Genetic parameter estimates for growth traits in Horro sheep

Variance components and genetic parameters were estimated for growth traits: birth weight (BWT), weaning weight (WWT), 6‐month weight (6MWT) and yearling weight (YWT) in indigenous Ethiopian Horro sheep using the average information REML (AIREML). Four different models: sire model (model 1), direct animal model (model 2), direct and maternal animal model (model 3) and direct–maternal animal model including the covariance between direct and maternal effects (model 4) were used. Bivariate analysis by model 2 was also used to estimate genetic correlation between traits. Estimates of direct heritability obtained from models 1–4, respectively, were for BWT 0.25, 0.27, 0.18 and 0.32; for WWT, 0.16, 0.26, 0.1 and 0.14; for 6MWT 0.18, 0.26, 0.16 and 0.16; and for YWT 0.30, 0.28, 0.23, and 0.31. Maternal heritability estimates of 0.12 and 0.23 for BWT; 0.19 and 0.24 for WWT; 0.09 and 0.09 for 6MWT and 0.08 and 0.14 for YWT were obtained from models 3 and 4, respectively. The correlations between direct and maternal additive genetic effects for BWT, WWT, 6MWT and YWT were –0.64, –0.42, 0.002 and –0.46, respectively. On the other hand, the genetic correlations between BWT and the rest of growth traits (WWT, 6MWT and YWT, respectively) were 0.45, 0.33 and 0.31, whereas correlations between WWT and 6MWT, WWT and YWT and 6MWT and YWT were 0.98, 0.84 and 0.87, respectively. The medium to high direct and maternal heritability estimates obtained for BWT and YWT indicate that in Horro sheep faster genetic improvement through selection is possible for these traits and it should consider both (direct and maternal) h² estimates. However, since the direct‐maternal genetic covariances were found to be negative, caution should be made in making selection decisions. The high genetic correlation among early growth traits imply that genetic improvement in any one of the traits could be made through indirect selection for correlated traits.     

Estimates of (co)variance components and genetic parameters for body weights and first greasy fleece weight in Malpura sheep

Estimates of (co)variance components and genetic parameters were calculated for birth weight (BWT), weaning weight (WWT), 6 month weight (6WT), 9 month weight (9WT), 12 month weight (12WT) and greasy fleece weight at first clip (GFW) for Malpura sheep. Data were collected over a period of 23 years (1985–2007) for economic traits of Malpura sheep maintained at the Central Sheep & Wool Research Institute, Avikanagar, Rajasthan, India. Analyses were carried out by restricted maximum likelihood procedures (REML), fitting six animal models with various combinations of direct and maternal effects. Direct heritability estimates for BWT, WWT, 6WT, 9WT, 12WT and GFW from the best model (maternal permanent environmental effect in addition to direct additive effect) were 0.19 ± 0.04, 0.18 ± 0.04, 0.27, 0.15 ± 0.04, 0.11 ± 0.04 and 0.30 ± 0.00, respectively. Maternal effects declined as the age of the animal increased. Maternal permanent environmental effects contributed 20% of the total phenotypic variation for BWT, 5% for WWT and 4% for GFW. A moderate rate of genetic progress seems possible in Malpura sheep flock for body weight traits and fleece weight by mass selection. Direct genetic correlations between body weight traits were positive and ranged from 0.40 between BWT and 6WT to 0.96 between 9WT and 12WT. Genetic correlations of GFW with body weights were 0.06, 0.49, 0.41, 0.19 and 0.15 from birth to 12WT. The moderately positive genetic correlation between 6WT and GFW suggests that genetic gain in the first greasy fleece weight will occur if selection is carried out for higher 6WT.     

Genotypic expression with different ages of dams: III. Weight traits of sheep.

