猪育种中杂种信息利用的研究进展

在猪的商品生产中，主要是利用品种（品系）间的杂交，但是目前大部分选择方法局限于纯种群，只利用了加性遗传方差，而在杂交生产中起重要作用的非加性方差则没有考虑，基于最终的产品是杂种，要获得杂种性能的最大遗传进展，更为合乎逻辑的方法最将纯种和杂种信息结合选择。     

公猪纯种后裔鉴定与杂种后裔鉴定的比较

现在,猪的杂交利用已很广泛,美国商品猪肉中,杂交猪肉已占90％。猪杂交的广泛利用给纯种亲本选择提出了这样的一个问题,即应依据本品种的信息还是应依据其杂种后代信息选择亲本。用纯种内个体选择来有效地改良杂种群体,纯种和杂种间的遗传相关必须是正的,且要求相当大。如果相关不大或者为负,就须用正反交循环选择法,使肉猪群的遗传进展最     

种猪选择的注意事项

1遗传改良遗传上,优秀的种猪用于繁殖是由不同的繁殖效率所致,优秀的种猪留下的后代较多。选择,即利用加性遗传方差,主要应用于猪长期遗传改良。在商品猪生产中,选择重点在于确定种猪供应场。系统进行种猪选配,以产生非加性遗传变化,表现出杂交优势。但杂交优势并非在所有杂交或所有度量的性状均会发生,且其必须每世代通过选配重现。在商品猪     

荷斯坦杂种牛繁殖性能遗传改良效果评估

为评估种公牛对荷斯坦杂种牛繁殖性能的遗传改良效果,以荷黄低代杂种、荷黄高代杂种和纯种荷斯坦牛3种奶牛群体共计293头奶牛为研究材料,利用北美荷斯坦验证种公牛对不同奶牛群体进行杂交改良。根据系谱信息追踪各群体的后裔,统计整理空怀天数(DO)、产后第一次配种天数(DFB)和初产月龄(AFC),用最小二乘法分析群体、世代、配种年份、母本和胎次与繁殖性能的相关性。结果表明,高代杂种和低代杂种的DO显著低于纯种(P005);低代杂种DFB显著低于纯种(P005),高代杂种在数值上有低于纯种的趋势。1世代,高代杂种和低代杂种DFB显著低于纯种(P005);高代杂种AFC显著低于低代杂种(P005),高代杂种在数值上低于纯种。配种年份效应和母本效应显著影响繁殖性能(P005)。高代杂种在现有生产体系下实现最佳的遗传环境匹配,适宜在北方农区生产体系中推广养殖。     

选择对猪杂种生产性能的作用

美国绝大多数商品猪都是用某些杂交繁育方法所生产的猪,即杂交猪。到目前为止,人们把提高杂种生产性能的希望,完全寄托在纯种内部选择的基础上。然而也有理由怀疑提高纯种生产性能是提高杂种生产性能最有效方法的观点。     

山西马身猪与山西黑猪、巴克夏猪、内江猪杂交效果的观察

共用了116头不同组合的杂种和纯种猪来测定各项性能,30头杂种和纯种进行屠体品质测定。山西黑猪、内江猪、巴克夏猪分别与山西本地猪正反交,同时纯种也设平行的对照。日增重方面,除本地♂与巴克夏♀外,其它组合均表现较显著的杂种优势。其中黑本、本黑,巴本的杂种优势极显著。纯种猪中,黑猪的日增重显著地高于巴克夏和本地猪,但稍低于内江猪。父本的比较中,以黑猪的杂交效果为最好。肥育性能的正反交差异均不显著,但反交略优于正交。胴体品质方面,标志产肉能力的胴体长、眼肌面积、屠宰率呈中间遗传;腹内产脂能力的花油、板油呈显性或超显性遗传;皮厚,膘厚呈中间遗传,但不同的杂交组合表现出不同的遗传规律。改良产瘦肉能力的根本手段是选择而不是杂交。     

