Genetic evaluation of carcass yield using ultrasound measures on young replacement beef cattle

Live weight and ultrasound measures of fat thickness and longissimus muscle area were available on 404 yearling bulls and 514 heifers, and carcass measures of weight, longissimus muscle area, and fat thickness were available on 235 steers. Breeding values were initially estimated for carcass weight, longissimus muscle area, and fat thickness using only steer carcass data. Breeding values were also estimated for weight and ultrasound muscle area and fat thickness using live animal data from bulls and heifers, with traits considered sex-specific. The combination of live animal and carcass data were also used to estimate breeding values in a full animal model. Breeding values from the carcass model were less accurate and distributed more closely around zero than those from the live data model, which could at least partially be explained by differences in relative amounts of data and in phenotypic mean and heritability. Adding live animal data to evaluation models increased the average accuracy of carcass trait breeding values 91, 75, and 51% for carcass weight, longissimus muscle area, and fat thickness, respectively. Rank correlations between breeding values estimated with carcass vs live animal data were low to moderate, ranging from 0.16 to 0.43. Significant rank changes were noted when breeding values for similar traits were estimated exclusively with live animal vs carcass data. Carcass trait breeding values estimated with both live animal and carcass data were most accurate, and rank correlations reflected the relative contribution of carcass data and their live animal indicators. The addition of live animal data to genetic evaluation of carcass traits resulted in the most significant carcass trait breeding value accuracy increases for young replacements that had not yet produced progeny with carcass data.     

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。     

Comparison between genomic predictions using daughter yield deviation and conventional estimated breeding value as response variables

This study compared genomic predictions using conventional estimated breeding values (EBV) and daughter yield deviations (DYD) as response variables based on simulated data. Eight scenarios were simulated in regard to heritability (0.05 and 0.30), number of daughters per sire (30, 100, and unequal numbers with an average of 100 per sire) and numbers of genotyped sires (all or half of sires were genotyped). The simulated genome had a length of 1200 cM with 15,000 equally spaced Single-nucleotide polymorphism (SNP) markers and 500 randomly distributed Quantitative trait locus (QTL). In the simulated scenarios, the EBV approach was as effective as or slightly better than the DYD approach at predicting breeding value, dependent on simulated scenarios and statistical models. Applying a Bayesian common prior model (the same prior distribution of marker effect variance) and a linear mixed model (GBLUP), the EBV and DYD approaches provided similar genomic estimated breeding value (GEBV) reliabilities, except for scenarios with unequal numbers of daughters and half of sires without genotype, for which the EBV approach was superior to the DYD approach (by 1.2 and 2.4%). Using a Bayesian mixture prior model (mixture prior distribution of marker effect variance), the EBV approach resulted in slightly higher reliabilities of GEBV than the DYD approach (by 0.3-3.6% with an average of 1.9%), and more obvious in scenarios with low heritability, small or unequal numbers of daughters, and half of sires without genotype. Moreover, the results showed that the correlation between GEBV and conventional parent average (PA) was lower (corresponding to a relatively larger gain by including PA) when using the DYD approach than when using the EBV approach. Consequently, the two approaches led to similar reliability of an index combining GEBV and PA in most scenarios. These results indicate that EBV can be used as an alternative response variable for genomic prediction.     

Genetic and economic evaluation of Japanese Black (Wagyu) cattle breeding schemes

Deterministic simulation was used to evaluate 10 breeding schemes for genetic gain and profitability and in the context of maximizing returns from investment in Japanese Black cattle breeding. A breeding objective that integrated the cow-calf and feedlot segments was considered. Ten breeding schemes that differed in the records available for use as selection criteria were defined. The schemes ranged from one that used carcass traits currently available to Japanese Black cattle breeders (Scheme 1) to one that also included linear measurements and male and female reproduction traits (Scheme 10). The latter scheme represented the highest level of performance recording. In all breeding schemes, sires were chosen from the proportion selected during the first selection stage (performance testing), modeling a two-stage selection process. The effect on genetic gain and profitability of varying test capacity and number of progeny per sire and of ultrasound scanning of live animals was examined for all breeding schemes. Breeding schemes that selected young bulls during performance testing based on additional individual traits and information on carcass traits from their relatives generated additional genetic gain and profitability. Increasing test capacity resulted in an increase in genetic gain in all schemes. Profitability was optimal in Scheme 2 (a scheme similar to Scheme 1, but selection of young bulls also was based on information on carcass traits from their relatives) to 10 when 900 to 1,000 places were available for performance testing. Similarly, as the number of progeny used in the selection of sires increased, genetic gain first increased sharply and then gradually in all schemes. Profit was optimal across all breeding schemes when sires were selected based on information from 150 to 200 progeny. Additional genetic gain and profitability were generated in each breeding scheme with ultrasound scanning of live animals for carcass traits. Ultrasound scanning of live animals was more important than the addition of any other traits in the selection criteria. These results may be used to provide guidance to Japanese Black cattle breeders.     

