Multiple linear and nonlinear regression analyses of factors causing calving difficulty

Calving difficulty (CD) was analyzed as the dependent variable from observations on 592 first-calf, 2-year-old heifers that were either Angus X Hereford (AH), Charolais X AH or Simmental X AH. Independent variables were birth weight (BW), pelvic area (PA), BW.(33), PA.(5), cow weight (CW), cow condition score (CS) and sex of calf (S). CD was analyzed as score (1 = no difficulty through 4 = extreme difficulty) CD-I, % CD (1 vs 2 + 3 + 4 , CD-II) or % high CD (1 + 2 vs 3 + 4 , CD-III). R(2) values from CD-II and CD-III multiple correlation (R) analyses were consistently lower (.10 to .13) than from the CD-I analysis. When only BW and PA were included in the model, R(2) values for CD-I were .36, .39 and .39 for the linear, quadratic and cubic analyses, respectively. When BW, PA, CW, CS and S were included in the model, the R(2) values for CD-I were .40 and .42 for the linear and quadratic analyses (cubic effects were not tested). In the linear analysis with BW.(33) and PA.(5), the R(2) for CD-I was .36. In all analyses, the order of importance of the factors studied was BW and PA, with a much lower contribution from CW and S. CS did not account for a significant increase in R(2) in any analysis. CD remained below 50% whenever the PA BW ratio exceeded 8.4. This ratio is a convenient practical method to relate PA and BW to CD. Conclusions are that the linear effects of BW and PA account for the majority of the identified variation in CD (R(2)) and that small increases in R(2) can be obtained by adding CW, CS and S to the model and/or by expanding the model to include quadratic effects.     

Genetic analysis of sexual dimorphism of body weight in broilers

Variation in sexual dimorphism (SD) is particularly marked in meat-type chickens. This paper investigates the genetic basis of SD in an important economic trait, i.e. body weight (BW) at 35 days of age, in broilers by applying quantitative genetic analysis. A large dataset comprising 203,323 BW records of a commercial line of broiler chicken was used. First, a bivariate approach was employed treating BW as a sex-specific trait. During this approach, seven bivariate models were applied and variances due to direct additive genetic, maternal genetic and maternal environmental effects were estimated via the restricted maximum likelihood method. The best-fitting model included direct additive genetic, maternal genetic and maternal environmental effects with a direct–maternal genetic covariance. Differences between male and female direct heritabilities were non-significant (0.28 vs. 0.29 for males and females, respectively), implying no need for sex-specific selection strategies. The direct–maternal genetic correlation was more strongly negative in males than in females (?0.72 vs. ?0.56), implying a more profound antagonism between direct additive and maternal genetic effects in this particular gender. The direct genetic correlation of BW between the two sexes was as high as 0.91, i.e. only slightly lower than unity. Second, variance components and genetic parameters of two measures of SD, i.e. the weight difference (Δ) and the weight ratio (R), between the genders were estimated. Direct heritabilities for both measures were significantly different to 0 but of low magnitude (0.04). Apart from the additive–maternal covariance, no other random effects were found to be of importance for Δ and R. The results of the present study suggest that only minimal selection responses due to the selection of Δ and/or R and a small capacity for amplifying or reducing the BW differences between the sexes are to be expected in this specific population. Furthermore, selection pressure on BW is expected to amplify SD.     

(Co)variance components, genetic parameters and annual trends for calf weights in a Brahman herd kept on floodable savanna

