Genetic factors contributing to variation in littersize in British Large White gilts

The number of ova released (ovulation rate) by 516 Large White gilts born between 1986 and 1989 was recorded. The weight of the gilt at birth, weaning and time of ovulation rate measurement and her number of teats were also recorded. Parrowing data (number born alive and litter weight at birth) corresponding to the ovulation rate were recorded from 382 of the gilts, enabling calculation of prenatal survival (number born alive/ovulation rate). The data were analysed using univariate and multivariate restricted maximum likelihood (REML) techniques with an individual animal model. The additive genetic direct and maternal components of variance and the common family and residual environmental components of variance and the additive genetic and residual environmental covariances between traits were estimated. The univariate REML analyses showed that the additive genetic direct component was a significant source of variation for gilt weight at birth and weaning, teat number, ovulation rate on the left hand side, total ovulation rate and litter weight at birth. Common family environmental effects were significant sources of variation for gilt weights and teat number. The multivariate REML analyses indicated that the genetic correlations between total ovulation rate and ovulation rate from the left and right ovaries were close to unity, with an estimate of the heritability of total ovulation rate of 0.37±0.09. In the data from gilts that farrowed, the heritabilities of ovulation rate, number born alive and prenatal survival were 0.30±0.10, 0.09±0.06 and 0.00±0.00, respectively. The genetic correlation between ovulation rate and litter size was close to unity, suggesting that genetic variation in ovulation rate explains virtually all of the genetic variation in number born alive in the population of Large White gilts understudy.     

Genetic selection for increased mean and reduced variance of twinning rate in Belclare ewes

It is sometimes possible to breed for more uniform individuals by selecting animals with a greater tendency to be less variable, that is, those with a smaller environmental variance. This approach has been applied to reproduction traits in various animal species. We have evaluated fecundity in the Irish Belclare sheep breed by analyses of flocks with differing average litter size (number of lambs per ewe per year, NLB) and have estimated the genetic variance in environmental variance of lambing traits using double hierarchical generalized linear models (DHGLM). The data set comprised of 9470 litter size records from 4407 ewes collected in 56 flocks. The percentage of pedigreed lambing ewes with singles, twins and triplets was 30, 54 and 14%, respectively, in 2013 and has been relatively constant for the last 15 years. The variance of NLB increases with the mean in this data; the correlation of mean and standard deviation across sires is 0.50. The breeding goal is to increase the mean NLB without unduly increasing the incidence of triplets and higher litter sizes. The heritability estimates for lambing traits were NLB, 0.09; triplet occurrence (TRI) 0.07; and twin occurrence (TWN), 0.02. The highest and lowest twinning flocks differed by 23% (75% versus 52%) in the proportion of ewes lambing twins. Fitting bivariate sire models to NLB and the residual from the NLB model using a double hierarchical generalized linear model (DHGLM) model found a strong genetic correlation (0.88 ± 0.07) between the sire effect for the magnitude of the residual (V_E) and sire effects for NLB, confirming the general observation that increased average litter size is associated with increased variability in litter size. We propose a threshold model that may help breeders with low litter size increase the percentage of twin bearers without unduly increasing the percentage of ewes bearing triplets in Belclare sheep.     

Estimation of litter size variability phenotypes in Large White sows

The objective of this study was to obtain new phenotypes of phenotypic variability for the total number born (TNB) in pigs using the residual variance of TNB. The analysis was based on 246,799 Large White litter observations provided by Topigs Norsvin. Three animal models were used to obtain estimates of residual variance for TNB: the basic model (BM) containing fixed effects of farm–year and season and random effects of animal and permanent environmental sow, the basic model with an additional fixed effect of parity (BMP) and a random regression model (RRM). The within-individual variance of the residuals was calculated and log-transformed to obtain three new variability traits: LnVarBM, LnVarBMP and LnVarRRM. Then, (co)variance components, heritability, the genetic coefficient of variation at the standard deviation level (GCV_SDe) and genetic correlations between the three LnVar's and between the LnVar's and mean total number born (mTNB) were estimated with uni-, bi- and trivariate models. Results indicated that genetically LnVar's are the same trait and are positively correlated with the mTNB (~0.60). Thus, both traits should be included in breeding programmes to avoid an increase in TNB variability while selecting for increased TNB. Heritability of the LnVar's was estimated at 0.021. The GCV_SDe for LnVar's showed that a change of 8% in residual standard deviation of TNB could be obtained per generation. Those results indicate that phenotypic variability of litter size is under genetic control, thus it may be improved by selection.     

