Quantitative analysis of production traits in saltwater crocodiles (Crocodylus porosus): III. juvenile survival

Mortality records of 1302 juvenile crocodiles were available for analysis. Crocodiles that were slaughtered during this study were treated as censored (n = 2151). Additionally, records from animals that had neither died nor been slaughtered, i.e. were still alive in the production system (n = 1582), were censored at the last date of data collection. There were a total of 3733 censored records. The data were all full‐sib records from 29 parental pairs from Janamba Croc Farm (Northern Territory, Australia), collected over nine consecutive years. Data were analysed using an extension of Cox's proportional hazards model to include frailty (random) terms to account for genetic effects. Heritability of log survival time for juvenile crocodile survival was 0.15 (SE 0.04). The probability of a juvenile crocodile surviving to day 400 was estimated to be only 51%. These results are the first to quantify juvenile survival in a captive breeding situation. Also, this is the first heritability estimate of crocodile survival and is a fundamental element in the development of a genetic improvement programme.     

苏博美利奴羊主要经济性状的遗传参数估计

苏博美利奴羊是我国近年来培育出的超细型细毛羊品种,为了解该品种主要经济性状的遗传参数以及群体改变的速度和方向,本研究收集2014—2020年新疆巩乃斯种羊场苏博美利奴羊的周岁母羊鉴定记录共计9140条、剪毛称重记录共计7158条以及初生重记录5540条;利用DMU软件采用AIREML模块结合EM算法配合单性状动物模型估...     

Multiple-trait restricted maximum likelihood for simulated measures of ovulation rate with underlying multivariate normal distributions.

A data set that was used to estimate covariance components with REML for an animal model with eight measures of ovulation rate treated as separate traits was used as a template to simulate data sets of eight multivariate normal traits that were then truncated to binomial traits. The model for simulation included eight measures on 610 animals with 1,071 animals in the numerator relationship matrix. Heritabilities were equal for the eight measures, and both genetic and phenotypic correlations among the measures were equal. Ten replications for each combination of heritability (.15, .25, and .35) and genetic correlation (.50, .66, and .90) were simulated on the normal scale. For each replicate, estimates of the eight heritabilities and 28 genetic correlations were obtained by multiple-trait REML. The usual transformation of heritability estimated on the binomial scale overestimated heritability on the normal scale. Genetic correlations on the binomial scale seriously underestimated the correlations on the normal scale. Standard errors of the estimates obtained by replication were somewhat larger than the approximate SE from REMLPK (the multi-trait REML program of K. Meyer). A final set of 10 simulated replications with heritability of .25 and genetic correlation of 1.00 resulted in average estimates of .18 for heritability and of .66 for genetic correlation that agree closely with those from the analysis of measures of ovulation at eight estrous cycles used as a template; averages for heritability of .16 and for genetic correlation of .66 were obtained.     

Heritabilities and genetic trends for elbow score as recorded by the New Zealand Veterinary Association Elbow Dysplasia Scheme (1992–2013) in four breeds of dog

AIM: To estimate the heritability of the New Zealand Veterinary Association (NZVA) elbow phenotype, obtain estimated breeding values (EBV) for the worst-elbow score and estimate the genetic trends for this trait in four populous breeds of dogs, using the records from the NZVA Canine Elbow Dysplasia Scheme database (1992–2013).

METHODS: Overall, 4,070 elbow records from a pedigree of 11,311 dogs were available for animals scored between 1992 and 2013. The worst elbow score between the left and right elbows was identified for each dog and used for EBV analysis. Estimates of heritability and EBV for the elbow score of dogs from German Shepherd dog, Labrador Retriever, Golden Retriever and Rottweiler breeds were obtained using restricted maximum likelihood procedures with a within-breed linear animal model. The model included the fixed effects of sex and birth year, with age at scoring as a covariable, and the random effect of animal. Genetic trends for the worst-elbow score were calculated as the regression coefficient of the EBV, weighted by reliabilities, on year of birth.