(Co)variance components and genetic parameters were estimated for body weights of an elite Brahman herd under a designed, supervised management and genetic program, including strategic artificial insemination (AI). Restricted maximum likelihood methods were used with a univariate animal model for birth weight (BW) and a bivariate model for weaning weight (205-day weight, 205W) and 18-month weight (548-day weight, 548W). Models included random animal direct and maternal genetic effects, maternal permanent environmental effect (c2), and sex-year-month of birth-age of dam and genetic group (identified and unidentified paternity), as fixed effects. Analysis A1 included all calves and analysis A2 included only those with identified sires. Of the 8,066 calves born, 36% were progeny of AI, 11% from single sire and 53% from multi-sire herds. They were born from 1985 to 1998, from 2559 dams and 146 sires (78 identified). Estimates of direct, maternal and total heritabilities from A1 for BW, 205W and 548W were: 0.23, 0.07 and 0.30; 0.08, 0.14 and 0.16; 0.16, 0.04 and 0.28, respectively. Corresponding estimates of direct maternal genetic correlations were 0.22, 0.07 and 0.86, and c2 estimates were 0.04, 0.14 and 0.04, respectively. Estimates of direct and maternal genetic, and permanent environmental correlations between 205W and 548W were: 0.66, 0.70 and 1.00. Variances and genetic parameters from A1 and A2 were, in general, very similar. Estimates of phenotypic, and direct and maternal genetic trends per year from A1 were: 0.393, 0.004 and 0.003 kg (BW), 3.367, 0.142 and 0.115 kg (205W), 1.813, 0.263 and 0.095 kg (548W). Estimates of direct and maternal genetic trends from A2 were: 0.033 and -0.002 kg (BW); 0.186 and 0.276 kg (205W); 0.471 and 0.136 kg (548W). The modern selection methods that have been used recently should be continued, with emphasis on the improvement of cow efficiency for sustainable beef production on floodable savanna combined with improved pasture.     

Genetic parameter estimates for pre-weaning performance and reproduction traits in Markhoz goats

Genetic parameters for growth, mortality and reproductive performances of Markhoz goats were estimated from data collected during 1993–2010 at Markhoz goat Performance Testing Station in Sanandaj, Iran. For kid performance traits 3763 records were available for birth weight (BW), 2931 for weaning weight (WW), average daily gain (ADG) and Kleiber ratio (KR) (approximated as ADW/WW^0.75) and 3032 for pre-weaning mortality (PWM). For doe reproductive performance traits there were 2920 records available for litter size at birth (LSB), litter size at weaning (LSW), total litter weight at birth (TLWB) and litter mean weight per kid born (LMWKB), and 2182 for total litter weight at weaned (TLWW) and litter mean weight per kid weaned (LMWKW). Genetic parameters were estimated with univariate and bivariate models using restricted maximum likelihood (REML) procedures. Random effects were explored by fitting additive direct genetic effects, maternal additive genetic effects, maternal permanent environmental effects, the covariance between direct and maternal genetic effects, and common litter effects in different models for pre-weaning traits of kids. Also, in addition to an animal model, sire and threshold models, using a logit link function, were used for analyses of PWM. Models for LSB, LSW, TLWB, TLWW, LMWKB, and LMWKW included direct additive genetic effects, permanent environmental effects due to the animal as well as service sire effects. Estimated direct heritabilities were moderate for pre-weaning traits (0.22 for BW, 0.16 for WW, 0.21 for ADG, and 0.27 for KR and 0.29 for PWM), and low for reproduction traits (0.01 for LSB, 0.01 for LSW, 0.02 for TLWB, 0.03 for TLWW, 0.07 for LMWKB, and 0.06 for LMWKW). The estimates for the maternal additive genetic variance ratios were lower than direct heritability for BW (0.07) and KR (0.04). The estimate for the maternal permanent environmental variance ratios (c²) varied from 0.01 for KR to 0.07 for WW and ADG. The magnitude of common litter variance ratios (l²) was more substantial for BW (0.46) than the PWM (0.19) and KR (0.16). The estimate for the permanent environmental variance due to the animal (c²) ranged from 0.03 for LMWKB to 0.07 for TLWB and LMWKW, whereas service sire effects (s²) ranged from 0.02 to 0.04. The correlation between direct and maternal genetic effects were negative and high for BW (?0.51) and KR (?0.62). The genetic correlations between pre-weaning growth traits were positive and moderate to strong, as were genetic correlations between reproductive traits. Between BW and PWM the correlation was ?0.35. Phenotypic and environmental correlations for all traits were generally lower than genetic correlations.     

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle

Background

The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle.

Methods

Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (−maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models.

Results and discussion

On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (−maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (−maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence.

Conclusions

For the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (−maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions.     

