d. For EB 33,376 average weekly records were available with a mean of 3.20 ± 29.4 MJ of NEL/d. With the Illumina Bovine SNP50 BeadChip (Illumina Inc., San Diego, CA) 1,128 of phenotyped cows were genotyped. Thirty-five female candidates of the HF population were genotyped but not phenotyped. Pedigree information contained sires and dams 4 generations back. The random regression animal model included the fixed effects of herd test week (alternatively, herd group test week), parity, and stage of lactation, modeled by the function according to Ali and Schaeffer (1987). For both the random permanent environmental effect across lactations and the random additive genetic effect, third-order Legendre polynomials were chosen. Additionally, a random permanent environmental cow effect within lactation was included. Analyses for heritabilities, genetic correlations between different lactation stages, and breeding values were estimated using, respectively, pedigree relationships and single-step genomic evaluation, carried out with the DMU software package (Madsen et al., 2013). This allowed for comparison of conventional reliabilities with genomic-assisted reliabilities based on real data, to evaluate the gain of genotyping. Heritability estimates ranged between 0.12 and 0.50 for FI, and 0.15 and 0.48 for EB, and increased toward the end of lactation. Genetic correlations were weak between early and late lactation, with a value of 0.05 for FI and negative with a value of -0.05 for EB. Reliabilities for genomic values of cows for FI and EB ranged between 0.33 and 0.61, and 0.27 and 0.47, respectively. For the genotyped cows without phenotypes, the inclusion of genomic relationship leads to an increase of the average reliability of the breeding value for FI by nearly 9% and for EB by 4%. The results show the possibility of combining pedigree, genotypes, and phenotypes for increasing FI or EB to reduce health and reproductive problems, especially at the beginning of lactation. Nevertheless, the reference population needs to be extended to reach higher breeding value reliabilities.

Time class for racing performance of the Quarter Horse: Genetic parameters and trends using Bayesian and multivariate threshold models

The aim of this study was to evaluate racing performance in the Quarter Horse breed in Brazil using genetic parameter estimates, breeding values, and genetic trends for a differentiated trait, time class (TC), at four different distances. The speed records comprising races that occurred between 1981 and 2011 were obtained from hippodromes in the states of São Paulo, Ceará, Brasília, and Mato Grosso do Sul. The final archive analysed contained 4263 horses born to 431 stallions and 1716 dams. These animals participated in 3904 races, providing 17,342 records of final racing time. The four TC traits were defined by 5 scores based on the final times (in seconds) of each animal in each race. The scores for formation of the classes were attributed within each race based on the percent difference from winner's time. Time class was evaluated at distances of 301, 320, 365 and 402 m, generating four phenotypic measures: TC301, TC320, TC365 and TC402, respectively. The genetic parameters were estimated by Bayesian inference in multivariate analysis using a threshold animal model. The model included the fixed effects of race, sex and age class of animal in the race, in addition to additive genetic, animal permanent environmental and residual random effects. The mean heritability estimates were of high magnitude and ranged from 0.45 ± 0.06 (TC402) to 0.56 ± 0.04 (TC365). Repeatability estimates ranged from 0.78 ± 0.06 (TC402) to 0.97 ± 0.01 (TC320). The additive genetic and animal permanent environmental correlations were positive, with mean correlations ranging from 0.33 ± 0.06 between TC301 and TC320 to 0.62 ± 0.06 between TC365 and TC402 and from 0.44 ± 0.08 between TC301 and TC320 to 0.58 ± 0.06 between TC365 and TC402, respectively. The mean breeding values transformed by the cumulative distribution function of the standard normal distribution ranged from 54.6 ± 25.3 (TC365) to 57.8 ± 28.5 (TC320) in the group of animals included in the pedigree and born after 1980. The genetic trends observed indicated that TC301 (301 m) exhibited the greatest evolution between 1981 and 2008. The results suggest the possible use of TC traits as selection criteria since they respond positively to selection, permitting genetic gains in breeding programs of racehorses.

