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.     

Prediction of response to marker-assisted and genomic selection using selection index theory

Selection index methods can be used for deterministic assessment of the potential benefit of including marker information in genetic improvement programmes using marker-assisted selection (MAS). By specifying estimates of breeding values derived from marker information (M-EBV) as a correlated trait with heritability equal to 1, it was demonstrated that marker information can be incorporated in standard software for selection index predictions of response and rates of inbreeding, which requires specifying phenotypic traits and their genetic parameters. Path coefficient methods were used to derive genetic and phenotypic correlations between M-EBV and the phenotypic data. Methods were extended to multi-trait selection and to the case when M-EBV are based on high-density marker genotype data, as in genomic selection. Methods were applied to several example scenarios, which confirmed previous results that MAS substantially increases response to selection but also demonstrated that MAS can result in substantial reductions in the rates of inbreeding. Although further validation by stochastic simulation is required, the developed methodology provides an easy means of deterministically evaluating the potential benefits of MAS and to optimize selection strategies with availability of marker data.     

Joint evaluation of purebreds and crossbreds in swine

Data from two purebred swine lines A (n = 6,022) and B (n = 24,170), and their reciprocal, cross C (n = 6,135), were used to examine gains in reliability of combined purebred and crossbred evaluation over conventional within-line evaluations using crossbred and pureline models. Random effects in the pureline model included additive, parental dominance, and litter. In the crossbred model, effects were as in the pureline model except traits of each line were treated as separate traits and two additive effects were present. The approximate model was the same as the pureline except it was used for all lines disregarding breed differences. The traits in the evaluation were lifetime daily gain (LDG) and backfat. When separate line evaluations were replaced by evaluations with crossbreds, mean reliabilities of predicted breeding values increased by 2 to 9% for purebreds and by 21 to 72% for crossbreds. Rank correlations between these breeding values were > 0.99 for purebreds but 0.85 to 0.87 for crossbreds. Rank correlations between predicted breeding values obtained from crossbred and approximate models were 0.98 to 0.99 for purebreds and 0.96 to 0.98 for crossbreds. When the number of crossbreds was small in comparison to purebreds, the increase in reliability by using the crossbred data and the crossbred model as opposed to purebred models was small for purebreds but large for crossbreds. The approximate model provided very similar rankings to the crossbred model for purebreds but rankings were less consistent for crossbreds.     

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.     

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.     

Genetic parameter estimates from joint evaluation of purebreds and crossbreds in swine using the crossbred model.

Records on lifetime daily gain and backfat from two purebred lines A (n = 6,022), B (n = 24,170), and their reciprocal crosses C (n = 6,135) were used to estimate genetic parameters using within-line and terminal-cross models. The models that were fitted included fixed (contemporary group and sex), random additive A and(or) random additive B, random dominance, and random litter effects. Model for purebreds included only one additive effect, whereas the model for crossbreds included two additive effects. End weight was included as a covariable for backfat. Heritability estimates for lifetime daily gain were 0.26, 0.28, and 0.23 with within-line models for lines A, B, and C, respectively, and 0.26, 0.30, and 0.27 with the crossbred model, respectively. Heritability estimates for backfat were 0.52, 0.35, and 0.29 with within-line models for lines A, B, and C, respectively, and 0.51, 0.38, and 0.29 with the crossbred model, respectively. The genetic correlations between purebreds and crossbreds (r(pc)) for lifetime daily gain were 0.99 (A-C) and 0.62 (B-C); for backfat the correlations were 0.32 (A-C) and 0.70 (B-C). The amount of dominance variance from the crossbred model expressed as a proportion of phenotypic variance for lifetime daily gain was 0.39, 0.16, and 0.29 for lines A, B, and C respectively. Dominance variance for backfat was estimated as 0. A joint evaluation of purebreds and crossbreds would be most efficient with the crossbred model. The dominance variation should be accounted for lifetime daily gain.     

