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.     

Comparison of models for genetic evaluation of number of inseminations to conception in Danish Holstein cows

Number of inseminations to conception (NINS), an important fertility trait, requires appropriate approaches for genetic evaluation due to its non‐normal distribution and censoring records. In this study, we analyzed NINS in 474 837 Danish Holstein cows at their first lactation by using seven models which deal with the categorical phenotypes and censored records in different manners, further assessed these models with regard to stability, lack of bias and accuracy of prediction. The estimated heritability from four models based on original NINS specified as a linear Gaussian model, categorical threshold model, threshold linear model and survival model were similar (0.031‐0.037). While for the other three models based on the binary response derived from NINS, referred as threshold model (TM), logistic and probit models (LOGM and PROM), the heritability were estimated as 0.027, 0.063 and 0.027, respectively. The model comparison concluded that different models could lead to slightly different sire rankings in terms of breeding values; a more complicated model led to less stability of prediction; the models based on the binary response derived from NINS (TM, LOGM and PROM) had slightly better performances in terms of unbiased and accurate prediction of breeding values.     

Threshold-linear versus linear-linear analysis of birth weight and calving ease using an animal model: I. Variance component estimation.

Birth weight and calving difficulty were analyzed with Bayesian methodology using univariate linear models, a bivariate linear model, a threshold model for calving difficulty, and a joint threshold-linear model using a probit approach. Field data included 26,006 records of Gelbvieh cattle. Simulated populations were generated using parameters estimated from the field data. The Gibbs sampler was used to obtain estimates of the marginal posterior mean and standard deviation of the (co)variance components, heritabilities, and correlations. In the univariate analyses, the posterior mean of direct heritability for calving difficulty was .23 with the threshold model and .18 with the linear model. Maternal heritabilities were .10 and .08, respectively. In the bivariate analysis, posterior means of direct heritability for calving difficulty were .21 and .18 for the bivariate linear-threshold and linear-linear model, respectively. Maternal heritabilities were .09 and .06, respectively. Direct heritability for birth weight was .25 for the univariate model and .26 for bivariate models. Maternal heritability was .05 for the linear-threshold model and the univariate model and .06 for the bivariate linear model. Genetic correlation between direct genetic effects in both traits was .81 for the linear-threshold model and .79 for the bivariate linear. Residual correlation was .35 for the bivariate linear model and .50 for the bivariate linear-threshold. A simulation study confirmed that the posterior mean of the marginal distribution was suitable as a point estimate for univariate threshold and bivariate linear-threshold models.     

Genetic parameters for direct and maternal calving ease in Walloon dairy cattle based on linear and threshold models

Calving ease scores from Holstein dairy cattle in the Walloon Region of Belgium were analysed using univariate linear and threshold animal models. Variance components and derived genetic parameters were estimated from a data set including 33 155 calving records. Included in the models were season, herd and sex of calf × age of dam classes × group of calvings interaction as fixed effects, herd × year of calving, maternal permanent environment and animal direct and maternal additive genetic as random effects. Models were fitted with the genetic correlation between direct and maternal additive genetic effects either estimated or constrained to zero. Direct heritability for calving ease was approximately 8% with linear models and approximately 12% with threshold models. Maternal heritabilities were approximately 2 and 4%, respectively. Genetic correlation between direct and maternal additive effects was found to be not significantly different from zero. Models were compared in terms of goodness of fit and predictive ability. Criteria of comparison such as mean squared error, correlation between observed and predicted calving ease scores as well as between estimated breeding values were estimated from 85 118 calving records. The results provided few differences between linear and threshold models even though correlations between estimated breeding values from subsets of data for sires with progeny from linear model were 17 and 23% greater for direct and maternal genetic effects, respectively, than from threshold model. For the purpose of genetic evaluation for calving ease in Walloon Holstein dairy cattle, the linear animal model without covariance between direct and maternal additive effects was found to be the best choice.     

