Review: optimizing genomic selection for crossbred performance by model improvement and data collection

Breeding programs aiming to improve the performance of crossbreds may benefit from genomic prediction of crossbred (CB) performance for purebred (PB) selection candidates. In this review, we compared genomic prediction strategies that differed in 1) the genomic prediction model used or 2) the data used in the reference population. We found 27 unique studies, two of which used deterministic simulation, 11 used stochastic simulation, and 14 real data. Differences in accuracy and response to selection between strategies depended on i) the value of the purebred crossbred genetic correlation (rpc), ii) the genetic distance between the parental lines, iii) the size of PB and CB reference populations, and iv) the relatedness of these reference populations to the selection candidates. In studies where a PB reference population was used, the use of a dominance model yielded accuracies that were equal to or higher than those of additive models. When rpc was lower than ~0.8, and was caused mainly by G × E, it was beneficial to create a reference population of PB animals that are tested in a CB environment. In general, the benefit of collecting CB information increased with decreasing rpc. For a given rpc, the benefit of collecting CB information increased with increasing size of the reference populations. Collecting CB information was not beneficial when rpc was higher than ~0.9, especially when the reference populations were small. Collecting only phenotypes of CB animals may slightly improve accuracy and response to selection, but requires that the pedigree is known. It is, therefore, advisable to genotype these CB animals as well. Finally, considering the breed-origin of alleles allows for modeling breed-specific effects in the CB, but this did not always lead to higher accuracies. Our review shows that the differences in accuracy and response to selection between strategies depend on several factors. One of the most important factors is rpc, and we, therefore, recommend to obtain accurate estimates of rpc of all breeding goal traits. Furthermore, knowledge about the importance of components of rpc (i.e., dominance, epistasis, and G × E) can help breeders to decide which model to use, and whether to collect data on animals in a CB environment. Future research should focus on the development of a tool that predicts accuracy and response to selection from scenario specific parameters.     

Short communication: investigation of the feasibility of genomic selection in Icelandic Cattle

Icelandic Cattle is a local dairy cattle breed in Iceland. With about 26,000 breeding females, it is by far the largest among the indigenous Nordic cattle breeds. The objective of this study was to investigate the feasibility of genomic selection in Icelandic Cattle. Pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) were compared. Accuracy, bias, and dispersion of estimated breeding values (EBV) for milk yield (MY), fat yield (FY), protein yield (PY), and somatic cell score (SCS) were estimated in a cross validation-based design. Accuracy (r^) was estimated by the correlation between EBV and corrected phenotype in a validation set. The accuracy (r^) of predictions using ssGBLUP increased by 13, 23, 19, and 20 percentage points for MY, FY, PY, and SCS for genotyped animals, compared with PBLUP. The accuracy of nongenotyped animals was not improved for MY and PY, but increased by 0.9 and 3.5 percentage points for FY and SCS. We used the linear regression (LR) method to quantify relative improvements in accuracy, bias (Δ^), and dispersion (b^) of EBV. Using the LR method, the relative improvements in accuracy of validation from PBLUP to ssGBLUP were 43%, 60%, 50%, and 48% for genotyped animals for MY, FY, PY, and SCS. Single-step GBLUP EBV were less underestimated (Δ^), and less overdispersed (b^) than PBLUP EBV for FY and PY. Pedigree-based BLUP EBV were close to unbiased for MY and SCS. Single-step GBLUP underestimated MY EBV but overestimated SCS EBV. Based on the average accuracy of 0.45 for ssGBLUP EBV obtained in this study, selection intensities according to the breeding scheme of Icelandic Cattle, and assuming a generation interval of 2.0 yr for sires of bulls, sires of dams and dams of bulls, genetic gain in Icelandic Cattle could be increased by about 50% relative to the current breeding scheme.     