RESULTS: The estimates of heritability for worst-elbow score were 0.25 (SE 0.06) in German Shepherd dogs, 0.46 (SE 0.06) in Labrador Retrievers, 0.18 (SE 0.07) in Golden Retrievers and 0.29 (SE 0.11) in Rottweilers. The genetic trend for German Shepherd dogs was ?0.0082 (SE 0.0015), for Labrador Retrievers was ?0.0016 (SE 0.0016), for Golden Retrievers was ?0.0033 (SE 0.0010) and for Rottweilers was ?0.0070 (SE 0.0023) units per annum, which were different from zero (p<0.01) in all breeds except Labrador Retrievers.

CONCLUSIONS AND CLINICAL RELEVANCE: A small but favourable response to selection was achieved by three of the four breeds in the study period; during which selection for elbow traits has been largely voluntary. While the magnitude of genetic change in terms of elbow units per annum may appear small, it must be remembered that elbow scoring grades only range from 0–3. Greater improvement may be possible if compulsory screening was a requirement for pedigree breeding stock, and if greater selection pressure were applied on the basis on an individual’s EBV, rather than the worst-elbow score alone. The maintenance of an open registry, with transparency of EBV information made available to all breeders, may enhance selection intensity opportunities and potentially assist with the process and progress of breeding selection.     

Genetic parameters for cattle price and body weight from routinely collected data at livestock auctions and commercial farms

Beef outputs from dairy farms make an important contribution to overall profitability in Irish dairy herds and are the sole source of revenue in many beef herds. The aim of this study was to estimate genetic parameters for animal BW and price across different stages of maturity. Data originated from 2 main sources: price and BW from livestock auctions and BW from on-farm weighings between 2000 and 2008. The data were divided into 4 distinct maturity categories: calves (n = 24,513), weanlings (n = 27,877), postweanlings (n = 23,279), and cows (n = 4,894). A univariate animal model used to estimate variance components was progressively built up to include a maternal genetic effect and a permanent environmental maternal effect. Bivariate analyses were used to estimate genetic covariances between BW and price per animal within and across maturity category. Direct heritability estimates for price per animal were 0.34 ± 0.03, 0.31 ± 0.05, 0.19 ± 0.04, and 0.10 ± 0.04 for calves, weanling, postweanlings, and cows, respectively. Direct heritability estimates for BW were 0.26 ± 0.03 for weanlings, 0.25 ± 0.04 for postweanlings, and 0.24 ± 0.06 for cows; no BW data were available on calves. Significant maternal genetic and maternal permanent environmental effects were observed for weanling BW only. The genetic correlation between price per animal and BW within each maturity group varied from 0.55 ± 0.06 (postweanling price and BW) to 0.91 ± 0.04 (cow price and BW). The availability of routinely collected data, along with the existence of ample genetic variation for animal BW and price per animal, facilitates their inclusion in Irish dairy and beef breeding objectives to better reflect the profitability of both enterprises.     

Genetic parameter estimation for number born alive at different parities in Landrace and Large White pigs

We estimated genetic parameters for number born alive (NBA) from the first to the seventh parities in Landrace and Large White pigs using three models. Analyzing 55,160 farrowing records for 12,677 Landrace dams and 43,839 for 10,405 Large White dams, we used a single‐trait animal model to estimate the heritability of NBA at each parity and a two‐trait animal model and a single‐trait random regression model to estimate the genetic correlations between parities. Heritability estimates of NBA at each parity ranged from 0.08 to 0.13 for Landrace and from 0.05 to 0.16 for Large White. Estimated genetic correlations between parities in all cases were positive. Genetic correlations between the first and second parities were slightly lower than those between other neighboring parities. Genetic correlations between more distant parities tended to be lower, in some cases <0.8. The results indicate the necessity to investigate the applicability of evaluating NBA at different parities as different traits (e.g., the first and later parities), although a repeatability model might still be reasonable.     

