Asymptotic rates of response from forest tree breeding strategies using best linear unbiased prediction

 Genetic gain equations are developed for selection on multiple traits using either multi- or univariate best linear unbiased predictors (BLUP) and for selection under controlled and open pollination and polymix mating schemes. The equations assume an infinite population and account for the effects of selection. A comparison with simulated populations under the same mating schemes show that the gain equations predict selection response well, with the predictions having some upward bias. The gain equations are used to compare across mating schemes, to compare univariate to multivariate analyses, and to measure the reduction in the rate of genetic gain due to selection disequilibrium. Results show controlled pollination schemes can offer as much as a 56% advantage in genetic gain relative to open pollination. The reduction in the rate of genetic gain due to selection disequilibrium is approximately 27% under controlled pollination for the breeding goals studied. The results show a limited benefit in using multivariate analyses for predicting breeding values. Received: 20 April 1997 / Accepted: 8 October 1997     

Genome-enabled prediction of meat and carcass traits using Bayesian regression,single-step genomic best linear unbiased prediction and blending methods in Nelore cattle

Several methods have been used for genome-enabled prediction (or genomic selection) of complex traits, for example, multiple regression models describing a target trait with a linear function of a set of genetic markers. Genomic selection studies have been focused mostly on single-trait analyses. However, most profitability traits are genetically correlated, and an increase in prediction accuracy of genomic breeding values for genetically correlated traits is expected when using multiple-trait models. Thus, this study was carried out to assess the accuracy of genomic prediction for carcass and meat quality traits in Nelore cattle, using single- and multiple-trait approaches. The study considered 15 780, 15 784, 15 742 and 526 records of rib eye area (REA, cm²), back fat thickness (BF, mm), rump fat (RF, mm) and Warner–Bratzler shear force (WBSF, kg), respectively, in Nelore cattle, from the Nelore Brazil Breeding Program. Animals were genotyped with a low-density single nucleotide polymorphism (SNP) panel and subsequently imputed to arrays with 54 and 777 k SNPs. Four Bayesian specifications of genomic regression models, namely, Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression; blending methods, BLUP; and single-step genomic best linear unbiased prediction (ssGBLUP) methods were compared in terms of prediction accuracy using a fivefold cross-validation. Estimates of heritability ranged from 0.20 to 0.35 and from 0.21 to 0.46 for RF and WBSF on single- and multiple-trait analyses, respectively. Prediction accuracies for REA, BF, RF and WBSF were all similar using the different specifications of regression models. In addition, this study has shown the impact of genomic information upon genetic evaluations in beef cattle using the multiple-trait model, which was also advantageous compared to the single-trait model because it accounted for the selection process using multiple traits at the same time. The advantage of multi-trait analyses is attributed to the consideration of correlations and genetic influences between the traits, in addition to the non-random association of alleles.     

Evaluation of the best linear unbiased prediction method for breeding values of fruit-quality traits in citrus

Fruit-quality trait improvement is an important objective in citrus breeding; however, fruit breeding programs often accumulate highly unbalanced phenotypic records, which are a serious obstacle in comparing and selecting genotypes. The best linear unbiased prediction (BLUP) method can be used to overcome these difficulties, but few fruit breeding programs have adopted the method, and to our knowledge, the method has not yet been used to predict breeding values of traits based on pedigree information and genetic correlations between traits in citrus. Accordingly, we used the BLUP method to predict the breeding values of nine fruit-quality traits (fruit weight, fruit skin color, fruit surface texture, peelability, flesh color, pulp firmness, segment firmness, sugar content, and acid content) utilizing phenotypic records collected over several years as part of the citrus breeding program conducted at the Kuchinotsu branch of the National Institute of Fruit Tree Science in Japan. Although the accumulated phenotypic records were highly unbalanced, the BLUP method was able to predict the breeding values of all 2122 genotypes (111 parental cultivars and 2011 F₁ offspring from 126 pair-cross families), as well as estimates of several genetic parameters, including narrow-sense heritability and phenotypic and genotypic correlations. These findings demonstrate the utility of the BLUP method in citrus crossbreeding and provide predicted breeding values, which can be used to select superior genotypes in the Kuchinotsu Citrus Breeding Program and related genetic selection endeavors.     