Correlations between genetic expression in lambs when dams were young (1 yr), middle-aged (2 and 3 yr), or older (older than 3 yr) were estimated with three-trait analyses for weight traits. Weights at birth (BWT) and weaning (WWT) and ADG from birth to weaning were used. Numbers of observations were 7,731, 9,518, 9,512, and 9,201 for Columbia (COLU), Polypay (POLY), Rambouillet (RAMB), and Targhee (TARG) breeds of sheep, respectively. When averaged, relative estimates for WWT and ADG were similar across breeds. Estimates were variable across breeds. On average, direct heritability was greater when environment was young dams (.44 for BWT and .34 for WWT) than when environment was dams of middle age or older (.24 and .28 for BWT and .20 and .16 for WWT, respectively). Maternal heritability was greater when dams were middle-aged or older (.28 and .22 vs .18) for BWT but was greater when dams were younger (.10 vs .05 and .04) for WWT. The estimates of genetic correlations for direct effects across age of dam environments averaged .32 for birth weight and averaged .70 for weaning weight. Average estimates of maternal genetic correlations across age of dam classes were .36 or less for both BWT and WWT. Average estimates of correlations among maternal permanent environmental effects were .49 or less across age of dam classes. Total maternal effects accounted for .33 to .42 of phenotypic variance for BWT and for .09 to .26 of phenotypic variance for WWT. The average estimates of genetic correlations between expressions of the same genotypes with different ages of dams suggest that measurements of BWT of lambs with dams in young, middle, and older age classes should be considered to be separate traits for genetic evaluation and that for WWT measurements with young age of dam class and combined middle and older age of dam classes should be considered to be separate traits for genetic evaluation.     

Investigation of genotype by country interactions for growth traits for Charolais populations in Australia,Canada, New Zealand and USA

Evidence of heterogeneity of parameters and genotype by country interactions was investigated for birth weight (BWT), weaning weight (WWT) and postweaning gain (PWG) between Australian (AUS), Canadian (CAN), New Zealand (NZ) and USA populations of Charolais cattle. An animal model was fit to data sets for each individual country to compare the within-country parameter estimates for homogeneity. The direct heritability estimates of BWT in AUS (0.34) and NZ (0.31) were less than CAN (0.55) and USA (0.47). Maternal BWT heritabilities (0.13–0.18), direct WWT heritabilities (0.22–0.27), and maternal WWT heritabilities (0.12–0.18) were similar across all four countries. Direct PWG heritability for AUS (0.14) was smaller than the same estimate in the other three countries (0.24–0.31). The phenotypic variances for all three traits were similar across AUS, CAN and USA; however, NZ was higher for BWT and WWT and lower for PWG. A multiple trait animal model that considered each trait as a different trait in each country was also fit to the data for pairs of countries. Direct (maternal) estimated genetic correlations for BWT for AUS–CAN, AUS–USA, USA–CAN, NZ–CAN and NZ–USA were 0.88 (0.86), 0.85 (0.82), 0.88 (0.82), 0.85 (0.83), and 0.84 (0.80), respectively. Direct (maternal) estimated genetic correlations for WWT for AUS–CAN, AUS–USA, USA–CAN, NZ–CAN and NZ–USA were 0.96 (0.91), 0.95 (0.90), 0.95 (0.91), 0.95 (0.92), and 0.95 (0.92), respectively. Direct estimated genetic correlations for PWG for AUS–CAN, AUS–USA, USA–CAN, NZ–CAN and NZ–USA were 0.89, 0.91, 0.94, 0.90, and 0.91, respectively. The magnitude of the across-country genetic correlations indicates that genotype by country interactions were biologically unimportant. However, strong evidence exists for heterogeneity of parameters across the countries for some traits and effects. Therefore, combining these countries into one single analysis to produce a common set of genetic values will depend on the development of methods to adjust for heterogeneous parameters for models containing both direct and maternal effects, and for circumstances where constant variance ratios or heritabilities are not present across populations.     

Genetic parameters for growth traits for a composite terminal sire breed of sheep.

Records of 9,055 lambs from a composite population originating from crossing Columbia rams to Hampshire x Suffolk ewes at the U.S. Meat Animal Research Center were used to estimate genetic parameters among growth traits. Traits analyzed were weights at birth (BWT), weaning (7 wk, WWT), 19 mo (W19), and 31 mo (W31) and postweaning ADG from 9 to 18 or 19 wk of age. The ADG was also divided into daily gain of males (DGM) and daily gain of females (DGF). These two traits were analyzed with W19 and with W31 in three-trait analyses. (Co)variance components were estimated with REML for an animal model that included fixed effects of sex, age of dam, type of birth or rearing, and contemporary group. Random effects were direct and maternal genetic of animal and dam with genetic covariance, maternal permanent environmental, and random residual. Estimates of direct heritability were .09, .09, .35, .44, .19, .16, and .23 for BWT, WWT, W19, W31, ADG, DGM, and DGF, respectively. Estimates of maternal permanent environmental variance as a proportion of phenotypic variance were .09, .12, .03, .03, .03, .06, and .02, respectively. Estimates of maternal heritability were .17 and .09 for BWT and WWT and .01 to .03 for other traits. Estimates of genetic correlations were large among W19, W31, and ADG (.69 to .97), small between BWT and W31 or ADG, and moderate for other pairs of traits (.32 to .45). The estimate of genetic correlation between DGM and DGF was .94, and the correlation between maternal permanent environmental effects for these traits was .56. For the three-trait analyses, the genetic correlations of DGM and DGF with W19 were .69 and .82 and with W31 were .67 and .67, respectively. Results show that models for genetic evaluation for BWT and WWT should include maternal genetic effects. Estimates of genetic correlations show that selection for ADG in either sex can be from records of either sex (DGM or DGF) and that selection for daily gain will result in increases in mature weight but that BWT is not correlated with weight at 31 mo.     

