Estimates of genetic parameters for growth traits in Kermani sheep

Birth weight (BW), weaning weight (WW), 6-month weight (W6), 9-month weight (W9) and yearling weight (YW) of Kermani lambs were used to estimate genetic parameters. The data were collected from Shahrbabak Sheep Breeding Research Station in Iran during the period of 1993-1998. The fixed effects in the model were lambing year, sex, type of birth and age of dam. Number of days between birth date and the date of obtaining measurement of each record was used as a covariate. Estimates of (co)variance components and genetic parameters were obtained by restricted maximum likelihood, using single and two-trait animal models. Based on the most appropriate fitted model, direct and maternal heritabilities of BW, WW, W6, W9 and YW were estimated to be 0.10 +/- 0.06 and 0.27 +/- 0.04, 0.22 +/- 0.09 and 0.19 +/- 0.05, 0.09 +/- 0.06 and 0.25 +/- 0.04, 0.13 +/- 0.08 and 0.18 +/- 0.05, and 0.14 +/- 0.08 and 0.14 +/- 0.06 respectively. Direct and maternal genetic correlations between the lamb weights varied between 0.66 and 0.99, and 0.11 and 0.99. The results showed that the maternal influence on lamb weights decreased with age at measurement. Ignoring maternal effects in the model caused overestimation of direct heritability. Maternal effects are significant sources of variation for growth traits and ignoring maternal effects in the model would cause inaccurate genetic evaluation of lambs.     

Estimation of (co)variance components and genetic parameters of greasy fleece weights in Muzaffarnagari sheep

Variance components and genetic parameters for greasy fleece weights of Muzaffarnagari sheep maintained at the Central Institute for Research on Goats, Makhdoom, Mathura, India, over a period of 29 years (1976 to 2004) were estimated by restricted maximum likelihood (REML), fitting six animal models including various combinations of maternal effects. Data on body weights at 6 (W6) and 12 months (W12) of age were also included in the study. Records of 2807 lambs descended from 160 rams and 1202 ewes were used for the study. Direct heritability estimates for fleece weight at 6 (FW6) and 12 months of age (FW12), and total fleece weights up to 1 year of age (TFW) were 0.14, 0.16 and 0.25, respectively. Maternal genetic and permanent environmental effects did not significantly influence any of the traits under study. Genetic correlations among fleece weights and body weights were obtained from multivariate analyses. Direct genetic correlations of FW6 with W6 and W12 were relatively large, ranging from 0.61 to 0.67, but only moderate genetic correlations existed between FW12 and W6 (0.39) and between FW12 and W12 (0.49). The genetic correlation between FW6 and FW12 was very high (0.95), but the corresponding phenotypic correlation was much lower (0.28). Heritability estimates for all traits were at least 0.15, indicating that there is potential for their improvement by selection. The moderate to high positive genetic correlations between fleece weights and body weights at 6 and 12 months of age suggest that some of the genetic factors that influence animal growth also influence wool growth. Thus selection to improve the body weights or fleece weights at 6 months of age will also result in genetic improvement of fleece weights at subsequent stages of growth.     

Maternal and direct genetic parameters for tail length,tail lesions,and growth traits in pigs