A combination of Lactobacillus buchneri and Pediococcus pentosaceus extended the aerobic stability of conventional and brown midrib mutants–corn hybrids ensiled at low dry matter concentrations by causing a major shift in their bacterial and fungal community

We evaluated the effects of applying a combination inoculant to four corn hybrids harvested at high moisture on their nutritive value and microbial populations. The treatment design was the factorial combination of corn hybrids ensiled with (INO) and without (CON) inoculant. The hybrids were TMF2R737 (MCN), F2F817 (MBR), P2089YHR (PCN), and PI144XR (PBR), ensiled at dry matter (DM) concentrations of 30.5%, 26.3%, 31.1%, and 31.5%, respectively; MBR and PBR were brown midrib mutants (BMR). The inoculant contained Lactobacillus buchneri and Pediococcus pentosaceus (4 × 10⁵ and 1 × 10⁵ cfu/g of fresh corn). The experiment had a complete randomized design with treatments replicated six times. Corn was treated or not with inoculant, packed into 7.6 L bucket silos, and stored for 100 d. At d 0, the relative abundance (RA, %) of Enterobacteriaceae was lower in PBR vs. the other hybrids [51.3 vs. x¯ = (average of) 58.4] and in the case of fungi, incertae sedis (i.s.) Tremellales and Mucoraceae were more and less abundant, respectively, in conventional hybrids vs. BMRs (x¯= 25.8 vs. x¯ = 13.9 and x¯ = 3.64 vs. x¯ = 7.52; P < 0.04). After ensiling, INO had higher LAB (9.3 vs. 7.1 log cfu/g of fresh corn) and acetic acid (3.44% vs. 1.32% of DM) and lower yeast (3.1 vs. 4.6) and molds (1.5 vs. 3.0), and also extended the aerobic stability (582 vs. 111 h) but decreased DM recovery (95.6% vs. 97.4%) vs. CON (P < 0.02). Inoculation reduced bacterial phylogenetic diversity (6.75 vs. 14.4) but increased fungal observed taxonomical units (46 vs. 20) vs. CON (P < 0.01). Also, a higher relative abundance (RA) for Lactobacillaceae (99.2% vs. 75.7%) and lower for Enterobacteriaceae (0.28 vs. 9.93) was observed due to inoculation (P < 0.001). For fungi, INO had a lower RA compared to CON for Monascaceae (12.6 vs. 44.7) and increased i.s. Tremellales (8.0 vs. 1.2) and i.s. Saccharomycetales (6.4% vs. 0.3%; P < 0.006). Inoculation changed the diverse bacterial community found in the phyllosphere across hybrids to a taxonomically uneven one dominated by Lactobacillaceae. In the case of fungi, INO application increased the fungal diversity at d 100 mainly by reducing the dominance of Monascaceae vs. CON. In conclusion, the INO treatment overwhelmed the disparate microbial populations found across BMR and conventional hybrids ensiled at low DM concentrations and ensured a significant concentration of acetic acid that modified fungal populations and in turn extended the aerobic stability of all hybrids.     

Purebred-crossbred genetic parameters for reproductive traits in swine

For swine breeding programs, testing and selection programs are usually within purebred (PB) populations located in nucleus units that are generally managed differently and tend to have a higher health level than the commercial herds in which the crossbred (CB) descendants of these nucleus animals are expected to perform. This approach assumes that PB animals selected in the nucleus herd will have CB progeny that have superior performance at the commercial level. There is clear evidence that this may not be the case for all traits of economic importance and, thus, including data collected at the commercial herd level may increase the accuracy of selection for commercial CB performance at the nucleus level. The goal for this study was to estimate genetic parameters for five maternal reproductive traits between two PB maternal nucleus populations (Landrace and Yorkshire) and their CB offspring: Total Number Born (TNB), Number Born Alive (NBA), Number Born Alive > 1 kg (NBA > 1 kg), Total Number Weaned (TNW), and Litter Weight at Weaning (LWW). Estimates were based on single-step GBLUP by analyzing any two combinations of a PB and the CB population, and by analyzing all three populations jointly. The genomic relationship matrix between the three populations was generated by using within-population allele frequencies for relationships within a population, and across-population allele frequencies for relationships of the CB with the PB animals. Utilization of metafounders for the two PB populations had no effect on parameter estimates, so the two PB populations were assumed to be genetically unrelated. Joint analysis of two (one PB plus CB) vs. three (both PB and CB) populations did not impact estimates of heritability, additive genetic variance, and genetic correlations. Heritabilities were generally similar between the PB and CB populations, except for LWW and TNW, for which PB populations had about four times larger estimates than CB. Purebred-crossbred genetic correlations (rpc) were larger for Landrace than for Yorkshire, except for NBA > 1 kg. These estimates of rpc indicate that there is potential to improve selection of PB animals for CB performance by including CB information for all traits in the Yorkshire population, but that noticeable additional gains may only occur for NBA > 1 kg and TNW in the Landrace population.     

