Genomic evaluation using SNP‐ and haplotype‐based genomic relationship matrices in a closed line of Duroc pigs

A simulation analysis and real phenotype analysis were performed to evaluate the impact of three different relationship matrices on heritability estimation and prediction accuracy in a closed‐line breeding of Duroc pigs. The numerator relationship matrix (NRM), single nucleotide polymorphism (SNP)‐based genomic relationship matrix (GRM) (G_S), and haplotype‐based GRM (G_H) were applied in this study. We used PorcineSNP60 genotype array data (38 114 SNPs) of 831 Duroc pigs with four selection traits. In both heritability estimation and prediction accuracy, the accuracy depended on the number of animals with records. For heritability estimation, a large difference in the results among three relationship matrices was not shown, but the trend of the estimated heritabilities between GRMs, that is G_S < G_H, was shown in this population. For the accuracy of prediction values in test animals, the accuracies of prediction values obtained by two GRMs were higher than that by the NRM in this population. The accuracies obtained by GRMs using animals with no records were lower than that by the NRM using animals with their performance records, but were close to that by the NRM using animals with full‐sib testing records.     

Selection for feed efficiency does not change the selection for growth and carcass traits in Nellore cattle

The objectives were to conduct a genetic evaluation of residual feed intake (RFI) and residual feed intake adjusted for fat (RFIFat) and to analyse the effect of selection for these traits on growth, carcass and reproductive traits. Data from 945 Nellore bulls in seven feed efficiency tests in a feedlot were analysed. Genetic evaluation was performed using an animal model in which the feed efficiency test and age of the animal at the beginning of the test were considered as a systematic effect. Direct additive genetic and residual effects were considered as random effects. Correlations and genetic gains were estimated by two‐trait analysis between feed efficiency measures (RFI and RFIFat) and other traits. Feed conversion showed low heritability (0.06), but dry matter intake (DMI), average daily gain, RFI, RFIFat, metabolic body weight and scrotal circumference measured at 450 days of age (SC450) showed moderate to high heritability (0.49, 0.28, 0.33, 0.36, 0.38 and 0.80, respectively). Similarly, ribeye area, backfat thickness, rump cap fat thickness, marbling score and subcutaneous fat thickness also had high heritability values (0.46, 0.37, 0.57, 0.51 and 0.47, respectively). Genetic correlations between RFI and SC450 were null, and between RFIFat and SC450 were strongly positive. Genetic and phenotypic correlations of RFI and RFIFat with carcass traits were not different from zero, as correlated responses for carcass traits were also not different from zero. The Nellore selection for feed efficiency by RFI or RFIFat allows the recognition of feed efficient animals, with DMI reduction and without significant changes in growth and carcass traits. However, because of the observed results between RFIFat and SC450, selection of animals should be analysed with caution and a preselection for reproductive traits is necessary to avoid reproductive impairments in the herd.     

动物模型BLUP选择效果的计算机模拟研究

在采用动物模型最佳线性无偏预测(BLUP) 方法对个体育种值进行估计的基础上, 模拟了在一个闭锁群体内连续对单个性状选择10个世代的情形, 并系统地比较了群体规模、公母比例和性状遗传力对选择所获得的遗传进展和群体近交系数变化的影响。结果表明, 扩大育种群规模不仅可以获得更大的持续进展, 同时还可有效缓解近交系数的过快上升; 育种群中公畜比例过低时, 不仅会降低遗传进展, 群体近交系数的上升速度也会加快, 实际中应保证育种群具有一定的规模和适宜的公母比例。对高遗传力性状进行选择时, 可望获得更大的遗传进展, 同时近交系数的上升速度也会快一些。     

闭锁群体BLUP选择下遗传方差和近交系数的变化

采用计算机随机模拟方法模拟了在一个闭锁群体内连续对单个性状进行 1 5个世代选择的情况。选择过程中世代不重叠 ,每个世代的种畜根据动物模型最佳线性无偏预测 (BLUP)法估计的育种值进行选留 ,并在此基础上系统地比较了不同群体规模、公母比例和性状遗传力对群体遗传方差和近交系数变化的影响。结果表明 ,扩大育种群规模、增加公畜比例以及对低遗传力性状进行选择时 ,群体遗传方差降低的速度和近交系数上升的速度会更慢 ,在长期选择时可望获得更大的持续进展和适宜的近交增量     