Genetic parameters for calving rate and calf survival from linear, threshold, and logistic models in a multibreed beef cattle population

Generalized mixed linear, threshold, and logistic sire models and Markov chain, Monte Carlo simulation procedures were used to estimate genetic parameters for calving rate and calf survival in a multibreed beef cattle population. Data were obtained from a 5-generation rotational crossbreeding study involving Angus, Brahman, Charolais, and Hereford (1969 to 1995). Gelbvieh and Simmental bulls sired terminal-cross calves from a sample of generation 5 cows. A total of 1,458 cows sired by 158 bulls had a mean calving rate of 78% based on 4,808 calving records. Ninety-one percent of 5,015 calves sired by 260 bulls survived to weaning. Mean heritability estimates and standard deviations for daughter calving rate from posterior distributions were 0.063 +/- 0.024, 0.150 +/- 0.049, and 0.130 +/- 0.047 for linear, threshold, and logistic models, respectively. For calf survival, mean heritability estimates and standard deviations from posterior distributions were 0.049 +/- 0.022, 0.160 +/- 0.058, and 0.190 +/- 0.078 from linear, threshold, and logistic models, respectively. When transformed to an underlying normal scale, linear sire, mixed model, heritability estimates were similar to threshold and logistic sire mixed model estimates. Posterior density distributions of estimated heritabilities from all models were normal. Spearman rank correlations between sire EPD across statistical models were greater than 0.97 for daughter calving rate and for calf survival. Sire EPD had similar ranges across statistical models for daughter calving rate and for calf survival.     

利用广义线性方法定位家畜抗性等级性状的QTL

在广义线性模型的框架内模拟研究了家畜抗性等级性状的QTL定位方法，QTL参数的估计采用最大似然方法，比较了阈模型方法与一般线性方法的QTL定位效率，并对影响等级性状QTL定位效率的主要因素（QTL效应、性状的遗传力）进行了模拟研究。试验为多个家系的女儿设计，资源群体大小为500头。结果表明：在QTL位置参数估计及检验功效方面，阈模型方法具有一定的优势，对抗性等级性状QTL定位的功效也高于线性方法。另外，性状遗传力和QTL效应的大小对QTL定位的准确度也有直接的影响，随着性状遗传力QTL效应的增大，2种方法QTL定位的效率均有不同程度的提高。     

Analysis of prevalence of presumed inherited eye diseases in Entlebucher Mountain Dogs

We analyzed the prevalence of the presumed inherited eye diseases (PIED) noncongenital cataract and progressive retinal atrophy in the Entlebucher Mountain Dog for systematic environmental influences and the additive genetic variation. Multivariate linear animal models using residual maximum likelihood methods and multivariate threshold animal models using Gibbs sampling in Bayesian analyses were used to estimate variance and covariance components. Data were obtained from the kennel club for Swiss Mountain Dog breeds in Germany. PIED were recorded using the standardized protocols of the Dortmunder Kreis, the German panel of the European Eye Scheme for Diagnosis of Inherited Eye Diseases in Animals (DOK). The material included 515 Entlebucher Mountain Dogs from 344 litters at 77 different kennels. Veterinary diagnoses for PIED were from the years 1981-2001. Pedigree information was available for up to nine generations. The multivariate animal model regarded the fixed effects of sex, birth year, experience of the veterinary ophthalmologist, litter size, percentage of examined dogs per litter, inbreeding coefficient and age at examination. The common environment of the litter and the additive genetic effect of the animal were taken into account as randomly distributed effects. The heritability estimates for PIED in the Entlebucher Mountain Dog were h2=0.15+/-0.06 (noncongenital cataract), and h2=0.34+/-0.08 (progressive retinal atrophy) in the linear model and h2=0.32+/-0.05 (noncongenital cataract) and h2=0.59+/-0.03 (progessive retinal atrophy) in the threshold model. The additive genetic correlation between noncongenital cataract and progressive retinal atrophy was moderately positive (r(g)=0.54+/-0.08) in the threshold model. The number of examinations performed by the veterinary ophthalmologists was associated with slightly higher heritabilities for noncongenital cataract and considerably higher heritabilities for progressive retinal atrophy. The investigated PIED in the Entlebucher Mountain Dog are genetically influenced and the size of the genetic parameters estimated may be sensitive to the accuracy of the diagnosis and how the data were collected.     