Impact of inclusion rates of crossbred phenotypes and genotypes in nucleus selection programs

Numerous methods have been suggested to incorporate crossbred (CB) phenotypes and genotypes into swine selection programs, yet little research has focused on the implicit trade-off decisions between generating data at the nucleus or commercial level. The aim of this study was to investigate the impact of altering the proportion of purebred (PB) and CB phenotypes and genotypes in genetic evaluations on the response to selection of CB performance. Assuming CB and PB performance with moderate heritabilities (h2=0.4), a three-breed swine crossbreeding scheme was simulated and selection was practiced for six generations, where the goal was to increase CB performance. Phenotypes, genotypes, and pedigrees for three PB breeds (25 and 175 mating males and females for each breed, respectively), F₁ crosses (400 mating females), and terminal cross progeny (2,500) were simulated. The genome consisted of 18 chromosomes with 1,800 quantitative trait loci and 72k single nucleotide polymorphism (SNP) markers. Selection was performed in PB breeds using estimated breeding value for each phenotyping/genotyping strategy. Strategies investigated were: 1) increasing the proportion of CB with genotypes, phenotypes, and sire pedigree relationships, 2) decreasing the proportion of PB phenotypes and genotypes, and 3) altering the genetic correlation between PB and CB performance (rpc). Each unique rpc scenario and data collection strategy was replicated 10 times. Results showed that including CB data improved the CB performance regardless of rpc or data collection strategy compared with when no CB data were included. Compared with using only PB information, including 10% of CB progeny per generation with sire pedigrees and phenotypes increased the response in CB phenotype by 134%, 55%, 33%, 23%, and 21% when rpc was 0.1, 0.3, 0.5, 0.7, and 0.9, respectively. When the same 10% of CB progeny were also genotyped, CB performance increased by 243%, 54%, 38%, 23%, and 20% when the rpc was 0.1, 0.3, 0.5, 0.7, and 0.9, respectively, compared with when no CB data were utilized. Minimal change was observed in the average CB phenotype when PB phenotypes were included or proportionally removed when CB were genotyped. Removal of both PB phenotypes and genotypes when CB were genotyped greatly reduced the response in CB performance. In practice, the optimal inclusion rate of CB and PB data depends upon the genetic correlation between CB and PB animals and the expense of additional CB data collection compared with the economic benefit associated with increased CB performance.     

Genetic parameters and purebred–crossbred genetic correlations for growth,meat quality,and carcass traits in pigs

Growth, meat quality, and carcass traits are of economic importance in swine breeding. Understanding their genetic basis in purebred (PB) and commercial crossbred (CB) pigs is necessary for a successful breeding program because, although the breeding goal is to improve CB performance, phenotype collection and selection are usually carried out in PB populations housed in biosecure nucleus herds. Thus, the selection is indirect, and the accuracy of selection depends on the genetic correlation between PB and CB performance (rpc). The objectives of this study were to 1) estimate genetic parameters for growth, meat quality, and carcass traits in a PB sire line and related commercial CB pigs and 2) estimate the corresponding genetic correlations between purebred and crossbred performance (rpc). Both objectives were investigated by using pedigree information only (PBLUP) and by combining pedigree and genomic information in a single-step genomic BLUP (ssGBLUP) procedure. Growth rate showed moderate estimates of heritability for both PB and CB based on PBLUP, while estimates were higher in CB based on ssGBLUP. Heritability estimates for meat quality traits were diverse and slightly different based on PB and CB data with both methods. Carcass traits had higher heritability estimates based on PB compared with CB data based on PBLUP and slightly higher estimates for CB data based on ssGBLUP. A wide range of estimates of genetic correlations were obtained among traits within the PB and CB data. In the PB population, estimates of heritabilities and genetic correlations were similar based on PBLUP and ssGBLUP for all traits, while based on the CB data, ssGBLUP resulted in different estimates of genetic parameters with lower SEs. With some exceptions, estimates of rpc were moderate to high. The SE on the rpc estimates was generally large when based on PBLUP due to limited sample size, especially for CBs. In contrast, estimates of rpc based on ssGBLUP were not only more precise but also more consistent among pairs of traits, considering their genetic correlations within the PB and CB data. The wide range of estimates of rpc (less than 0.70 for 7 out of 13 traits) indicates that the use of CB phenotypes recorded on commercial farms, along with genomic information, for selection in the PB population has potential to increase the genetic progress of CB performance.     