Muscle fibre traits as additional selection criteria for muscle growth and meat quality in pigs – results of a simulated selection

To estimate the direct and correlated responses in meatiness and meat quality, simulated selection was applied using one‐trait selection and index selection including muscle fibre traits. In a total of 2024 pigs of German Landrace, Large White, Leicoma, and Schwerfurter breeds, carcass composition, meat quality, and fibre characteristics of the M. longissimus lumborum were analysed and genetic parameters were calculated by using REML variance component estimation. Coefficients of heritability ranged from low to moderate (growth traits: h² = 0.22–0.32; meat quality traits: h² = 0.17–0.27; muscle fibre traits: h² = 0.12–0.20). The total fibre number and the frequency of white fibres correlated positively with live weight (r_g = 0.44 and 0.44, respectively) and with loin muscle area (r_g = 0.38 and 0.19, respectively) while the relationships to pH value and drip loss were not as close (r_g = ?0.29–0.19). Selection indices were constructed from live weight and muscle area, from pH value and drip loss, and from muscle structure traits. As expected, simulated selection for live weight or loin muscle area lead to direct positive effects but these were associated with negative effects on meat quality traits (selection intensities: SI = 0.1; 0.5). Using selection for an index from loin area and muscle structure (loin muscle area + total fibre number – frequency of white fibres – frequency of giant fibres) the adverse effect on meat quality was minimized (responses in pH value: ?0.05; ?0.01) or was changed towards desired direction (responses in drip loss: ?0.65%; ?0.26%). The results show that fibre characteristics of pig muscle can be used as selection criteria for simultaneous improvement of carcass composition and meat quality in pigs by including indices developed from performance and fibre traits.     

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.     

Two-stage selection strategies utilizing marker-quantitative trait locus information and individual performance.

Short- and long-term response to marker-assisted selection in two stages was studied using a stochastic simulation of a closed nucleus herd for beef production. First-stage selection was carried out within families based on information at a fully additive quantitative trait locus (QTL). Second-stage selection strategies were based on 1) individual phenotype, 2) individual phenotype precorrected for QTL, 3) a selection index incorporating phenotype and QTL information, 4) a standard animal model BLUP, and 5) a selection index incorporating marker-QTL information and standard animal model BLUP on records precorrected for QTL. All strategies were efficient in moving the favorable allele at the QTL to fixation, but they differed in the time to reach fixation. Mass selection was less efficient in changing allele frequencies than BLUP. Discounted accumulated response, accounting for the time response was realized and inflation rate, was proposed to rank strategies and to elude the conflict between short- and long-term response in marker-assisted selection. Discounted accumulated response at a time horizon of 20 yr for alternative two-stage selection strategies was compared with conventional BLUP carried out in second stage only. Within-family selection increased discounted accumulated response by more than 11% using Strategy 4 and by up to 12% using Strategy 5 at an inflation rate of 2%. The percentage increase in response was less for highly heritable traits and when the proportion of additive variance explained by the QTL was small. Strategy 5 gave larger response with reduced inbreeding. This strategy also resulted in the lowest cost-benefit ratio, requiring less genotyping per unit of response. Cost-benefit ratio for discounted genotyping and for discounted in vitro production of embryos for traits with low heritability was two to four times that for traits with high heritability. The use of first-stage selection slightly increased the level of inbreeding for both mass (Strategy 1) and BLUP selection (Strategies 4 and 5).     