荷斯坦杂种牛生长性能遗传改良效果评估

为了评估验证荷斯坦种公牛对荷斯坦杂种牛生长性能的遗传改良效果,以荷黄低代杂种、荷黄高代杂种和纯种荷斯坦牛3种群体共计293头奶牛为研究材料,利用北美荷斯坦种公牛对不同奶牛群体进行杂交改良,根据系谱信息追踪各群体的后裔,测定个体初生、2月龄、6月龄、12月龄、14月龄和成年体重,以纯种荷斯坦牛为对照组,用最小二乘法分析群体、世代和母本与生长性能的相关性,评估杂种奶牛生长性能的遗传改良效果。结果表明:高代杂种和低代杂种的初生重显著低于纯种(P0.05);高代杂种和纯种12月龄重、14月龄重、成年体重显著高于低代杂种(P0.05),高代杂种与纯种之间差异不显著(P0.05)。二世代生长性能显著高于一世代和零世代(P0.05),一世代显著高于零世代(P0.05)。群体和世代间互作效应仅对2月龄重有显著影响(P0.05)。母本效应对生长性能无显著影响(P0.05)。本研究提示:高代杂种初生重低、育成期生长发育快,而成年体重与纯种荷斯坦牛无显著差异,在现有生产体系下实现最佳的遗传环境匹配,适宜在北方农区生产体系中推广养殖。     

荷斯坦杂种牛泌乳性能遗传改良效果评估

【目的】评估荷斯坦验证种公牛对荷斯坦杂种牛泌乳性能的遗传改良效果,【方法】以荷黄低代杂种、荷黄高代杂种和纯种荷斯坦牛3种奶牛群体共计293头奶牛为研究材料,利用北美荷斯坦验证种公牛对不同奶牛群体进行杂交改良,根据系谱信息追踪各群体的后裔,参照DHI生产性能测定方法采集产奶量和乳成份数据,用最小二乘法分析群体、世代、投产年份、母本和母本年龄与泌乳性能的相关性。【结果】高代杂种与纯种间产奶量差异不显著(P0.05),高代杂种305d乳脂量,305d乳蛋白量和305d乳糖量显著高于纯种(P0.05);1世代泌乳性能显著高于0世代(P0.05);饲养管理水平和母本效应显著影响泌乳性能(P0.05)。【结论】高代杂种在现有生产体系下实现最佳的遗传环境匹配,适宜在北方农区生产体系中推广养殖。     

湖羊与杂交羊的区别鉴定

湖羊杂交历史长达60余年,目前纯种资源濒临灭绝,几乎被杂种羊取而代之,血缘关系错综复杂。如何识别纯种与杂种,是湖羊保种和杂种资源的开发利用技术工作中遇到的最大难题之一。本文简要介绍从外形特征如何区别鉴定纯种与杂种,以避免指鹿为马的现象发生。     

商品猪生产中的杂交亲本选择

商品肥猪绝大多数都是杂交猪。这是因为通过杂交可以获得杂种优势。杂种优势就是杂交后代在生产性能和生活力方面优于亲本的现象。关于杂种优势，让我们举一个很通俗的例子来加以理解：假如日增重都是700g的两个纯繁品种杂交，其后代的日增重可能达到750g。这高出的50g就是杂交优势，在纯种生产中是不可能得到的。除了日增重外，还有许多性状，特别是遗传力低的性状(如繁殖力)在杂种中表现出更高的杂种优势。要想获得理想的杂种优势，杂交亲本的选择是非常重要的。     

Genetic relationship between purebred and crossbred sow longevity

Background: The overall breeding objective for a nucleus swine selection program is to improve crossbred commercial performance. Most genetic improvement programs are based on an assumed high degree of positive relationship between purebred performance in a nucleus herd and their relatives' crossbred performance in a commercial herd. The objective of this study was to examine the relationship between purebred and crossbred sow longevity performance. Sow longevity was defined as a binary trait with a success occurring if a sow remained in the herd for a certain number of parities and including the cumulative number born alive as a measure of reproductive success. Heritabilities, genetic correlations, and phenotypic correlations were estimated using THRGIBBS1F90.Results: Results indicated little to no genetic correlations between crossbred and purebred reproductive traits.This indicates that selection for longevity or lifetime performance at the nucleus level may not result in improved longevity and lifetime performance at the crossbred level. Early parity performance was highly correlated with lifetime performance indicating that an indicator trait at an early parity could be used to predict lifetime performance. This would allow a sow to have her own record for the selection trait before she has been removed from the herd.Conclusions: Results from this study aid in quantifying the relationship between purebred and crossbred performance and provide information for genetic companies to consider when developing a selection program where the objective is to improve crossbred sow performance. Utilizing crossbred records in a selection program would be the best way to improve crossbred sow productivity.     