Genetics and genomics of uniformity and resilience in livestock and aquaculture species: A review

Genetic control of residual variance offers opportunities to increase uniformity and resilience of livestock and aquaculture species. Improving uniformity and resilience of animals will improve health and welfare of animals and lead to more homogenous products. Our aims in this review were to summarize the current models and methods to study genetic control of residual variance, genetic parameters and genomic results for residual variance and discuss future research directions. Typically, the genetic coefficient of variation is high (median = 0.27; range 0–0.86) and the heritability of residual variance is low (median = 0.01; range 0–0.10). Higher heritabilities can be achieved when increasing the number of records per animal. Divergent selection experiments have supported the feasibility of selecting for high or low residual variance. Genomic studies have revealed associations in regions related to stress, including those from the heat shock protein family. Although the number of studies is growing, genetic control of residual variance is still poorly understood, but big data and genomics offer great opportunities.     

Genetic correlations between male reproductive traits and growth traits in growth performance tested Duroc,Landrace and Yorkshire breed boars

Male‐related traits at 180–225 days of age for 6464 grow‐finish performance tested boars were measured from 2000 to 2016. Heritability estimates and genetic correlations among average daily gain, feed efficiency, back fat thickness, teat counts, mounting libido, leg locomotion, penile length, sperm motility, sperm concentration and total sperm counts were estimated by VCE software using a multiple traits animal model in each breed. Growth‐tested boars had heritability estimates of male reproductive traits in 0.34–0.56 of teat counts, 0.12–0.20 of libido, 0.08–0.12 of locomotion, 0.17–0.58 of penile length, 0.04–0.21 of sperm motility and concentration, 0.17–0.30 of total sperm counts. Total sperm counts were genetically positively correlated with penile length in all breeds. Boars with higher total sperm counts had genetically better libido and locomotion. Genetic correlation between feed efficiency and sperm motility and feed efficiency and sperm concentration were positive in Duroc and negative in Landrace and Yorkshire. Sperm motility and concentration were genetically negatively correlated with average daily gain in Yorkshire. Male reproductive traits of imported breeds could be improved with care in the change of growth traits, especially in Yorkshire.     

Stability of genetic parameter estimates for production traits in pigs

Changes in variance component estimates in growing sets of performance data in two pig breeds were investigated. Data was used from the field and station test of Czech Landrace (LA: 75 099 observations) and the Slovakian breed, White Meaty swine (WM: 32 203 observations). In LA the traits analysed were estimated lean meat content (LM) and average daily gain (ADGF) on field test and average daily gain (ADGS) and weight of valuable cuts (VCW) on station test. In WM the traits analysed were backfat thickness on field and station test (BFF, BFS, respectively), proportion of valuable cuts (VCP) on station test, ADGF and ADGS. Covariance components were estimated from four- and five-trait animal models using the VCE software. Omitting data from factor levels with a low number of records led to 4.2% of LA records and 21.7% of WM records being deleted. Changes in genetic and residual variance estimates were less than 5% for all traits in LA and less than 12% for all traits except ADGS in WM. The changes in estimated genetic variances caused by 18 months (LA) or 24 months (WM) of new data were 2–25% and the changes in estimated residual variances were less than 5% in LA and less than 20% in WM. In both breeds, changes in heritability estimates did not exceed 0.06 in absolute value. In LA, it is reasonable to use genetic parameter estimates for 3 years before re-estimation. In WM the time interval should be shorter because of changes in the estimates caused by their lower accuracy arising from the smaller size of the data-set and smaller frequency of station testing.     