Theoretical efficiency of multiple-trait quantitative trait loci-assisted selection

The effectiveness of five selection methods for genetic improvement of net merit comprising trait 1 of low heritability (h² = 0.1) and trait 2 of high heritability (h² = 0.4) was examined: (i) two‐trait quantitative trait loci (QTL)‐assisted selection; (ii) partial QTL‐assisted selection based on trait 1; (iii) partial QTL‐assisted selection based on trait 2; (iv) QTL‐only selection; and (v) conventional selection index without QTL information. These selection methods were compared under 72 scenarios with different combinations of the relative economic weights, the genetic correlations between traits, the ratio of QTL variance to total genetic variance of the trait, and the ratio of genetic variances between traits. The results suggest that the detection of QTL for multiple‐trait QTL‐assisted selection is more important when the index traits are negatively correlated than when they are positively correlated. In contrast to literature reports that single‐trait marker‐assisted selection (MAS) is the most efficient for low heritability traits, this study found that the identified QTL of the low heritability trait contributed negligibly to total response in net merit. This is because multiple‐trait QTL‐assisted selection is designed to maximize total net merit rather than the genetic response of the individual index trait as in the case of single‐trait MAS. Therefore, it is not economical to identify the QTL of the low heritability traits for the improvement of total net merit. The efficient, cost‐effective selection strategy is to identify the QTL of the moderate or high heritability traits of the QTL‐assisted selection index to facilitate total economic returns. Detection of the QTL of the low h² traits for the QTL‐assisted index selection is justified when the low h² traits have high negative genetic correlation with the other index traits and/or when both economic weights and genetic variances of the low h² traits are larger as compared to the other index traits of higher h². This study deals with theoretical efficiency of QTL‐assisted selection, but the same principle applies to SNP‐based genomic selection when the proportion of the genetic variance ‘explained by the identified QTLs’ in this study is replaced by ‘explained by SNPs’.     

Selection for placental efficiency in swine: genetic parameters and trends

The objectives of this study were to estimate response to divergent selection for an index of placental efficiency in swine, and to evaluate the effect of placental efficiency on litter size. The selection index (SI) included total born (TB), birth weight (BRWT), and placental weight (PW), and was designed to increase in the high line (H) or decrease in the low line (L) the efficiency of the placental function (PE), defined as the ratio BRWT:PW. (Co)variance components were estimated for direct and maternal additive effects by using an animal model with MTDFREML procedures. Estimated breeding values were calculated by using records on individual BRWT (n = 2,111), PW (n = 2,006), PE (n = 1,677), and SI (n = 1,677). Litter traits were evaluated using records on 193 litters. The model included the fixed effects of contemporary group for all traits, with the addition of sex for individual traits and parity for litter traits. Litter was fitted as an uncorrelated random effect for all traits, and TB was used as a linear and quadratic covariate for BRWT, PW, and PE. Direct heritability estimates from single-trait models were 0.03, 0.25, 0.18, 0.11, and 0.08 for BRWT, PW, PE, SI, and TB, respectively. Estimated breeding values were compared between lines by using a model including generation, line within generation, and replicate within line as the error term. Estimates of genetic divergence were 20.7 +/- 2.7 g, 0.24 +/- 0.03, 0.11 +/- 0.02, and 0.07 +/- 0.02 per generation for PW, PE, SI, and TB, respectively (P < 0.01), but divergence was not significant for BRWT. At Generation 4, direct EBV was higher in L than in H for PW (55.9 +/- 8.7 vs. -24.2 +/- 9.5 g, respectively; P < 0.01) and higher in H than in L for PE (0.58 +/- 0.10 vs. -0.35 +/- 0.09 g, respectively; P < 0.01). However, EBV was not different for BRWT, SI, or TB. These results indicate that PW and PE are susceptible to change by genetic selection; however, the correlated response in TB was an unexpected genetic trend toward a higher TB in L of 0.05 +/- 0.01 piglets per generation (P < 0.01).     