Use of serial pig body weights for genetic evaluation of daily gain

This study examined the utility of serial weights from FIRE (Feed Intake Recording Equipment, Osborne Industries, Inc., Osborne, KS, USA) stations for an analysis of daily gain. Data included 884 132 body weight records from 3888 purebred Duroc pigs. Pigs entered the feeder station at age 77–149 days and left at age 95–184 days. A substantial number of records were abnormal, showing body weight close to 0 or up to twice the average weight. Plots of body weights for some animals indicated two parallel growth curves. Initial editing used a robust regression, which was a two‐step procedure. In the first step, a quadratic growth curve was estimated assuming small or 0 weights for points far away from the curve; the process is iterative. In the second step, weights more than 1.5 SD from the estimated growth curve were treated as outliers. The retained body weight records (607 597) were averaged to create average daily weight (170 443) and then used to calculate daily gains (152 636). Additional editing steps included retaining only animals with ≥50 body weight records and SD of the daily gain ≤2 kg, followed by removing records outside 3 SD from the mean for given age, across all the animals – the resulting data set included 69 068 records of daily gain from 1921 animals. Daily gain based on daily, weekly and bi‐weekly intervals was analysed using repeatability models. Heritability estimates were 0.04, 6 and 9%, respectively. The last two estimates correspond to heritability of 28% for a 12 week interval. For daily gain averaged weekly, the estimate of heritability obtained with a random regression model varied from 0.07 to 0.10. After extensive editing, body weight records from automatic feeding stations are useful for genetic analyses of daily gain from weekly or bi‐weekly but not daily intervals.     

Heritability estimates of liabilities to digestive diseases in heavy racehorses

Data on 1410 heavy racehorses were taken from the Hokkaido Banei Horse Racing Result Book published during 1997–2000. Heritabilities were estimated using the restricted maximum likelihood method with a full data set of the accumulated prize winnings and the frequency of medical treatment against digestive diseases. Heritability estimates for the same traits were also obtained using a partial data set from affected animals only. In addition, a ‘two classes, one threshold’ model was applied to the full data set for the heritability estimation of liability to the diseases. Heritabilities estimated by restricted maximum likelihood with the full data set were quite low: 0.09 ± 0.02 for the prize winnings and 0.08 ± 0.03 for all three digestive diseases – colic resulting from flatulence, constipation and overfeeding. Low heritabilities were also estimated for each of the three kinds of colic. Medium heritabilities were estimated for colic resulting from constipation (0.30 ± 0.19) and overfeeding (0.46 ± 0.22) using the partial data set taken from the affected animals. Using the threshold model, higher heritabilities from 0.42 ± 0.04 to 0.57 ± 0.03 were estimated for the liabilities to all three digestive diseases and to the individual digestive diseases. These results suggest that liability evaluation of the frequency of medical treatment is insufficient because all non‐affected animals are scored as 0. The high heritabilities estimated by the threshold model with half‐sib relationships should be verified in future studies by comparing them with estimates from other genetic relationships and with realized heritabilities from a small‐scale practical selection program.     

Genetic and crossbreeding parameters for incidence of recorded clinical lameness in New Zealand dairy cattle

AIM: To estimate genetic and crossbreeding parameters for the incidence of recorded clinical lameness in New Zealand dairy cattle.

METHODS: Herd records from 76,357 cows, collected during the 2005/06 to 2008/09 milking seasons from 155 herds in the Livestock Improvement Corporation young sire progeny test scheme, were used to estimate genetic parameters and breed effects for incidence of recorded clinical lameness in HolsteinFriesian, Jersey and crossbred dairy cattle. Recorded clinical lameness was coded “1” for cows that presented at least one event of clinical lameness at any day during the season and “0” for unaffected cows. Genetic parameters were estimated using an animal model across breeds considering all and then only first lactation records. Heritability and repeatability of recorded clinical lameness were calculated from the variance component estimates both with and without logit transformation.

RESULTS: The mean incidence of recorded clinical lameness per herd was 6.3 (min 2, max 34)%. The incidence of recorded clinical lameness in Holstein Friesian cows (mean 6.8, SE 0.24%) was higher than the incidence of recorded clinical lameness in crossbred (mean 6.1, SE 0.19%) and Jersey cows (mean 6.0, SE 0.28%) (p=0.0002). There was no difference in incidence between crossbred and Jersey cows (p=0.96).