Comparison of repeatability and multiple trait threshold models for litter size in sheep using observed and simulated data in Bayesian analyses

Bayesian analyses were used to estimate genetic parameters on 5580 records of litter size in the first four parities from 1758 Mule ewes. To examine the appropriateness of fitting repeatability (RM) or multiple trait threshold models (MTM) to litter size of different parities, both models were used to estimate genetic parameters on the observed data and were thereafter compared in a simulation study. Posterior means of the heritabilities of litter size in different parities using a MTM ranged from 0.12 to 0.18 and were higher than the heritability based on the RM (0.08). Posterior means of the genetic correlations between litter sizes of different parities were positive and ranged from 0.24 to 0.71. Data sets were simulated based on the same pedigree structure and genetic parameters of the Mule ewe population obtained from both models. The simulation showed that the relative loss in accuracy and increase in mean squared error (MSE) was substantially higher when using the RM, given that the parameters estimated from the observed data using the opposite model are the true parameters. In contrast, Bayesian information criterion (BIC) selected the RM as most appropriate model given the data because of substantial penalty for the higher number of parameters to be estimated in the MTM model. In conclusion, when the relative change in accuracy and MSE is of main interest for estimation of breeding values of litter size of different parities, the MTM is recommended for the given population. When reduction in risk of using the wrong model is the main aim, the BIC suggest that the RM is the most appropriate model.     

Comparison of estimates of hip dysplasia genetic parameters in Estrela Mountain Dog using linear and threshold models

Genetic parameters, breeding values, and genetic trends of hip dysplasia in Estrela Mountain Dogs were estimated using a linear model (LM) and a threshold model (TM). A database with 313 animals was used. Right and left hip joints were individually scored, according to the Fédération Cynologic Internationale grading rules of the canine hip dysplasia system, as normal (1), borderline (2), slight (3), moderate (4), and severe (5 and 6). The estimate of repeatability was lower in LM (0.86) than in TM (0.90). The same tendency was verified with the heritability because its estimate in LM was 0.38 and in TM was 0.43. However, these results did not establish any statistical differences between the models. The genetic trend of canine hip dysplasia for LM and TM showed a similarity in shape, but considerable individual differences were found in the EBV ranking lists. Therefore, the selection of breeding animals would not be the same with the 2 methodologies. To select the best method for genetic evaluation of hip dysplasia, further studies using more data and other dog breeds are required.     

Reduced-rank estimation of genetic parameters for egg production traits and cluster analyses with predicted breeding values

The aims of this study were to compare the suitability of the multi-trait (MUT) model to estimate genetic parameters with that of 13 reduced-rank principal component models (PC1 to PC13), and then to explore the additive genetic patterns of the breeding values obtained from these using clustering analyses of egg production traits. A total of 1,212 records were used to estimate genetic parameters using the MUT and PC models. The PC4 model was the best representation of the data since it had a lower AIC value and was more parsimonious than the MUT model. The estimated heritability of the age at the first egg (AFE) trait from this model was 0.28?±?0.06, and the estimated genetic correlation between AFE and total egg production (TP) was ?0.52?±?0.23. Potentially animals from cluster 2 are more likely to be in the selected group to help improve the egg production.     

Genetic parameters for racing records in trotters using linear and generalized linear models

Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success.     

基于系谱和基因组信息估计荷斯坦青年母牛体重性状遗传参数

旨在设计利用不同信息来源的模型估计荷斯坦后备牛不同月龄体重性状的遗传参数。本研究于2014—2020年测定并收集了7 122头荷斯坦牛32 338条0～12月龄体重数据,分别利用系谱信息(linear mixed model with pedigree relationship matrix, LM＿A)和系谱-基因组信息构建亲缘关系矩阵(linear mixed model with genotype-pedigree joint relationship matrix, LM＿H),基于母体效应动物模型估计初生重,基于是否考虑初生重作为协变量的单性状动物模型估计2～12月龄各月龄体重遗传力,并利用双性状动物模型估计初生重与其它月龄体重的遗传相关。结果显示,对于初生重,根据赤池信息量准则(Akaike information criterion, AIC),LM＿H方法的拟合程度显著优于LM＿A方法,但两种方法估计的遗传参数相差不大：直接遗传力分别为0.30和0.32,母体遗传力分别为0.08和0.09,个体直接遗传效应和母体遗传效应遗传相关系数分别为-0.65和-0.64;对于2～...     