Influence of maternal and additive genetic effects on offspring growth traits in Beetal goat

The purpose of the present study was to obtain estimates of variance components and genetic parameters for direct and maternal effects on various growth traits in Beetal goat by fitting four animal models, attempting to separate direct genetic, maternal genetic and maternal permanent environmental effects under restricted maximum likelihood procedure. The data of 3,308 growth trait records of Beetal kids born during the period from 2004 to 2019 were used in the present study. Based on best fitted models, the direct additive h² estimates were 0.06, 0.27, 0.37, 0.17 and 0.10 for birth weight (BWT), weight at 3 (WT3), 6 (WT6), 9 (WT9) and 12 (WT12) months of age, respectively. Maternal permanent environmental effects significantly contributed for 10% and 7% of total variance for BWT and WWT, respectively, which reduced direct heritability by 40 and 10% for respective traits from the models without these effects. For average daily gain (ADG1) and Kleiber ratios (KR1) up to weaning period (3 months) traits, maternal permanent environmental effects accounted for 7% and 8% of phenotypic variance, respectively, and resulted in a reduction of 6.6% and 5.4% in direct h² of respective traits. For post-weaning traits, the maternal effects were non-significant (p > .05) which indicates diminishing influence of mothering ability for these traits. High and positive genetic correlations were obtained among WT3-WT6, WT6-WT9 and WT9-WT12 with correlations of 0.96 ± 0.25, 0.84 ± 0.23 and 0.90 ± 0.13, respectively. Thus, early selection at weaning age can be practised taking into consideration maternal variation for effective response to selection in Beetal goat.     

Investigating maternal effects on production traits in Duroc pigs using animal and sire models

Variance components for production traits were estimated using different models to evaluate maternal effects. Data analysed were records from the South African pig performance testing scheme on 22 224 pigs from 18 herds, tested between 1990 and 2008. The traits analysed were backfat thickness (BFAT), test period weight gain (TPG), lifetime weight gain (LTG), test period feed conversion ratio (FCR) and age at slaughter (AGES). Data analyses were performed by REML procedures in ASREML, where random effects were successively fitted into animal and sire models to produce different models. The first animal model had one random effect, the direct genetic effects, while the additional random effects were maternal genetic and maternal permanent environmental effects. In the sire model, the random effects fitted were sire and maternal grand sire effects. The best model considered the covariance between direct and maternal genetic effects or between sire and maternal grand sire effects. Fitting maternal genetic effects into the animal model reduced total additive variance, while the total additive variance increased when maternal grand sire effects were fitted into the sire model. The correlations between direct and maternal genetic effects were all negative, indicating antagonism between these effects, hence the need to consider both effects in selection programmes. Direct genetic correlations were higher than other correlations, except for maternal genetic correlations of FCR with TPG, LTG and AGES. There has been direct genetic improvement and almost constant maternal ability in production traits as shown by trends for estimated (EBVs) and maternal breeding values (MBVs), while phenotypic trends were similar to those for EBVs. These results suggest that maternal genetic effects should be included in selection programmes for these production traits. Therefore, the animal–maternal model may be the most appropriate model to use when estimating genetic parameters for production traits in this population.     