Herd-of-origin effect on the post-weaning performance of centrally tested Nellore beef cattle

The objective of a performance test station is to evaluate the performance of potential breeding bulls earlier in order to decrease the generation interval and increase genetic gain as well. This study evaluates the herd-of-origin influence on end-of-test weight (ETW), average daily weight gain during testing (ADG), average daily weight gain during the adjustment period (ADG_adj), rib eye area (REA), marbling (MARB), subcutaneous fat thickness (SFT), conformation (C), early finishing (EF), muscling (M), navel (N) and temperament (T) scores, and scrotal circumference (SC) of Nellore cattle that underwent a performance test. We evaluated 664 animals that participated in the performance tests conducted at the Center for Performance CRV Lagoa between 2007 and 2012. Components of variance for each trait were estimated by an animal model (model 1), using the restricted maximum likelihood method. An alternative animal model (model 2) included, in addition to the fixed effects present in S1, the non-correlated random effect of herd-year (HY). A significant HY effect was observed on ETW, REA, SFT, ADG_adj, C, and C_w (p?相似文献   

Influence of model specifications on the reliabilities of genomic prediction in a Swedish-Finnish red breed cattle population

Using a combined multi‐breed reference population, this study explored the influence of model specification and the effect of including a polygenic effect on the reliability of genomic breeding values (DGV and GEBV). The combined reference population consisted of 2986 Swedish Red Breed (SRB) and Finnish Ayrshire (FAY) dairy cattle. Bayesian methodology (common prior and mixture models with different prior distribution settings for the marker effects) as well as a best linear unbiased prediction with a genomic relationship matrix [genomic best linear unbiased predictor (GBLUP)] was used in the prediction of DGV. Mixture models including a polygenic effect were used to predict GEBV. In total, five traits with low, high and medium heritability were analysed. For the models using a mixture prior distribution, reliabilities of DGV tended to decrease with an increasing proportion of markers with small effects. The influence of the inclusion of a polygenic effect on the reliability of DGV varied across traits and model specifications. Average correlation between DGV with the Mendelian sampling term, across traits, was highest (R² = 0.25) for the GBLUP model and decreased with increasing proportion of markers with large effects. Reliabilities increased when DGV and parent average information were combined in an index. The GBLUP model with the largest gain across traits in the reliability of the index achieved the highest DGV mean reliability. However, the polygenic models showed to be less biased and more consistent in the estimation of DGV regardless of the model specifications compared with the mixture models without the polygenic effect.     

Persistency of accuracy of genomic breeding values for different simulated pig breeding programs in developing countries

Genetic improvement of pigs in tropical developing countries has focused on imported exotic populations which have been subjected to intensive selection with attendant high population‐wide linkage disequilibrium (LD). Presently, indigenous pig population with limited selection and low LD are being considered for improvement. Given that the infrastructure for genetic improvement using the conventional BLUP selection methods are lacking, a genome‐wide selection (GS) program was proposed for developing countries. A simulation study was conducted to evaluate the option of using 60 K SNP panel and observed amount of LD in the exotic and indigenous pig populations. Several scenarios were evaluated including different size and structure of training and validation populations, different selection methods and long‐term accuracy of GS in different population/breeding structures and traits. The training set included previously selected exotic population, unselected indigenous population and their crossbreds. Traits studied included number born alive (NBA), average daily gain (ADG) and back fat thickness (BFT). The ridge regression method was used to train the prediction model. The results showed that accuracies of genomic breeding values (GBVs) in the range of 0.30 (NBA) to 0.86 (BFT) in the validation population are expected if high density marker panels are utilized. The GS method improved accuracy of breeding values better than pedigree‐based approach for traits with low heritability and in young animals with no performance data. Crossbred training population performed better than purebreds when validation was in populations with similar or a different structure as in the training set. Genome‐wide selection holds promise for genetic improvement of pigs in the tropics.     

苏博美利奴羊主要经济性状的遗传参数估计

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

Estimates of phenotypic and genetic parameters for birth weight of Brown Swiss calves in Turkey using an animal model