Genomic selection in American mink (Neovison vison) using a single-step genomic best linear unbiased prediction model for size and quality traits graded on live mink

Genomic selection relies on single-nucleotide polymorphisms (SNPs), which are often collected using medium-density SNP arrays. In mink, no such array is available; instead, genotyping by sequencing (GBS) can be used to generate marker information. Here, we evaluated the effect of genomic selection for mink using GBS. We compared the estimated breeding values (EBVs) from single-step genomic best linear unbiased prediction (SSGBLUP) models to the EBV from ordinary pedigree-based BLUP models. We analyzed seven size and quality traits from the live grading of brown mink. The phenotype data consisted of ~20,600 records for the seven traits from the mink born between 2013 and 2016. Genotype data included 2,103 mink born between 2010 and 2014, mostly breeding animals. In total, 28,336 SNP markers from 391 scaffolds were available for genomic prediction. The pedigree file included 29,212 mink. The predictive ability was assessed by the correlation (r) between progeny trait deviation (PTD) and EBV, and the regression of PTD on EBV, using 5-fold cross-validation. For each fold, one-fifth of animals born in 2014 formed the validation set. For all traits, the SSGBLUP model resulted in higher accuracies than the BLUP model. The average increase in accuracy was 15% (between 3% for fur clarity and 28% for body weight). For three traits (body weight, silky appearance of the under wool, and guard hair thickness), the difference in r between the two models was significant (P < 0.05). For all traits, the regression slopes of PTD on EBV from SSGBLUP models were closer to 1 than regression slopes from BLUP models, indicating SSGBLUP models resulted in less bias of EBV for selection candidates than the BLUP models. However, the regression coefficients did not differ significantly. In conclusion, the SSGBLUP model is superior to conventional BLUP model in the accurate selection of superior animals, and, thus, it would increase genetic gain in a selective breeding program. In addition, this study shows that GBS data work well in genomic prediction in mink, demonstrating the potential of GBS for genomic selection in livestock species.     

Genetic evaluation of somatic cell score in dairy cattle considering first and later lactations as two different but correlated traits

A test‐day (TD) random regression model (RRM) was described for the genetic evaluation of somatic cell score (SCS) where first and later lactations were considered as two different but correlated traits. A two‐step covariance function procedure was used to estimate variance–covariances and associated genetic parameters. Analysis of estimated breeding values (EBV), ranking of top bulls and cows and some computational aspects were used to compare RRM with TD repeatability model (RPM) and lactation average model (LAM). Residuals were analysed to assess the relative fit of TD models. Comparison between RRM and RPM showed that RRM has lower mean squared error and gave better fit to the data. For young bulls and cows, the standard deviation (SD) of EBVs was highest for RRM and lowest for LAM implying efficient utilization of information on SCS, in terms of revealing more genetic variation. A much lower correlation of EBVs ranging from 0.80 to 0.92 and significant re‐ranking of top bulls and cows were observed between RRM and LAM. The lower across‐lactation correlation between RRM and LAM indicated that LAM is directed to give more weight to first lactation breeding values. The RRM, where SCS in the first and later lactations was considered as two different but correlated traits was able to make effective use of available information on young bulls and cows, and could offer an opportunity to breeders to utilize EBVs for first and later lactations.     