Heat stress effects on farrowing rate in sows: genetic parameter estimation using within-line and crossbred models

The pork supply chain values steady and undisturbed piglet production. Fertilization and maintaining gestation in warm and hot climates is a challenge that can be potentially improved by selection. The objective of this study was to estimate 1) genetic variation for farrowing rate of sows in 2 dam lines and their reciprocal cross; 2) genetic variation for farrowing rate heat tolerance, which can be defined as the random regression slope of farrowing rate against increasing temperature at day of insemination, and the genetic correlation between farrowing rate and heat tolerance; 3) genetic correlation between farrowing rate in purebreds and crossbreds; and 4) genetic correlation between heat tolerance in purebreds and crossbreds. The estimates were based on 93,969 first insemination records per cycle from 24,456 sows inseminated between January 2003 and July 2008. These sows originated from a Dutch purebred Yorkshire dam line (D), an International purebred Large White dam line (ILW), and from their reciprocal crosses (RC) raised in Spain and Portugal. Within-line and crossbred models were used for variance component estimation. Heritability estimates for farrowing rate were 0.06, 0.07, and 0.02 using within-line models for D, ILW, and RC, respectively, and 0.07, 0.07, and 0.10 using the crossbred model, respectively. For farrowing rate, purebred-crossbred genetic correlations were 0.57 between D and RC and 0.50 between ILW and RC. When including heat tolerance in the within-line model, heritability estimates for farrowing rate were 0.05, 0.08, and 0.03 for D, ILW, and RC, respectively. Heritability for heat tolerance at 29.3°C was 0.04, 0.02, and 0.05 for D, ILW, and RC, respectively. Genetic correlations between farrowing rate and heat tolerance tended to be negative in crossbreds and ILW-line sows, implying selection for increased levels of production traits, such as growth and reproductive output, is likely to increase environmental sensitivity. This study shows that genetic selection for farrowing rate and heat tolerance is possible. However, when this selection is based solely on purebred information, the expected genetic progress on farrowing rate and heat tolerance in crossbreds (commercial animals) would be inconsequential.     

Genetic correlations between two strains of Durocs and crossbreds from differing production environments for slaughter traits

The aim of this study was to estimate the genetic correlations between 2 purebred Duroc pig populations (P1 and P2) and their terminal crossbreds [C1 = P1 x (Landrace x Large White) and C2 = P2 x (Landrace x Large White)] raised in different production environments. The traits analyzed were backfat (BF), muscle depth (MD), BW at slaughter (WGT), and weight per day of age (WDA). Data sets from P1, P2, C1, and C2 included 26,674, 8,266, 16,806, and 12,350 animals, respectively. Two-trait models (nucleus and commercial crossbreds) for each group included fixed (contemporary group, sex, weight, and age), random additive (animal for P1 and P2 and sire for C1 and C2), random litter, and random dam (C1 and C2 only) effects. Heritability estimates (+/-SE) for BF were 0.46 +/- 0.04, 0.38 +/- 0.02, 0.32 +/- 0.02, and 0.33 +/- 0.02 for P1, P2, C1, and C2, respectively. Heritability estimates for MD were 0.31 +/- 0.01, 0.23 +/- 0.02, 0.19 +/- 0.01, and 0.12 +/- 0.01 for P1, P2, C1, and C2, respectively. The estimates for WGT and WDA were 0.31 +/- 0.01, 0.21 +/- 0.02, 0.16 +/- 0.01, and 0.18 +/- 0.01 and 0.32 +/- 0.01, 0.22 +/- 0.02, 0.16 +/- 0.01, and 0.19 +/- 0.01, respectively. Genetic correlations between purebreds and crossbreds for BF were 0.83 +/- 0.09 (P1 x C1) and 0.89 +/- 0.05 (P2 x C2), for MD 0.78 +/- 0.05 (P1 x C1) and 0.80 +/- 0.08 (P2 x C2). For WGT and WDA, the correlations were 0.53 +/- 0.08 (P1 x C1), 0.80 +/- 0.10 (P2 x C2), and 0.60 +/- 0.07 (P1 x C1) and 0.79 +/- 0.09 (P2 x C2), respectively. (Co)variances in crossbreds were adjusted to a live BW scale. Compared with purebreds, the genetic variances in crossbreds were lower, and the residual variances were greater. Sire variances in crossbreds were approximately 20 to 30% of the animal variances in purebreds for BF and MD but were 13 to 25% for WGT and WDA. The efficiency of purebred selection on crossbreds, assessed by EBV prediction weights, ranged from 0.43 to 0.91 for line 1 and 0.70 to 0.92 for line 2. When nucleus and commercial environments differ substantially, the efficiency of selection varies by line and traits, and selection strategies that include crossbred data from typical production environments may therefore be desirable.     