Estimates of the heritability of recorded clinical lameness as an untransformed trait were 0.053 (SE 0.014) for first lactation records and 0.016 (SE 0.003) for all lactation records. As a transformed (logit) trait heritabilities were 0.067 (SE 0.024) and 0.044 (SE 0.016) for first and all lactation records, respectively. The repeatability estimates of recorded clinical lameness were 0.071 (SE 0.005) and 0.107 (SE 0.011) for untransformed and logit transformed lactation records, respectively. Sire estimated breeding values for recorded clinical lameness showed the lowest values in Jersey sires, and ranged between -5 and 8%.

CONCLUSIONS: Despite the low heritability of recorded clinical lameness, this study provided evidence that there is significant exploitable animal genetic variation. Selection of specific sires across and within breeds could be an option for increasing genetic resistance to lameness in New Zealand dairy cattle.     

Genetic analysis of the rates of conception using a longitudinal threshold model with random regression in dairy crossbreeding within a tropical environment

This study was designed to: (i) estimate genetic parameters and breeding values for conception rates (CR) using the repeatability threshold model (RP‐THM) and random regression threshold models (RR‐THM); and (ii) compare covariance functions for modeling the additive genetic (AG) and permanent environmental (PE) effects in the RR‐THM. The CR was defined as the outcome of an insemination. A data set of 130 592 first‐lactation insemination records of 55 789 Thai dairy cows, calving between 1996 and 2011, was used in the analyses. All models included fixed effects of year × month of insemination, breed × day in milk to insemination class and age at calving. The random effects consisted of herd × year interaction, service sire, PE, AG and residual. Variance components were estimated using a Bayesian method via Gibbs sampling. Heritability estimates of CR ranged from 0.032 to 0.067, 0.037 to 0.165 and 0.045 to 0.218 for RR‐THM with the second, third and fourth‐order of Legendre polynomials, respectively. The heritability estimated from RP‐THM was 0.056. Model comparisons based on goodness of fit, predictive abilities, predicted service results of animal, and pattern of genetic parameter estimates, indicated that the model which fit the desired outcome of insemination was the RR‐THM with two regression coefficients.     

Genetic parameters of racing performance traits of Quarter horses in Brazil

The data used in the present study were recorded at the Jockey Club of Sorocaba for 5094 racing performance of 1350 Quarter Horses at the Paulista Race Track of Sorocaba, state of São Paulo, Brazil, from 1991 to 1997. The considered traits were time and final rank. The model used in analysis included random animal and permanent environmental effects, and race, sex, age and origin as fixed effects. The variance and covariance components were estimated by the restricted maximum likelihood for an animal model, using the derivative-free process method and the MTDFREML software. For the time, heritability was 0.17 (0.05), while estimate of repeatability 0.55 (0.05). The lower heritability for the final rank, 0.13 (0.04), indicate that this trait is not the most appropriate one for inclusion in programs of Quarter horse selection in Sorocaba racetrack. The repeatability estimate for rank was 0.44 (0.04) and the genetic correlation between this trait and time was 0.99.     

Random regression models on Legendre polynomials to estimate genetic parameters for weights from birth to adult age in Canchim cattle*

The objective of this work was to estimate covariance functions for direct and maternal genetic effects, animal and maternal permanent environmental effects, and subsequently, to derive relevant genetic parameters for growth traits in Canchim cattle. Data comprised 49 011 weight records on 2435 females from birth to adult age. The model of analysis included fixed effects of contemporary groups (year and month of birth and at weighing) and age of dam as quadratic covariable. Mean trends were taken into account by a cubic regression on orthogonal polynomials of animal age. Residual variances were allowed to vary and were modelled by a step function with 1, 4 or 11 classes based on animal’s age. The model fitting four classes of residual variances was the best. A total of 12 random regression models from second to seventh order were used to model direct and maternal genetic effects, animal and maternal permanent environmental effects. The model with direct and maternal genetic effects, animal and maternal permanent environmental effects fitted by quadric, cubic, quintic and linear Legendre polynomials, respectively, was the most adequate to describe the covariance structure of the data. Estimates of direct and maternal heritability obtained by multi‐trait (seven traits) and random regression models were very similar. Selection for higher weight at any age, especially after weaning, will produce an increase in mature cow weight. The possibility to modify the growth curve in Canchim cattle to obtain animals with rapid growth at early ages and moderate to low mature cow weight is limited.     