Linking first lactation survival to milk yield and components and lactation persistency in Tunisian Holstein cows.

Genetic parameters were estimated for first lactation survival defined as a binary trait (alive or dead to second calving) and the curve shape traits of milk yield, fat and protein percentages using information from 25 981 primiparous Tunisian Holsteins. For each trait, shape curves (i.e. peak lactation, persistency), level of production adjusted to 305 days in milk (DIMs) for total milk yield (TMY), and average fat (TF %) and protein (TP %) percentages were defined. Variance components were estimated with a linear random regression model under three bivariate animal models. Production traits were modelled by fixed herd test-day (TD) interaction effects, fixed classes of 25 DIMs age of calving season of calving interaction effects, fixed classes of pregnancy, random environment effects and random additive genetic effects. Survival was modelled by fixed herd year of calving interaction effects and age of calving season of calving interaction effects, random permanent environment effects, and random additive genetic effects. Heritability () estimates were 0.03 () for survival and 0.23 (), 0.31 () and 0.31 () for TMY, TF % and TP %, respectively. Genetic correlations between survival and TMY, TF % and TP % were 0.26 (), () and (), respectively. Genetic correlations between survival and persistency for fat and protein percentages were () and (), respectively. Cows that had higher persistencies for fat and protein percentages were more likely not to survive.

Estimates of genetic parameters and heterosis for birth weight, one-month weight and litter size at birth in five goat breeds

Records of birth weight, one-month old weight and litter size at birth, from 19,887 kids were collected from 1979 to 2000 at the National Goat Centre of Tlahualilo, located in northern Mexico. Local goats of a non-defined breed were recurrently crossed with imported sires of Granadina, Nubian, Alpine, Saanen and Toggenburg breeds. After editing, the data comprised of 12,641 kids and a pedigree file of 14,762 animals. Estimates of (co)variance components, heritability and repeatability of the aforementioned traits were obtained using a mixed model that included the fixed effects of sex, litter size, age of the dam at kidding, season-year of kidding, breed group, level of upgrading of the dam and the interaction between the breed of dam and breed of sire, as well as direct genetic, maternal genetic and maternal permanent environment random effects. The Granadina kids had the lowest birth and one-month weights. Estimates of direct heritability of the five breeds ranged from 0.202 to 0.510, 0.036 to 0.414 and 0.034 to 0.154 for birth weight, weight at one month of age and litter size, respectively, with several estimates for LS being non estimable. Maternal heritabilities ranged from 0.154 to 0.278 for birth weight and 0.023 to 0.378 for weight at one month of age. Only two estimates of maternal heritability were estimated for litter size and both were not significantly different from zero. Correlations between direct and maternal genetic effects were all negative for birth weight and litter size. Genetic and maternal correlations among all traits, estimated in the overall multi-breed population, were not significantly different from zero. These estimates are generally within the range of values reported for other breeds. A negative heterosis was found for both weight traits in the case of Granadina sires. Our estimates for birth weight and litter size are higher than the values reported in other studies with meat breeds.

Genetic and phenotypic parameters for litter size, survival rate, gestation length, and litter weight traits in American mink.