A comparison of economic performance between high-yielding temperate breeds and zebu-crossbreds on smallholder dairy farms in Southern Malawi with particular focus on reproductive performance

As in other sub-Saharan African countries, purebred dairy genetics such as Holsteins were imported to Malawi. The study investigated their economic performance by comparing them with local Zebu-crossbreds based on 131 smallholder dairy farm observations from Southern Malawi. High-yielding purebred cows and crossbred cows showed no significant differences in lactation yield and calving interval. Looking at the farms’ actual costs, by-products such as maize bran clearly dominated the cost structure for both breeds, but crossbreeds showed significantly lower concentrate costs. While there was no statistically significant difference in income for both breed types, a substantial share (23%) of farms under investigation shows negative incomes. Based on survey data, two typical farms were established representing standard costs with homogenous assumptions such as identical milk price. The comparison of typical farms covering the full dairy system clearly indicated that crossbred dairy cows outperformed purebreds. In addition, a simulation of a shorter calving interval for both typical farms revealed a substantial positive impact on income for both breed types with more than 30% increase. We conclude that focusing on crossbreds in combination with improved feeding and fertility management offers a more promising strategy for smallholder dairy farms in Southern Malawi than just acquiring high-yielding purebreds.     

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.     

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.     

Purebred-crossbred performance and genetic evaluation of postweaning growth and carcass traits in Bos indicus x Bos taurus crosses in Australia

Growth and carcass data on 7,154 cattle from a purebred project and 1,241 cattle from a crossbred project, comprising 916 first-crosses and 325 purebred Brahman controls, were analyzed to estimate genetic parameters, including the genetic correlations between purebred and crossbred performance (rpc). The data also allowed the estimation of sire breed means for various growth and carcass traits. Crossbred calves were produced using 9 Angus, 8 Hereford, 7 Shorthorn, 14 Belmont Red, and 8 Santa Gertrudis sires bred to Brahman dams. These same sires produced 1,568 progeny in a separate purebreeding project. Cattle in both projects were managed under two finishing regimens (pasture and feedlot) to representative market live weights of 400 (domestic), 520 (Korean), and 600 kg (Japanese). The traits studied included live weight at around 400 d of age (400W), hot carcass weight (CWT), retail beef yield percentage (RBY), intramuscular fat percentage (IMF), rump fat depth (P8), and preslaughter ultrasound scanned eye muscle area (SEMA). Estimated breeding values (EBV) of sires from their BREEDPLAN genetic evaluations were used to assess their value in predicting crossbred performance. Regressions of actual crossbred calf performance on sire EBV for each of the traits differed little from their expectation of 0.5. Angus sires produced crossbred carcasses with the highest P8 and lowest RBY but highest IMF. In contrast, crossbred progeny from Belmont Red sires had the lightest 400W and CWT, lowest P8, and highest RBY. Estimates of rpc were 0.48, 0.48, 0.83, 0.95, 1.00, and 0.78 for 400W, CWT, RBY, IMF, P8, and SEMA, respectively. Commercial breeders selecting sires for crossbreeding programs with Brahman females, based on EBV computed from purebred data, might encounter some reranking of sire's performance for weight-related traits, with little expected change in carcass traits.     