Tail length and tail lesions are the major triggers for tail biting in pigs. Against this background, 2 datasets were analyzed to estimate genetic parameters for tail characteristics and growth traits. Dataset 1 considered measurements for trait tail length (T-LEN) and for the growth traits birth weight (BW), weaning weight (WW), postweaning weight (PWW), and average daily gain (ADG) from 9,348 piglets. Piglets were born in the period from 2015 to 2018 and kept on the university Gießen research station. Dataset 2 included 4,943 binary observations from 1,648 pigs from the birth years 2016 to 2019 for tail lesions (T-LES) as indicators for nail necrosis, tail abnormalities, or tail biting. T-LES were recorded at 30 ± 7 d after entry for rearing (T-Les-1), at 50 ± 7 d after entry for rearing (end of the rearing period, T-LES-2), and 130 ± 20 d after entry for rearing (end of fattening period, T-LES-3). Genetic statistical model evaluation for dataset 1 based on Akaike’s information criterion and likelihood ration tests suggested multiple-trait animal models considering covariances between direct and maternal genetic effects. The direct heritability for T-LEN was 0.42 (±0.03), indicating the potential for genetic selection on short tails. The maternal genetic heritability for T-LEN was 0.05 (±0.04), indicating the influence of uterine characteristics on morphological traits. The negative correlation between direct and maternal effects for T-LEN of –0.35 (±0.13), as well as the antagonistic relationships (i.e., positive direct genetic correlations in the range from 0.03 to 0.40) between T-LEN with the growth traits BW, WW, PWW, and ADG, complicate selection strategies and breeding goal definitions. The correlations between direct effects for T-LEN and maternal effects for breeding goal traits, and vice versa, were positive but associated with a quite large SE. The heritability for T-LES when considering the 3 repeated measurements was 0.23 (±0.04) from the linear (repeatability of 0.30) and 0.21 (±0.06; repeatability of 0.29) from the threshold model. The breeding value correlations between T-LES-3 with breeding values from the repeatability models were quite large (0.74 to 0.90), suggesting trait lesion recording at the end of the rearing period. To understand all genetic mechanisms in detail, ongoing studies are focusing on association analyses between T-LEN and T-LES, and the identification of tail biting from an actor’s perspective.     

Use of robust multivariate linear mixed models for estimation of genetic parameters for carcass traits in beef cattle

Assumptions of normality of residuals for carcass evaluation may make inferences vulnerable to the presence of outliers, but heavy‐tail densities are viable alternatives to normal distributions and provide robustness against unusual or outlying observations when used to model the densities of residual effects. We compare estimates of genetic parameters by fitting multivariate Normal (MN) or heavy‐tail distributions (multivariate Student's t and multivariate Slash, MSt and MS) for residuals in data of hot carcass weight (HCW), longissimus muscle area (REA) and 12th to 13th rib fat (FAT) traits in beef cattle using 2475 records from 2007 to 2008 from a large commercial operation in Nebraska. Model comparisons using deviance information criteria (DIC) favoured MSt over MS and MN models, respectively. The posterior means (and 95% posterior probability intervals, PPI) of v for the MSt and MS models were 5.89 ± 0.90 (4.35, 7.86) and 2.04 ± 0.18 (1.70, 2.41), respectively. Smaller values of posterior densities of v for MSt and MS models confirm that the assumption of normally distributed residuals is not adequate for the analysis of the data set. Posterior mean (PM) and posterior median (PD) estimates of direct genetic variances were variable with MSt having the highest mean value followed by MS and MN, respectively. Posterior inferences on genetic variance were, however, comparable among the models for FAT. Posterior inference on additive heritabilities for HCW, REA and FAT using MN, MSt and MS models indicated similar and moderate heritability comparable with the literature. Posterior means of genetic correlations for carcass traits were variable but positive except for between REA and FAT, which showed an antagonistic relationship. We have demonstrated that genetic evaluation and selection strategies will be sensitive to the assumed model for residuals.     

Genetic parameters for litter size,piglet growth and sow's early growth and body composition in the Chinese–European line Tai Zumu

Genetics of piglet growth in association with sow's early growth and body composition were estimated in the Tai Zumu line. Piglet and sow's litter growth traits were calculated from individual weights collected at birth and at 3 weeks of age. Sow's litter traits included the number of piglets born alive (NBA), the mean piglet weight (MW) and the standard deviation of weights within the litter (SDW). Sow's early growth was measured by the age at 100 kg (A₁₀₀), and body composition included backfat thickness (BF₁₀₀). A main objective of this study was to estimate separately the direct genetic effect (d) and the maternal genetic effect (m) on piglet weight and daily weight gain during lactation. Variance components were estimated using the restricted maximum likelihood methodology based on animal models. The heritability estimates were 0.19 for NBA, 0.15 and 0.26 for SDW and MW at 3 weeks and 0.42 and 0.70 for A₁₀₀ and BF₁₀₀. The NBA was almost independent from SDW. Conversely, the A₁₀₀ and BF₁₀₀ were correlated unfavourably with SDW (r_g<−0.24, SE<0.12). A stronger selection for litter size should have little effect on litter homogeneity in weights. Selection for lean growth rate tends to favour heterogeneity in weights. The direct effect on piglet weight at birth and daily weight gain accounted for 12% (h² (d) = 0.02) and 50% (h² (d) = 0.11) of the genetic variance, respectively. The association between d and m for piglet weight was not different from zero at birth (r_g = 0.19, SE = 0.27), but a strong antagonism between d and m for daily weight gain from birth to 3 weeks was found (r_g = −0.41, SE = 0.17). Substantial direct and maternal genetic effects influenced piglet growth until weaning in opposite way.     