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.     

Estimates of genetic variance and variance of predicted genetic merits using pedigree or genomic relationship matrices in six Brown Swiss cattle populations for different traits

The amount of variance captured in genetic estimations may depend on whether a pedigree‐based or genomic relationship matrix is used. The purpose of this study was to investigate the genetic variance as well as the variance of predicted genetic merits (PGM) using pedigree‐based or genomic relationship matrices in Brown Swiss cattle. We examined a range of traits in six populations amounting to 173 population‐trait combinations. A main aim was to determine how using different relationship matrices affect variance estimation. We calculated ratios between different types of estimates and analysed the impact of trait heritability and population size. The genetic variances estimated by REML using a genomic relationship matrix were always smaller than the variances that were similarly estimated using a pedigree‐based relationship matrix. The variances from the genomic relationship matrix became closer to estimates from a pedigree relationship matrix as heritability and population size increased. In contrast, variances of predicted genetic merits obtained using a genomic relationship matrix were mostly larger than variances of genetic merit predicted using pedigree‐based relationship matrix. The ratio of the genomic to pedigree‐based PGM variances decreased as heritability and population size rose. The increased variance among predicted genetic merits is important for animal breeding because this is one of the factors influencing genetic progress.     

河北省中国荷斯坦牛产奶和体型性状遗传参数分析

旨在探究河北省中国荷斯坦牛产奶和体型性状的遗传参数,为育种提供参考.本研究收集了2012-2018年河北省133个牛场8 891头中国荷斯坦母牛第一胎次的3个产奶性状记录(产奶量、乳脂率和乳蛋白率)和26个体型性状记录,利用DMU软件,以场年季、产犊月龄、鉴定年季和鉴定员效应为固定效应,以个体的加性遗传效应为随机效应,...     

Within-litter variation of birth weight in hyperprolific Czech Large White sows and its relation to litter size traits, stillborn piglets and losses until weaning

Data from about 2900 litters (approximately 40,000 piglets) originating from 1063 Czech Large White hyperprolific sows were analyzed. The phenotypic and genetic relations between litter size traits, piglet mortality during farrowing and from birth to weaning and several statistics referring to the distribution of the birth weight within litter were analyzed. All genetic parameters were estimated from multi-trait animal models including the following factors: mating type (natural service or insemination), parity, linear and quadratic regression on age at first farrowing (1st litter) or farrowing interval (2nd and subsequent litters), herd-year-season effect and additive-genetic effect of the sow. The phenotypic correlations of the mean birth weight with the total number of piglets born and piglets born alive were − 0.30. Traits describing the variability of the birth weight within litter (range, variance, standard deviation, coefficient of variation) were mostly positively correlated with litter size. A statistically significant phenotypic correlation (− 0.09 to − 0.15) between mean birth weight and losses at birth and from birth to weaning was found. The heritability for the number of piglets born, piglets born alive and piglets weaned was around 0.15. The number of stillborn piglets had only a very low heritability less than 0.05, whereas the heritability for losses from birth to weaning was 0.13. The heritabilities of the mean, minimal and maximal birth weight were 0.16, 0.10 and 0.10, respectively. The heritability for all statistics and measures referring to the variability of the birth weight within litter was very low and did never exceed the value of 0.05. An increase in litter size was shown to be genetically connected with a decrease in the mean piglet birth weight and an increase in the within-litter variability of birth weight. Selection on litter size should be accompanied by selection on mortality traits and/or birth-weight traits. Losses from birth to weaning and the minimal birth weight in the litter were proposed as potential traits for a selection against piglet mortality.     