The economic efficiency of mink production is greatly influenced by reproductive performance. Therefore, the objective of this study was to estimate phenotypic and genetic parameters for reproduction traits including total number of kits born (TB), number of live kits at birth (LB), number of live kits at weaning (LW), survival rate at birth (SB), survival rate at weaning (SW), gestation length (GL), average kit weight per litter at birth (AWB), average kit weight per litter at week 3 (AW3), and average kit weight per litter at weaning (AWW) in American mink. Data included records of 3,046 litters collected by the Canadian Centre for Fur Animal Research at Dalhousie Faculty of Agriculture between 2002 and 2016. Significance (P < 0.05) of fixed effects (year, number of matings, color type, age of dam, origin of dam, sex ratio, and number of live kits) and random effects of permanent environment were determined using univariate repeatability models. A significant effect of permanent environment was only found for survival rate traits (P < 0.05). Subsequently, genetic and phenotypic parameters for all traits were estimated by fitting a set of bivariate models using ASREML 4.0. Heritabilities (± SE) were estimated to be 0.07 ± 0.03 for TB, 0.07 ± 0.02 for LB, 0.09 ± 0.04 for LW, 0.13 ± 0.03 for SB, 0.10 ± 0.02 for SW, 0.29 ± 0.03 for GL, 0.28 ± 0.05 for AWB, 0.19 ± 0.04 for AW3, and 0.10 ± 0.04 for AWW. Moderate positive genetic correlation was observed between AWB with SB (0.66 ± 0.10) and SW (0.61 ± 0.13). Furthermore, genetic correlations of LB with SW and AWB were 0.55 ± 0.16 and 0.53 ± 0.18, respectively. On the other hand, negative and moderate genetic correlations were observed between GL and survival rates at birth (-0.43 ± 0.14) and at weaning (-0.37 ± 0.15). These results indicated that selection for higher litter weights at birth can effectively improve survival rate and number of live kits in mink farms. It was suggested to incorporate litter weight traits as a selection criterion to increase maternal ability in mink breeding programs. Unfavorable genetic trends were observed for the studied traits indicating that phenotypic selection with low selection intensity had not been an efficient method to improve them over the last 10 yr. It was recommended to use genetic or genomic evaluation methods for mink selection.

Adjustment of Lactation Curves of Holstein Cows from Herds of Minas Gerais, Brazil

Random regression models (RRM) differ in terms of the functions used to describe the shape of lactation curves. The aim was to compare random regression models under different functions to describe the lactation curves from Holstein cows in herds of the state of Minas Gerais. A database of 28,118 production records was analyzed using the test-day records of 4,230 first parity cows from five herds. The Wilmink, Ali &amp; Schaeffer and Legendre polynomial (orders 4, 5 and 6) functions were adjusted in RRM to model the mean production trend (fixed) and genetic and permanent environmental (random) effects. The residual variances were assumed to be constant throughout lactation. Analyses were performed using the AIREMLF90 program. Except for the model with the polynomial function of order 5, all models converged. The Wilmink function showed lower values for criteria based on the -2log (L), AIC and BIC. The model with the Legendre polynomial of order 6 showed lower residual variance. Heritability estimates were similar between functions, ranging from 0.07 to 0.18 and were higher from 215 days of lactation. From 155 days of lactation, genetic and permanent environmental correlations between successive controls are of high magnitude. The Wilmink function is the most suitable for the study of milk yields from primiparous Holstein cows. The selection of animals is possible from 155 days of lactation on. Permanent environmental effects have greater influence on the milk production at the end of lactation of primiparous cows and should be considered since they are important and may be cumulative throughout lactation.

The genetics of antibody response to paratuberculosis in dairy cattle

Genetic parameters were estimated for antibody response to paratuberculosis (Mycobacterium avium ssp. paratuberculosis) using milk ELISA test results, collected and analyzed by National Milk Records, from Holstein Friesian cows on UK dairy farms in their first 3 lactations. Milk ELISA test results were obtained from 2007 to 2012 and combined with milk recording data and pedigree information. The reduced data set edited for the purposes of genetic parameter estimation consisted of 148,054 milk ELISA records from 64,645 lactations in 40,142 cows of 908 sires, recorded in 641 herds. Milk ELISA test results were loge-transformed and univariate analysis of 3 alternative animal models and equivalent sire models were considered. The most appropriate model included additive genetic and permanent environmental random effects, whereas maternal effects were significant according to likelihood ratio test and Akaike's information criterion but not for Bayesian information criterion. Heritability and repeatability estimates were 0.06 and 0.37, respectively, for the chosen animal model and its equivalent sire model. A subset of the data including herds with greater than 10% positive tests gave a slightly higher heritability of 0.08. Favorable but generally low significant genetic correlations were obtained between antibody response with 305-d milk yield (-0.16), 305-d protein yield (-0.16), loge-transformed lactation-average somatic cell count (0.15), and the number of mastitis episodes (0.22). Thus, selection on the antibody response to paratuberculosis, should not be detrimental to production or udder health traits. Testing cattle for paratuberculosis is important for its use in control programs and although the heritability of antibody response was low, breeding against the disease might be a good prospect as a preventative measure to assist together with other approaches in an overall control strategy.