Evaluation of non-linear models for genetic parameters estimation of growth curve traits in Kermani sheep

Tropical Animal Health and Production - In the present study, 10,116 body weight-age records were measured on 2537 Kermani lambs. The records were collected from Kermani Sheep Breeding Station,...     

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.     

Dominance genetic and maternal effects for genetic evaluation of egg production traits in dual-purpose chickens

• 1.?A study was conducted to study direct dominance genetic and maternal effects on genetic evaluation of production traits in dual-purpose chickens. The data set consisted of records of body weight and egg production of 49 749 Mazandaran fowls from 19 consecutive generations. Based on combinations of different random effects, including direct additive and dominance genetic and maternal additive genetic and environmental effects, 8 different models were compared.

• 2.?Inclusion of a maternal genetic effect in the models noticeably improved goodness of fit for all traits. Direct dominance genetic effect did not have noticeable effects on goodness of fit but simultaneous inclusion of both direct dominance and maternal additive genetic effects improved fitting criteria and accuracies of genetic parameter estimates for hatching body weight and egg production traits.

• 3.?Estimates of heritability (h²) for body weights at hatch, 8 weeks and 12 weeks of age (BW0, BW8 and BW12, respectively), age at sexual maturity (ASM), average egg weights at 28–32 weeks of laying period (AEW), egg number (EN) and egg production intensity (EI) were 0.08, 0.21, 0.22, 0.22, 0.21, 0.09 and 0.10, respectively. For BW0, BW8, BW12, ASM, AEW, EN and EI, proportion of dominance genetic to total phenotypic variance (d²) were 0.06, 0.08, 0.01, 0.06, 0.06, 0.08 and 0.07 and maternal heritability estimates (m²) were 0.05, 0.04, 0.03, 0.13, 0.21, 0.07 and 0.03, respectively. Negligible coefficients of maternal environmental effect (c²) from 0.01 to 0.08 were estimated for all traits, other than BW0, which had an estimate of 0.30.

• 4.?Breeding values (BVs) estimated for body weights at early ages (BW0 and BW8) were considerably affected by components of the models, but almost similar BVs were estimated by different models for higher age body weight (BW12) and egg production traits (ASM, AEW, EN and EI). Generally, it could be concluded that inclusion of maternal effects (both genetic and environmental) and, to a lesser extent, direct dominance genetic effect would improve the accuracy of genetic evaluation for early age body weights in dual-purpose chickens.

     

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.     

Multi-trait animal model estimation of genetic parameters for linear type and gait traits in the Belgian warmblood horse

Genetic parameters for the height at withers, 27 linear type and six linear gait traits were estimated for the Belgian warmblood horse. Observations on 987 mares, mostly 3 years old, were analysed using a multi-trait animal model. The statistical model included appraiser, age and location (date × place of appraisal) as fixed effects. Genetic parameters were estimated using a canonical transformation and an expectation-maximization restricted maximum likelihood algorithm with an additional deceleration step. Estimates of heritability for the 33 linear traits were between 0.15 and 0.55. Heritability of the height at withers was 0.34 ± 0.06. Estimated genetic correlations ranged from −0.60 to 0.98 with an average SE of 0.10. The highest positive correlations were found among traits of walk and among traits of trot. Volume and the quality of legs were the most negatively correlated. Estimated genetic parameters indicated that the linear scoring system is a valuable tool to assess conformation. The full (co)variance matrix is now available for breeding value estimation to support selection for conformation and gaits.     