Genetic parameter estimates for growth traits and prolificacy in Raeini Cashmere goats

The main objectives of this study were to estimate genetic and phenotypic parameters for growth traits and prolificacy in the Raeini Cashmere goat. Traits included, birth weight (BWT), weaning weight (WWT), 6-month weight (6WT), 9-month weight (9WT), 12-month weight (12WT), average daily gain from birth to weaning (ADG1), average daily gain from weaning to 6WT (ADG2), average daily gain from 6WT to 12WT (ADG3), survival rate (SR), litter size at birth (LSB) and litter size at weaning (LSW) and total litter weight at birth (LWB). Data were collected over a period of 28 years (1982-2009) at the experimental breeding station of Raeini goat, southeast of Iran. Genetic parameters were estimated with univariate models using restricted maximum likelihood (REML) procedures. In addition to an animal model, sire and threshold models, using a logit link function, were used for analyses of SR. Age of dam, birth of type, sex and of kidding had significant influence (p < 0.05 or 0.01) all the traits. Direct heritability estimates were low for prolificacy traits (0.04 ± 0.01 for LSB, 0.09 ± 0.02 for LSW, 0.16 ± 0.02 for LWB and 0.05 ± 0.02 for SR) and average daily gain (0.12 ± 0.03 for ADG1, 0.08 ± 0.02 for ADG2, and 0.07 ± 0.03 for ADG3) to moderate for production traits (0.22 ± 0.02 for BWT, 0.25 ± 0.02 for WWT, 0.29 ± 0.04 for 6WT, 0.30 ± 0.02 for 9WT, 0.32 ± 0.05 for 12WT). The estimates for the maternal additive genetic variance ratios were lower than direct heritability for BWT (0.17 ± 0.03) and WWT (0.07 ± 0.02).     

Genetic parameters estimated with multitrait and linear spline-random regression models using Gelbvieh early growth data

Estimates of direct and maternal genetic parameters in beef cattle were obtained with a random regression model with a linear spline function (SFM) and were compared with those obtained by a multitrait model (MTM). Weight data of 18,900 Gelbvieh calves were used, of which 100, 75, and 17% had birth (BWT), weaning (WWT), and yearling (YWT) weights, respectively. The MTM analysis was conducted with a three-trait maternal animal model. The MTM included an overall linear partial fixed regression on age at recording for WWT and YWT, and direct-maternal genetic and maternal permanent environmental effects. The SFM included the same effects as MTM, plus a direct permanent environmental effect and heterogeneous residual variance. Three knots, or breakpoints, were set to 1, 205, and 365 d. (Co)variance components in both models were estimated with a Bayesian implementation via Gibbs sampling using flat priors. Because BWT had no variability of age at recording, there was good agreement between corresponding components of variance estimated from both models. For WWT and YWT, with the exception of the sum of direct permanent environmental and residual variances, there was a general tendency for SFM estimates of variances to be lower than MTM estimates. Direct and maternal heritability estimates with SFM tended to be lower than those estimated with MTM. For example, the direct heritability for YWT was 0.59 with MTM, and 0.48 with SFM. Estimated genetic correlations for direct and maternal effects with SFM were less negative than those with MTM. For example, the direct-maternal correlation for WWT was -0.43 with MTM and -0.33 with SFM. Estimates with SFM may be superior to MTM due to better modeling of age in both fixed and random effects.     

Genetic evaluation of growth in a multibreed beef cattle population using random regression-linear spline models

The objective of this study was to examine the feasibility of using random regression-spline (RR-spline) models for fitting growth traits in a multibreed beef cattle population. To meet the objective, the results from the RR-spline model were compared with the widely used multitrait (MT) model when both were fit to a data set (1.8 million records and 1.1 million animals) provided by the American Gelbvieh Association. The effect of prior information on the EBV of sires was also investigated. In both RR-spline and MT models, the following effects were considered: individual direct and maternal additive genetic effects, contemporary group, age of the animal at measurement, direct and maternal heterosis, and direct and maternal additive genetic mean effect of the breed. Additionally, the RR-spline model included an individual direct permanent environmental effect. When both MT and RR-spline models were applied to a data set containing records for weaning weight (WWT) and yearling weight (YWT) within specified age ranges, the rankings of bulls' direct EBV (as measured via Pearson correlations) provided by both models were comparable, with slightly greater differences in the reranking of bulls observed for YWT evaluations (>or=0.99 for BWT and WWT and >or=0.98 for YWT); also, some bulls dropped from the top 100 list when these lists were compared across methods. For maternal effects, the estimated correlations were slightly smaller, particularly for YWT; again, some drops from the top 100 animals were observed. As in regular MT multibreed genetic evaluations, the heterosis effects and the additive genetic effects of the breed could not be estimated from field data, because there were not enough contemporary groups with the proper composition of purebred and crossbred animals; thus, prior information based on literature values had to be included. The inclusion of prior information had a negligible effect in the overall ranking for bulls with greater than 20 birth weight progeny records; however, the effect of prior information for breeds or groups poorly represented in the data was important. The Pearson correlations for direct and maternal WWT and YWT ranged from 0.95 to 0.98 when comparing evaluations of data sets for which the out-of-range age records were removed or retained. Random regression allows for avoiding the discarding of records that are outside the usual age ranges of measurement; thus, greater accuracies are achieved, and greater genetic progress could be expected.     

