Genetic parameters for maternal behaviour traits in sows

Data from 32 nucleus and multiplier herds in Germany was used to estimate variance components and breeding values for five maternal behaviour traits in sows. The estimation was performed univariately using an animal threshold model. About 31,000 farrowings recorded from December 2003 until July 2005 were included. The heritability coefficients were 0.07 (0.06) for group behaviour, 0.06 (0.03) for attitude to people, 0.05 (0.01) for maternal ability, 0.03 (0.01) for crushing of piglets and 0.02 (0.02) for savaging of piglets. Additionally, genetic correlations between the behaviour traits and between the behaviour traits and litter size, respectively, were estimated multivariately by REML with a linear model. Low heritability and weak genetic correlation to litter size at birth indicate that it may be difficult to genetically improve the maternal behaviour, and that selection for better mothering ability is not necessarily accompanied by reduced litter size at birth.     

Genetic parameters for testosterone production in boars

Data were collected in 1982 through 1989 from 66 sires and 358 Duroc boars. Testosterone production was measured from peripheral blood samples before (PRE) and after (POST) GnRH challenge. Additionally, data were collected on testes length at 168 d (TL168), testes width at 168 d (TW168), testes volume at 168 d (TVOL), birth weight (BWT), average daily gain (ADG), days to 104 kg (DAYS104), and backfat adjusted to 104 kg (FAT). Overall means for these traits were 24.6 ng.ml-1.h-1, 75.7 ng.ml-1.h-1, 12.3 cm, 11.6 cm, 422.0 cm3, 1.5 kg, .5 kg, 189.3 d, and 18.5 mm, respectively. Son-sire regressions were used to calculate genetic parameters. Heritabilities for PRE, POST, TL168, TW168, TVOL, BWT, ADG, DAYS104, and FAT were .37, .26, .33, .34, .33, .21, .42, .35, and 0, respectively. Moderately favorable genetic correlations were obtained for PRE and POST with growth measurements. Large positive genetic correlations were present for both PRE and POST with TL168, TW168, and TVOL, and testes measurements had large positive genetic correlations with growth traits. Selection for testes size or testosterone production should be equally effective. However, it seems that selection for testes size would result in larger changes in measures of growth than selection for testosterone. This study suggests that testes measurements are good predictors of both basal and challenge testosterone levels. Selection for increased testis size or increased testosterone levels would be expected to enhance growth.     

Genetic relationships among direct and maternal components of milk yield and maternal weaning gain in a multibreed beef herd.

Data spanning 1980 to 1993 from a multibreed beef herd including primarily eight breeds (Angus, Charolais, Gelbvieh, Hereford, Maine-Anjou, Pinzgauer, Simmental, and Tarentaise) were used to obtain 2,207 records on 200-d weaning gain (WG) and 1,826 records on 200-d milk yield (MY), obtained by machine milking after oxytocin injection. Estimates of (co)variances for the two traits (WG and MY) were obtained with REML with breed of calf, breed of cow, and heterotic effects modeled for the two traits. Animal effects of calf (CalfWG, CalfMY) and cow (CowWG, CowMY) contributions to each trait were modeled including 2,926 animals. The permanent environmental effect of the cow was modeled for MY, with 693 levels. Estimates of breed differences were generally similar to literature estimates. Simmental, Charolais, and Maine-Anjou were highest for CalfWG, and Tarentaise, Simmental, Gelbvieh, and Maine-Anjou were highest for CowMY. Heterosis was estimated at 8.00, 2.58, 4.05, and 5.50% of the mean for CalfWG, CowWG, CalfMY, and CowMy, respectively. Variance attributable to repeated records on CowMy represented 9% of phenotypic variance. Heritabilities estimated were .22 and .24 for CalfWG and CowWG and .04 and .35 for CalfMY and CowMY. Genetic correlations estimated between CalfWG and CowWG and between CalfMY and CowMY were -.35 and -.64, respectively. A genetic correlation between CowWG and CowMY of .76 indicates that maternal weaning gain evaluations are a good predictor of a cow's potential for milk yield.     