Genetic analyses of elbow and hip dysplasia in the German shepherd dog

Results from radiographic screening for canine hip dysplasia (CHD) and elbow dysplasia (CED) of 48 367 German shepherd dogs born in 2001–07 were used for the population genetic analyses. Available information included CHD scores for 47 730 dogs, CED scores for 28 011 dogs and detailed veterinary diagnoses of primary ED lesions for a subsample of 18 899 dogs. Quasi‐continuous traits were CHD, CED and cases of CED without radiographically visible primary lesion (CED‐ARTH). Binary coding was used for fragmented medial coronoid process of the ulna (FCP), borderline findings and mild to severe signs of dysplasia in hip and elbow joints. Genetic parameters were estimated in univariate threshold and multivariate linear and mixed linear‐threshold models using Gibbs sampling. Correlations between univariately predicted breeding values (BV) indicated genetic differences between borderline and affected disease status for both CHD (r_BV = 0.5) and CED (r_BV = 0.3). Multivariate genetic analyses with separate consideration of borderline findings revealed moderate heritabilities of 0.2–0.3 for the quasi‐continuous traits with positive additive genetic correlation of 0.3 between CHD and both CED and CED‐ARTH. For FCP, heritability of 0.6 and additive genetic correlations of +0.1 to CHD and ?0.1 to CED‐ARTH were estimated. Results supported the relevant genetic determination of CHD and CED, argued for both diseases against interpretation of borderline findings as healthy and implied genetic heterogeneity of CED. Accordingly, future breeding strategies to reduce the prevalences of CHD and CED in the German shepherd dog should be most efficient when based on BV from multivariate genetic evaluation for CHD, CED‐ARTH and FCP with use of the whole scale of categories for classification of CHD and CED.     

快速型黄羽肉鸡饲料利用效率性状的基因组选择研究

旨在探究快速型黄羽肉鸡饲料利用效率性状的遗传参数,评估不同方法所得估计育种值的准确性。本研究以自主培育的快速型黄羽肉鸡E系1 923个个体（其中公鸡1 199只,母鸡724只）为研究素材,采用"京芯一号"鸡55K SNP芯片进行基因分型。分别利用传统最佳线性无偏预测（BLUP）、基因组最佳线性无偏预测（GBLUP）和一步法（SSGBLUP）3种方法,基于加性效应模型进行遗传参数估计,通过10倍交叉验证比较3种方法所得估计育种值的准确性。研究性状包括4个生长性状和4个饲料利用效率性状：42日龄体重（BW42D）、56日龄体重（BW56D）、日均增重（ADG）、日均采食量（ADFI）和饲料转化率（FCR）、剩余采食量（RFI）、剩余增长体重（RG）、剩余采食和增长体重（RIG）。结果显示,4个饲料利用效率性状均为低遗传力（0.08~0.20）,其他生长性状为中等偏低遗传力（0.11~0.35）;4个饲料利用效率性状间均为高度遗传相关,RFI、RIG与ADFI间为中度遗传相关,RFI与ADG间无显著相关性,RIG与ADG间为低度遗传相关。本研究在获得SSGBLUP方法的最佳基因型和系谱矩阵权重比基础上,比较8个性状的估计育种值准确性,SSGBLUP方法获得的准确性分别比传统BLUP和GBLUP方法提高3.85%~14.43%和5.21%~17.89%。综上,以RIG为选择指标能够在降低日均采食量的同时保持日均增重,比RFI更适合快速型黄羽肉鸡的选育目标;采用最佳权重比进行SSGBLUP分析,对目标性状估计育种值的预测性能最优,建议作为快速型黄羽肉鸡基因组选择方法。     