Linear and threshold analysis of direct and maternal genetic effects for secondary sex ratio in Iranian buffaloes

The objective of this study was to estimate variance components and genetic parameters for secondary sex ratio (SSR) in Iranian buffaloes. Calving records from April 1995 to June 2010 comprising 15,207 calving events from the first three lactations of 1066 buffalo herds of Iran were analyzed using linear and threshold animal models to estimate variance components, heritabilities and genetic correlations between direct and maternal genetic effects for SSR. Linear and threshold animal models included direct and maternal genetic effects with covariance between them and maternal permanent environmental effects were implemented by Gibbs sampling methodology. Posterior means of direct and maternal heritabilities and repeatability for SSR obtained from linear animal model were 0.15, 0.10, and 0.17, respectively. Threshold estimates of direct and maternal heritabilities and repeatability for SSR were 0.48, 0.27, and 0.52, respectively. The results showed that the correlations between direct and maternal genetic effects of SSR were negative and high in both models. In addition, the ratios of maternal permanent environmental variance were low. Exploitable genetic variation in SSR can take advantage of sexual dimorphism for economically important traits which may facilitate greater selection intensity and thus greater response to selection, as well as reducing the replacement costs. Threshold animal model may be applied in selection programs where animals are to be genetically ranked for female rate.     

Inferring causal structures and comparing the causal effects among calving difficulty,gestation length and calf size in Japanese Black cattle

The objectives of this study were to infer phenotypic causal networks involving gestation length (GL) and calving difficulty (CD) for the primiparity of 1850 Japanese Black heifers, and the birth weight (BWT), withers height (WH) and chest girth (CHG) of their full blood calves, and to compare the causal effects among them. The inductive causation (IC) algorithm was employed to search for causal links among these traits; it was applied to the posterior distribution of the residual (co)variance matrix of a multiple-trait sire-maternal grand sire (MGS) model. The IC algorithm implemented with 95% and 90% highest posterior density intervals detected only one structure with links between GL and BWT (WH or CHG) and between BWT (WH or CHG) and CD, although their directions were not resolved. Therefore, a possible causal structure based on the networks obtained from the IC algorithm [GL→BWT (WH or CHG)→CD] was fitted using a structural equation model to infer causal structure coefficients between the traits. The structural coefficients of GL on BWT and of BWT on GL on the observable scale showed that an extra day of GL led to a 270-g gain in BWT, and a 1-kg increase in BWT increased the risk for dystocia by 1.1%, in the causal structure. Similarly, an increase in GL by 1 day resulted in a 2.1 (2.0)-mm growth in WH (CHG), and a 1-cm increase in WH (CHG) increased the risk of dystocia by 1.2% (0.9%). The structural equation model was also fitted to alternative causal structures, which involved the addition of a directed link from GL to CD, or GL→CD to the structures described above. The inferred structural coefficients with the alternative structures were almost the same as the corresponding ones that had GL→BWT (WH or CHG)→CD. However, the direct causal effect of the extra link from GL on CD was similar to the indirect causal effect of GL through the mediating effect of BWT (WH or CHG) on CD and significant (P<0.05). This suggest that maternal genetic effects might not be removed completely from the residual variance components in the sire-MGS model, and the application of the IC algorithm to the variances from the model could detect an incorrect structure. Nonetheless, fitting the structural equation model to the causal structure provided useful information such as the magnitude of the causal effects between the traits.     

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.     

Variance and covariance components for liability of piglet survival during different periods

Variance and covariance components for piglet survival in different periods were estimated from individual records of 133 004 Danish Landrace piglets and 89 928 Danish Yorkshire piglets, using a liability threshold model including both direct and maternal additive genetic effects. At the individual piglet level, the estimates of direct heritability in Landrace were 0.035, 0.057 and 0.027, and in Yorkshire the estimates were 0.012, 0.030 and 0.025 for liability of survival at farrowing (SVB), from birth to day 5 (SV5) and from day 6 to weaning (SVW), respectively. The estimates of maternal heritability for SVB, SV5 and SVW were, respectively, 0.057, 0.040 and 0.030 in Landrace, and 0.050, 0.038 and 0.019 in Yorkshire. Both direct and maternal genetic correlations between the three survival traits were low and not significantly different from zero, except for a moderate direct genetic correlation between SVB and SV5 and between SV5 and SVW in Landrace. Direct and maternal genetic correlations between piglet birth weight (BW) and SV5 were moderately high, but the correlations between BW and SVB and between BW and SVW were low and most of them were not significantly different from zero. These results suggest that effective genetic improvement in piglet survival before weaning by selection should be based on both direct and maternal additive genetic effects and treat survival in different periods as different traits.     