Genetic change results from selection on an economic breeding objective in beef cattle

The objective of this study was to evaluate and quantify the genetic progress achieved in a New Zealand Angus nucleus herd through long-term selection for an economically based, multi-trait breeding objective. A 4-trait breeding objective was implemented in 1976 and selected on through 1993 with traits consisting of slaughter weight and dressing percentage of harvest progeny and cull cows, and the number of calves weaned in the lifetime of each cow. These traits were related to gross income with none related to costs of production. To overcome this, economic weights were adjusted down for increased feed requirements of faster growing (and generally larger) animals. Performance and pedigree information was recorded on 16,189 animals from 1976 through 1993 and included weaning, yearling, and mature cow weights along with the lifetime number of calves weaned by each cow. These traits were used in the phenotypic selection indexes developed to predict the defined breeding objective. Individual performance was adjusted by least squares for major environmental fixed effects and deviated from contemporaneous means. Genetic and residual (co)variances were re-estimated for each of the traits using REML techniques and used to calculate EBV for each trait. These EBV were in turn used to calculate annual genetic changes. The average annual genetic changes for weaning weight direct and maternal breeding value were 0.43 +/- 0.05 and 0.03 +/- 0.22 kg/yr, respectively. Corresponding annual genetic changes for postweaning BW gain, yearling weight, harvest weight, and mature BW were 0.29 +/- 0.03, 0.72 +/- 0.06, 1.7 +/- 0.13, and 0.13 +/- 0.09 kg, respectively. The annual change in number of calves weaned per cow lifetime was 0.006 +/- 0.001 calves/cow and the change in dressing percentage was estimated to be -0.035 +/- 0.003 %/yr. At the end of the program, 3.21 generations of selection had occurred with a mean accumulated selection differential of 3.87 SD. Change in objective traits due to selection was similar to or exceeded change predicted at the onset of the program with the exception of mature BW and dressing percentage. Genetic change in mature BW was not different from zero, whereas the predicted change was 29.3 kg. The overall genetic trend in the breeding objective exceeded that predicted at the onset of the program. Results of this study showed that selection on indexes developed to predict an economically based, multi-trait breeding objective will produce genetic change.     

Genetic parameters for semen production traits in Swiss dairy bulls

Variance components (VC) were estimated for the semen production trait ejaculate volume, sperm concentration and sperm motility in the Swiss cattle breeds Brown Swiss (BS), Original Braunvieh (OB), Holstein (HO), Red‐Factor‐Carrier (RF), Red Holstein (RH), Swiss Fleckvieh (SF) and Simmental (SI). For this purpose, semen production traits from 2,617 bulls with 124,492 records were used. The data were collected in the years 2000–2012. The model for genetic parameter estimation across all breeds included the fixed effects age of bull at collection, year of collection, month of collection, number of collection per bull and day, interval between consecutive collections, semen collector, bull breed as well as a random additive genetic component and a permanent environmental effect. The same model without a fixed breed effect was used to estimate VC and repeatabilities separately for each of the breeds BS, HO, RH, SF and SI. Estimated heritabilities across all breeds were 0.42, 0.25 and 0.09 for ejaculate volume, sperm concentration and sperm motility, respectively. Different heritabilities were estimated for ejaculate volume (0.42; 0.45; 0.49; 0.40; 0.10), sperm concentration (0.34; 0.30; 0.20; 0.07; 0.23) and number of semen portions (0.18; 0.30; 0.04; 0.14; 0.04) in BS, HO, RH, SF and SI breed, respectively. The phenotypic and genetic correlations across all breeds between ejaculate volume and sperm concentration were negative (?0.28; ?0.56). The other correlations across all breeds were positive. The phenotypic and genetic correlations were 0.01 and 0.19 between sperm motility and ejaculate volume, respectively. Between sperm motility and sperm concentration, the phenotypic and genetic correlations were 0.20 and 0.36, respectively. The results are consistent with other analyses and show that genetic improvement through selection is possible in bull semen production traits.     