Empirical best linear unbiased prediction in cultivar trials using factor-analytic variance-covariance structures

 Results of multi-environment trials to evaluate new plant cultivars may be displayed in a two-way table of genotypes by environments. Different estimators are available to fill the cells of such tables. It has been shown previously that the predictive accuracy of the simple genotype by environment mean is often lower than that of other estimators, e.g. least-squares estimators based on multiplicative models, such as the additive main effects multiplicative interaction (AMMI) model, or empirical best-linear unbiased predictors (BLUPs) based on a two-way analysis-of-variance (ANOVA) model. This paper proposes a method to obtain BLUPs based on models with multiplicative terms. It is shown by cross-validation using five real data sets (oilseed rape, Brassica napus L.) that the predictive accuracy of BLUPs based on models with multiplicative terms may be better than that of least-squares estimators based on the same models and also better than BLUPs based on ANOVA models. Received: 18 October 1997 / Accepted: 31 March 1998     

Origin and assessment of bruises in beef cattle at slaughter

Studies of bruises, as detected on carcasses at the slaughterhouse, may provide useful information about the traumatic situations the animals endure during the pre-slaughter period. In this paper, we review scientific data on the prevalence, risk factors and estimation of the age of bruises in beef cattle. Risk factors such as animal characteristics, transport conditions, stocking density, livestock auction and handling of the animals are discussed. Investigation of the age of bruises could provide information on when in the meat chain bruises occur and, could help to pinpoint where preventive measures should be taken, from the stage of collecting the animals on the farm until slaughter. We review the methods available to assess the age of the bruises; data on human forensic research are also included. The feasibility to identify traumatic episodes during the pre-slaughter period, in order to improve animal welfare is discussed.     

Bayesian estimates of genetic parameters for pre-conception traits, gestation length and calving interval in beef cattle

A total of 5253 records obtained from 2081 Rubia Gallega beef cows managed using artificial insemination as the only reproduction system were analysed to estimate genetic parameters for days to first insemination (DFI), days from first insemination to conception (FIC), number of inseminations per conception (IN), days open (DO), gestation length (GL) and calving interval (CI) via multitrait Bayesian procedures. Estimates of the mean of posterior distribution of the heritability of DFI, FIC, IN, DO, GL and CI were, respectively, 0.050, 0.078, 0.071, 0.053, 0.037 and 0.085 and the corresponding estimates for repeatability of these traits were 0.116, 0.129, 0.147, 0.138, 0.082 and 0.132, respectively. No significant genetic correlations associated to DFI or GL were found. However, genetic correlations between the other four analysed traits were high and significant. Genetic correlations between FIC and IN, DO and CI were similar and higher than 0.85. Genetic correlations of IN-DO and IN-CI were over 0.65. The highest genetic correlation was estimated for the pair DO-CI (0.992) that can be considered the same trait in genetic terms. Results indicated that DFI can be highly affected by non-genetic factors thus limiting its usefulness to be used as an earlier indicator of reproductive performance in beef cattle. Moreover, GL could not be associated to the reproductive performance of the cow before conception. The other four analysed traits, FIC, IN, DO and CI, have close genetic relationships. The inclusion of IN as an earlier indicator of fertility in beef cattle improvement programs using artificial insemination as the main reproductive system can be advisable due to the low additional recording effort needed.     

Testcross additive and dominance effects in best linear unbiased prediction of maize single-cross performance