National evaluation for calving ease,gestation length and birth weight by linear and threshold model methodologies

Data included 393,097 calving ease, 129,520 gestation length, and 412,484 birth weight records on 412,484 Gelbvieh cattle. Additionally, pedigrees were available on 72,123 animals. Included in the models were effects of sex and age of dam, treated as fixed, as well as direct, maternal genetic and permanent environmental effects and effects of contemporary group (herd-year-season), treated as random. In all analyses, birth weight and gestation length were treated as continuous traits. Calving ease (CE) was treated either as a continuous trait in a mixed linear model (LM), or as a categorical trait in linear-threshold models (LTM). Solutions in TM obtained by empirical Bayes (TMEB) and Monte Carlo (TMMC) methodologies were compared with those by LM. Due to the computational cost, only 10,000 samples were obtained for TMMC. For calving ease, correlations between LM and TMEB were 0.86 and 0.78 for direct and maternal genetic effects, respectively. The same correlations but between TMEB and TMMC were 1.00 and 0.98, respectively. The correlations between LM and TMMC were 0.85 and 0.75, respectively. The correlations for the linear traits were above.97 between LM and TMEB but as low as 0.91 between LM and TMMC, suggesting insufficient convergence of TMMC. Computing time required was about 2 hrs, 5 hrs, and 6 days for LM, TMEB and TMMC, respectively, and memory requirements were 169, 171, and 445 megabytes, respectively. Bayesian implementation of threshold model is simple, can be extended to multiple categorical traits, and allows easy calculation of accuracies; however, computing time is prohibitively long for large models.     

Farmer views on calving difficulty consequences on dairy and beef farms

Calving difficulty (CD) is a key functional trait with significant influence on herd profitability and animal welfare. Breeding plays an important role in managing CD both at farm and industry level. An alternative to the economic value approach to determine the CD penalty is to complement the economic models with the analysis of farmer perceived on-farm impacts of CD. The aim of this study was to explore dairy and beef farmer views and perceptions on the economic and non-economic on-farm consequences of CD, to ultimately inform future genetic selection tools for the beef and dairy industries in Ireland. A standardised quantitative online survey was released to all farmers with e-mail addresses on the Irish Cattle Breeding Federation database. In total, 271 farmers completed the survey (173 beef farmers and 98 dairy farmers). Both dairy and beef farmers considered CD a very important issue with economic and non-economic components. However, CD was seen as more problematic by dairy farmers, who mostly preferred to slightly reduce its incidence, than by beef farmers, who tended to support increases in calf value even though it would imply a slight increase in CD incidence. Farm size was found to be related to dairy farmer views of CD with farmers from larger farms considering CD as more problematic than farmers from smaller farms. CD breeding value was reported to be critical for selecting beef sires to mate with either beef or dairy cows, whereas when selecting dairy sires, CD had lower importance than breeding values for other traits. There was considerable variability in the importance farmers give to CD breeding values that could not be explained by the farm type or the type of sire used, which might be related to the farmer non-economic motives. Farmer perceived economic value associated with incremental increases in CD increases substantially as the CD level considered increases. This non-linear relationship cannot be reflected in a standard linear index weighting. The results of this paper provide key underpinning support to the development of non-linear index weightings for CD in Irish national indexes.     

Designing an early selection morphological linear traits index for dressage in the Pura Raza Español horse

Making a morphological pre-selection of Pura Raza Español horses (PRE) for dressage is a challenging task within its current breeding program. The aim of our research was to design an early genetic selection morphological linear traits index to improve dressage performance, using 26 morphological linear traits and six dressage traits (walk, trot, canter, submission, general impression – partial scores – and total score) as selection criteria. The data set included morphological linear traits of 10 127 PRE (4159 males and 5968 females) collected between 2008 and 2013 (one record per horse) and 19 095 dressage traits of 1545 PRE (1476 males and 69 females; 12.4 records of average) collected between 2004 and 2014. A univariate animal model was applied to predict the breeding values (PBV). A partial least squares regression analysis was used to select the most predictive morphological linear traits PBV on the dressage traits PBV. According to the Wold Criterion, the 13 morphological linear traits (width of head, head–neck junction, upper neck line, neck–body junction, width of chest, angle of shoulder, lateral angle of knee, frontal angle of knee, cannon bone perimeter, length of croup, angle of croup, ischium–stifle distance and lateral hock angle) most closely related to total score PBV, partial scores PBV and gait scores PBV (walk, trot and canter) were selected. A multivariate genetic analysis was performed among the 13 morphological linear traits selected and the six dressage traits to estimate the genetic parameters. After it, the selection index theory was used to compute the expected genetic response using different strategies. The expected genetic response of total score PBV (0.76), partial scores PBV (0.04) and gait scores PBV (0.03) as selection objectives using morphological linear traits PBV as criteria selection were positive, but lower than that obtained using dressage traits PBV (1.80, 0.16 and 0.14 for total score PBV, partial scores PBV and gait scores PBV) or dressage traits PBV and morphological linear traits PBV (2.97, 0.16 and 0.15 for total score PBV, partial scores PBV and gait scores PBV), as selection criteria. This suggests that it is possible to preselect the PRE without dressage traits PBV using as selection criteria the morphological linear traits PBV, but the expected genetic response will be lower.     