Genetic parameters for direct and maternal calving ability over parities in Piedmontese cattle

Estimates of heritabilities and genetic correlations for calving ease over parities were obtained for the Italian Piedmontese population using animal models. Field data were calving records of 50,721 first- and 44,148 second-parity females and 142,869 records of 38,213 cows of second or later parity. Calving ability was scored in five categories and analyzed using either a univariate or a bivariate linear model, treating performance over parities as different traits. The bivariate model was used to investigate the genetic relationship between first- and second- or between first- and third-parity calving ability. All models included direct and maternal genetic effects, which were assumed to be mutually correlated. (Co)variance components were estimated using restricted maximum likelihood procedures. In the univariate analyses, the heritability for direct effects was .19 +/- .01, .10 +/- .01, and .08 +/- .004 for first, second, and second and later parities, respectively. The heritability for maternal effects was .09 +/- .01, .11 +/- .01, and .05 +/- .01, respectively. All genetic correlations between direct and maternal effects were negative, ranging from -.55 to -.43. Approximated standard errors of genetic correlations between direct and maternal effects ranged from .041 to .062. For multiparous cows, the fraction of total variance due to the permanent environment was greater than the maternal heritability. With bivariate models, direct heritability for first parity was smaller than the corresponding univariate estimate, ranging from .18 to .14. Maternal heritabilities were slightly higher than the corresponding univariate estimates. Genetic correlation between first and second parity was .998 +/- .00 for direct effects and .913 +/- .01 for maternal effects. When the bivariate model analyzed first- and third-parity calving ability, genetic correlation was .907 +/- .02 for direct effects and .979 +/- .01 for maternal effects. Residual correlations were low in all bivariate analyses, ranging from .13 for analysis of first and second parity to .07 for analysis of first and third parity. In conclusion, estimates of genetic correlations for calving ease in different parities obtained in this study were very high, but variance components and heritabilities were clearly heterogeneous over parities.     

Genetic parameters for carcass composition and pork quality estimated in a commercial production chain

Breeding goals in pigs are subject to change and are directed much more toward retail carcass yield and meat quality because of the high economic value of these traits. The objective of this study was to estimate genetic parameters of growth, carcass, and meat quality traits. Carcass components included ham and loin weights as primal cuts, which were further dissected into boneless subprimal cuts. Meat quality traits included pH, drip loss, purge, firmness, and color and marbling of both ham and loin. Phenotypic measurements were collected on a commercial crossbred pig population (n = 1,855). Genetic parameters were estimated using REML procedures applied to a bivariate animal model. Heritability estimates for carcass traits varied from 0.29 to 0.51, with 0.39 and 0.51 for the boneless subprimals of ham and loin, respectively. Heritability estimates for meat quality traits ranged from 0.08 to 0.28, with low estimates for the water holding capacity traits and higher values for the color traits: Minolta b*(0.14), L* (0.15), a* (0.24), and Japanese color scale (0.25). Heritability estimates differed for marbling of ham (0.14) and loin (0.31). Neither backfat nor ADG was correlated with loin depth (r(g) = 0.0), and their mutual genetic correlation was 0.27. Loin primal was moderately correlated with ham primal (r(g) = 0.31) and more strongly correlated with boneless ham (r(g) = 0.58). Backfat was negatively correlated with (sub)primal cut values. Average daily gain was unfavorably correlated with subprimals and with most meat quality characteristics measured. Genetic correlations among the color measurements and water-holding capacity traits were high (average r(g) = 0.70), except for Minolta a* (average r(g) = 0.17). The estimated genetic parameters indicate that meat quality and valuable cut yields can be improved by genetic selection. The estimated genetic parameters make it possible to predict the response to selection on performance, carcass, and meat quality traits and to design an effective breeding strategy fitting pricing systems based on retail carcass and quality characteristics.     