Estimation of direct and social effects of feeding duration in growing pigs using records from automatic feeding stations

Automatic feeding systems in pig production allow for the recording of individual feeding behavior traits, which might be influenced by the social interactions among individuals. This study fitted mixed models to estimate the direct and social effects on visit duration at the feeder of group-housed pigs. The dataset included 74,413 records of each visit duration time (min) event at the automatic feeder from 135 pigs housed in 14 pens. The sequence of visits at the feeder was employed as a proxy for the social interaction between individuals. To estimate animal effects, the direct effect was apportioned to the animal feeding (feeding pig), and the social effect was apportioned to the animal that entered the feeder immediately after the feeding pig left the feeding station (follower). The data were divided into two subsets: “non-immediate replacement” time (NIRT, N = 6,256), where the follower pig occupied the feeder at least 600 s after the feeding pig left the feeder, and “immediate replacement” time (IRT, N= 58,255), where the elapsed time between replacements was less than or equal to 60 s. The marginal posterior distribution of the parameters was obtained by Bayesian method. Using the IRT subset, the posterior mean of the proportion of variance explained by the direct effect (Prpσ^d2) was 18% for all models. The proportion of variance explained by the follower social effect (Prpσ^f2) was 2%, and the residual variance (σ^e2) decreased, suggesting an improved model fit by including the follower effect. Fitting the models with the NIRT subset, the estimate of Prpσ^d2 was 20% but the Prpσ^f2 was almost zero and σ^e2 was identical for all models. For the IRT subset, the predicted best linear unbiased predictor (BLUP) of direct (Direct BLUP) and social (Follower BLUP) random effects on visit duration at the feeder of an animal was calculated. Feeder visit duration time was not correlated with traits, such as weight gain or average feed intake (P > 0.05), whereas for the daily feeder occupation time, the estimated correlation was positive with the Direct BLUP (r^= 0.51, P < 0.05) and negative with the Follower BLUP (r^= −0.26, P < 0.05). The results suggest that the visit duration of an animal at the single-space feeder was influenced by both direct and social effects when the replacement time between visits was less than 1 min. Finally, animals that spent a longer time per day at the feeder seemed to do so by shortening the meal length of the preceding individual at the feeder.     

Comparison of models for missing pedigree in single-step genomic prediction

Pedigree information is often missing for some animals in a breeding program. Unknown-parent groups (UPGs) are assigned to the missing parents to avoid biased genetic evaluations. Although the use of UPGs is well established for the pedigree model, it is unclear how UPGs are integrated into the inverse of the unified relationship matrix (H-inverse) required for single-step genomic best linear unbiased prediction. A generalization of the UPG model is the metafounder (MF) model. The objectives of this study were to derive 3 H-inverses and to compare genetic trends among models with UPG and MF H-inverses using a simulated purebred population. All inverses were derived using the joint density function of the random breeding values and genetic groups. The breeding values of genotyped animals (u₂) were assumed to be adjusted for UPG effects (g) using matrix Q₂ as u2∗=u2+Q2g before incorporating genomic information. The Quaas–Pollak-transformed (QP) H-inverse was derived using a joint density function of u2∗ and g updated with genomic information and assuming nonzero cov(u2∗,g′). The modified QP (altered) H-inverse also assumes that the genomic information updates u2∗ and g, but cov(u2∗,g′)=0. The UPG-encapsulated (EUPG) H-inverse assumed genomic information updates the distribution of u2∗. The EUPG H-inverse had the same structure as the MF H-inverse. Fifty percent of the genotyped females in the simulation had a missing dam, and missing parents were replaced with UPGs by generation. The simulation study indicated that u2∗ and g in models using the QP and altered H-inverses may be inseparable leading to potential biases in genetic trends. Models using the EUPG and MF H-inverses showed no genetic trend biases. These 2 H-inverses yielded the same genomic EBV (GEBV). The predictive ability and inflation of GEBVs from young genotyped animals were nearly identical among models using the QP, altered, EUPG, and MF H-inverses. Although the choice of H-inverse in real applications with enough data may not result in biased genetic trends, the EUPG and MF H-inverses are to be preferred because of theoretical justification and possibility to reduce biases.     