(Co)Variance components and genetic parameter estimates for growth traits in Moghani sheep

Genetic parameters were estimated for birth weight (BW), weaning weight (WW), yearling weight (YW), average daily gain from birth to weaning (ADG1) and average daily gain from weaning to yearling (ADG2) in Moghani sheep. Maximum number of data was 4237 at birth, but only 1389 records at yearling were investigated. The data was collected from 1995 to 2007 at the Breeding Station of Moghani sheep in Jafarabad, Moghan, Iran. (Co)Variance components and genetic parameters were estimated with different models which including direct effects, with and without maternal additive genetic effects as well as maternal permanent environmental effects using restricted maximum likelihood (REML) method. The most appropriate model for each trait was determined based on likelihood ratio tests and Akaike's Information Criterion (AIC). Maternal effects were important only for pre-weaning traits. Direct heritability estimates for BW, ADG1, WW, ADG2 and YW were 0.07, 0.08, 0.09, 0.09 and 0.17, respectively. Fractions of variance due to maternal permanent environmental effects on phenotypic variance were 0.08 for ADG1. Maternal heritability estimates for BW and WW were 0.18 and 0.06, respectively. Multivariate analysis was performed using the most appropriate models obtained in univariate analysis. Direct genetic correlations among studied traits were positive and ranged from 0.37 for BW–ADG2 to 0.85 for ADG1–YW. Maternal genetic correlation estimate between BW and WW was 0.33. Phenotypic and environmental correlation estimates were generally lower than those of genetic correlation. Low direct heritability estimates imply that mass selection for these traits results in slow genetic gain.     

Genetic parameters of body weight in sheep estimated via random regression and multi-trait animal models

Variance components for five consecutive measurements of body weight in Polish sheep were estimated using random regression and multi-trait animal models. The data included between 7856 and 31694 body weight records at 5 age classes from birth to 150 days of age. The random additive genetic, maternal environmental and individual permanent environmental effects were fitted. All variance components were increasing over time (not at equal rates), which reflects increasing phenotypic mean and variance with age. Direct heritability tended to increase with age, whereas the effect of dam was reduced for older ages, and the proportion of permanent environmental component was relatively stable. Generally, similar tendencies were registered for estimates obtained via multi-trait animal model. The results confirm that there is a scope for genetic improvement in growth pattern in Polish sheep.     

Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle

The objectives of the present study were: (1) to evaluate the importance of genotype×production environment interaction for the genetic evaluation of birth weight (BW) and weaning weight (WW) in a population of composite beef cattle in Brazil, and (2) to investigate the importance of sire×contemporary group interaction (S×CG) to model G×E and improve the accuracy of prediction in routine genetic evaluations of this population. Analyses were performed with one, two (favorable and unfavorable) or three (favorable, intermediate, unfavorable) different definitions of production environments. Thus, BW and WW records of animals in a favorable environment were assigned to either trait 1, in an intermediate environment to trait 2 or in an unfavorable environment to trait 3. The (co)variance components were estimated using Gibbs sampling in single-, bi- or three-trait animal models according to the definition of number of production environments. In general, the estimates of genetic parameters for BW and WW were similar between environments. The additive genetic correlations between production environments were close to unity for BW; however, when examining the highest posterior density intervals, the correlation between favorable and unfavorable environments reached a value of only 0.70, a fact that may lead to changes in the ranking of sires across environments. The posterior mean genetic correlation between direct effects was 0.63 in favorable and unfavorable environments for WW. When S×CG was included in two- or three-trait analyses, all direct genetic correlations were close to unity, suggesting that there was no evidence of a genotype×production environment interaction. Furthermore, the model including S×CG contributed to prevent overestimation of the accuracy of breeding values of sires, provided a lower error of prediction for both direct and maternal breeding values, lower squared bias, residual variance and deviance information criterion than the model omitting S×CG. Thus, the model that included S×CG can therefore be considered the best model on the basis of these criteria. The genotype×production environment interaction should not be neglected in the genetic evaluation of BW and WW in the present population of beef cattle. The inclusion of S×CG in the model is a feasible and plausible alternative to model the effects of G×E in the genetic evaluations.     