A study was conducted to assess the influence of genetic and environmental factors on Brown Swiss calf birth weight, and to estimate variance components, genetic parameters, and breeding values. Data were collected on 1,761 Brown Swiss calves born from 1990 to 2005 in the Konuklar State Farm in Turkey. Mean birth weight for all calves was 39.3 ± 0.09 kg. Least squares mean birth weights for male and female Brown Swiss calves were 40.3 ± 0.02 and 39.0 ± 0.02 kg, respectively. Variance components, genetic parameters, and breeding values for birth weight in Brown Swiss calves were estimated by restricted error maximum likelihood (REML)–best linear unbiased prediction(BLUP) procedures using an MTDFREML (multiple trait derivative free restricted maximum likelihood) program employing an animal model. Direct heritability (h _d²), maternal heritability (h _m²), total heritability (h _T²), r _am and c _am estimates were 0.12, 0.09, 0.23, −0.58, and −0.06, respectively. The estimated maternal permanent environmental variance expressed as a proportion of the phenotypic variance (c ²) was 0.05. Breeding values were estimated for the trait and used to evaluate genetic trends across the time period investigated. The genetic trend linear regression was not different from zero. No genetic trend for birth weight was expected, since there had been no direct selection pressure on the trait. Absence of a trend confirms that there was no change due to selection pressure on correlated traits. Genetic and environmental parameter estimates were similar to literature values indicating that effective selection methods used in more developed improvement programs would be effective in Turkey as well.     

Genetic parameters for fertility traits in Nellore bulls

Nellore is the main cattle breed used in Brazil, being the largest commercial herd in the world. Beyond the importance of male reproductive efficiency for farm profit, the use of reproductive techniques, mainly artificial insemination, turns the evaluation of male reproductive traits even more important. Estimation of genetic parameters increases the knowledge on traits variances and allows envisaging the possibility of the inclusion of new traits as selection criterion. Genetic parameters for fifteen traits that can be classified as testicular biometry or physical and morphological semen traits were estimated for a Nellore bull population ranging from 18 to 36 months. Single-trait and bi-trait animal models were used for (co)variance components estimation. The contemporary group was considered as fixed effect and age at measurement as covariable. Scrotal circumference presented heritability of 0.47 ± 0.12. This value is similar to the heritabilities found for all testicular biometry traits (0.34–0.48). Sperm progressive motility, which has a direct effect on bull fertility, presented low heritability (0.07 ± 0.08). Major and total sperm defects presented moderate to high heritabilities (0.49 ± 0.18 and 0.39 ± 0.15, respectively), indicating that great genetic gain can be obtained through selection against sperm defects. High and positive genetic correlations were observed among testicular biometry traits, which also presented favourable genetic correlations with physical and morphological traits of the semen with magnitude ranging from high to low. Scrotal circumference presented moderate to high and favourable genetic correlations with sperm progressive motility, sperm turbulence, major sperm defects and total sperm defects. Thus, the selection for scrotal circumference results in favourable correlated genetic response for semen quality. The results show that the use of scrotal circumference as reference trait for bull fertility is appropriate, since it presents high heritability and favourable genetic correlation with semen quality.     

Bayesian estimates of genetic parameters for metritis, retained placenta, milk fever, and clinical mastitis in Holstein dairy cows via Gibbs sampling

The objective of this study was to estimate heritability and genetic correlations between the liabilities of clinical mastitis (CM), milk fever (MF), metritis (MET), and retained placenta (RP) within the first three lactations of Holstein dairy cows. The records of 57,301 dairy cows from 20 large dairy herds in Iran between January 2005 and June 2009 were analysed with univariate and bivariate threshold animal models, using Gibbs sampling methodology. The final model included the fixed class effects of herd-year, season of calving, parity of dam, the linear covariate effect of age at calving, and the random direct genetic effect of animal. Posterior means of heritability for liabilities in first, second, and third lactations were 0.06, 0.08, and 0.09, respectively, for CM; 0.10, 0.12, and 0.11, respectively, for MF; 0.09, 0.07, and 0.10, respectively, for MET, and 0.07, 0.08, and 0.08, respectively, for RP. Posterior means of genetic correlations between disease liabilities were low or moderate (from −0.01 to 0.26). The results of this study indicated the importance of health traits for considering in the selection index of Iranian Holstein dairy cows.     