Genetic and environmental aspects of the growth curve parameters in beef cows

Brody's growth curve, a three-parameter function, and Richards' function, a four-parameter function, were fit to data from 233 inbred and linecross cows to study the genetic and environmental aspects of the growth curve parameters and to compare the two functions. Fitting Brody's curve was faster and less costly to compute than Richards' function, but Richards' function had smaller sums of squares and a better fit to actual data points. Year of birth had an effect on the A (P less than .05), b (P less than .01) and k (P less than .01) parameters of Brody's curve. Parameter estimates from data of the youngest cows were at the extremes. The b parameter was the largest when estimated from data with no recorded birth weights. Year of birth was also an important effect for the b (P less than .01), k (P less than .05) and m (P less than .01) parameters of Richards' function, but year effects were less interpretable. Mating system affected (P less than .01) the A parameter of both functions; inbreds were lighter than linecrosses at maturity. Line of sire was an important source of variation (P less than .01) for the A parameter of both functions. The heritability estimate of the A parameter from both functions was .44 +/- .27; apparently the same trait in both curves. The estimate for the b parameter from Brody's curve was .39 +/- .27, comparable with literature estimates of birth weight. The heritability estimate for k from Brody's curve was .20 +/- .26. The heritability estimates for b, k and m parameters from Richards' function were .24 +/- .26, .32 +/- .27 and .21 +/- .26, respectively. The genetic correlations between the A and k parameters in both curves indicated that cows with lighter mature weights reached that weight at younger ages.     

Genetic antagonism between body weight and milk production in beef cattle

Korean cattle have an unusually short suckling period (4 mo) due to poor milking ability, and this is a hindrance to growth of calves. Therefore, Korean cattle breeders have shown interest in genetic improvement of milking ability. In this study, body weight (birth weight, weaning weight, and yearling weight) and five daily milk yields by period in Korean cattle (Hanwoo) were analyzed using a two-trait sire and maternal grandsire mixed model. The milk yields used were actually measured at sequential intervals from 1 to 4 mo after calving. Posterior means of the parameters were estimated using Gibbs sampling. Heritability estimates (0.25 to 0.26) for daily milk yield at weaning were larger than those with other periods. Genetic impact on daily milk yield, especially at weaning, was emphasized in order to lengthen the suckling period of Korean cattle. Genetic correlation estimates between BW and daily milk yield were all negative (-0.08 to -0.16 for birth weight, -0.04 to -0.21 for weaning weight, and -0.12 to -0.19 for yearling weight), whereas environmental correlation estimates were all positive (0.20 to 0.39 for birth weight, 0.34 to 0.51 for weaning weight, and 0.30 to 0.45 for yearling weight). The negative estimates of genetic correlation between weight and milk yield implied genetic antagonism between direct and maternal effects for weaning weight of beef cattle.     

Genetic parameters for egg production traits in purebred and hybrid chicken in a tropical environment

1. Genetic parameters were estimated for 5 economically important egg production traits using records collected over 9 years in chickens reared under tropical conditions in Thailand. The data were from two purebred lines and two hybrid lines of layer parent stocks.

2. The two purebred lines were Rhode Island Red (RIR) and White Plymouth Rock (WPR) and the hybrid lines were formed by crossing a commercial brown egg laying strain to Rhode Island Red (RC) and White Plymouth Rock (WC), respectively.

3. Five egg production traits were analysed, including age at first egg (AFE), body weight at first egg (BWT), egg weight at first egg (EWFE), number of eggs from the first 17 weeks of lay (EN) and average egg weight over the 17th week of lay (EW).

4. Fixed effects of year and hatch within year were significant for all 5 traits and were included in the model.

5. Maternal genetic and permanent environmental effects of the dam were not significant, except for EN and EW in RIR and BWT and EW in WPR.

6. Estimated heritability of AFE, BWT, EWFE, EN and EW were 0.45, 0.50, 0.29, 0.19 and 0.43 in RIR; 0.44, 0.38, 0.33, 0.20 and 0.38 in WPR; 0.37, 0.41, 0.38, 0.18 and 0.36 in RC; and 0.46, 0.53, 0.36, 0.38 and 0.45 in WC lines, respectively.