Approaches to the management of inbreeding and relationship in the German Holstein dairy cattle population

The aim of this study was to estimate the current level of inbreeding in the German cow population and for bull dams born in Germany, to find out sires most related to different subsets of their breed and to demonstrate the negative effect of homozygosity in the case of complex vertebral malformation (CVM). Further on, the application of optimum genetic contribution (OGC) theory for the selection of bull dams and bull sires in different breeding scenarios was investigated. Levels of inbreeding for the cow population were in a low range from 0.97% to 1.70% evaluating birth years from 1996 to 1999 in a total dataset of 244,427 registered Holstein cows. The inbreeding coefficient of 8030 bull dams was much higher, i.e. 3.71%, for the birth year 1999. Increases in inbreeding of 0.19% per year indicated an effective population size of only 52 animals. Individual sires like R.O.R.A. Elevation and Hannoverhill Starbuck were highly related to potential bull dams with coefficients of relationship of 13.4% and 12.9%, respectively, whereas P.F. Arlinda Chief (16.3%) and Carlin-M Ivanhoe Bell (16.1%) were highest related to the best available AI sires. Coefficients of relationship were calculated by classes of estimated breeding values (EBV) for production traits showing highest values above 7% in the two highest EBV-classes. The optimum genetic contribution theory using official EBVs and approximative, for zero inbreeding corrected EBVs, was applied for elite matings in a breeding program embracing 30 young bulls per year to find the optimal allocations of bull sires and bull dams. Compared with the actual breeding program applied in practice, OGC-theory has the potential to increase genetic gain under the same constraint for the increase of average relationship by 13.1%. A more relaxed constraint on increase in inbreeding allowed even higher expected genetic gain whereas a more severe constraint resulted in more equal contributions of selected bull sires. Contributions from 21 selected bull sires and 30 selected bull dams for a scenario at 5% constrained relationship were used to develop a specific mating plan to minimise inbreeding in the short term in the following generation applying a simulated annealing algorithm. The expected coefficient of inbreeding of progeny was 66.3% less then the one resulting from random mating. Mating programs can address inbreeding concerns on the farm, at least in the short term, but long-term control of inbreeding in a dairy population requires consideration of relationships between young bulls entering AI progeny test programs. Significantly better EBVs of CVM-free bulls compared with CVM-carriers for the paternal fertility justify the application of OGC for elite matings.     

我国荷斯坦青年公牛基因组选择效果分析

本研究基于我国荷斯坦奶牛基因组遗传评估和生产性能测定（DHI）结果,旨在分析我国荷斯坦公牛基因组选择的效果。选择1 686头既有基因组遗传评估成绩又有后裔测定成绩的荷斯坦公牛,利用2019年12月基因组遗传评估结果及其女儿的产奶和体型性状数据,通过R软件与Excel计算公牛基因组评估结果与公牛女儿表型数据间的相关性,对我国荷斯坦青年公牛基因组选择效果进行分析。相关性分析结果表明,荷斯坦公牛的基因组性能指数（GCPI）与后裔测定性能指数（CPI）呈正相关（r_s>0.3）,其中产奶量和体细胞评分的基因组育种值（GEBV）与估计育种值（EBV）呈较强的正相关（0.4 < r_s < 0.8）。对公牛女儿表型数据分析结果表明,女儿产奶量、乳蛋白率、乳脂率与肢蹄评分的表型值与公牛GEBV分组趋势一致,且公牛不同产奶性状GEBV组间的女儿性状表型值大部分达到极显著差异（P<0.01）;北京及上海地区公牛产奶性状、体细胞评分和肢蹄评分的GEBV分组与女儿表型值趋势较其他省市（地区）更一致,且GEBV高组与低组之间差值均高于其他省市（地区）。基于1 686头荷斯坦公牛基因组选择及其女儿表型数据的分析结果表明,我国荷斯坦公牛的基因组遗传评估准确性较好,其中产奶量、乳蛋白率、体细胞评分和肢蹄评分的表型数据更好地反映了基因组选择的效果;北京及上海地区较其他省市（地区）更能反映我国荷斯坦公牛基因组选择的效果。     

Evaluation of Breeding Value and Selection of Bull Dams in the Danish Dairy Breeds: I. Studies on Realized Efficiency of Bull Dam and Bull Sire Selection