Different models for evaluation of growth traits and Kleiber ratio in an experimental flock of Iranian fat-tailed Afshari sheep

Records for Afshari sheep were retrieved from data collected between 2000 and 2005 at the Zanjan University experimental flock, at Zanjan, Iran. (Co)variance components and corresponding genetic parameters for birth weight (BW), weaning weight (WW), 6-month weight (W6), average daily gain from birth to weaning (ADGa), from birth to 6 months (ADGb), from weaning to 6 months (ADGc), Kleiber ratio at weaning (WWKR) and Kleiber ratio at 6 months of age (W6KR) were estimated using univariate and bivariate analyses by the DFREML procedure. The Kleiber ratio, defined as growth rate/metabolic weight, has been suggested to be a useful indicator of growth efficiency and an indirect selection criterion for feed conversion. Estimates of direct heritability ( h ²) were 0.23, 0.27, 0.11, 0.22, 0.07, 0.01, 0.13 and 0.06 for BW, WW, W6, ADGa, ADGb, ADGc, WWKR and W6KR, respectively. Maternal genetic effects represented a relatively large proportion of the total phenotypic variance for BW ( m ² = 0.22), whereas maternal permanent environmental effects were significant for W6 ( c ² = 0.15), ADGb ( c ² = 0.16), ADGc ( c ² = 0.14) and W6KR ( c ² = 0.16). Results of bivariate analyses indicated the variable genetic correlations between traits. The largest positive genetic relationships were between adjacent measurements. The moderate estimates of h ² for early growth traits indicate that in Afshari sheep faster genetic improvement through selection is possible for these traits. In order to increase the efficiency of feed conversion, use of Kleiber ratio in selection programmes was recommended.     

Multiple trait genetic evaluation of ewe traits in Icelandic sheep

The prolificacy of the ewes was measured as the number of lambs born per ewe mated (NLB) when the ewes were 1–4 years of age. The ewe productivity related to the same age interval was measured by special ewe production indices (EPI). The genetic parameters for these traits were estimated by a series of bivariate REML analyses using animal models. The material used for the genetic analysis contained records on 193 213 ewes. The heritability estimates for NLB were h² = 0.17, 0.13, 0.11, 0.10 for the four respective age classes. Corresponding estimates for EPI were h² = 0.16, 0.17, 0.17, 0.15. The genetic correlations among NLB at different ages ranged from 0.63 to 0.98 and among EPI from 0.82 to 0.99. The genetic correlations between NLB and EPI were generally low. The material used for estimating the breeding values by the MT‐BLUP Animal Model consisted of 1.5 million individuals in the pedigree file. In total 815 782 ewes had records for the NLB and 763 491 ewes had production index (at least 1 year). The records were registered in the years 1990–2006. All possible missing patterns were present in the data. In the iteration process expected values for missing traits were generated and solutions were obtained on canonical transformed scale. The genetic evaluations were run independently for NLB and EPI for computational convenience given the correlations between these traits were negligible.     

Comparison between methods for measuring fecal egg count and estimating genetic parameters for gastrointestinal parasite resistance traits in sheep

Fecal egg count (FEC) is an indicative measurement for parasite infection in sheep. Different FEC methods may show inconsistent results. Not accounting for inconsistencies can be problematic when integrating measurements from different FEC methods for genetic evaluation. The objectives of this study were to evaluate the difference in means and variances between two fecal egg counting methods used in sheep—the Modified McMaster (LMMR) and the Triple Chamber McMaster (LTCM); to estimate variance components for the two FEC methods, treating them as two different traits; and to integrate FEC data from the two different methods and estimate genetic parameters for FEC and other gastrointestinal parasite resistance traits. Fecal samples were collected from a commercial Rideau-Arcott sheep farm in Ontario. Fecal egg counting was performed using both LMMR and the LTCM methods. Other parasite resistance trait records were collected from the same farm including eye score (FAMACHA), body condition score (BCS), and body weight (WT). The two FEC methods were highly genetically (0.94) and phenotypically (0.88) correlated. However, the mean and variance between the two FEC methods were significantly different (P < 0.0001). Therefore, re-scaling is required prior to integrating data from the different methods. For the multiple trait analysis, data from the two fecal egg counting methods were integrated (LFEC) by using records for the LMMR when available and replacing missing records with re-standardized LTCM records converted to the same mean and variance of LMMR. Heritability estimates were 0.12 ± 0.04, 0.07 ± 0.05, 0.17 ± 0.06, and 0.24 ± 0.07 for LFEC egg count, FAMACHA, BCS, and WT, respectively. The estimated genetic correlations between FEC and the other parasite resistance traits were low and not significant (P > 0.05) for FAMACHA (r = 0.24 ± 0.32) and WT (r = 0.22 ± 0.19), and essentially zero for BCS (r = −0.03 ± 0.25), suggesting little to no benefit of using such traits as indicators for LFEC.     