Is single-step genomic REML with the algorithm for proven and young more computationally efficient when less generations of data are present?

Efficient computing techniques allow the estimation of variance components for virtually any traditional dataset. When genomic information is available, variance components can be estimated using genomic REML (GREML). If only a portion of the animals have genotypes, single-step GREML (ssGREML) is the method of choice. The genomic relationship matrix (G) used in both cases is dense, limiting computations depending on the number of genotyped animals. The algorithm for proven and young (APY) can be used to create a sparse inverse of G (GAPY~-1) with close to linear memory and computing requirements. In ssGREML, the inverse of the realized relationship matrix (H⁻¹) also includes the inverse of the pedigree relationship matrix, which can be dense with a long pedigree, but sparser with short. The main purpose of this study was to investigate whether costs of ssGREML can be reduced using APY with truncated pedigree and phenotypes. We also investigated the impact of truncation on variance components estimation when different numbers of core animals are used in APY. Simulations included 150K animals from 10 generations, with selection. Phenotypes (h² = 0.3) were available for all animals in generations 1–9. A total of 30K animals in generations 8 and 9, and 15K validation animals in generation 10 were genotyped for 52,890 SNP. Average information REML and ssGREML with G⁻¹ and GAPY~-1 using 1K, 5K, 9K, and 14K core animals were compared. Variance components are impacted when the core group in APY represents the number of eigenvalues explaining a small fraction of the total variation in G. The most time-consuming operation was the inversion of G, with more than 50% of the total time. Next, numerical factorization consumed nearly 30% of the total computing time. On average, a 7% decrease in the computing time for ordering was observed by removing each generation of data. APY can be successfully applied to create the inverse of the genomic relationship matrix used in ssGREML for estimating variance components. To ensure reliable variance component estimation, it is important to use a core size that corresponds to the number of largest eigenvalues explaining around 98% of total variation in G. When APY is used, pedigrees can be truncated to increase the sparsity of H and slightly reduce computing time for ordering and symbolic factorization, with no impact on the estimates.     

Quantification of transmission of foot-and-mouth disease virus caused by an environment contaminated with secretions and excretions from infected calves

Foot-and-mouth disease virus (FMDV) infected animals can contaminate the environment with their secretions and excretions. To quantify the contribution of a contaminated environment to the transmission of FMDV, this study used calves that were not vaccinated and calves that were vaccinated 1 week prior to inoculation with the virus in direct and indirect contact experiments. In direct contact experiments, contact calves were exposed to inoculated calves in the same room. In indirect contact experiments, contact calves were housed in rooms that previously had held inoculated calves for three days (either from 0 to 3 or from 3 to 6 days post inoculation). Secretions and excretions from all calves were tested for the presence of FMDV by virus isolation; the results were used to quantify FMDV transmission. This was done using a generalized linear model based on a 2 route (2R, i.e. direct contact and environment) SIR model that included information on FMDV survival in the environment. The study shows that roughly 44% of transmission occurs via the environment, as indicated by the reproduction ratio R^02Renvironment that equalled 2.0, whereas the sum of R^02Rcontact and R^02Renvironment equalled 4.6. Because vaccination 1 week prior to inoculation of the calves conferred protective immunity against FMDV infection, no transmission rate parameters could be estimated from the experiments with vaccinated calves. We conclude that a contaminated environment contributes considerably to the transmission of FMDV therefore that hygiene measures can play a crucial role in FMD control.

Electronic supplementary material

The online version of this article (doi:10.1186/s13567-015-0156-5) contains supplementary material, which is available to authorized users.     