Best linear unbiased prediction (BLUP) has been found to be useful in maize (Zea mays L.) breeding. The advantage of including both testcross additive and dominance effects (Intralocus Model) in BLUP, rather than only testcross additive effects (Additive Model), has not been clearly demonstrated. The objective of this study was to compare the usefulness of Intralocus and Additive Models for BLUP of maize single-cross performance. Multilocation data from 1990 to 1995 were obtained from the hybrid testing program of Limagrain Genetics. Grain yield, moisture, stalk lodging, and root lodging of untested single crosses were predicted from (1) the performance of tested single crosses and (2) known genetic relationships among the parental inbreds. Correlations between predicted and observed performance were obtained with a delete-one cross-validation procedure. For the Intralocus Model, the correlations ranged from 0.50 to 0.66 for yield, 0.88 to 0.94 for moisture, 0.47 to 0.69 for stalk lodging, and 0.31 to 0.45 for root lodging. The BLUP procedure was consistently more effective with the Intralocus Model than with the Additive Model. When the Additive Model was used instead of the Intralocus Model, the reductions in the correlation were largest for root lodging (0.06–0.35), smallest for moisture (0.00–0.02), and intermediate for yield (0.02–0.06) and stalk lodging (0.02–0.08). The ratio of dominance variance (v _D) to total genetic variance (v _G) was highest for root lodging (0.47) and lowest for moisture (0.10). The Additive Model may be used if prior information indicates that V_D for a given trait has little contribution to V_G. Otherwise, the continued use of the Intralocus Model for BLUP of single-cross performance is recommended.     

A description of the findings from bull breeding soundness evaluations and their association with pregnancy outcomes in a study of western Canadian beef herds

The primary objectives were to describe beef bulls considered for use and those reported as used in 205 beef herds in western Canada, and to determine whether factors typically assessed during breeding soundness evaluations were associated with reproductive success. More than 100 veterinary clinics reported 2990 breeding soundness evaluations for bulls considered for natural service in client's herds. Differences among clinics explained 5.2% of the variation in scrotal circumference (SC) and 6.9% of the variation in percentage of morphologically normal sperm of all bulls considered for use (after accounting for age, breed, body condition, significant physical abnormalities, month, and year). The percentage of morphologically normal sperm was lower in bulls with an SC ≤34 versus >34 cm (P < 0.006). This study included data from 1384 and 1370 bulls used for breeding in 2001 and 2002, respectively. Most (80%) of the bulls used were Simmental, Black Angus, Charolais, Red Angus, or Hereford, and 80% were ≤4 y of age. Before the breeding season, a veterinarian evaluated 89.5% of all bulls used in these herds. Of the bulls subjected to a breeding soundness evaluation and subsequently used, 93.1% were satisfactory. In 2001 and 2002, injuries were reported in 2.5 and 2.1% of bulls and in 16.6 and 11.4% of herds, and necrobacillosis of the foot was reported in 2.5 and 1.2% of bulls and 11.2 and 6.5% of the herds. The average number of cows exposed to each bull was 26 (both years). Cows exposed to bulls with a smaller SC were less likely to be diagnosed pregnant (P < 0.047) and had a longer median interval from first bull exposure to calving (P < 0.016) than bulls with a larger SC. In conclusion, our findings emphasized the value of breeding soundness evaluations, including measurements of SC, in fertility management of beef cattle.     

Crossbreeding applied to systems of beef cattle production to improve performance traits and carcass quality

Crossbreeding represents an important technique to improve growth, beef quality and adaptability in beef production systems in tropical countries. The aim of this study was to evaluate sire and dam breed effects on performance and carcass traits of crossbred cattle produced in a tropical environment. Heifers and steers were evaluated during the pre-weaning, the post-weaning (n = 173) and the finishing phase (n = 123). Animals were produced by mating Nellore (N_N), Angus × Nellore (A_N) and Caracu × Nellore (C_N) dams with Braford, Charbray and Caracu sires. After weaning, animals were raised grazing on Marandu grass for 12 months; thereafter they were housed in individual pens and finished in a feedlot, receiving a total mixed ration. Ultrasound carcass evaluations were performed to determine ribeye area (R_A), backfat thickness (B_T) and rump fat thickness (R_T). A_N progeny were heavier at birth than N_N (P < 0.05), and Braford progeny had greater birth BW than Caracu (P < 0.05). Greater weaning BW was observed in the A_N and C_N offspring compared to N_N (P < 0.01). Greater average daily gain during the post-weaning period was verified in the N_N progeny compared to C_N (P < 0.05). No dam or sire breed effects were observed for BW at the end of the post-weaning period (P > 0.05). Progeny of N_N cows had greater B_T (P < 0.05) and R_T (P < 0.01) at the end of the post-weaning period in relation to C_N. Greater R_A was observed in the Caracu progeny than in the Braford (P < 0.05), which showed greater R_T than the Charbray progeny at the end of the post-weaning period (P < 0.05). No dam or sire breed effects were verified for final BW at the feedlot or for feed efficiency traits (P > 0.05). A_N progeny were superior in final B_T compared to C_N (P < 0.01), and Braford progeny had greater R_T at the end of finishing than Charbray (P = 0.05). The use of crossbred dams allows an increase in productivity until weaning, but this is not maintained in the post-weaning and finishing periods. The use of Braford sires produces similar growth performance in the different stages of the production system to those seen with Charbray and Caracu sires but generates animals with higher fat thickness at the end of finishing, which may improve carcass quality and commercial value.     