Estimation of direct and maternal genetic parameters for growth and carcass traits in a herd of Japanese Black cattle in Miyagi prefecture, using a multitrait animal model

Data from 1170 records of fattening calves were collected on growth and carcass traits from a Japanese Black cattle herd located in Miyagi prefecture, Japan. The objective was to determine direct and maternal heritabilities, direct and maternal genetic correlations and phenotypic correlations between bodyweight at the beginning of the fattening period (BWS), bodyweight at the end of the fattening period (BWF), carcass weight (CW), average daily gain during the fattening period (ADG), rib eye area (REA), rib thickness, subcutaneous backfat thickness (SFT), yield estimate (YE) and beef marbling score (BMS). Direct heritability estimates of 0.16 (SFT) and 0.07 (BMS) were low, whereas estimates of the other traits were medium to high and ranged between 0.44 (REA) and 0.78 (CW). Direct genetic correlations were all positive, except those that were between BWS and SFT, and between BWS and YE (?0.49 and ?0.14, respectively). The lowest positive genetic correlation was between BWS and BMS (0.04) and the highest was between BWF and CW (0.99). The phenotypic correlation coefficients ranged between ?0.41 (between SFT and YE) and 0.96 (between BWF and CW). Maternal heritability estimates were generally low and ranged between 0.00 for BMS and 0.08 for BWS, CW and ADG. Selection programs comprising information on growth and carcass traits of calves and maternal traits of dams were suggested.     

Estimates of genetic parameters for worm resistance,wool and growth traits in Merino sheep of Uruguay

The genotype of an individual and the environment as the maternal ability of its dam have substantial effects on the phenotype expression of many production traits. The aim of the present study was to estimate the (co)variance components for worm resistance, wool and growth traits in Merino sheep, testing the importance of maternal effects and to determine the most appropriate model for each trait. The traits analyzed were Greasy Fleece Weight (GFW), Clean Fleece Weight (CFW), average Fibre Diameter (FD), Coefficient of Variation of FD (CVFD), Staple Length (SL), Comfort Factor (CF30), Weaning Weight (WWT), Yearling Body Weight (YWT) and Faecal worm Egg Count (FEC). The data were recorded during a 15-year period from 1995 to 2010, from Uruguayan Merino stud flocks. A Bayesian analysis was performed to estimate (co)variance components and genetic parameters. By ignoring or including maternal genetic or environmental effects, five different univariate models were fitted in order to determine the most effective for each trait. For CVFD and YWT, the model fitting the data best included direct additive effects as the only significant random source of variation. For GFW, CFW, FD, SL and CF30 the most appropriate model included direct-maternal covariance; while for FEC included maternal genetics effects with a zero direct-maternal covariance. The most suitable model for WWT included correlated maternal genetic plus maternal permanent environmental effects. The estimates of direct heritability were moderate to high and ranged from 0.15 for log transformed FEC to 0.74 for FD. Most of the direct additive genetic correlation (rg) estimations were in the expected range for Merino breed. However, the estimate of rg between FEC and FD was unfavourable (−0.18±0.03). In conclusion, there is considerable genetic variation in the traits analyzed, indicating the potential to make genetic progress on these traits. This study showed that maternal effects are influencing most of traits analyzed, thus these effects should be considered in Uruguayan Merino breeding programs; since the implementation of an appropriate model of analysis is critical to obtain accurate estimates.     