山东省荷斯坦奶牛体型性状遗传参数估计及系谱世代数的影响

旨在估计山东省荷斯坦奶牛体型性状遗传参数,为育种方案制定提供参考。本研究收集了山东省2010—2020年间的144个牛场31 963头头胎中国荷斯坦母牛的20个体型性状记录,其中性状评分由线性分转为功能分,将场、泌乳月、产犊月龄、鉴定员效应为固定效应,以个体的加性遗传效应作为随机效应,利用 DMU 软件,采用AI-REML结合EM算法并配合动物模型进行遗传参数估计。结果表明,体型性状的遗传力属于中等偏低水平,其估计值变化范围为0.049(后肢侧视)到 0.282(棱角性),性状间的遗传相关范围为-0.558(前乳头位置与乳房深度)至0.717(蹄踵深度与蹄角度)。体躯容量各性状间的遗传相关范围为0.118 (体深与体高)至0.461(胸宽与腰强度);尻角度与尻宽的遗传相关为-0.251;肢蹄各性状间的遗传相关范围为-0.035(蹄踵深度与后肢后视)到 0.717(蹄踵深度与蹄角度);泌乳系统各性状间的遗传相关范围为-0.558 (前乳头位置与乳房深度)至0.587(悬韧带与前乳房附着)。另外,体型性状的遗传力估计标准误在查找的系谱世代数为3的情况下为最小,这可能是由于系谱数据完整性的限制导致了该种情况,具体还需要进一步验证。加强对体型性状中遗传力较高且与泌乳系统遗传相关较强性状的选择,有利于奶牛生产性能的提高。另外,在本研究数据中,使用前3代系谱估计的遗传力标准误最小,因此,利用前3代系谱估算遗传参数可能较佳。     

撒坝猪乳头数遗传力及其与繁殖性能关系的研究

本研究对 4个世代共 577头撒坝猪的乳头数进行了分析 ,并用HARVEY程序对乳头数的遗传力进行了估计 ,同时利用 1 2 8头有繁殖性能记录的母猪资料对乳头数与繁殖性状的关系进行了分析。结果表明 ,各世代的乳头数存在着显著差异 ,且逐代均有显著提高 ;乳头数的遗传力为 0 .331 ;乳头数与总产仔数和活产仔数间遗传相关和表型相关均为负值 ,与初生窝重、2 0日窝重、断奶仔数和断奶窝重间则存在着正的遗传相关和表型相关 ;乳头数与所有繁殖性状的环境相关都较弱 ( -0 .0 0 2～ 0 .0 94 )     

Genetic parameter estimation for pre- and post-weaning traits in Brahman cattle in Brazil

Beef cattle producers in Brazil use body weight traits as breeding program selection criteria due to their great economic importance. The objectives of this study were to evaluate different animal models, estimate genetic parameters, and define the most fitting model for Brahman cattle body weight standardized at 120 (BW120), 210 (BW210), 365 (BW365), 450 (BW450), and 550 (BW550) days of age. To estimate genetic parameters, single-, two-, and multi-trait analyses were performed using the animal model. The likelihood ratio test was verified between all models. For BW120 and BW210, additive direct genetic, maternal genetic, maternal permanent environment, and residual effects were considered, while for BW365 and BW450, additive direct genetic, maternal genetic, and residual effects were considered. Finally, for BW550, additive direct genetic and residual effects were considered. Estimates of direct heritability for BW120 were similar in all analyses; however, for the other traits, multi-trait analysis resulted in higher estimates. The maternal heritability and proportion of maternal permanent environmental variance to total variance were minimal in multi-trait analyses. Genetic, environmental, and phenotypic correlations were of high magnitude between all traits. Multi-trait analyses would aid in the parameter estimation for body weight at older ages because they are usually affected by a lower number of animals with phenotypic information due to culling and mortality.     

Somatic cell score genetic parameter estimates of dairy cattle in Portugal using fractional polynomials

Milk somatic cell count is an indicator trait for mastitis resistance. Genetic parameters for somatic cell score in the Portuguese Holstein-Friesian population were estimated by modeling the pattern of genetic correlation over the first 3 lactations (days in milk) with a random regression model. Data records from the first 3 lactations were from the national database of the Portuguese Holstein Association herds. Heritability estimates ranged from 0.05 at the beginning of the lactation for the 3 lactations, to 0.07 at the end of the lactation period for the first and third lactations, to 0.09 for the second lactation. This increase in the heritability values was due to an increase in the genetic variance and a decrease in the residual variances. Genetic correlations evaluated for monthly time points were high (0.65 to 0.99) for all 3 lactations, whereas phenotypic correlations were much less than the genetic correlations (0.13 to 0.62).     