外源NO调控盐胁迫下蒺藜苜蓿种子萌发生理特性及抗氧化酶的研究

本试验以蒺藜苜蓿种子为材料,预先用0.1,0.3和1.0 mmol/L 硝普钠(SNP, NO 供体)浸种,通过计算相关萌发指标,测定种子萌发过程中各项生理指标及抗氧化系统酶活性,研究外源NO对2.0% NaCl胁迫下蒺藜苜蓿种子萌发生理特性及活性氧代谢的影响。结果表明,0.1 mmol/L SNP能显著缓解盐胁迫对蒺藜苜蓿种子造成的伤害,使蒺藜苜蓿种子的发芽率、发芽势、发芽指数和活力指数分别提高了333.40%,79.64%,171.93%和100.00%;种子可溶性糖、可溶性蛋白和脯氨酸含量分别提高了21.1%,42.3%和123.1%,淀粉含量降低了17.7%,淀粉酶活性提高了29.7%,丙二醛(MDA)和超氧阴离子(O2-·)含量分别降低了21.8%和27.2%,超氧化物歧化酶(SOD)、过氧化物酶(POD)、过氧化氢酶(CAT)活性和抗坏血酸过氧化物酶(APX)活性分别增加了28.6%,43.1%,56.2%和60.3%;与0.1 mmol/L SNP处理相比,0.3 mmol/L SNP处理对盐胁迫下蒺藜苜蓿种子萌发的促进、氧化损伤的缓解和抗氧化系统酶活性的提高显著降低;1.0 mmol/L SNP处理对盐胁迫下蒺藜苜蓿种子的萌发起到抑制作用。说明低浓度的NO可通过降低种子MDA和O2-·含量,提高种子脯氨酸含量以及激活抗氧化系统酶活性,减轻盐胁迫对蒺藜苜蓿种子的伤害,促进淀粉、可溶性蛋白的水解,从而加速种子萌发。     

Quantitative Accuracy of the Simplified Strong Ion Equation to Predict Serum pH in Dogs

Background

Electrochemical approach to the assessment of acid‐base states should provide a better mechanistic explanation of the metabolic component than methods that consider only pH and carbon dioxide.

Hypothesis/Objectives

Simplified strong ion equation (SSIE), using published dog‐specific values, would predict the measured serum pH of diseased dogs.

Animals

Ten dogs, hospitalized for various reasons.

Methods

Prospective study of a convenience sample of a consecutive series of dogs admitted to the Massey University Veterinary Teaching Hospital (MUVTH), from which serum biochemistry and blood gas analyses were performed at the same time. Serum pH was calculated (Hcal+) using the SSIE, and published values for the concentration and dissociation constant for the nonvolatile weak acids (A_tot and K _a), and subsequently Hcal+ was compared with the dog''s actual pH (Hmeasured+). To determine the source of discordance between Hcal+ and Hmeasured+, the calculations were repeated using a series of substituted values for A_tot and K _a.

Results

The Hcal+ did not approximate the Hmeasured+ for any dog (P = 0.499, r ² = 0.068), and was consistently more basic. Substituted values A_tot and K _a did not significantly improve the accuracy (r ² = 0.169 to <0.001). Substituting the effective SID (Atot−[HCO3−]) produced a strong association between Hcal+ and Hmeasured+ (r ² = 0.977).

Conclusions and clinical importance

Using the simplified strong ion equation and the published values for A_tot and K _a does not appear to provide a quantitative explanation for the acid‐base status of dogs. Efficacy of substituting the effective SID in the simplified strong ion equation suggests the error lies in calculating the SID.     

Pharmacokinetics of IV Ketorolac in Horses Undergoing Orchiectomy

Ketorolac (KET) is a nonsteroidal anti-inflammatory drug for human use, with a potent analgesic activity, that is used in the relief of moderate-to-severe postoperative pain. The pharmacokinetics of KET tromethamine was evaluated after single IV injection at 0.5 mg/kg body weight, after intubation and 10 minutes before surgery, to six Arabian colts undergoing orchiectomy. Intraoperative cardiorespiratory variables were monitored. Blood samples were collected for 36 hours, and serum samples were analyzed by high performance liquid chromotography with ultraviolet-visible detection. During surgery, all monitored physiological parameters were stable. Intermittent positive pressure ventilation, and normocapnia were maintained throughout the procedure in all animals. No adverse effects were observed. The kinetics of KET was described by a two-compartment models, and also a noncompartmental analysis was performed. The distribution and elimination half-lives were t_1/2λ1$t_{1/2{\lambda }_1}$ 0.06 ± 0.02 and t_1/2λ2$t_{1/2{\lambda }_2}$ 0.59 ± 0.21 hours, respectively. Body clearance and mean residence time were 339.99 ± 120.19 mL/h/kg and 0.49 ± 0.22 hours, respectively. The volume of distribution at steady state and volume of distribution based on the terminal phase were 218.83 ± 134.26 mL/kg and 522.5 ± 529.3 mL/kg, respectively. The serum protein binding was 75.8 ± 2.9%. The results indicate that KET at 0.5 mg/kg IV was very rapidly eliminated and thus was likely not effective in the postoperative period. However, further studies including a control group and at higher doses are suggested to investigate the KET kinetics and the analgesic efficacy in horse and define the most appropriate dosage scheme.     