Marker-assisted selection for commercial crossbred performance

Several studies have shown that selection of purebreds for increased performance of their crossbred descendants under field conditions is hampered by low genetic correlations between purebred and commercial crossbred (CC) performance. Although this can be addressed by including phenotypic data from CC relatives for selection of purebreds through combined crossbred and purebred selection (CCPS), this also increases rates of inbreeding and requires comprehensive systems for collection of phenotypic data and pedigrees at the CC level. This study shows that both these limitations can be overcome with marker-assisted selection (MAS) by using estimates of the effects of markers on CC performance. To evaluate the potential benefits of CC-MAS, a model to incorporate marker information in selection strategies was developed based on selection index theory, which allows prediction of responses and rates of inbreeding by using standard deterministic selection theory. Assuming a genetic correlation between purebred and CC performance of 0.7 for a breeding program representing a terminal sire line in pigs, CC-MAS was shown to substantially increase rates of response and reduce rates of inbreeding compared with purebred selection and CCPS, with 60 CC half sibs available for each purebred selection candidate. When the accuracy of marker-based EBV was 0.6, CC-MAS resulted in 34 and 10% greater responses in CC performance than purebred selection and CCPS. Corresponding rates of inbreeding were 1.4% per generation for CC-MAS, compared with 2.1% for purebred selection and 3.0% for CCPS. For marker-based EBV with an accuracy of 0.9, CC-MAS resulted in 75 and 43% greater responses than purebred selection and CCPS, and further reduced rates of inbreeding to 1.0% per generation. Selection on marker-based EBV derived from purebred phenotypes resulted in substantially less response in CC performance than in CC-MAS. In conclusion, effective use of MAS requires estimates of the effect on CC performance, and MAS based on such estimates enables more effective selection for CC performance without the need for extensive pedigree recording and while reducing rates of inbreeding.     

Estimation of genetic parameters on test stations using purebred and crossbred progeny of sires of the Bavarian Piétrain

Genetic parameters were estimated for purebred and crossbred progeny of Bavarian Piétrain sires on two test stations. The data set used contained 4276 purebred pigs and 13,980 crossbred pigs recorded between 2000 and 2004. In total 332 sires having purebred and crossbred progeny were available to estimate the genetic correlations between purebred and crossbred performances. Though the genetic correlations between purebred and crossbred pigs are fairly high (0.7–0.9), their performances have to be considered as genetically different traits, because variance components and heritabilities differ substantially. Therefore, purebred and crossbred breeding values of candidates are not identical, and thus result in different rankings. However, due to the high correlations purebred pigs provide a lot of information for estimating the crossbred breeding values of the real selection criterion. The Halothan locus, whose effects have been analyzed in detail, affects both purebred and crossbred parameters. To avoid detrimental effects on the efficiency of the breeding programme, the n-allele could be either eliminated or the genotypes of all test animals should be known. Differences in the variance components between the two test stations have been found and are problematic with respect to the breeding value estimation utilizing the pooled data set. Hence, it should be attempted to further improve the standardization of the performance test on both stations.     

Impact of dominance effects on sow longevity

The purpose of the current study was to estimate variance components, especially dominance genetic variation, for overall leg action, length of productive life and sow stayability until third and fifth parity in the Finnish pig populations. The variance components were estimated in two purebred [Landrace (LR), n = 23 602 and Large White (LW), n =22 984] and crossbred (LR × LW, n = 17 440) data sets. Five different analyses were carried out for all the traits to compare the effect of sows’ inbreeding, common litter environment and parental dominance in the statistical model when determining the genetic correlations of the traits for the two purebred and crossbred populations. Estimated heritabilities for the traits ranged from 0.04 to 0.06. The estimates for the proportion of dominance variance of phenotypic variance (d²) varied between 0.01 and 0.17, and was highest in the crossbred dataset. The genetic correlations of the same traits in purebred and crossbred were all high (>0.75). Based on current results, the effect of dominance should be accounted for in the breeding value estimation of sow longevity, especially when data from crossbred animals are included in the analyses. Because dominance genetic variation for sow longevity exists that variation should be utilized through planned matings in producing sows for commercial production.     