Bayesian analysis of birth weight and litter size in Baluchi sheep using Gibbs sampling

Variance and covariance components for birth weight (BWT), as a lamb trait, and litter size measured on ewes in the first, second, and third parities (LS1 through LS3) were estimated using a Bayesian application of the Gibbs sampler. Data came from Baluchi sheep born between 1966 and 1989 at the Abbasabad sheep breeding station, located northeast of Mashhad, Iran. There were 10,406 records of BWT recorded for all ewe lambs and for ram lambs that later became sires or maternal grandsires. All lambs that later became dams had records of LS1 through LS3. Separate bivariate analyses were done for each combination of BWT and one of the three variables LS1 through LS3. The Gibbs sampler with data augmentation was used to draw samples from the marginal posterior distribution for sire, maternal grandsire, and residual variances and the covariance between the sire and maternal grandsire for BWT, variances for the sire and residual variances for the litter size traits, and the covariances between sire effects for different trait combinations, sire and maternal grandsire effects for different combinations of BWT and LS1 through LS3, and the residual covariations between traits. Although most of the densities of estimates were slightly skewed, they seemed to fit the normal distribution well, because the mean, mode, and median were similar. Direct and maternal heritabilities for BWT were relatively high with marginal posterior modes of .14 and .13, respectively. The average of the three direct-maternal genetic correlation estimates for BWT was low, .10, but had a high standard deviation. Heritability increased from LS1 to LS3 and was relatively high, .29 to .37. Direct genetic correlations between BWT and LS1 and between BWT and LS3 were negative, -.32 and -.43, respectively. Otherwise, the same correlation between BWT and LS2 was positive and low, .06. Genetic correlations between maternal effects for BWT and direct effects for LS1 through LS3 were all highly negative and consistent for all parities, circa -.75. Environmental correlations between BWT and LS1 through LS3 were relatively low and ranged from .18 to .29 and had high standard errors.     

Variance components and breeding values for growth traits from different statistical models.

Estimates of genetic parameters resulting from various analytical models for birth weight (BWT, n = 4,155), 205-d weight (WWT, n = 3,884), and 365-d weight (YWT, n = 3,476) were compared. Data consisted of records for Line 1 Hereford cattle selected for postweaning growth from 1934 to 1989 at ARS-USDA, Miles City, MT. Twelve models were compared. Model 1 included fixed effects of year, sex, age of dam; covariates for birth day and inbreeding coefficients of animal and of dam; and random animal genetic and residual effects. Model 2 was the same as Model 1 but ignored inbreeding coefficients. Model 3 was the same as Model 1 and included random maternal genetic effects with covariance between direct and maternal genetic effects, and maternal permanent environmental effects. Model 4 was the same as Model 3 but ignored inbreeding. Model 5 was the same as Model 1 but with a random sire effect instead of animal genetic effect. Model 6 was the same as Model 5 but ignored inbreeding. Model 7 was a sire model that considered relationships among males. Model 8 was a sire model, assuming sires to be unrelated, but with dam effects as uncorrelated random effects to account for maternal effects. Model 9 was a sire and dam model but with relationships to account for direct and maternal genetic effects; dams also were included as uncorrelated random effects to account for maternal permanent environmental effects. Model 10 was a sire model with maternal grandsire and dam effects all as uncorrelated random effects. Model 11 was a sire and maternal grandsire model, with dams as uncorrelated random effects but with sires and maternal grandsires assumed to be related using male relationships. Model 12 was the same as Model 11 but with all pedigree relationships from the full animal model for sires and maternal grandsires. Rankings on predictions of breeding values were the same regardless of whether inbreeding coefficients for animal and dam were included in the models. Heritability estimates were similar regardless of whether inbreeding effects were in the model. Models 3 and 9 best fit the data for estimation of variances and covariances for direct, maternal genetic, and permanent environmental effects. Other models resulted in changes in ranking for predicted breeding values and for estimates of direct and maternal heritability. Heritability estimates of direct effects were smallest with sire and sire-maternal grandsire models.     