Adjusting for heterogeneity of experimental data in genetic evaluation of dry matter intake in dairy cattle

The objectives of the present study were (i) to find the best fitted model for repeatedly measured daily dry matter intake (DMI) data obtained from different herds and experiments across lactations and (ii) to get better estimates of the genetic parameters and better genetic evaluations. After editing, there were 572,512 daily DMI records of 3,495 animals (Holstein cows) from 11 different herds across 13 lactations and the animals were under 110 different nutritional experiments. The fitted model for this data set was a univariate repeated‐measure animal model (called model 1) in which additive genetic and permanent environmental (within and across lactations) effects were fitted as random. Model 1 was fitted as two distinct models (called models 2 and 3) based on alternative fixed effect corrections. For unscaled data, each model (models 2 and 3) was fitted as a homoscedastic (HOM) model first and then as a heteroscedastic (HET) model. Then, data were scaled by multiplying with particular herd‐scaling factors, which were calculated by accounting for heterogeneity of phenotypic within‐herd variances. Models were selected based on cross‐validation and prediction accuracy results. Scaling factors were re‐estimated to determine the effectiveness of accounting for herd heterogeneity. Variance components and respective heritability and repeatability were estimated based on a pedigree‐based relationship matrix. Results indicated that the model fitted for scaled data showed better fit than the models (HOM or HET) fitted for unscaled data. The heritability estimates of the models 2 and 3 fitted for scaled data were 0.30 and 0.08, respectively. The repeatability estimates of the model fitted for scaled data ranged from 0.51 to 0.63. The re‐estimated scaling factor after accounting for heterogeneity of residual variances was close to 1.0, indicating the stabilization of residual variances and herd accounted for most of the heterogeneity. The rank correlation of EBVs between scaled and unscaled data ranged from 0.96 to 0.97.     

Genetic parameter estimates for growth traits in Horro sheep

Variance components and genetic parameters were estimated for growth traits: birth weight (BWT), weaning weight (WWT), 6‐month weight (6MWT) and yearling weight (YWT) in indigenous Ethiopian Horro sheep using the average information REML (AIREML). Four different models: sire model (model 1), direct animal model (model 2), direct and maternal animal model (model 3) and direct–maternal animal model including the covariance between direct and maternal effects (model 4) were used. Bivariate analysis by model 2 was also used to estimate genetic correlation between traits. Estimates of direct heritability obtained from models 1–4, respectively, were for BWT 0.25, 0.27, 0.18 and 0.32; for WWT, 0.16, 0.26, 0.1 and 0.14; for 6MWT 0.18, 0.26, 0.16 and 0.16; and for YWT 0.30, 0.28, 0.23, and 0.31. Maternal heritability estimates of 0.12 and 0.23 for BWT; 0.19 and 0.24 for WWT; 0.09 and 0.09 for 6MWT and 0.08 and 0.14 for YWT were obtained from models 3 and 4, respectively. The correlations between direct and maternal additive genetic effects for BWT, WWT, 6MWT and YWT were –0.64, –0.42, 0.002 and –0.46, respectively. On the other hand, the genetic correlations between BWT and the rest of growth traits (WWT, 6MWT and YWT, respectively) were 0.45, 0.33 and 0.31, whereas correlations between WWT and 6MWT, WWT and YWT and 6MWT and YWT were 0.98, 0.84 and 0.87, respectively. The medium to high direct and maternal heritability estimates obtained for BWT and YWT indicate that in Horro sheep faster genetic improvement through selection is possible for these traits and it should consider both (direct and maternal) h² estimates. However, since the direct‐maternal genetic covariances were found to be negative, caution should be made in making selection decisions. The high genetic correlation among early growth traits imply that genetic improvement in any one of the traits could be made through indirect selection for correlated traits.     

Estimation of heritability for hip dysplasia in German Shepherd Dogs in Finland

The heritability of hip dysplasia in the German Shepherd Dog was estimated by applying the animal model and the Restricted Maximum Likelihood (REML) method to a data‐set which consisted of the hip scores of 10335 dogs. Fixed effects of the model were the month and the year of birth, screening age, the panelist responsible for screening and the origin of the animal's sire. The litter and the breeder had only minor effects on hip joints. Heritability estimates were moderate (0.31–0.35). The moderate heritability, which was found in this study, enables a much better genetic gain in the breeding programme, if proper evaluation methods, such as BLUP animal model, and effective selection is used instead of phenotypic selection.     

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。