Genetic evaluation of egg production curve in Thai native chickens by random regression and spline models

The objective of this research is to investigate appropriate random regression models with various covariance functions, for the genetic evaluation of test-day egg production. Data included 7,884 monthly egg production records from 657 Thai native chickens (Pradu Hang Dam) that were obtained during the first to sixth generation and were born during 2007 to 2014 at the Research and Development Network Center for Animal Breeding (Native Chickens), Khon Kaen University. Average annual and monthly egg productions were 117 ± 41 and 10.20 ± 6.40 eggs, respectively. Nine random regression models were analyzed using the Wilmink function (WM), Koops and Grossman function (KG), Legendre polynomials functions with second, third, and fourth orders (LG2, LG3, LG4), and spline functions with 4, 5, 6, and 8 knots (SP4, SP5, SP6, and SP8). All covariance functions were nested within the same additive genetic and permanent environmental random effects, and the variance components were estimated by Restricted Maximum Likelihood (REML). In model comparisons, mean square error (MSE) and the coefficient of detemination (R2) calculated the goodness of fit; and the correlation between observed and predicted values (ρyiy^ir) was used to calculate the cross-validated predictive abilities. We found that the covariance functions of SP5, SP6, and SP8 proved appropriate for the genetic evaluation of the egg production curves for Thai native chickens. The estimated heritability of monthly egg production ranged from 0.07 to 0.39, and the highest heritability was found during the first to third months of egg production. In conclusion, the spline functions within monthly egg production can be applied to breeding programs for the improvement of both egg number and persistence of egg production.

Estimation of genetic parameters for test-day milk yield in Khuzestan buffalo

Abstract: The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects, as well as to obtain genetic parameters for buffalo test-day milk yield using random regression models on Legendre polynomials (LPs). A total of 2,538 test-day milk yield (TDMY) records from 516 first lactation records of Khuzestan buffalo, calving from 1993 to 2009 and belonging to 150 herds located in the state of Khuzestan, Iran, were analyzed. The residual variances were modeled through a step function with 1, 5, 6, 9, and 19 classes. The additive genetic and permanent environmental random effects were modeled by LPs of days in milk using quadratic to septic polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by cubic and third order LP, respectively, and with the residual variance modeled through a step function with nine classes was the most adequate one to describe the covariance structure. The model with the highest significant log-likelihood ratio test (LRT) and with the lowest Akaike information criterion (AIC) and Bayesian information criterion (BIC) was considered to be the most appropriate one. Unexpected negative genetic correlation estimates were obtained between TDMY records of the twenty-fifth and thirty-seventh week (-0.03). Genetic correlation estimates were generally higher, close to unity, between adjacent weeks during the middle of lactation. Random regression models can be used for routine genetic evaluation of milk yield in Khuzestan buffalo.

Cluster analysis of breeding values for milk yield and lactation persistency in Guzerá cattle

ABSTRACT: The aim of this study was to explore the pattern of genetic lactation curves of Guzerá cattle using cluster analysis. Test-day milk yields of 5,274 first-lactation Guzerá cows were recorded in a progeny test. A total of 34,193 monthly records were analyzed with a random regression animal model using Legendre polynomials to fit additive genetic and permanent environmental random effects and mean trends. Hierarchical and non-hierarchical cluster analyses were performed based on the EBVs for monthly test-day milk yield, peak yield, lactation persistency, and partial cumulative and 305-day yields. The heritability estimates for test-day milk yields ranged from 0.24 to 0.52. Cluster analysis identified animals in the population that belong to different groups according to milk production level and lactation persistency.