Age of dam and sex of calf adjustments and genetic parameters for gestation length in Charolais cattle

To estimate adjustment factors and genetic parameters for gestation length (GES), AI and calving date records (n = 40,356) were extracted from the Canadian Charolais Association field database. The average time from AI to calving date was 285.2 d (SD = 4.49 d) and ranged from 274 to 296 d. Fixed effects were sex of calf, age of dam (2, 3, 4, 5 to 10, > or = 11 yr), and gestation contemporary group (year of birth x herd of origin). Variance components were estimated using REML and 4 animal models (n = 84,332) containing from 0 to 3 random maternal effects. Model 1 (M1) contained only direct genetic effects. Model 2 (M2) was G1 plus maternal genetic effects with the direct x maternal genetic covariance constrained to zero, and model 3 (M3) was G2 without the covariance constraint. Model 4 (M4) extended G3 to include a random maternal permanent environmental effect. Direct heritability estimates were high and similar among all models (0.61 to 0.64), and maternal heritability estimates were low, ranging from 0.01 (M2) to 0.09 (M3). Likelihood ratio tests and parameter estimates suggested that M4 was the most appropriate (P < 0.05) model. With M4, phenotypic variance (18.35 d2) was partitioned into direct and maternal genetic, and maternal permanent environmental components (hd2 = 0.64 +/- 0.04, hm2 = 0.07 +/- 0.01, r(d,m) = -0.37 +/- 0.06, and c2 = 0.03 +/- 0.01, respectively). Linear contrasts were used to estimate that bull calves gestated 1.26 d longer (P < 0.02) than heifers, and adjustments to a mature equivalent (5 to 10 yr old) age of dam were 1.49 (P < 0.01), 0.56 (P < 0.01), 0.33 (P < 0.01), and -0.24 (P < 0.14) d for GES records of calves born to 2-, 3-, 4-, and > or = 11-yr-old cows, respectively. Bivariate animal models were used to estimate genetic parameters for GES with birth and adjusted 205-d weaning weights, and postweaning gain. Direct GES was positively correlated with direct birth weight (BWT; 0.34 +/- 0.04) but negatively correlated with maternal BWT (-0.20 +/- 0.07). Maternal GES had a low, negative genetic correlation with direct BWT (-0.15 +/- 0.05) but a high and positive genetic correlation with maternal BWT (0.62 +/- 0.07). Generally, GES had near-zero genetic correlations with direct and maternal weaning weights. Results suggest that important genetic associations exist for GES with BWT, but genetic correlations with weaning weight and postweaning gain were less important.     

Genetic variation in litter size and kit survival of mink (Neovison vison)

The aims of this study are to estimate variance components of litter size and kit survival rate and estimate genetic correlations of litter size and kit survival rate with dam's juvenile body weight and pregnancy length. Variance components for litter size and kit survival were analysed using an AI-REML approach, based on data from 1940 litters of the black colour type mink from 1996 to 2001. The models included (i) additive genetic effect of dam; (ii) dam and sire genetic effects; (iii) additive genetic effect of dam in relation to litter size and dam and sire genetic effects in relation to survival rate; (iv) additive genetic effect of dam to estimate the correlations of litter size or kit survival with dam juvenile body weight and pregnancy length on yearling dams (1357 litters). The dam heritabilities were of litter size (0.02-0.08) and survival rate (0.05-0.10). The permanent effects of dam were important for litter size (0.15-0.19) but not for survival rate. A positive dam genetic correlation between litter size and survival rate was found at 1 week postpartum (0.42), and a positive sire genetic correlation between number of weaned kits and survival rate at the age of 6 month (0.72). Litter size and survival rate were genetically antagonistically related to dam's juvenile body weight (-0.34 to -0.53). These results indicate the following: (i) it is possible to improve litter size and kit survival by selection, (ii) effective improvement of kit survival rate in the suckling period requires selection for maternal effect on kit survival and kit's own capacity to survive and later in the growth period for kit's own ability to survive and (iii) antagonistic genetic correlation of dam juvenile body weight with litter size and survival rate should be taken into consideration in mink breeding programs.     