Carriage of four bacterial pathogens by beef cattle in Northern Ireland at time of slaughter

AIMS: To determine the prevalence of four bacterial zoonotic pathogens in beef cattle at time of slaughter in Northern Ireland (NI), in order to assess their potential for reducing beef safety. METHODS AND RESULTS: Faeces were collected postmortem from beef cattle (n =220) at seven EU registered abattoirs. Standard enrichment culturing methods were employed, plus immunomagnetic enrichment in the case of Escherichia coli O157:H7. Campylobacter spp. were found in 52 samples (24.8%), Listeria monocytogenes in 10 (4.8%), E. coli O157:H7 in 2 (0.9%) whilst Salmonella spp. were isolated from six out of 200 samples (3.0%). Five salmonellas were Salmonella Chandans and one was Salmonella Liverpool. CONCLUSIONS: Campylobacter spp. were the most frequently isolated pathogen, despite being relatively rare in beef. Genotyping showed the campylobacters to be very diverse, indicating cattle encounter campylobacters from many sources. The remaining three pathogens, which are associated with meats, occurred at relatively low frequencies, especially E. coli O157:H7. The Salmonella serovars found rarely infect humans. SIGNIFICANCE AND IMPACT OF THE STUDY: The low prevalence of E. coli O157:H7 in NI beef cattle was confirmed and the reasons for this merit further study. The four pathogens should have little impact on beef quality.     

Non-synonymous mutations mapped to chromosome X associated with andrological and growth traits in beef cattle

Background

Previous genome-wide association analyses identified QTL regions in the X chromosome for percentage of normal sperm and scrotal circumference in Brahman and Tropical Composite cattle. These traits are important to be studied because they are indicators of male fertility and are correlated with female sexual precocity and reproductive longevity. The aim was to investigate candidate genes in these regions and to identify putative causative mutations that influence these traits. In addition, we tested the identified mutations for female fertility and growth traits.

Results

Using a combination of bioinformatics and molecular assay technology, twelve non-synonymous SNPs in eleven genes were genotyped in a cattle population. Three and nine SNPs explained more than 1% of the additive genetic variance for percentage of normal sperm and scrotal circumference, respectively. The SNPs that had a major influence in percentage of normal sperm were mapped to LOC100138021 and TAF7L genes; and in TEX11 and AR genes for scrotal circumference. One SNP in TEX11 was explained ~13% of the additive genetic variance for scrotal circumference at 12 months. The tested SNP were also associated with weight measurements, but not with female fertility traits.

Conclusions

The strong association of SNPs located in X chromosome genes with male fertility traits validates the QTL. The implicated genes became good candidates to be used for genetic evaluation, without detrimentally influencing female fertility traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1595-0) contains supplementary material, which is available to authorized users.     

Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle

The objectives of the present study were: (1) to evaluate the importance of genotype×production environment interaction for the genetic evaluation of birth weight (BW) and weaning weight (WW) in a population of composite beef cattle in Brazil, and (2) to investigate the importance of sire×contemporary group interaction (S×CG) to model G×E and improve the accuracy of prediction in routine genetic evaluations of this population. Analyses were performed with one, two (favorable and unfavorable) or three (favorable, intermediate, unfavorable) different definitions of production environments. Thus, BW and WW records of animals in a favorable environment were assigned to either trait 1, in an intermediate environment to trait 2 or in an unfavorable environment to trait 3. The (co)variance components were estimated using Gibbs sampling in single-, bi- or three-trait animal models according to the definition of number of production environments. In general, the estimates of genetic parameters for BW and WW were similar between environments. The additive genetic correlations between production environments were close to unity for BW; however, when examining the highest posterior density intervals, the correlation between favorable and unfavorable environments reached a value of only 0.70, a fact that may lead to changes in the ranking of sires across environments. The posterior mean genetic correlation between direct effects was 0.63 in favorable and unfavorable environments for WW. When S×CG was included in two- or three-trait analyses, all direct genetic correlations were close to unity, suggesting that there was no evidence of a genotype×production environment interaction. Furthermore, the model including S×CG contributed to prevent overestimation of the accuracy of breeding values of sires, provided a lower error of prediction for both direct and maternal breeding values, lower squared bias, residual variance and deviance information criterion than the model omitting S×CG. Thus, the model that included S×CG can therefore be considered the best model on the basis of these criteria. The genotype×production environment interaction should not be neglected in the genetic evaluation of BW and WW in the present population of beef cattle. The inclusion of S×CG in the model is a feasible and plausible alternative to model the effects of G×E in the genetic evaluations.     

A comparison of antibiotic resistance integrons in cattle from separate beef meat production systems at slaughter

Aims: To compare antibiotic resistance integrons in cattle from three separate grass‐fed, grain‐fed and certified organic cattle production systems at slaughter. Methods and Results: In this study 198 samples from three separate cattle production systems were tested by PCR for the presence of class 1 and class 2 integrons. Integron‐containing bacteria were readily isolated from pen faeces and hide samples regardless of production system. Lower numbers of integron‐containing bacteria were isolated from the remaining sample types. Ninety‐one class 1 and 34 class 2 integron‐containing bacteria were isolated. Characterization of the integrons demonstrated a high degree of similarity across the three production systems with aadA1 and aadA2 routinely present. Integrons harbouring the cassette array cmlA5–bla_OXA‐10–aadA1 and the putative insertion sequence IS1066 were isolated from organic and grass‐fed cattle and have not been described previously. Conclusions: Integrons carrying antibiotic resistance genes were common in cattle from differing production systems at slaughter and the likelihood of presence appears unrelated to the production system. Significance and Impact of the Study: Similar integron arrays are present in different cattle production systems suggesting that their presence may be independent of production practices. This is the first report of two novel integron structures present in Aeromonas.     

Evaluation of feeding behaviour traits to predict efficiency traits in pigs using partial least square regression

The improvement of efficiency traits, such as protein efficiency (PE), digestible energy efficiency (EnE) and lipid gain (LipG), are relevant given their associations with environmental pollution, cost of production, and the quality of meat. However, these traits are difficult to measure and usually require slaughtering of pigs. Efficiency traits are complex, and several factors, such as genetic predisposition, feed composition, but also individual feeding behaviour may contribute to efficiency. The objective of this study was therefore to evaluate the potential of using feeding behaviour traits to predict efficiency traits under dietary protein restriction. A total of 587 Swiss Large White pigs, consisting of 312 females and 275 castrated males, had ad libitum access to feed and water, and were fed a protein-reduced diet (80% of recommended digestible protein and essential amino acids) from 22.5 ± 1.6 to 106.6 ± 4.6 kg BW. Individual feed intake was monitored and carcass composition (lean and fat mass) at slaughter was determined by dual-energy X-ray absorptiometry. The PE and EnE were calculated as the ratio of protein or energy in the carcass (estimated by dual-energy X-ray absorptiometry) to the total protein or energy consumed. Feeding behaviour traits monitored were daily feed intake, feed intake per meal, number of daily meals, duration per meal, feeding rate, and feeder occupation. A partial least square (PLS) regression was used to predict PE, EnE and LipG from feeding behaviour traits, while including farrowing series (for PE only), age at slaughter and BW at slaughter. Accuracy of PLS regression was assessed based on RMSE and R² for calibration and validation sets, and on concordance correlation coefficient, which were estimated over 100 replicates of calibration and validation sets. Models with a number of latent variables of 5, 2 and 3 were identified as optimal for PE, EnE, and LipG, which explained 34.64%, 55.42% and 82.68% of the total variation in PE, EnE, and LipG, respectively. Significant concordance correlation coefficient was found between predicted and observed values for PE (0.50), EnE (0.70), and LipG (0.90). In conclusion, individual feeding behaviour traits can better predict EnE and LipG than for PE under dietary protein restriction when fed ad libitum.     