Genetic variability of Wagyu cattle estimated by statistical approaches

The genetic evaluation of economically important traits utilizes estimates of genetic variability, which are represented by heritability. This review summarizes the published heritabilities of traits estimated in Wagyu cattle. Two different mean heritabilities, unweighted and weighted by standard errors, were calculated. In Japanese Black cattle, the average unweighted and weighted direct heritabilities of birth weight were 0.35 and 0.28, respectively, whereas the respective maternal heritabilities were 0.17 and 0.07. The mean unweighted heritability of calf market weight was estimated to be 0.30 in Japanese Black cattle. The mean unweighted heritability of daily gain during performance testing was 0.29 in Japanese Black and 0.40 in Japanese Shorthorn cattle. In Japanese Black cattle, the unweighted mean heritability was 0.48 for carcass weight, 0.46 for rib‐eye area, 0.38 for rib thickness, 0.39 for subcutaneous fat thickness, and 0.55 for marbling. The mean weighted heritability of the calving interval was low, and estimated to be 0.05. In general, the heritabilities estimated in Wagyu cattle were similar to those estimated in other beef breeds.     

Estimation of variance components for postpartum dysgalactia syndrome in sows

The postpartum dysgalactia syndrome (PDS) represents one of the most important diseases after parturition in sows. The genetic background of the disease has been investigated some time ago and heritability estimates around 0.10 have been obtained. To compute current estimates, a dataset of 1680 sampled sows and their 2001 clinically examined litters was used for variance components estimation with a threshold liability model. Affected sows were defined through clinical examination 12–48 h after parturition. Posterior mean of additive genetic variance was 0.10 and estimated heritability for PDS averaged 0.0879 with a 95% confidence interval of 0.0876 and 0.0881. The results are in agreement with those of other studies and emphasize the importance of considering the genetic predisposition for susceptibility to PDS as well as of additional factors including hygiene and management conditions.     

Estimation of correlation between maternal permanent environmental effects of related dams in beef cattle

Weaning weights from Gelbvieh (GV; n = 82,138) and Limousin (LM; n = 88,639) calves were used to estimate genetic and environmental variance components with models that included different values for the correlation (lambda) between permanent environmental effects of dams and their daughters. Each analysis included fixed discrete effects of contemporary group, sex of calf, age of dam at calving, and month of calving, a fixed continuous effect of age of calf, random direct and maternal additive genetic effects, permanent environmental effects due to dams, and residual effects. The REML procedure was employed with a "grid search," in which the likelihood was computed for a series of values for lambda. For both breeds, models that included a nonzero value for lambda fitted the data significantly better than the model that did not include lambda. The maximum restricted likelihood was obtained for lambda of approximately -0.2 for both breeds. Estimates of residual and direct genetic variances were similar for all values of lambda, including zero; however, estimates of maternal genetic variance and maternal heritability increased slightly, and maternal permanent environmental variance and the proportion of the maternal variance to the total (phenotypic) variance decreased slightly, when the correlated structure for permanent environmental effects was assumed. As the value of lambda became more negative, absolute values of the direct-maternal genetic covariance and direct-maternal correlation estimates were decreased. Pearson and rank correlations for direct genetic, maternal genetic, and maternal environmental effects estimated with and without lambda were very high (>0.99). These results indicated that the linear relationship between maternal permanent environmental effects of dams and their daughters for weaning weight is negative but low in both breeds. Considering this relationship in the operational model did not significantly affect estimated breeding values, and thus, it may not be important in genetic evaluations.     

Genetic parameters for nuclear and nonnuclear inheritance in three synthetic lines of beef cattle differing in mature size.