7. The EN was negatively correlated with other traits, except for BWT in RC and AFE and BWT in WC.

8. It was concluded that selection for increased EN will reduce other egg production traits in purebred and hybrid chicken and therefore EN needs to be combined with other egg production traits in a multi-trait selection index to improve all traits optimally according to a defined breeding objective.

     

Evaluation of methods for computing approximate accuracies of predicted breeding values in maternal random regression models for growth traits in beef cattle

The objective of this study was to determine the suitability of 2 methods for computing approximate accuracies of predicted breeding values, in which accuracy was defined as the squared correlation between the predicted and true breeding value, when modeling growth traits in beef cattle using random regression (RR) models. The first method (Strabel et al., S-M-B) was designed for use with multitrait models; thus, its use with RR models requires the clustering of measurements into different traits. The second method (Tier and Meyer, T-M) was more general, because it accounted for random coefficients other than zeros and ones and thus it could be used directly when fitting RR models. To investigate the performance of both methods, their results were compared with the true accuracies using a balanced simulated data set. The largest difference between approximate and true average accuracies for direct effects was observed at 205 d when S-M-B was used (4.6% males and 8.8% females). With regard to maternal effects, the largest differences in average accuracies were observed at 205 d in males when S-M-B was used (31.8%) and at the same age in females but when using T-M (33.3%). In general, bias increased for direct effect accuracies in males at the tails of the accuracy range, but for females and for maternal effect accuracies in both sexes, bias increased as accuracy increased. When a population was simulated to create large numbers of progeny for base females that did not have individual records, much greater errors were observed in the regression of approximate values on the true ones. When both approximate methods were compared using a real beef cattle data set, a good agreement was observed, particularly for direct effect accuracies in sires [i.e., at 205 d, the regressions were 0.98 (direct) and 0.95 (maternal) with r(2) over 0.99]. The largest discrepancies for sires between the methods were observed at 205 d for direct (2.7%) and maternal (16.3%) effect accuracies. For dams, the largest differences between methods were also observed at 205 d, 9.3% (direct), and 15.2% (maternal). The differences between methods for nonparent cattle were greater than for dams for maternal effect accuracies but intermediate between sires and dams for direct effect accuracies. In spite of the less biased results provided by T-M, its use could be problematic when employed in evaluations of large populations due to its greater memory and computation requirements (e.g., 170 and 478% more than S-M-B for a population of 11 million).     

Genetic relationships between calving performance and beef production traits in Piemontese cattle

The aim of the study was to obtain estimates of genetic correlations between direct and maternal calving performance of heifers and cows and beef production traits in Piemontese cattle. Beef production traits were daily gain, live fleshiness, and bone thinness measured on 1,602 young bulls tested at a central station. Live fleshiness (six traits) and bone thinness were subjectively scored by classifiers using a nine-point linear grid. Data on calving performance were calving difficulty scores (five classes from unassisted to embryotomy) routinely recorded in the farms. Calving performance of heifers and cows were considered different traits. A total of 30,763 and 80,474 calving scores in first and later parities, respectively, were used to estimate covariance components with beef traits. Data were analyzed using bivariate linear animal models, including direct genetic effects for calving performance and beef traits and maternal genetic effects only for calving performance. Due to the nature of the data structure, which involved traits measured in different environments and on different animals, covariances were estimated mostly through pedigree information. Genetic correlations of daily gain were positive with direct calving performance (0.43 in heifers and 0.50 in cows) and negative with maternal calving performance (-0.23 and -0.28 for heifers and cows, respectively). Live fleshiness traits were moderately correlated with maternal calving performance in both parities, ranging from 0.06 to 0.33. Correlations between live fleshiness traits and direct calving performance were low to moderate and positive in the first parity, but trivial in later parities. Bone thinness was negatively correlated with direct calving performance (-0.17 and -0.38 in heifers and cows, respectively), but it was positively correlated to maternal calving performance (0.31 and 0.40). Estimated residual correlations were close to zero. Results indicate that, due to the existence of antagonistic relationships between the investigated traits, specific selection strategies need to be studied.