Variance components and genetic parameters for weight and size at birth in the Boer goat

Variance components, heritability (direct additive and maternal) and correlations (additive genetic, phenotypic, maternal genetic and environmental) of body weight (BW) and body size including length (BL), height (BH) and chest girth (BCG) at birth in Boer goats were estimated on the basis of 5096 records obtained from a Boer Goat Breeding Station in Yidu, China, during 2001–2005. The parameters were estimated using a DFREML procedure by excluding or including maternal genetic or permanent maternal environmental effects, four different analysis models were fitted in order to determine the optimum model for each trait. The environmental factors such as year, season, sex and litter size (LS, number of kids) were investigated as the fixed effects. The results showed that the maternal effects were important determinants of estimated the genetic parameters for birth traits. Year and season had significant effect on birth traits. Single births and male kids had the heaviest live weight and the largest body size at birth. The mean values and standard deviation (SD) of BW, BL, BH and BCG were 3.87 ± 0.85 kg, 31.67 ± 2.87 cm, 32.92 ± 2.80 cm, 33.46 ± 3.21 cm. The mean values and standard error (SE) of direct additive heritability estimates for BW, BL, BH and BCG calculated with the optimum model were 0.19 ± 0.08, 0.14 ± 0.07, 0.24 ± 0.09 and 0.25 ± 0.10, respectively. For all the birth traits, estimates of the correlations between direct additive and maternal genetic (r_a–m) were negative. The estimates of additive genetic and phenotypic correlations among the birth traits were high and positive, and implied no genetic antagonisms among these traits analyzed. The estimates of maternal genetic correlations also were high and positive. Medium and positive environmental correlations indicated the important effects of environmental factors on early growth traits.     

Genetics and non-genetics parameters of body weight for post-weaning traits in Raini Cashmere goats

Genetic parameters were estimated for 6-month weight (W6), 9-month weight (W9), 12-month weight (W12), average daily gain from birth to 6 months old (ADG6), and Kleiber ratio at 6 months (KL6) traits using 6,442 records obtained from a Raini Cashmere goat flock. The parameters were estimated using the restricted maximum likelihood procedure and applying four animal models excluding or including maternal additive genetic and permanent environmental effects. Heritability estimates for W6, W9, W12, ADG6, and KL6, under the most appropriate model were 0.028, 0.26, 0.29, 0.02, and 0.25, respectively. The estimates of genetic and phenotypic correlations among W6, W9, W12, and ADG6 were high and ranged from 0.73 to 0.99. The estimates of genetic and phenotypic correlations among KL6 and others traits were negative and low. Thus, these estimates of genetic parameters may provide a basis for deriving selection indices for postweaning growth traits also low genetic correlation between growth traits with KL6, it is possible to increase efficiency in Raini kids by multitrait selection.     

Evaluation of cytoplasmic genetic effects in beef cattle using an animal model

Mixed model techniques were used to evaluate the importance of cytoplasmic genetic effects on beef cattle performance. Birth weight (BWT), preweaning average daily gain (ADG), weaning weight (WT205), postweaning gain (PG), ultrasonic backfat thickness (FAT) and predicted milk yield (MILK) data were collected in two herds of Hereford cattle located at Plymouth and Raleigh, North Carolina. Cytoplasmic lines were determined based on the foundation female in the maternal lineage of each animal. An animal model was used to account for all nuclear genetic variation among animals within herds. Direct breeding values were estimated for all animals with records and their parents for all traits. For MILK, permanent environmental effects were estimated for animals with multiple records. For preweaning traits, maternal breeding values and permanent maternal environmental effects also were estimated. In all analyses, F-tests for cytoplasmic effects were not significant. Probability values approached significance (P = .15 to P = .10) only for PG and FAT at Plymouth. Assumptions regarding the ratios of genetic and environmental variances and covariances had no effect on F-tests. Results contrast with earlier analyses of the same data in which nuclear genetic effects were accounted for by including sire and maternal grandsire in the statistical model. This study failed to show that cytoplasmic genetic effects were important sources of variation in performance; residual additive genetic effects were confounded with cytoplasmic lines for these herds. Because cytoplasmic sources may be regarded as founder effects, further research is needed in other populations.     