Accuracies of genomic prediction for twenty economically important traits in Chinese Simmental beef cattle

Genomic prediction has been widely utilized to estimate genomic breeding values (GEBVs) in farm animals. In this study, we conducted genomic prediction for 20 economically important traits including growth, carcass and meat quality traits in Chinese Simmental beef cattle. Five approaches (GBLUP, BayesA, BayesB, BayesCπ and BayesR) were used to estimate the genomic breeding values. The predictive accuracies ranged from 0.159 (lean meat percentage estimated by BayesCπ) to 0.518 (striploin weight estimated by BayesR). Moreover, we found that the average predictive accuracies across 20 traits were 0.361, 0.361, 0.367, 0.367 and 0.378, and the averaged regression coefficients were 0.89, 0.86, 0.89, 0.94 and 0.95 for GBLUP, BayesA, BayesB, BayesCπ and BayesR respectively. The genomic prediction accuracies were mostly moderate and high for growth and carcass traits, whereas meat quality traits showed relatively low accuracies. We concluded that Bayesian regression approaches, especially for BayesR and BayesCπ, were slightly superior to GBLUP for most traits. Increasing with the sizes of reference population, these two approaches are feasible for future application of genomic selection in Chinese beef cattle.     

Accuracy of predicting genomic breeding values for carcass merit traits in Angus and Charolais beef cattle

Accuracy of predicting genomic breeding values for carcass merit traits including hot carcass weight, longissimus muscle area (REA), carcass average backfat thickness (AFAT), lean meat yield (LMY) and carcass marbling score (CMAR) was evaluated based on 543 Angus and 400 Charolais steers genotyped on the Illumina BovineSNP50 Beadchip. For the genomic prediction within Angus, the average accuracy was 0.35 with a range from 0.32 (LMY) to 0.37 (CMAR) across different training/validation data‐splitting strategies and statistical methods. The within‐breed genomic prediction for Charolais yielded an average accuracy of 0.36 with a range from 0.24 (REA) to 0.46 (AFAT). The across‐breed prediction had the lowest accuracy, which was on average near zero. When the data from the two breeds were combined to predict the breeding values of either breed, the prediction accuracy averaged 0.35 for Angus with a range from 0.33 (REA) to 0.39 (CMAR) and averaged 0.33 for Charolais with a range from 0.18 (REA) to 0.46 (AFAT). The prediction accuracy was slightly higher on average when the data were split by animal's birth year than when the data were split by sire family. These results demonstrate that the genetic relationship or relatedness of selection candidates with the training population has a great impact on the accuracy of predicting genomic breeding values under the density of the marker panel used in this study.     

Discovery of novel genetic networks associated with 19 economically important traits in beef cattle

Quantitative or complex traits are determined by the combined effects of many loci, and are affected by genetic networks or molecular pathways. In the present study, we genotyped a total of 138 mutations, mainly single nucleotide polymorphisms derived from 71 functional genes on a Wagyu x Limousin reference population. Two hundred forty six F₂ animals were measured for 5 carcass, 6 eating quality and 8 fatty acid composition traits. A total of 2,280 single marker-trait association runs with 120 tagged mutations selected based on the HAPLOVIEW analysis revealed 144 significant associations (P < 0.05), but 50 of them were removed from the analysis due to the small number of animals (≤ 9) in one genotype group or absence of one genotype among three genotypes. The remaining 94 single-trait associations were then placed into three groups of quantitative trait modes (QTMs) with additive, dominant and overdominant effects. All significant markers and their QTMs associated with each of these 19 traits were involved in a linear regression model analysis, which confirmed single-gene associations for 4 traits, but revealed two-gene networks for 8 traits and three-gene networks for 5 traits. Such genetic networks involving both genotypes and QTMs resulted in high correlations between predicted and actual values of performance, thus providing evidence that the classical Mendelian principles of inheritance can be applied in understanding genetic complexity of complex phenotypes. Our present study also indicated that carcass, eating quality and fatty acid composition traits rarely share genetic networks. Therefore, marker-assisted selection for improvement of one category of these traits would not interfere with improvement of another.