Estimation of heritability of atopic dermatitis in Labrador and Golden Retrievers

OBJECTIVE: To estimate the heritability of atopic dermatitis in Golden and Labrador Retrievers. ANIMALS: 429 dogs related to 13 dogs with atopic dermatitis. PROCEDURE: Atopic dermatitis was defined on the basis of the type and frequency of clinical signs recorded in the clinical records, and each dog was classified with atopic dermatitis or probable atopic dermatitis or as nonatopic. By use of data from atopic and nonatopic dogs, regression analyses of parental status on offspring status were performed to estimate heritability. RESULTS: There was no difference in the frequency of atopic dermatitis between sexes or between breeds. There was a marked association between the atopic status of the parent and that of the offspring, particularly for sires. By use of data from 32 litters in which the status of both parents was known and considering only those dogs classified with atopic dermatitis or as nonatopic, the heritability (+/- SE) of atopic dermatitis was estimated to be 0.47 (+/- 0.17). CONCLUSIONS AND CLINICAL RELEVANCE: Atopic dermatitis has a strong genetic component, and breeding of dogs with clinical signs of atopic dermatitis should be discouraged.     

Estimation of direct and maternal genetic and permanent environmental effects for weights from birth to 356 days of age in a herd of Japanese Black cattle using random regression

A total of 11,815 weight records from 23,94 Japanese Black calves was used to estimate direct, maternal, direct permanent environmental, and maternal permanent environmental effects on growth from birth to 356 d of age. The data were collected from a herd of Japanese Black cattle in Shiroshi city, Miyagi prefecture, Japan. A random regression model, including parity of dam and year-season of calving-sex of calf as fixed effects and animal, dam, animal permanent environmental, and maternal permanent environmental as random effects, was fitted to the data using Legendre polynomials for age of calf. Direct heritability estimates increased from 0.38 at birth to 0.65 at 120 d of age, decreased to 0.38 at 300 d, and then increased again up to 0.47 at 356 d. The ratio of animal permanent environmental variance to phenotypic variance decreased from 0.41 at birth to 0.12 at 90 d, and then increased gradually up to 0.40 at 270 d and oscillated around this value up to the end of the test period. Maternal genetic heritabilities increased from 0.04 at birth to 0.09 at 120 d and then decreased to 0.06 thereafter, whereas the variance ratios due to maternal permanent environment were fairly constant across the age trajectory, fluctuating around the value of 0.03. Direct genetic, phenotypic, maternal genetic, animal permanent environmental, and maternal permanent environmental correlations between different ages were all positive, and they generally decreased as the interval between ages increased. These correlations were lower between weights from nonadjacent ages than those between weights from adjacent ages. Results suggest that selection on preweaning weights would have a positive effect on weights at later ages.     

Random regression models to estimate genetic parameters for weights in Murrah buffaloes

This article reports genetic analysis of the weight at different ages of Murrah water buffaloes, using random regression models (RRM). Models ranging from third to sixth order polynomial were used to describe direct genetic and animal permanent environmental effects. Contemporary group was included as a fixed effect, and a cubic polynomial was used to model the mean curve of the population. The residual was modeled considering a log‐linear function. Two models were selected for study of genetic parameters. The first model included third and sixth order polynomials for direct genetic and animal permanent environmental effects (M36). The second model included sixth order polynomials for all random effects (M66). The estimates of heritability varied from 0.16 + 0.04 (44 days) to 0.38 + 0.04 (568 days) for model M36 and from 0.16 + 0.05 (33 days) to 0.42 + 0.05 (600 days) for model M66. Regarding estimates of the correlation for all effects, the magnitude tended to decline with the increase of the time span between measurements. These results indicate that the species has potential for genetic selection based on weight at different ages, since we found favorable genetic variability within the herd, with selection likely to be more efficient at ages near 600 days.     