Estimation of genetic parameters for growth and feed utilization traits in Japanese Black cattle

Performance test results of 3250 sire candidates were used to estimate the genetic parameters of growth and feed utilization traits in Japanese Black cattle. Growth traits analyzed were six body measurements at the end of the performance test and daily gain (DG) during the test. Feed utilization traits were intakes and conversions of concentrate, roughage, digestible crude protein and total digestible nutrient (TDN). Genetic (co)variance components were estimated by the restricted maximum likelihood procedure using an expectation maximization algorithm under the two‐trait animal model. Heritabilities for growth traits ranged from 0.40 to 0.70 and for feed utilization traits from 0.21 to 0.74. Genetic correlations of DG were positive with feed intake (0.15–0.77) and negative with feed conversions (?0.63 to ?0.30). These relationships indicate that the selection based on DG improves feed efficiency but it simultaneously increases feed intake. Feed conversions showed genetic correlations ranging from ?0.09 to 0.03 with total available energy consumption, TDN intake. Thus the results suggested that feed conversions were not efficient selection criteria to decrease TDN intake and to improve comprehensive feed utilization ability.     

Variance components due to direct genetic, maternal genetic and permanent environmental effect for growth and feed-efficiency traits in young male Japanese Black cattle

Variance components and genetic parameters were estimated using data recorded on 740 young male Japanese Black cattle during the period from 1971 to 2003. Traits studied were feed intake (FI), feed‐conversion ratio (FCR), residual feed intake (RFI), average daily gain (ADG), metabolic body weight (MWT) at the mid‐point of the test period and body weight (BWT) at the finish of the test (345 days). Data were analysed using three alternative animal models (direct, direct + maternal environmental, and direct + maternal genetic effects). Comparison of the log likelihood values has shown that the direct genetic effect was significant (p < 0.05) for all traits and that the maternal environmental effects were significant (p < 0.05) for MWT and BWT. The heritability estimates were 0.20 ± 0.12 for FI, 0.14 ± 0.10 for FCR, 0.33 ± 0.14 for RFI, 0.19 ± 0.12 for ADG, 0.30 ± 0.14 for MWT and 0.30 ± 0.13 for BWT. The maternal effects (maternal genetic and maternal environmental) were not important in feed‐efficiency traits. The genetic correlation between RFI and ADG was stronger than the corresponding correlation between FCR and ADG. These results provide evidence that RFI should be included for genetic improvement in feed efficiency in Japanese Black breeding programmes.     

Genetic correlations among and between wool, growth and reproduction traits in Merino sheep

Summary Data from seven research resource flocks across Australia were combined to provide accurate estimates of genetic correlations among production traits in Merino sheep. The flocks represented contemporary Australian Merino fine, medium and broad wool strains over the past 30 years. Over 110 000 records were available for analysis for each of the major wool traits, and 50 000 records for reproduction and growth traits with over 2700 sires and 25 000 dams. Individual models developed from the single trait analyses were extended to the various combinations of two-trait models to obtain genetic correlations among six wool traits [clean fleece weight (CFW), greasy fleece weight, fibre diameter (FD), yield, coefficient of variation of fibre diameter and standard deviation of fibre diameter], four growth traits [birth weight, weaning weight, yearling weight (YWT), and hogget weight] and four reproduction traits [fertility, litter size, lambs born per ewe joined, lambs weaned per ewe joined (LW/EJ)]. This study has provided for the first time a comprehensive matrix of genetic correlations among these 14 wool, growth and reproduction traits. The large size of the data set has also provided estimates with very low standard errors. A moderate positive genetic correlation was observed between CFW and FD (0.29 ± 0.02). YWT was positively correlated with CFW (0.23 ± 0.04), FD (0.17 ± 0.04) and LWEJ (0.58 ± 0.06), while LW/EJ was negatively correlated with CFW (−0.26 ± 0.05) and positively correlated with FD (0.06 ± 0.04) and LS (0.68 ± 0.04). These genetic correlations, together with the estimates of heritability and other parameters provide the basis for more accurate prediction of outcomes in complex sheep-breeding programmes designed to improve several traits.     