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression analyses, all female weight records from birth to eight years of age (data set I) were considered. From this general data set, a subset was created (data set II), which included only nine weight records: at birth, weaning, 365 and 550 days of age, and 2, 3, 4, 5, and 6 years of age. Data set II was analyzed using random regression and multi-trait models. The model of analysis included the contemporary group as fixed effects and age of dam as a linear and quadratic covariable. In the random regression analyses, average growth trends were modeled using a cubic regression on orthogonal polynomials of age. Residual variances were modeled by a step function with five classes. Legendre polynomials of fourth and sixth order were utilized to model the direct genetic and animal permanent environmental effects, respectively, while third-order Legendre polynomials were considered for maternal genetic and maternal permanent environmental effects. Quadratic polynomials were applied to model all random effects in random regression models on B-spline functions. Direct genetic and animal permanent environmental effects were modeled using three segments or five coefficients, and genetic maternal and maternal permanent environmental effects were modeled with one segment or three coefficients in the random regression models on B-spline functions. For both data sets (I and II), animals ranked differently according to expected breeding value obtained by random regression or multi-trait models. With random regression models, the highest gains in accuracy were obtained at ages with a low number of weight records. The results indicate that random regression models provide more accurate expected breeding values than the traditionally finite multi-trait models. Thus, higher genetic responses are expected for beef cattle growth traits by replacing a multi-trait model with random regression models for genetic evaluation. B-spline functions could be applied as an alternative to Legendre polynomials to model covariance functions for weights from birth to mature age.     

Genetic variation in piglet mortality in outdoor organic production systems

Piglet mortality from farrowing to weaning is a major concern, especially in outdoor organic production systems. This issue might impair animal welfare and generate economic losses for the farmer. In particular, it is difficult to apply management tools that are commonly used for indoor pig production systems to organic or outdoor production systems. Genetics and breeding approaches might be used to improve piglet survival. However, knowledge remains limited on the genetic background underlying survival traits in organic pigs that are born and reared outdoors. Here, we investigated the mortality of piglets from farrowing to weaning in an outdoor organic pig population and suggested genetic strategies to reduce piglet mortality in this production system. The experiment included mortality records of piglets from farrowing to weaning (around 69 days of age). Pedigree-based threshold models were used to analyse the mortality traits of piglets at 0–3 days of age, 4–11 days, and 12 days to weaning. Stillborn piglets were included in the group of piglets that died at 0–3 days of age. We found that the mortality rate from farrowing to weaning was, on average, 19.2%. However, most piglet deaths (79.1%) occurred at 0–11 days of age. As the age of piglets increased, the direct heritability of piglet mortality rose from 0 to 0.04, whereas maternal heritability decreased from 0.03 to a non-significant value. Piglets with higher BW had a lower mortality rate. However, the genetic correlations between maternal effects on piglet mortality and piglet BW were not significant; thus, selection for piglets with higher BW at around 10 days of age, through improving maternal genetics, would not reduce piglet mortality. Piglet mortality increased from sows with increasing number of parities. Crossbreeding also reduced piglet mortality. In conclusion, selection focusing on sow genotype, the use of younger sows, and crossbreeding could contribute to maintain piglet mortality at lower levels in outdoor organic pig production systems.     