Impact of variation in length of individual testing periods on estimation of (co)variance components of a random regression model for feed intake of growing pigs

A simulation study was conducted to assess the influence of differences in the length of individual testing periods on estimates of (co)variance components of a random regression model for daily feed intake of growing pigs performance tested between 30 and 100 kg live weight. A quadratic polynomial in days on test with fixed regressions for sex, random regressions for additive genetic and permanent environmental effects and a constant residual variance was used for a bivariate simulation of feed intake and daily gain. (Co)variance components were estimated for feed intake only by means of a Bayesian analysis using Gibbs sampling and restricted maximum likelihood (REML). A single trait random regression model analogous to the one used for data simulation was used to analyse two versions of the data: full data sets with 18 weekly means of feed intake per animal and reduced data sets with the individual length of testing periods determined when tested animals reached 100 kg live weight. Only one significant difference between estimates from full and reduced data (REML estimate of genetic covariance between linear and quadratic regression parameters) and two significant differences from expected values (Gibbs estimates of permanent environmental variance of quadratic regression parameters) occurred. These differences are believed to be negligible, as the number lies within the expected range of type I error when testing at the 5% level. The course of test day variances calculated from estimates of additive genetic and permanent environmental covariance matrices also supports the conclusion that no bias in estimates of (co)variance components occurs due to the individual length of testing periods of performance‐tested growing pigs. A lower number of records per tested animal only results in more variation among estimates of (co)variance components from reduced compared with full data sets. Compared with the full data, the effective sample size of Gibbs samples from the reduced data decreased to 18% for residual variance and increased up to five times for other (co)variances. The data structure seems to influence the mixing of Gibbs chains.     

Inheritance of faecal nematode egg count in Barbari goats following natural Haemonchus contortus infection

Genetic parameters for faecal nematode egg count were estimated in naturally infected Barbari goats maintained at the Central Institute for Research on Goats, Makhdoom, Mathura, India, over a period of 5 years (1999 through 2003). Faecal egg count (FEC) data on 891 records of Barbari goats descended from 69 bucks and 241 does were used in this study. Analyses were carried out by restricted maximum likelihood (REML), fitting an animal model and ignoring or including maternal genetic or permanent environmental effects. Three different animal models were fitted. Direct heritability estimates were inflated substantially for this trait when maternal effects were ignored. The direct heritability estimates for the trait ranged from 0.05 to 0.13 depending on the model used. Low (0.04) maternal heritability estimate was observed for this trait in our study. Moderate estimate of the fraction of variance due to maternal permanent environmental effects (c(2)) for faecal egg count (c(2)=0.10) was also observed. Results suggest that direct and permanent environmental maternal effects were important for this trait, however, maternal additive effects had less impact on this trait.     

Testicular traits as selection criteria for young Nellore bulls

The objective of this study was to evaluate the possible use of biometric testicular traits as selection criteria for young Nellore bulls using Bayesian inference to estimate heritability coefficients and genetic correlations. Multitrait analysis was performed including 17,211 records of scrotal circumference obtained during andrological assessment (SCAND) and 15,313 records of testicular volume and shape. In addition, 50,809 records of scrotal circumference at 18 mo (SC18), used as an anchor trait, were analyzed. The (co)variance components and breeding values were estimated by Gibbs sampling using the Gibbs2F90 program under an animal model that included contemporary groups as fixed effects, age of the animal as a linear covariate, and direct additive genetic effects as random effects. Heritabilities of 0.42, 0.43, 0.31, 0.20, 0.04, 0.16, 0.15, and 0.10 were obtained for SC18, SCAND, testicular volume, testicular shape, minor defects, major defects, total defects, and satisfactory andrological evaluation, respectively. The genetic correlations between SC18 and the other traits were 0.84 (SCAND), 0.75 (testicular shape), 0.44 (testicular volume), -0.23 (minor defects), -0.16 (major defects), -0.24 (total defects), and 0.56 (satisfactory andrological evaluation). Genetic correlations of 0.94 and 0.52 were obtained between SCAND and testicular volume and shape, respectively, and of 0.52 between testicular volume and testicular shape. In addition to favorable genetic parameter estimates, SC18 was found to be the most advantageous testicular trait due to its easy measurement before andrological assessment of the animals, even though the utilization of biometric testicular traits as selection criteria was also found to be possible. In conclusion, SC18 and biometric testicular traits can be adopted as a selection criterion to improve the fertility of young Nellore bulls.     