Optimal definition of contemporary groups for crossbred pigs in a joint purebred and crossbred genetic evaluation

In the pig industry, purebred animals are raised in nucleus herds and selected to produce crossbred progeny to perform in commercial environments. Crossbred and purebred performances are different, correlated traits. All purebreds in a pen have their performance assessed together at the end of a performance test. However, only selected crossbreds are removed (based on visual inspection) and measured at different times creating many small contemporary groups (CGs). This may reduce estimated breeding value (EBV) prediction accuracies. Considering this sequential recording of crossbreds, the objective was to investigate the impact of different CG definitions on genetic parameters and EBV prediction accuracy for crossbred traits. Growth rate (G_P) and ultrasound backfat (BF_P) records were available for purebreds. Lifetime growth (G_X) and backfat (BF_X) were recorded on crossbreds. Different CGs were tested: CG_all included farm, sex, birth year, and birth week; CG_week added slaughter week; and CG_day used slaughter day instead of week. Data of 124,709 crossbreds were used. The purebred phenotypes (62,274 animals) included three generations of purebred ancestors of these crossbreds and their CG mates. Variance components for four-trait models with different CG definitions were estimated with average information restricted maximum likelihood. Purebred traits’ variance components remained stable across CG definitions and varied slightly for BF_X. Additive genetic variances (and heritabilities) for G_X fluctuated more: 812 ± 36 (0.28 ± 0.01), 257 ± 15 (0.17 ± 0.01), and 204 ± 13 (0.15 ± 0.01) for CG_all, CG_week, and CG_day, respectively. Age at slaughter (AAS) and hot carcass weight (HCW) adjusted for age were investigated as alternatives for G_X. Both have potential for selection but lower heritabilities compared with G_X: 0.21 ± 0.01 (0.18 ± 0.01), 0.16 ± 0.02 (0.16 + 0.01), and 0.10 ± 0.01 (0.14 ± 0.01) for AAS (HCW) using CG_all, CG_week, and CG_day, respectively. The predictive ability, linear regression (LR) accuracy, bias, and dispersion of crossbred traits in crossbreds favored CG_day, but correlations with unadjusted phenotypes favored CG_all. In purebreds, CG_all showed the best LR accuracy, while showing small relative differences in bias and dispersion. Different CG scenarios showed no relevant impact on BF_X EBV. This study shows that different CG definitions may affect evaluation stability and animal ranking. Results suggest that ignoring slaughter dates in CG is more appropriate for estimating crossbred trait EBV for purebred animals.     

The crossbred sire: experimental results for swine

Experiments aimed at comparing crossbred and purebred boars were reviewed. These experiments showed that crossbred boars matured sexually more quickly than corresponding purebred boars: they exhibited greater testis weight, large ejaculate volume and had better semen quality. Young crossbred boars were more aggressive sexually and achieved a higher conception rate, particularly on first service. Differences between the two types of boars for litter size and weight were generally small and variable in direction. Growth rate, feed efficiency and carcass characteristics of progeny of purebred and crossbred boars were generally similar. In addition, there was little evidence that use of crossbred sires had any effect on variability of pig performance.     

Genetic evaluation combining purebred and crossbred data in a pig breeding scheme

Genetic evaluations using purebred data alone and combined purebred and crossbred information were performed for lean meat percentage in a pig breeding scheme. One purebred (PB) model and 2 crossbred models (CCPS1 and CCPS2) were used in the analyses. Data were obtained from the Selección Batallé S.A. Company (Riudarenes, Spain) and spanned a period of 4 yr (2006 to 2009). The data corresponded to 3 nuclei of purebred populations, Landrace (LD), Duroc (DU), and Pietrain (PI); 1 multiplying farm with animals from a 2-way cross (TB1; DU × LD); and commercial farms with animals from a 3-way cross (TB2; TB1 × PI). Genetic parameters were similar across the models, with the exception of purebred PI. The DU and LD purebreds presented large heritabilities (0.5 to 0.6) for lean meat percentage, whereas the PI purebred showed a lower heritability (approximately 0.1) for the PB model and moderate heritability for the CCPS1 and CCPS2 models (0.2 to 0.3). The mean reliability of the predicted purebred breeding values was clearly increased when the CCPS1 and CCPS2 models were used. Moreover, a reranking of the animals with important changes in the selection decisions was observed in the PI purebred. In a simulation study, the CCPS1 model achieved a greater response to selection than the PB model for the PI purebred. On another hand, between the CCPS1 and CCPS2 models, CCPS1 was slightly superior in terms of predictive ability, exhibiting a greater robustness. These results illustrate the usefulness of using crossbred models to evaluate lean meat percentage in this pig breeding scheme.     