Abstract

The relationship between twice the adjusted daughter yield deviation (DYD) of the son and the average of the estimated breeding values (EBV) of his parents was investigated for milk and fat yield. Deviations from expectations of DYD minus the pedigree index and the regression of DYD on the EBV for each of the parents were estimated. The EBV of each bull dam was calculated in several ways using different combinations of pedigree information and their own records. In all, 1693 bulls (880 Black and White (BW), 418 Red Danish (RD) and 395 Danish Jersey (DJ)) with Direct Updating indices for milk and fat yield were included in the investigation. Mean discrepancies between estimated and observed genetic merit for kg of milk yield were ?348 for BW, ?213 for RD and ?228 for DJ, when all of the bull dams' individual records were utilized in breeding value estimation. The corresponding mean discrepancies for kg of fat yield were ?14.7, ?11.5 and ?11.9, respectively. The discrepancies were positively correlated with the number of lactation records included in the dams' EBVs. Regression coefficients of bull DYDs on bull dam breeding values were significantly lower than expected for RD and BW regardless of the number of individual lactation records included in the dams' indexes for milk and fat yield. For all three breeds, the regression coefficients were lowest for fat yield. The most probable cause of overestimation in bull dam EBVs is preferential treatment, particularly in second and later lactations. To avoid this bias, estimation of a bull dam's breeding value should be based on pedigree information and on records from only her first lactation.     

Growth traits and composition of two- and three-way-cross intact male progeny of Bos taurus and Bos indicus X Bos taurus dams

Feedlot traits, carcass traits and distribution of commercial cuts of crossbred intact male progeny (n = 556) from young and mature Hereford, Red Poll, Hereford X Red Poll, Red Poll X Hereford, Angus X Hereford, Angus X Charolais, Brahman X Hereford and Brahman X Angus dams were evaluated. First-calf heifers were bred to Red Angus bulls; Santa Gertrudis sires were used for each cow's second and third breeding seasons. Calves from these young dams were slaughtered at 13 mo. Calves of mature dams were all sired by Limousin bulls and slaughtered at 12 mo. Dam breed was a major source of variation in most bull traits. Progeny of Brahman-cross dams were inferior (P less than .01) in daily gain, final weight, carcass weight and in edible cuts/day of age compared with progeny from Bos taurus dams. Intact male progeny of Angus X Charolais dams ranked highest in longissimus area, cutability, and edible cuts/day of age. The range of dam breed means in percentage of steak, roast, bone-in cuts (chuck short ribs and back ribs), short plate and thin cuts, and lean trim was just over 1%. Greater variation among dam breeds existed in fat measurements. Analyses in which Hereford-Red Poll diallel data for young dams and mature dams were combined showed positive maternal heterosis for dressing percentage (P less than .05), carcass weight (P less than .05), carcass weight/day of age (P less than .05), estimated carcass fat (P less than .05), fat thickness (P less than .01) and marbling score (P less than .01). Reciprocal effects were inconsequential. Results illustrate the importance of dam breed-type effects in formulating breeding strategies for commercial beef herds.     

National cattle evaluation system for combined analysis of carcass characteristics and indicator traits recorded by using ultrasound in Angus cattle

The objectives were to 1) evaluate genetic relationships of sex-specific indicators of carcass merit obtained by using ultrasound with carcass traits of steers; 2) estimate genetic parameters needed to implement combined analyses of carcass and indicator traits to produce unified national cattle evaluations for LM area, subcutaneous fat depth (SQF), and marbling (MRB), with the ultimate goal of publishing only EPD for the carcass traits; and 3) compare resulting evaluations with previous ones. Four data sets were extracted from the records of the American Angus Association from 33,857 bulls, 33,737 heifers, and 1,805 steers that had measures of intramuscular fat content (IMF), LM area (uLMA), and SQF derived from interpretation of ultrasonic imagery, and BW recorded at the time of scanning. Also used were 38,296 records from steers with MRB, fat depth at the 12th to 13th rib interface (FD), carcass weight, and carcass LM area (cLMA) recorded on slaughter. (Co)variance components were estimated with ASREML by using the same models as used for national cattle evaluations by the American Angus Association. Heritability estimates for carcass measures were 0.45 +/- 0.03, 0.34 +/- 0.02, 0.40 +/- 0.02, and 0.33 +/- 0.02 for MRB, FD, carcass weight, and cLMA, respectively. Genetic correlations of carcass measures from steers with ultrasonic measures from bulls and heifers indicated sex-specific relationships for IMF (0.66 +/- 0.05 vs. 0.52 +/- 0.06) and uLMA (0.63 +/- 0.06 vs. 0.78 +/- 0.05), but not for BW at scanning (0.46 +/- 0.07 vs. 0.40 +/- 0.07) or SQF (0.53 +/- 0.06 vs. 0.55 +/- 0.06). For each trait, estimates of genetic correlations between bulls and heifers measured by using ultrasound were greater than 0.8. Prototype national cattle evaluations were conducted by using the estimated genetic parameters, resulting in some reranking of sires relative to previous analyses. Rank correlations of high-impact sires were 0.91 and 0.84 for the joint analysis of MRB and IMF with previous separate analyses of MRB and IMF, respectively. Corresponding results for FD and SQF were 0.90 and 0.90, and for cLMA and uLMA were 0.79 and 0.89. The unified national cattle evaluation for carcass traits using measurements from slaughtered animals and ultrasonic imagery of seed stock in a combined analysis appropriately weights information from these sources and provides breeders estimates of genetic merit consistent with traits in their breeding objectives on which to base selection decisions.     