Genetic parameters for stayability, stayability at calving, and stayability at weaning to specified ages for Hereford cows

Genetic parameters for stayability to six ages (ST1, . . ., ST6), for five measures of stayability to calving (SC2, . . ., SC6), and for five measures of stayability to weaning (SW2, . . ., SW6), were estimated using records of 2,019 Hereford cows collected from 1964 to 1979 from a selection experiment with a control line and three lines selected for weaning weight, yearling weight, and an index of yearling weight and muscle score. The model included birth year of the cow as a fixed effect and the cow's sire as a random effect. Analyses were performed with 1) a generalized linear mixed model for binary data using a probit link with a penalized quasi-likelihood function, and 2) with a linear mixed model using REML. Genetic trends were estimated by regressing weighted means of estimated transmitting abilities (ETA) of sires by birth year of their daughters on birth year. Environmental trends were estimated by regressing solutions for year of birth on birth year. Estimates of heritability (SE) for ST were between 0.09 (0.08) and 0.30 (0.14) for threshold model and between 0.05 (0.04) and 0.19 (0.09) for linear model. Estimates of heritability from linear model analyses transformed to an underlying normal scale were between 0.09 and 0.35. Estimates of heritability (SE) for SC were between 0.29 (0.10) and 0.39 (0.11) and between 0.18 (0.09) and 0.25 (0.08) with threshold and linear models. Estimates of heritability transformed to an underlying normal scale were between 0.30 and 0.40. Estimates of heritability (SE) for SW were between 0.21 (0.14) and 0.47 (0.19) and between 0.12 (0.08) and 0.26 (0.12) with threshold and linear models, respectively. Estimates of heritability transformed to an underlying normal scale were between 0.21 and 0.50. Estimates of genetic and environmental trends for all lines were nearly zero for all traits. Correlations between ETA of sires for stayability to specific ages, for stayability to calving, and for stayability to weaning with threshold and linear models ranged from 0.09 to 0.82, from 0.68 to 0.90, and from 0.67 to 0.87, respectively. Selection for stayability would be possible in a breeding program and could be relatively effective as a result of the moderate estimates of heritability, which would allow selection of sires whose daughters are more likely to remain longer in the herd. Selection for weaning and yearling weights resulted in little correlated response for any of the measures of stayability.     

Genomic prediction of growth in pigs based on a model including additive and dominance effects

Independent of whether prediction is based on pedigree or genomic information, the focus of animal breeders has been on additive genetic effects or ‘breeding values’. However, when predicting phenotypes rather than breeding values of an animal, models that account for both additive and dominance effects might be more accurate. Our aim with this study was to compare the accuracy of predicting phenotypes using a model that accounts for only additive effects (MA) and a model that accounts for both additive and dominance effects simultaneously (MAD). Lifetime daily gain (DG) was evaluated in three pig populations (1424 Pietrain, 2023 Landrace, and 2157 Large White). Animals were genotyped using the Illumina SNP60K Beadchip and assigned to either a training data set to estimate the genetic parameters and SNP effects, or to a validation data set to assess the prediction accuracy. Models MA and MAD applied random regression on SNP genotypes and were implemented in the program Bayz. The additive heritability of DG across the three populations and the two models was very similar at approximately 0.26. The proportion of phenotypic variance explained by dominance effects ranged from 0.04 (Large White) to 0.11 (Pietrain), indicating that importance of dominance might be breed‐specific. Prediction accuracies were higher when predicting phenotypes using total genetic values (sum of breeding values and dominance deviations) from the MAD model compared to using breeding values from both MA and MAD models. The highest increase in accuracy (from 0.195 to 0.222) was observed in the Pietrain, and the lowest in Large White (from 0.354 to 0.359). Predicting phenotypes using total genetic values instead of breeding values in purebred data improved prediction accuracy and reduced the bias of genomic predictions. Additional benefit of the method is expected when applied to predict crossbred phenotypes, where dominance levels are expected to be higher.