Investigating pig survival in different production phases using genomic models

Pig survival is an economically important trait with relevant social welfare implications, thus standing out as an important selection criterion for the current pig farming system. We aimed to estimate (co)variance components for survival in different production phases in a crossbred pig population as well as to investigate the benefit of including genomic information through single-step genomic best linear unbiased prediction (ssGBLUP) on the prediction accuracy of survival traits compared with results from traditional BLUP. Individual survival records on, at most, 64,894 crossbred piglets were evaluated under two multi-trait threshold models. The first model included farrowing, lactation, and combined postweaning survival, whereas the second model included nursery and finishing survival. Direct and maternal breeding values were estimated using BLUP and ssGBLUP methods. Furthermore, prediction accuracy, bias, and dispersion were accessed using the linear regression validation method. Direct heritability estimates for survival in all studied phases were low (from 0.02 to 0.08). Survival in preweaning phases (farrowing and lactation) was controlled by the dam and piglet additive genetic effects, although the maternal side was more important. Postweaning phases (nursery, finishing, and the combination of both) showed the same or higher direct heritabilities compared with preweaning phases. The genetic correlations between survival traits within preweaning and postweaning phases were favorable and strong, but correlations between preweaning and postweaning phases were moderate. The prediction accuracy of survival traits was low, although it increased by including genomic information through ssGBLUP compared with the prediction accuracy from BLUP. Direct and maternal breeding values were similarly accurate with BLUP, but direct breeding values benefited more from genomic information. Overall, a slight increase in bias was observed when genomic information was included, whereas dispersion of breeding values was greatly reduced. Combined postweaning survival presented higher direct heritability than in the preweaning phases and the highest prediction accuracy among all evaluated production phases, therefore standing out as a candidate trait for improving survival. Survival is a complex trait with low heritability; however, important genetic gains can still be obtained, especially under a genomic prediction framework.     

Genetic analysis of age at first service, return rate, litter size, and weaning-to-first service interval of gilts and sows

The aim of this study was to estimate genetic parameters of seven traits related to sow reproductive performance. Data on all Norwegian Landrace pigs (NL) born in nucleus herds and raised in nucleus or multiplying herds from 1990 to 2000 were extracted from the Norwegian national recording scheme. Reproductive traits investigated were age at first service (AFS), return rate in gilts (RRg), age at first farrowing (AFF), live-born piglets in the first litter (NBA1), interval from weaning to first service after first litter (WTS1), return rate after first litter (RR1), live-born piglets in the second litter (NBA2), and interval from weaning to first service after second litter (WTS2). After editing, the data set comprised 12,583 to 56,042 records, depending on the trait. A mixed linear and a joint linear threshold animal model were used to estimate (co)variance components. A full Bayesian approach via Gibbs sampling was adopted. The statistical model used for analysis included contemporary groups of herd-year (-season), purebred or crossbred litter, single or double insemination, mating type, parity in which the animal was born, a regression on lactation length, and an additive genetic effect. Neither the estimated heritabilities nor the genetic correlations differed much between the two approaches, but there was a tendency for higher genetic correlations using the joint linear threshold model approach. Average heritabilities were as follows: AFS = 0.31; RRg = 0.03; RR1 = 0.02; NBA1 = 0.12; NBA2 = 0.14; WTS1 = 0.08; and WTS2 = 0.03. The highest genetic correlations were estimated between NBA1 and NBA2 (r(g) = 0.95), RR1 and WTS1 (r(g) = 0.93), and between WTS1 and WTS2 (r(g) = 0.78). The estimated genetic correlation between NBA and WTS were close to zero. Selection for increased NBA will slightly increase AFS and reduce the probability of a return. Selection for decreased AFS will have a favorable effect on WTS intervals; however, selection for decreased AFS seems to have an unfavorable effect on return rate both on gilts and sows. Conversely, selection for decreased WTS intervals will reduce the probability of a return. Potential selection candidates to include in a multivariate fertility index are AFS, NBA, and WTS1. Due to the low heritability and low, but favorable, genetic correlations to NBA and WTS, RR is not recommended as a selection candidate.     

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.     