Comparison of different methods to calculate venous admixture in anaesthetized horses

Objective

The aim of this study was to compare different methods to determine venous admixture (${\dot{Q}}_{\text{s}}/{\dot{Q}}_{\text{t}}$) in anaesthetized horses. The first objective was to estimate ${\dot{Q}}_{\text{s}}/{\dot{Q}}_{\text{t}}$ using jugular venous blood oxygen content (${\dot{Q}}_{\text{s}}/{\dot{Q}}_{\text{t}\text{jugular}}$), and a fixed value for the oxygen extraction (F-shunt). The second objective was to assess the influence of blood pressure and positioning on oxygen extraction. The third objective was to perform regression analysis between jugular and mixed venous blood oxygen tensions.

Discrepancies in Identification of Left Atrial Enlargement Using Left Atrial Volume versus Left Atrial‐to‐Aortic Root Ratio in Dogs

Background

Left atrial size is prognostically important in dogs with myxomatous mitral valve disease (MMVD).

Hypothesis/Objectives

To compare the level of agreement in identification of left atrial enlargement (LAE) between the left atrial‐to‐aortic root ratio (LA : Ao) and left atrial volume using the biplane area‐length method indexed to body weight (LA Vol/BW).

Animals

Sixty dogs with MMVD and 22 normal dogs were prospectively studied with 2‐dimensional echocardiography.

Methods

The upper limit of normal for LA Vol/BW was defined as 1.1 mL/kg. LA : Ao was deemed normal if ≤1.5. To define overall disease severity, each dog was assigned a mitral regurgitation severity score (MRSS) based on echocardiographic parameters that did not include left atrial size. ACVIM staging also was utilized.

Results

Of 60 affected dogs, 20 were ACVIM Stage B1, 25 were Stage B2, and 15 were Stage C. LA Vol/BW identified LAE in 12 cases in which LA : Ao was normal; 7 of these were Stage B1 and 5 were Stage B2. This diagnostic disagreement was significant (P = .00012). Of the 12 cases in which diagnostic discrepancies were identified, 5/5 of the B2 dogs and 3/7 B1 dogs had a moderate MRSS, whereas 4/7 B1 dogs had a mild MRSS. No diagnostic discrepancies between LA : Ao and LA Vol/BW were apparent in dogs with a severe MRSS.

Conclusions and Clinical Importance

This study shows evidence of diagnostic disagreement between LA : Ao and LA Vol/BW for assessment of LAE. LA Vol/BW may be superior to LA : Ao for identification of mild LAE.     

Effects of different dietary energy and protein levels and sex on growth performance,carcass characteristics and meat quality of F1 Angus?×?Chinese Xiangxi yellow cattle

Background

The experiment evaluated the effect of nutrition levels and sex on the growth performance, carcass characteristics and meat quality of F1 Angus × Chinese Xiangxi yellow cattle.

Methods

During the background period of 184 d,23 steers and 24 heifers were fed the same ration,then put into a 2 × 2 × 2 factorial arrangement under two levels of - dietary energy (TDN: 70/80% DM), protein (CP: 11.9/14.3% DM) and sex (S: male/female) during the finishing phase of 146 d. The treatments were - (1) high energy/low protein (HELP), (2) high energy/high protein (HEHP), (3) low energy/low protein (LELP) and (4) low energy/high protein (LEHP). Each treatment used 6 steers and 6 heifers, except for HELP- 5 steers and 6 heifers.

Results

Growth rate and final carcass weight were unaffected by dietary energy and protein levels or by sex. Compared with the LE diet group, the HE group had significantly lower dry matter intake (DMI, 6.76 vs. 7.48 kg DM/d), greater chest girth increments (46.1 vs. 36.8 cm), higher carcass fat (19.9 vs.16.3%) and intramuscular fat content (29.9 vs. 22.8% DM). The HE group also had improved yields of top and medium top grade commercial meat cuts (39.9 vs.36.5%). The dressing percentage was higher for the HP group than the LP group (53.4 vs. 54.9%). Steers had a greater length increment (9.0 vs. 8.3 cm), but lower carcass fat content (16.8 vs. 19.4%) than heifers. The meat quality traits (shear force value, drip loss, cooking loss and water holding capacity) were not affected by treatments or sex, averaging 3.14 kg, 2.5, 31.5 and 52.9%, respectively. The nutritive profiles (both fatty and amino acid composition) were not influenced by the energy or protein levels or by sex.