Effect of selection and selective genotyping for creation of reference on bias and accuracy of genomic prediction

Reference populations for genomic selection usually involve selected individuals, which may result in biased prediction of estimated genomic breeding values (GEBV). In a simulation study, bias and accuracy of GEBV were explored for various genetic models with individuals selectively genotyped in a typical nucleus breeding program. We compared the performance of three existing methods, that is, Best Linear Unbiased Prediction of breeding values using pedigree‐based relationships (PBLUP), genomic relationships for genotyped animals only (GBLUP) and a Single‐Step approach (SSGBLUP) using both. For a scenario with no‐selection and random mating (RR), prediction was unbiased. However, lower accuracy and bias were observed for scenarios with selection and random mating (SR) or selection and positive assortative mating (SA). As expected, bias disappeared when all individuals were genotyped and used in GBLUP. SSGBLUP showed higher accuracy compared to GBLUP, and bias of prediction was negligible with SR. However, PBLUP and SSGBLUP still showed bias in SA due to high inbreeding. SSGBLUP and PBLUP were unbiased provided that inbreeding was accounted for in the relationship matrices. Selective genotyping based on extreme phenotypic contrasts increased the prediction accuracy, but prediction was biased when using GBLUP. SSGBLUP could correct the biasedness while gaining higher accuracy than GBLUP. In a typical animal breeding program, where it is too expensive to genotype all animals, it would be appropriate to genotype phenotypically contrasting selection candidates and use a Single‐Step approach to obtain accurate and unbiased prediction of GEBV.     

Effect of carcass price fluctuations on genetic and economic evaluation of carcass traits in Japanese Black cattle

The objectives of this study were 1) to investigate the effect of changes in carcass market prices due to bovine spongiform encephalopathy (BSE) occurrences on estimates of genetic parameters and economic weights for carcass traits; and 2) to compare direct and indirect approaches for prediction of genetic merit of Japanese Black cattle for profitability of their progeny. The direct approach utilized estimated breeding values of carcass prices, whereas in the indirect approach, selection indices were constructed as products of economic weights and breeding values of component traits. Data were composed of 80,191 carcass records divided into 5 periods based on changes in carcass prices as a result of occurrences of BSE in Japan and the United States. The periods ranged from a period before occurrence of BSE in Japan to a period of beef import restrictions and a rise in prices. Carcass traits analyzed included HCW, LM area, rib thickness, subcutaneous fat thickness, and marbling score (MS). Price traits included carcass unit price and carcass sale price. Estimates of heritability for price traits were moderate (0.32 to 0.46) and slightly sensitive to changes in carcass market prices. Genetic correlations of HCW and LM area with price traits increased and that between MS and carcass sale price decreased with period, whereas estimates of genetic correlation between MS and carcass unit price were high in all periods (0.96 to 0.98). Economic weights for carcass traits varied with periods because carcass prices were highly sensitive to economic importance of traits. Nevertheless, correlations between within-period breeding values for price traits estimated using direct and indirect approaches were high (0.92 to 0.99). This result indicates that selection realized by direct and indirect approaches will provide very similar results. A comparison among within-approach breeding values estimated in different periods showed that the largest differences in breeding values of sires for price traits were between the periods after occurrences of BSE in Japan and in the United States. Economic effects of BSE occurrences influenced the importance of carcass traits and economic merits of price traits through a change of carcass prices from period to period, irrespective of the approach taken in determining the genetic merit of breeding animals for profitability of their progeny.     