Genetic evaluation of Ethiopian Boran cattle and their crosses with Holstein Friesian for growth performance in central Ethiopia

Breed additive and non-additive effects, and heritabilities of birth weight (BWT), weaning weight (WWT), 6 months weight (SMWT), yearling weight (YWT), eighteen months weight (EWT), 2 years weight (TWT) and average daily weight gain from birth to 6 months (ADG1) and from 6 months to 2 years (ADG2) were estimated in Ethiopian Boran (B) cattle and their crosses with Holstein Friesian (F) in central Ethiopia. The data analysed were spread over 15 years. Ethiopian Boran were consistently lighter (p < 0.01) than the B-F crosses at all ages. Ethiopian Boran also gained lower weight than all the crosses. At birth, 50% F crosses were significantly (p < 0.01) lighter than all the other crosses. However, the differences in SMWT, YWT, EWT, TWT, ADG1 and ADG2 were all non-significant among the crosses. The individual additive breed differences between B and F breeds were positive and significant (p < 0.01) for all traits. The individual heterosis effects were significant (p < 0.05) for all traits except WWT for which the effect was non-significant. The maternal heterosis effects were significant (p < 0.01) for BWT (2.5 kg) and WWT (-3.0 kg). The heritability estimates for all traits in B and crosses were generally moderate to high indicating that there is scope for genetic improvement through selection. Selection within B and crossbreeding should be the strategy to enhance the growth performance under such production systems.     

Estimating non-genetic and genetic parameters of pre-weaning growth traits in Raini Cashmere goat

Data and pedigree information used in the present study were 3,022 records of kids obtained from the breeding station of Raini goat. The studied traits were birth weight (BW), weaning weight (WW), average daily gain from birth to weaning (ADG) and Kleiber ratio at weaning (KR). The model included the fixed effects of sex of kid, type of birth, age of dam, year of birth, month of birth, and age of kid (days) as covariate that had significant effects, and random effects direct additive genetic, maternal additive genetic, maternal permanent environmental effects and residual. (Co) variance components were estimated using univariate and multivariate analysis by WOMBAT software applying four animal models including and ignoring maternal effects. Likelihood ratio test used to determine the most appropriate models. Heritability ( \texth_\texta² ) \left( {{\text{h}}_{\text{a}}^2} \right) estimates for BW, WW, ADG, and KR according to suitable model were 0.12 ± 0.05, 0.08 ± 0.06, 0.10 ± 0.06, and 0.06 ± 0.05, respectively. Estimates of the proportion of maternal permanent environmental effect to phenotypic variance (c ²) were 0.17 ± 0.03, 0.07 ± 0.03, and 0.07 ± 0.03 for BW, WW, and ADG, respectively. Genetic correlations among traits were positive and ranged from 0.53 (BW-ADG) to 1.00 (WW-ADG, WW-KR, and ADG-KR). The maternal permanent environmental correlations between BW-WW, BW-ADG, and WW-ADG were 0.54, 0.48, and 0.99, respectively. Results indicated that maternal effects, especially maternal permanent environmental effects are an important source of variation in pre-weaning growth trait and ignoring those in the model redound incorrect genetic evaluation of kids.     

Genetic and phenotypic aspects of early reproductive performance in Raeini Cashmere goats

This study used pedigree information and data collected from 1979 to 2012 at the Raeini Cashmere goat breeding station, located in Baft City in Kerman Province in southeastern Iran. Genetic and phenotypic parameters for early reproductive traits of breeding does, including total numbers of kids born at first kidding (LSB1), total numbers of kids weaned at first kidding (LSW1), total birth weight of all kids born at first kidding (LWB1), total weaning weight of all kids weaned at first kidding (LWW1), and age at first kidding (AFK), were estimated using a Bayesian approach via Gibbs sampling. Posterior means for heritability estimates of LSB1, LSW1, LWB1, LWW1, and AFK were statistically significant, with values of 0.12, 0.23, 0.17, 0.15, and 0.46, respectively. Low-to-moderate additive genetic variation was present for the studied reproductive traits. Estimated genetic correlations among LSB1, LSW1, LWB1, and LWW1 were statistically significant and ranged from 0.12 between LWB1 and LWW1 to 0.72 between LSB1 and LSW1. Corresponding phenotypic correlation estimates were also statistically significant and ranged from 0.04 between LWB1 and LWW1 to 0.55 between LSB1 and LSW1. Posterior means of genetic and phenotypic correlations between AFK and other studied traits were statistically significant only for LSB1 and LWB1. For LSB1, LSW1, LWB1, and LWW1, we conclude that genetic and phenotypic improvement in any of these traits in Raeini Cashmere does would favorably influence all of the other traits. However, does that first kidded at younger ages have smaller litters at birth and lower litter birth weights at their first parity.