Comparison of genetic improvement for litter size at birth by direct and indirect selection in swine herd

Responses to selection for number of piglets born alive (NBA) by the total number of piglets born (TNB), the NBA, and the NBA plus number of piglets born dead (NBD) were compared using the accuracy of selection and expected genetic gain calculated from the selection index with family information and the real response to selection, using data generated by Monte Carlo computer simulation. The accuracy of selection for NBA selected by TNB was higher than that by NBA only if the genetic correlation between TNB and NBA was close to 1.0, or the value of heritability for the TNB was much larger than that for the NBA. The accuracy of selection for the NBA selected by the combination of the TNB and the NBA was generally highest in the three selection methods in each family structure. Selection by the TNB resulted in the greatest expected genetic gain for the TNB among the selection methods. In the best linear unbiased prediction (BLUP) selection, the genetic gain for the NBA accumulated by the NBA tended to be similar to that accumulated by the combination of the NBA and the NBD, and both genetic gains at generation 10 were significantly larger than that by the TNB (P < 0.001). The accumulated responses selected by the two‐trait animal model BLUP estimated from genetic parameters with errors were similar to those estimated from the true parameters, and there was no significant difference between them. These results indicate that selection by the NBA or by the NBA and the NBD gives more genetic improvement in the NBA than that by the TNB.     

Direct and maternal (co)variance components, genetic parameters, and annual trends for growth traits of Makooei sheep in Iran

Genetic parameters and genetic trends for birth weight (BW), weaning weight (WW), 6-month weight (6MW), and yearling weight (YW) traits were estimated by using records of 5,634 Makooei lambs, descendants of 289 sires and 1,726 dams, born between 1996 and 2009 at the Makooei sheep breeding station, West Azerbaijan, Iran. The (co)variance components were estimated with different animal models using a restricted maximum likelihood procedure and the most appropriate model for each trait was determined by Akaike’s Information Criterion. Breeding values of animals were predicted with best linear unbiased prediction methodology under multi-trait animal models and genetic trends were estimated by regression mean breeding values on birth year. The most appropriate model for BW was a model including direct and maternal genetic effects, regardless of their covariance. The model for WW and 6MW included direct additive genetic effects. The model for YW included direct genetic effects only. Direct heritabilities based on the best model were estimated 0.15?±?0.04, 0.16?±?0.03, 0.21?±?0.04, and 0.22?±?0.06 for BW, WW, 6MW, and YW, respectively, and maternal heritability obtained 0.08?±?0.02 for BW. Genetic correlations among the traits were positive and varied from 0.28 for BW–YW to 0.66 for BW–WW and phenotypic correlations were generally lower than the genetic correlations. Genetic trends were 8.1?±?2, 67.4?±?5, 38.7?±?4, and 47.6?±?6 g per year for BW, WW, 6MW, and YW, respectively.     

Estimation of genetic parameters for hip dysplasia in Czech Labrador Retrievers

The objective of this study was to estimate the genetic parameters, genetic trends and breeding values using linear model (LM) and threshold model (TM) for the development of hip dysplasia (HD) in Labrador Retrievers in the Czech Republic (n = 3151). The right and left hip joints were evaluated separately using the Fédération Cynologique Internationale scoring system. Four linear and four TMs were tested for the correct estimation of genetic parameters. All the tested models utilized fixed effects of sex, assessor, year of birth, regression of age at evaluation, random direct genetic effects and the effect of the animals' permanent environments. The models differed in the inclusion of the following effects: fixed effects of regression of inbreeding coefficient, random maternal effect and random effect of the maternal permanent environment. Compared to the TM, the LM provided lower coefficients of direct (0.25-0.29 versus 0.26-0.35) and maternal heritability (0.01-0.02 versus 0.03-0.05), repeatability (0.76-0.77 versus 0.78-0.83) and of the correlation between direct and maternal effects (-0.55 to -0.21 versus -0.80 to -0.27). In the tested models, no statistical significance was found for fixed regression of inbreeding coefficients or for the random effect of the permanent maternal environment. In spite of the similarity of the LM and TM results, the TM is recommended as the more suitable model for estimating genetic parameters and subsequent breeding values for HD in Labrador Retrievers in the Czech Republic.