国内外肉牛遗传评估体系概况

种公牛的选育是肉牛育种工作的核心。传统选育肉用种公牛需要经过后裔测定进行选择,其优点是准确性高,但存在周期长、屠宰和肉质性状难以收集、成本高等问题,致其选择效率低。自2001年全基因组选择概念提出后,该技术迅速成为动植物育种领域研究的热点。利用全基因组选择进行肉用种公牛的选育,进行早期选择从而大幅度缩短世代间隔,可以提高繁殖性状等低遗传力性状的选择准确性,加快遗传进展,并大大降低育种成本。2014年,美国安格斯协会开始应用全基因组选择技术,其他欧美发达国家也陆续使用,肉牛育种进入基因组时代。中国自2017年开始使用全基因组选择技术选择青年肉用种公牛,并于2020年在全国范围内使用该技术进行基因组遗传评估。本文综述了国内外肉牛遗传评估现状,以期为我国肉牛育种工作提供参考和借鉴。     

Breeding for veal production in black and white dairy cattle

In 1983 a field trial was conducted to rear progeny of performance tested Black and White bulls with 0–100% Holstein Friesian (HF) genes as veal calves. The purpose was to establish the relationship between performance test traits of sires and veal production traits of their progeny, to estimate genetic parameters for veal production and to study the possibilities of selection for veal production.In total 1060 progeny of 55 performance tested bulls were reared, in a specialised rearing unit, to an average live weight of 208 kg with about 300 kg milk replacer per head. Heritabilities were estimated after correction for month of supply and proportion of HF genes of sires and dams. Heritabilities for weight, type score and price at the start were 0.34, 0.29 and 0.19, respectively. Estimates for daily gain, feed conversion and carcass traits varied between 0.45 and 0.62. The net value of the calves, which was calculated as carcass value minus costs during rearing, showed a heritability of 0.44 and a genetic variation of Dfl. 71.00. This indicates that selection for veal production might be effective.No significant relationship could be detected between the performance test in Black and Whites on a roughage diet, and the progeny test for daily gain and feed conversion on a milk replacer diet. This implies that present methods of performance testing are not effective in improving veal production. Index calculations demonstrated that recording the pedigree on the farm at birth and sampling slaughter data, i.e. carcass weight and score for fleshiness of 50 progeny per sire, may be an effective procedure to obtain a reliable breeding value estimate or sires for veal production.     

Consequences of specialized breeding in the Swedish Warmblood horse population

In many European warmblood studbooks, clear specialization toward either jumping or dressage horses is evident. The Swedish Warmblood (SWB) is also undergoing such specialization, creating a possible need for separate breeding programs and a discipline-specific Young Horse Test (YHT). This study investigated how far specialization of the SWB breed has proceeded and the potential consequences. Individuals in a population of 122,054 SWB horses born between 1980 and 2020 were categorized according to pedigree as jumping (J), dressage (D), allround (AR), or thoroughbred (Th). Data on 8,713 J horses and 6,477 D horses assessed for eight traits in YHT 1999–2020 were used to estimate genetic parameters within and between J and D horses and between different periods. Future scenarios in which young horses are assessed for either jumping or dressage traits at YHT were also analyzed. More than 80% of horses born in 1980–1985 were found to be AR horses, while 92% of horses born in 2016–2020 belonged to a specialized category. The average relationship within J or D category was found to increase during the past decade, whereas the relationship between these categories decreased. Heritability estimates for gait traits were 0.42–0.56 for D horses and 0.25–0.38 for J horses. For jumping traits, heritability estimates were 0.17–0.26 for J horses and 0.10–0.18 for D horses. Genetic correlations between corresponding traits assessed in J and D horses were within the range 0.48–0.81, with a tendency to be lower in the late study period. In the future scenarios, heritability and genetic variance both decreased for traits that were not assessed in all horses, indicating that estimation of breeding value and genetic progress for these traits could be affected by a specialized YHT. However, ranking of sires based on estimated breeding values (EBVs) and accuracy of EBVs was only slightly altered for discipline-specific traits. With continued specialization in SWB, specialization of the YHT should thus be considered.     