Genetic parameters and purebred–crossbred genetic correlations for growth,meat quality,and carcass traits in pigs

Growth, meat quality, and carcass traits are of economic importance in swine breeding. Understanding their genetic basis in purebred (PB) and commercial crossbred (CB) pigs is necessary for a successful breeding program because, although the breeding goal is to improve CB performance, phenotype collection and selection are usually carried out in PB populations housed in biosecure nucleus herds. Thus, the selection is indirect, and the accuracy of selection depends on the genetic correlation between PB and CB performance (rpc). The objectives of this study were to 1) estimate genetic parameters for growth, meat quality, and carcass traits in a PB sire line and related commercial CB pigs and 2) estimate the corresponding genetic correlations between purebred and crossbred performance (rpc). Both objectives were investigated by using pedigree information only (PBLUP) and by combining pedigree and genomic information in a single-step genomic BLUP (ssGBLUP) procedure. Growth rate showed moderate estimates of heritability for both PB and CB based on PBLUP, while estimates were higher in CB based on ssGBLUP. Heritability estimates for meat quality traits were diverse and slightly different based on PB and CB data with both methods. Carcass traits had higher heritability estimates based on PB compared with CB data based on PBLUP and slightly higher estimates for CB data based on ssGBLUP. A wide range of estimates of genetic correlations were obtained among traits within the PB and CB data. In the PB population, estimates of heritabilities and genetic correlations were similar based on PBLUP and ssGBLUP for all traits, while based on the CB data, ssGBLUP resulted in different estimates of genetic parameters with lower SEs. With some exceptions, estimates of rpc were moderate to high. The SE on the rpc estimates was generally large when based on PBLUP due to limited sample size, especially for CBs. In contrast, estimates of rpc based on ssGBLUP were not only more precise but also more consistent among pairs of traits, considering their genetic correlations within the PB and CB data. The wide range of estimates of rpc (less than 0.70 for 7 out of 13 traits) indicates that the use of CB phenotypes recorded on commercial farms, along with genomic information, for selection in the PB population has potential to increase the genetic progress of CB performance.     

Purebred-crossbred genetic parameters for reproductive traits in swine

For swine breeding programs, testing and selection programs are usually within purebred (PB) populations located in nucleus units that are generally managed differently and tend to have a higher health level than the commercial herds in which the crossbred (CB) descendants of these nucleus animals are expected to perform. This approach assumes that PB animals selected in the nucleus herd will have CB progeny that have superior performance at the commercial level. There is clear evidence that this may not be the case for all traits of economic importance and, thus, including data collected at the commercial herd level may increase the accuracy of selection for commercial CB performance at the nucleus level. The goal for this study was to estimate genetic parameters for five maternal reproductive traits between two PB maternal nucleus populations (Landrace and Yorkshire) and their CB offspring: Total Number Born (TNB), Number Born Alive (NBA), Number Born Alive > 1 kg (NBA > 1 kg), Total Number Weaned (TNW), and Litter Weight at Weaning (LWW). Estimates were based on single-step GBLUP by analyzing any two combinations of a PB and the CB population, and by analyzing all three populations jointly. The genomic relationship matrix between the three populations was generated by using within-population allele frequencies for relationships within a population, and across-population allele frequencies for relationships of the CB with the PB animals. Utilization of metafounders for the two PB populations had no effect on parameter estimates, so the two PB populations were assumed to be genetically unrelated. Joint analysis of two (one PB plus CB) vs. three (both PB and CB) populations did not impact estimates of heritability, additive genetic variance, and genetic correlations. Heritabilities were generally similar between the PB and CB populations, except for LWW and TNW, for which PB populations had about four times larger estimates than CB. Purebred-crossbred genetic correlations (rpc) were larger for Landrace than for Yorkshire, except for NBA > 1 kg. These estimates of rpc indicate that there is potential to improve selection of PB animals for CB performance by including CB information for all traits in the Yorkshire population, but that noticeable additional gains may only occur for NBA > 1 kg and TNW in the Landrace population.