Animal model for genetic evaluation of multibreed data.

Extension of beef cattle genetic evaluation procedures to multibreed data sets is proposed as a way to allow inclusion of crossbred animals into current analyses and to provide comparisons between purebred animals of different breeds. Previous papers dealing with multibreed BLUP have proposed sire or sire-maternal grandsire models. Because current models used in the beef industry are predominantly of the reduced animal model form, models were developed for animal model and reduced animal model mixed-model evaluations that would account for fixed and random additive genetic effects, along with fixed and random nonadditive genetic effects for populations with heterogeneous means and variances.     

Genetic effects on preweaning weight gain of Nelore-Hereford calves according to different models and estimation methods

Additive and nonadditive genetic effects on preweaning weight gain (PWG) of a commercial crossbred population were estimated using different genetic models and estimation methods. The data set consisted of 103,445 records on purebred and crossbred Nelore-Hereford calves raised under pasture conditions on farms located in south, southeast, and middle west Brazilian regions. In addition to breed additive and dominance effects, the models including different epistasis covariables were tested. Models considering joint additive and environment (latitude) by genetic effects interactions were also applied. In a first step, analyses were carried out under animal models. In a second step, preadjusted records were analyzed using ordinary least squares (OLS) and ridge regression (RR). The results reinforced evidence that breed additive and dominance effects are not sufficient to explain the observed variability in preweaning traits of Bos taurus x Bos indicus calves, and that genotype x environment interaction plays an important role in the evaluation of crossbred calves. Data were ill-conditioned to estimate the effects of genotype x environment interactions. Models including these effects presented multicolinearity problems. In this case, RR seemed to be a powerful tool for obtaining more plausible and stable estimates. Estimated prediction error variances and variance inflation factors were drastically reduced, and many effects that were not significant under ordinary least squares became significant under RR. Predictions of PWG based on RR estimates were more acceptable from a biological perspective. In temperate and subtropical regions, calves with intermediate genetic compositions (close to 1/2 Nelore) exhibited greater predicted PWG. In the tropics, predicted PWG increased linearly as genotype got closer to Nelore.     

Prediction of performance of progeny from test station boars.

Data were obtained from 1,954 Duroc and 2,252 Yorkshire purebred and crossbred progeny sired by 34 Duroc and 32 Yorkshire boars, respectively. Boars were purchased from the North Carolina Swine Evaluation Station during August 1983 to December 1988. Boars were selected to represent high and low indexes at the test station. Progeny were raised and tested under conditions similar to commercial pig production at the Tidewater Research Station. For each breed of boar (Duroc and Yorkshire), breed type (purebred and crossbred), and sex (castrates and gilts) of progeny, regression coefficients of progeny traits on each sire trait were computed. Progeny traits were ADG, days to 104.3 kg BW (DAYS), backfat thickness (BF), and feed conversion ratio (FC). Sire traits were ADG, DAYS, BF, FC, and INDEX. Effects of boar test group and progeny test group were included in the models. Averaged over breed type and sex, a 25-unit (1 SD) increase in sire INDEX resulted in 14.5 g more ADG, 3.2 fewer DAYS, .57 mm more BF, and .017 lower FC in Durocs and 5.6 g more ADG, .01 more DAYS, .81 mm less BF, and .083 lower FC in Yorkshires. The low magnitude and variable signs of some regression coefficients suggested that predictions of progeny performance from performance of individual sires at the North Carolina Swine Evaluation Station were not very reliable. Differences between regressions for purebreds and crossbreds implied small correlations between the two breed types. Differences between Durocs and Yorkshires indicated that genetic parameters might not be the same for the two breeds.