The crossbred sire: experimental results for sheep

Crossbreeding of sheep is practiced to exploit simultaneously the use of additive and nonadditive genetic effects. The goal is to achieve optimal levels of performance appropriate for defined systems of sheep production and marketing. Although the beneficial effects of individual and maternal heterosis on sheep production have been well documented and widely implemented, considerably less is known about the effects of paternal heterosis. Limited evidence suggests that crossbred rams are more sexually aggressive and exhibit greater testicular growth than do purebred rams. Average estimates of paternal heterosis effects were 1.4, -.7 and 2.3% for seasonal fertility, prolificacy and preweaning survival, respectively. The average effect of paternal heterosis on fertility during spring breeding was 29.5%. Progeny of crossbred and purebred sires were similar in birth weight, weaning weight and postweaning growth rate and in phenotypic variation for these growth traits. However, favorable paternal heterosis effects need not exist to warrant the use of crossbred sires. Composite or F1 sires can be used as an effective method to manage the composition of additive breed effects. For example, varying proportions of germ plasm from highly prolific breeds such as the Finnsheep and Romanov can be realized through the use of crossbred sires to set reproductive rates at desired levels. Crossbred sires may be used to a greater extent to optimize additive breed effects than to exploit effects of paternal heterosis. The role of composite breeds in managing both additive and nonadditive effects is discussed.     

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是将纯种和杂种信息结合选择     

Variance components and heritabilities for sow productivity traits estimated from purebred versus crossbred sows

Genetic parameters were estimated for number of pigs born alive (NBA), adjusted litter weaning weight (ALWT), and the interval from weaning to first service (W2E) using 2002 purebred litter records and 14 583 crossbred litter records from a swine production unit with a defined great‐grandparent, grandparent, and parent stock genetic system structure. Estimation of (co)variance components was carried out by REML methods. Heritability estimates from this study for NBA were 0.155, 0.146, 0.145 for the purebred, crossbred, and pooled data, respectively. Heritability estimates for ALWT were 0.162, 0.195, and 0.183 for the purebred, crossbred and pooled data, respectively. Heritability estimates for W2E were 0.205, 0.239 and 0.202 for the purebred, crossbred and pooled data, respectively. Genetic correlations between NBA and ALWT were weak and positive for the three groups. The genetic correlation between W2E and ALWT were ?0.158 for the purebred Yorkshires, 0.031 for the crossbreds and 0.051 for the pooled data. The genetic correlation between W2E and NBA was ?0.027 for the purebred Yorkshires, 0.310 for the crossbreds and 0.236 for the pooled data. These similarities suggest that pooling of purebred and crossbred data may be considered, which may potentially increase the accuracy of breeding value estimates, which would result in increased genetic progress.     

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.     

Evaluation of strategies for selection for lean growth rate in pigs

Lean growth rate (LGR) in pigs is a nonlinear biological function of growth rate and lean quantity. According to animal breeding theory, genetic progress for LGR is maximized with selection on a linear index of its component traits, but selection on direct EBV for LGR is also common. In this study, the performance of five criteria for selection on estimated LGR in pigs was evaluated through simulation over five generations: linear indexes of multiple-trait EBV of component traits with or without updating index weights in each generation; a nonlinear index of multiple-trait EBV of component traits; and direct selection on EBV for LGR from a single-trait model or a multiple-trait model that included LGR and component traits. The nonlinear index yielded the highest response in LGR in Generation 5, but the linear index with updating performed almost as well. Not updating weights for the linear index reduced response in LGR by 1.1% in Generation 5 (P < 0.05). Direct selection on single-trait EBV for LGR yielded the lowest responses in Generation 5. Direct selection on EBV for LGR from a multiple-trait animal model yielded a 3.1% greater response in LGR in Generation 5 than direct selection on EBV for LGR based on a single-trait animal model (P < 0.05), but yielded a 1.9% lower response than the nonlinear index. Although differences in response in LGR were limited, alternative selection criteria resulted in substantially different responses in component traits. Linear index selection for LGR placed more emphasis on lean quantity, whereas direct selection for LGR emphasized growth rate. Based on the relative changes in the responses in LGR, selection for estimated LGR based on a nonlinear index or a linear index with updating is recommended for use in the swine industry.     