Analysis of genotype by environment interaction for milk yield traits in first lactation of Simmental cattle

The breeding goal for Simmental cattle is derived for intensively managed dairy farms. Its suitability for extensive farms was addressed by analysing possible genotype by environment interaction (G × E) between the management levels for first lactation milk yield traits. A first analysis was performed with the data collected from 300 000 purebred daughters of 278 second crop bulls born in Bavaria in 1993 and 1994. The farms were classified by herd‐year‐effect, using the sum of fat and protein yields into two levels of management, either with 33 or 10% quantiles, corresponding to approximately 100 000 cows and 30 000 cows, respectively. The comparison was based on ‘daughter yield’ deviations (DYD). Correlations between DYD of extensive and intensive environments were 0.90, 0.91 and 0.87 for milk, fat and protein yield (kg) for 33% quantiles, respectively. Corresponding correlations for 10% quantiles were 0.85, 0.83 and 0.77. Despite high correlations, 50 out of 149 sires showed significant differences between DYD in different environments. Bulls with higher DYD for milk yield on intensive farms were superior in all environments. For the second analysis extensive and intensive farms in northern and southern Bavaria were chosen at random. Approximately 20 000 cows in each management class were used for the estimation of genetic parameters. In both regions phenotypic and additive‐genetic variances were higher in the intensively managed herds. Likewise heritabilities were higher for fat and protein yield, but not for milk where higher heritabilities were observed in 33% quantiles. Genetic correlations between extensive and intensive environments were 0.97 and above (33% quantiles). Ten per cent quantiles led to lower genetic correlations (0.90–0.95). Although no serious re‐ranking effects of sires were evident, the scale effect and the differences in genetic parameters should be taken into consideration in practical breeding.     

Considering relationships and genetic grouping in mixed model sire evaluation: A simulation study

In sire evaluation using the best linear unbiased prediction (BLUP) method a relationship matrix including only the relationships among sires can be used. The aim of the present study was to show properties of this method when models with or without grouping of sires are applied. The examination consisted of Monte-Carlo simulation of special situations occurring in dairy sire evaluation. Up to 20 repetitions were generated for each data set. Sire effects were equal for all repetitions of a particular set, cow and residual effects being sampled afresh. Thus, in addition to the correlation between true and estimated breeding value, the true standard deviation of estimated breeding value could be calculated from the results of repeated sire evaluation.With respect to these parameters, the results show that models which do not contain sire grouping but include relationships were superior to grouping models even when relationships are considered in addition. This superiority increases with decreasing number of daughters per sire.The hypothesis that a model without sire grouping but including a relationship matrix leads to a bias in the estimation of breeding values when dams of bulls are selected, could not be confirmed. On condition that the frequency of sires which are related to other sires is high, a model including a relationship matrix but without grouping can be recommended.     

Estimation of accuracies and expected genetic change from selection for selection indexes that use multiple‐trait predictions of breeding values

Procedures are described for estimating selection index accuracies for individual animals and expected genetic change from selection for the general case where indexes of EBVs predict an aggregate breeding objective of traits that may or may not have been measured. Index accuracies for the breeding objective are shown to take an important general form, being able to be expressed as the product of the accuracy of the index function of true breeding values and the accuracy with which that function predicts the breeding objective. When the accuracies of the individual EBVs of the index are known, prediction error variances (PEVs) and covariances (PECs) for the EBVs within animal are able to be well approximated, and index accuracies and expected genetic change from selection estimated with high accuracy. The procedures are suited to routine use in estimating index accuracies in genetic evaluation, and for providing important information, without additional modelling, on the directions in which a population will move under selection.     

Using the genomic relationship matrix to predict the accuracy of genomic selection

Estimated breeding values (EBVs) using data from genetic markers can be predicted using a genomic relationship matrix, derived from animal's genotypes, and best linear unbiased prediction. However, if the accuracy of the EBVs is calculated in the usual manner (from the inverse element of the coefficient matrix), it is likely to be overestimated owing to sampling errors in elements of the genomic relationship matrix. We show here that the correct accuracy can be obtained by regressing the relationship matrix towards the pedigree relationship matrix so that it is an unbiased estimate of the relationships at the QTL controlling the trait. This method shows how the accuracy increases as the number of markers used increases because the regression coefficient (of genomic relationship towards pedigree relationship) increases. We also present a deterministic method for predicting the accuracy of such genomic EBVs before data on individual animals are collected. This method estimates the proportion of genetic variance explained by the markers, which is equal to the regression coefficient described above, and the accuracy with which marker effects are estimated. The latter depends on the variance in relationship between pairs of animals, which equals the mean linkage disequilibrium over all pairs of loci. The theory was validated using simulated data and data on fat concentration in the milk of Holstein cattle.