Genetic parameters for body weight,longissimus muscle depth and fat depth for Suffolk sheep in the Czech Republic

In this study, heritabilities and (co)variance components for body weight at 100 days (BW), muscle depth (MD) and fat depth (FD) were estimated for Suffolk, the most common sheep breed in the Czech Republic. Data from 1996 to 2004 were extracted from the sheep recording database of the Czech Sheep and Goat Breeding Association. Genetic parameters were estimated using multivariate animal models, including both direct and maternal genetic effects and permanent environmental effects. Average values for BW, MD and FD were 27.91 kg, 25.5 mm and 3.3 mm, respectively. Direct and maternal heritability for BW were 0.17 and 0.08, respectively, and direct heritabilities were 0.16 for MD and 0.08 for FD. Maternal heritability estimates for ultrasonic measurements were generally low. Direct genetic correlations between BW and MD and maternal genetic correlations between BW and MD were positive and favourable. Both direct genetic correlations between BW and FD and maternal genetic correlations between BW and FD were negative, but not significantly different from zero. The favourable genetic correlations between BW and MD make ultrasound measurements a valuable tool in breeding programs focusing on growth and carcass characteristics.     

A new model for parent-of-origin effect analyses applied to Brown Swiss cattle slaughterhouse data

Genomic imprinting is a phenomenon that arises when the expression of genes depends on the parental origin of alleles. Epigenetic mechanisms may induce the full or partial suppression of maternal or paternal alleles, thereby leading to different types of imprinting. However, imprinting effects have received little consideration in animal breeding programmes, although their relevance to some agricultural important traits has been demonstrated. A recently proposed model (imprinting model) with two path-of-transmission (male and female)-specific breeding values for each animal accounts for all types of imprinting simultaneously (paternal, maternal, full and partial). Imprinting effects (or more generally: parent-of-origin effects (POE)) are determined by taking the difference between the two genetic effects in each animal. However, the computation of their prediction error variance (PEV) is laborious; thus, we propose a new model that is equivalent to the aforementioned imprinting model, which facilitates the direct estimation of imprinting effects instead of taking the differences and the PEV is readily obtained. We applied the new model to slaughterhouse data for Brown Swiss cattle, among which imprinting has never been investigated previously. Data were available for up to 173 051 fattening bulls, where the pedigrees contained up to 428 710 animals representing the entire Brown Swiss population of Austria and Germany. The traits analysed comprised the net BW gain, fat score, EUROP class and killing out percentage. The analysis demonstrated that the net BW gain, fat score and EUROP class were influenced significantly by POE. After estimating the POE, the new model yielded estimates with reliabilities ranging between 0.4 and 0.9. On average, the imprinting variances accounted for 9.6% of the total genetic variance, where the maternal gamete was the main contributor. Moreover, our results agreed well with those obtained using linear models when the EUROP class and fat score were treated as categorical traits by applying a GLMM with a logit link function.     

Genotype by environment interaction in response to cold stress in a composite beef cattle breed

Extreme weather conditions such as cold stress influence the productivity and survivability of beef cattle raised on pasture. The objective of this study was to identify and evaluate the extent of the impact of genotype by environment interaction due to cold stress on birth weight (BW) and weaning weight (WW) in a composite beef cattle population. The effect of cold stress was modelled as the accumulation of total cold load (TCL) calculated using the Comprehensive Climate Index units, considering three TCL classes defined based on temperature: less than −5°C (TCL5), −15°C (TCL15) and −25°C (TCL25). A total of 4221 and 4217 records for BW and WW, respectively, were used from a composite beef cattle population (50% Red Angus, 25% Charolais and 25% Tarentaise) between 2002 and 2015. For both BW and WW, a univariate model (ignoring cold stress) and a reaction norm model were implemented. As cold load increased, the direct heritability slightly increased in both BW and WW for TCL5 class; however, this heritability remained consistent across the cold load of TCL25 class. In contrast, the maternal heritability of BW was constant with cold load increase in all TCL classes, although a slight increase of maternal heritability was observed for TCL5 and TCL15. The direct and maternal genetic correlation for BW and maternal genetic correlation for WW across different cold loads between all TCL classes were high (r > 0.99), whereas the lowest direct genetic correlations observed for WW were 0.88 for TCL5 and 0.85 for TCL15. The Spearman rank correlation between the estimated breeding value of top bulls (n = 79) using univariate and reaction norm models across TCL classes showed some re-ranking in direct and maternal effects for both BW and WW particularly for TCL5 and TCL15. In general, cold stress did not have a big impact on direct and maternal genetic effects of BW and WW.