Breeding programme for Piétrain pigs in Bavaria with an estimation of genetic trends and effective population size

Population structure, performance testing and breeding scheme of the sire breed Piétrain in Bavaria were analyzed as a basis for further optimization studies of the breeding programme. To evaluate the current breeding programme, genetic trends and effective population size were estimated. Four data sets were used which contained breeding animals born between 1981 and 2005, estimated breeding values of traits in the breeding goal, records from young boars in field test and records from purebred and crossbred progeny on test stations. The population is subdivided in many small herds. That has disadvantages with respect to a uniform breeding goal used across herds and with respect to selection intensity and the avoidance of inbreeding. The idealized selection practice consists of three selection stages. On the first two stages information from half and full sibs on test stations is most important so that the risk of co-selecting related animals is increased. The breeding scheme is a mixture of a half sib design and a progeny testing design, but both have disadvantages. Nevertheless, genetic trends are in the desired directions. To improve accuracy and intensity of selection, only AI-boars should be used instead of natural service sires. Though the effective population size is high, the recent trend of inbreeding shows that the extensive use of popular AI-boars can lead to a rapid increase of inbreeding.     

Analysis of the population structure of the Black Forest Draught Horse

Gene contributions of foreign populations as well as coefficients of inbreeding and relationship were evaluated in 699 Black Forest Draught horses of Baden-Württemberg actually registered in the year 2002. Based on nearly complete 5-generation-pedigrees and after taking into account the remaining incompleteness, the mean coefficient of inbreeding for the total population was 6.5%. The recently by incrossing with different breeds newly established lines of stallions showed significantly lower mean coefficients of inbreeding. High rates of inbreeding of about 1.6% in the last five generations could also be faced by incrossing stallions of foreign coldblooded populations what resulted in a decrease of inbreeding in the last generation. In the total population the mean degree of relationship was 16%. The mean degree of relationships within lines of stallions was between 18.3 and 26.8%. The coefficients of relationships between lines of stallions varied between 5.1 and 16.6%. Especially, the newly established lines of stallions showed a lower mean degree of relationships to the other different lines of stallions. The proportion of purebred Black Forest Draught horses in the total population was nearly 70%. Assuming that most animals of unknown origin were purebred, the proportion of purebred Black Forest Draught horses reached about 90%. Austrian Noric, Swiss Freiberg and South German Coldblood stallions were the most important contributors to the Black Forest Draught horse population.     

Potential gain from optimizing multigeneration selection on an identified quantitative trait locus.

The potential extra response that can be obtained from the optimal use of a known QTL in selection by optimizing weights in an index of breeding value for the QTL and polygenic EBV was investigated for a range of parameters. Optimal strategies were derived for a deterministic model of simultaneous selection on a QTL and polygenic effects using optimal control theory. Responses over 10 generations to the following selection strategies were compared: 1) standard QTL selection, with QTL weights equal to 1, 2) optimal QTL selection, 3) stepwise single-generation optimal QTL selection, and 4) non-QTL selection based on phenotype. Cumulative discounted response with discount rates of 10 or 30% per generation were evaluated and used as objective for optimal selection strategies. Optimal selection balanced the conflict between short- and long-term responses and gave greater cumulative discounted response than standard QTL selection of up to 20%, but less than 5% for most cases. Discount rate had limited impact. For a QTL with an additive effect of one polygenic standard deviation, cumulative discounted response from optimal QTL selection was less than 5% greater than response for non-QTL selection for most cases. Exceptions were traits with low heritability and recessive QTL at low frequency, for which extra response was up to 55% greater. Stepwise optimal selection resulted in less cumulative discounted response than standard QTL selection for QTL with negative dominance. The benefit of optimal over stepwise optimal selection was limited (less than 4%) for most cases, except for overdominant QTL. These results indicate that optimizing selection on an identified QTL can result in greater responses to selection but that extra responses tend to be limited for the situations studied here of single-stage purebred selection on a single QTL for a trait observed on both sexes.