Genotype by environment interaction for production, somatic cell score, workability, and conformation traits in Dutch Holstein-Friesian cows between farms with or without grazing

In this study, genotype by environment interaction was investigated for production traits, somatic cell score (SCS), workability traits, and conformation traits for Holstein-Friesian cows producing on farms with or without grazing in the Netherlands. Additionally, heritabilities and repeatabilities were estimated in both farm systems. Data were available for 1,019 Dutch farms, and farm type was known for those farms, 142 farms without grazing and 877 farms with grazing. The data set consisted of 428,600 test-day records for production from 49,412 cows, and from this data set a subset for SCS was created, consisting of 374,734 test-day records from 45,955 cows. For workability and conformation traits, the data set consisted of 30,180 cows. Bivariate mixed models with multiple fixed effects and random sire and random permanent environment effects were applied. The majority of sires had daughters in both farm types. The heritabilities for milk yield (0.27), fat yield (0.19), and protein yield (0.20) were higher in farms with grazing than in farms without grazing with heritabilities of 0.24 for milk yield, 0.18 for fat yield, and 0.18 for protein yield. Repeatability was lower in the grazing farms for milk yield, fat yield, and protein yield, probably because of alternating quality of dry matter intake during grazing. Genetic correlations between grazing and no grazing were 0.99, 0.98, 0.97, and 1.00 for milk yield, fat yield, protein yield, and SCS, respectively. Genetic correlations for workability traits and conformation traits between grazing and no grazing varied between 0.93 and 1.00. For all traits, genetic correlations were close to unity, indicating no genotype by environment interaction between farms with or without grazing for production traits, SCS, workability traits, and conformation traits in Dutch Holstein-Friesians. Therefore, the same sires can be used for farms both with and without grazing.

Random Regression Models Using Legendre Polynomials to Estimate Genetic Parameters for Test-day Milk Protein Yields in Iranian Holstein Dairy Cattle.

The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage (0.213±0.007). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran.

Genetic analysis of oocyte and embryo production traits in Guzerá breed donors and their associations with age at first calving.

The objective of this study was to estimate variance components for oocyte and embryo production traits in Guzerá breed female donors, and investigate their associations with age at first calving (AFC). The traits analyzed were the number of viable oocytes (NOV), the number of grade I oocytes (NGI), the number of cleaved embryos (NCLV), and viable embryos produced (NEMB), and the percentages of viable oocytes (POV), grade I oocytes (PGI), cleaved embryos (PCLV), and viable embryos (PEMB). Data were obtained from 5173 ovary puncture and in vitro fertilization (IVF) sessions using 1080 Guzerá female donors of different ages, occurred from March 2005 to July 2013. Variables were log-transformed (logeX+1) prior to analysis. (Co)variance components were estimated by restricted maximum likelihood (REML), using one- and two-trait animal models. Permanent environment and IVF sire (father of the embryos) random effects were included. Estimated heritabilities for NOV, NGI, NCLV, NEMB, POV, PGI, PCLV, and PEMB were 0.19, 0.08, 0.16, 0.14, 0.04, 0.03, 0.01, and 0.07, respectively. Repeatabilities for count traits (NOV, NGI, NCLV, and NEMB) varied from 0.14 and 0.32, higher than estimated for percentage traits (POV, PGI, PCLV, and PEMB), which varied from 0.01 to 0.08. Selection for NOV may be more appropriate in breeding programs than selection for NEMB, because of its strong genetic correlation (0.68) with NEMB and its greater time- and cost-effectiveness. AFC was only weakly associated with the oocyte and embryo production traits, which indicates that there would be no effect on AFC when selecting for these traits.