Genetic parameters for nuclear and cytoplasmic genetic effects were estimated from preweaning growth data collected on three synthetic lines of beef cattle differing in mature size. Lines of small-, medium-, and large-framed calves were represented in each of two research herds (Rhodes and McNay). Variance components were estimated separately by herd and size line for birth weight and 205-d weight (WW) by REML with an animal mode using an average of 847 and 427 calf records from Rhodes and McNay, respectively. Model 1 included effects of fixed year, sex of calf, age of dam, and random additive direct (a), additive maternal genetic (m), covariance (a,m), permanent environment affecting the dam, and residual error. Model 2 differed from Model 1 by including random cytoplasmic lineage effects and by ignoring permanent environmental effects. Model 1--direct (maternal) heritability estimates for birth weight at Rhodes were .62(.03) for small, .67(.06) for medium, and .30(.11) for large lines. Genetic correlations between direct and maternal effects for birth weight were .67, -.16, and .48 for the respective size groups. For WW at Rhodes, direct (maternal) heritability estimates were .30(.29), .30(.14), and .10(.16) for small, medium, and large lines, respectively, with genetic correlations of -.34 (small), -.12 (medium), and .17 (large). Heritability estimates at McNay were similar to those at Rhodes, except that maternal genetic heritabilities for WW were smaller (.10, small; .01, medium; .00, large). Model 2--estimates for nuclear genetic effects were consistent with the estimates from Model 1. Cytoplasmic variance accounted for 0 to 5% of the total random variance in birth weight. For WW, cytoplasmic variance was negligible at Rhodes and accounted for 4% of the total random variance in the large line at McNay, averaging less than the permanent environment. Results failed to indicate that cytoplasmic variance was important for preweaning performance.     

Multivariate analysis of mixed inheritance model of performance traits in layers using Gibbs sampling

The Gibbs sampling under a multitrait animal model was applied to detect the single gene affecting chicken performance traits and their pleiotropic actions as well as to estimate the heritability and correlations for these traits. A total of 14 823 individuals of a Rhode Island Red line (RIR) and 18 653 individuals of a Rhode Island White line (RIW) from six generations under long-term selection were recorded. Five performance traits were studied: initial egg production (IEP; until 38th week), egg production (until 54th week), egg weight at 33rd week (EW), age at first egg (AFE), and body weight at 20th week (BW). An analysis was based on the estimated marginal densities of the following parameters: frequencies, additive and dominance effects and variances and covariances (for single gene) as well as additive genetic and residual variances and respective covariances (for polygenes). An inference concerning the mixed inheritance model is performed by visualising the marginal posterior densities of major gene variance separately for all traits. The pleiotropic effect of single locus is expressed as the single gene correlation coefficient. It shows contributions of single genes to BW (10 and 15% of total variance for A22 and K44, respectively) and EW of K44 (9% of total variance). Moreover, a small positive pleiotropic single locus effect in line K44 was also registered. The polygenic heritability estimates obtained were low, except for EW and BW of both lines. Generally, the correlation estimates were in agreement with results reported in literature.     

Increased litter size in Rambouillet sheep: I. Estimation of genetic parameters.

The variance and covariance components needed to estimate heritabilities of and genetic correlations among litter size, ovulation rate, scrotal circumference, and BW in a flock of Rambouillet sheep were estimated using REML via an expectation-maximization type algorithm. The heritability estimates from univariate analyses were .14, .21, .25, .36, and .15 for litter size, ovulation rate, scrotal circumference, 180-d BW of females, and 180-d BW of males, respectively, and average heritability estimates from bivariate analyses were .19, .20, .20, .34, and .10 for litter size, ovulation rate, scrotal circumference, 180-d BW of females, and 180-d BW of males, respectively. The genetic correlation between litter size and ovulation rate was near unity. Body weight in ewes had a moderate genetic correlation with both litter size (.22) and ovulation rate (.20) and a low residual correlation with both litter size (.03) and ovulation rate (.09). The genetic correlation between BW in rams and scrotal circumference was 0, whereas the residual correlation was .71. The genetic correlations of scrotal circumference with litter size and ovulation rate were -.25 and +.20, respectively.