Conclusions

The dietary energy and protein levels and sex significantly influenced the carcass characteristics and chemical composition of meat but not thegrowth performance, meat quality traits and nutritive profiles.     

Selection problems when antagonistic effects exist between production characteristics and calving difficulties

The interrelations between the different traits related to calving ease are analysed. These traits are adult size, conformation, birthweight, gestation length and calving ability of the cow.Some of these traits being antagonistic, a compromise is to be found, and this implies that constraints are to be placed on some of them. When feasible, it seems better to select directly for ease of calving than on correlated traits such as birthweight or gestation length.Type of calving is a maternally influenced trait and therefore genetic direct (D) and maternal (M) effects are to be taken into account.Mathematical expectations of variances and covariances for a maternally influenced trait such as calving performance are presented as well as the expected superiority of selected sires when selection is based on: (1) the average as sire, $\text{P}{}_{\mathrm{o}}$; (2) the average as grandsire, $\text{P}{}_{\mathrm{G}}{}_{\mathrm{o}}$ ; (3) a weighted average of both,

; (4) the optimum index $\text{I=b}{}_1\text{P}{}_{\mathrm{o}}\text{+ b}{}_2\text{P}{}_{\mathrm{G}}{}_{\mathrm{o}}$ corresponding to the aggregate genotype H = D + M.The variations (1) of the “between maternal grandsires” and “between sires” components of variance, (2) of the phenotypic correlation between the two sires' averages and (3) of the genetic superiority of selected sires are studied and illustrated for different values of the correlation between the direct and maternal effects and for different values of the variance of genetic maternal effects relative to that of the direct effects. When the maternal effects are important relative to the direct effects, and even if the two are negatively correlated, it is possible to improve both together, but then the average as grandsire has to be considered.A combination of both averages, $\text{P}{}_{\mathrm{o}}$ and $\text{P}{}_{\mathrm{G}}{}_{\mathrm{o}}$, as in the optimum index, gives the best prospects for improvement of the total genotype (D + M). Therefore, in problem breeds, extensive progeny-testing for growth, carcass composition and calving ability in their direct and maternal components ought to be carried out. By so doing, the opportunity will be given to estimate the parameters characterising the relations between these traits and then to construct a selection index optimising the correlation with the appropriate aggregate genotype.     

Plasma and Urine Neutrophil Gelatinase–Associated Lipocalin (NGAL) in Dogs with Acute Kidney Injury or Chronic Kidney Disease

Background

Neutrophil gelatinase–associated lipocalin (NGAL) is a protein that is used in human medicine as a real‐time indicator of acute kidney injury (AKI).

Hypothesis

Dogs with AKI have significantly higher plasma NGAL concentration and urine NGAL‐to‐creatinine ratio (UNCR) compared with healthy dogs and dogs with chronic kidney disease (CKD).

Animals

18 healthy control dogs, 17 dogs with CKD, and 48 dogs with AKI.

Methods

Over a period of 1 year, all dogs with renal azotemia were prospectively included. Urine and plasma samples were collected during the first 24 hours after presentation or after development of renal azotemia. Plasma and urine NGAL concentrations were measured with a commercially available canine NGAL Elisa Kit (Bioporto® Diagnostic) and UNCR was calculated. A single‐injection plasma inulin clearance was performed in the healthy dogs.

Results

Median (range) NGAL plasma concentration in healthy dogs, dogs with CKD, and AKI were 10.7 ng/mL (2.5–21.2), 22.0 ng/mL (7.7–62.3), and 48.3 ng/mL (5.7–469.0), respectively. UNCR was 2 × 10⁻⁸ (0–46), 1,424 × 10⁻⁸ (385–18,347), and 2,366 × 10⁻⁸ (36–994,669), respectively. Dogs with renal azotemia had significantly higher NGAL concentrations and UNCR than did healthy dogs (P < .0001 for both). Plasma NGAL concentration was significantly higher in dogs with AKI compared with dogs with CKD (P = .027).

Conclusions and Clinical Importance

Plasma NGAL could be helpful to differentiate AKI from CKD in dogs with renal azotemia.