Additional considerations to the use of single‐step genomic predictions in a dominance setting

Recent publications indicate that single‐step models are suitable to estimate breeding values, dominance deviations and total genetic values with acceptable quality. Additive single‐step methods implicitly extend known number of allele information from genotyped to non‐genotyped animals. This theory is well derived in an additive setting. It was recently shown, at least empirically, that this basic strategy can be extended to dominance with reasonable prediction quality. Our study addressed two additional issues. It illustrated the theoretical basis for extension and validated genomic predictions to dominance based on single‐step genomic best linear unbiased prediction theory. This development was then extended to include inbreeding into dominance relationships, which is a currently not yet solved issue. Different parametrizations of dominance relationship matrices were proposed. Five dominance single‐step inverse matrices were tested and described as C¹ , C² , C³ , C⁴ and C⁵ . Genotypes were simulated for a real pig population (n = 11,943 animals). In order to avoid any confounding issues with additive effects, pseudo‐records including only dominance deviations and residuals were simulated. SNP effects of heterozygous genotypes were summed up to generate true dominance deviations. We added random noise to those values and used them as phenotypes. Accuracy was defined as correlation between true and predicted dominance deviations. We conducted five replicates and estimated accuracies in three sets: between all ( S₁ ), non‐genotyped ( S₂ ) and inbred non‐genotyped ( S₃ ) animals. Potential bias was assessed by regressing true dominance deviations on predicted values. Matrices accounting for inbreeding ( C³ , C⁴ and C⁵ ) best fit. Accuracies were on average 0.77, 0.40 and 0.46 in S₁ , S₂ and S₃ , respectively. In addition, C³ , C⁴ and C⁵ scenarios have shown better accuracies than C¹ and C² , and dominance deviations were less biased. Better matrix compatibility (accuracy and bias) was observed by re‐scaling diagonal elements to 1 minus the inbreeding coefficient ( C⁵ ).     

Low Occurrence of Extended‐Spectrum β‐lactamase‐Producing Escherichia coli in Finnish Food‐Producing Animals

ESBL/AmpC‐producing Escherichia coli is increasingly isolated from humans and animals worldwide. The occurrence of ESBL/AmpC‐producing E. coli was studied in food‐producing animals in Finland, a country with a low and controlled use of antimicrobials in meat production chain. A total of 648 cattle, 531 pig, 495 broiler and 35 turkey faecal samples were collected from four Finnish slaughterhouses to determine the presence of extended‐spectrum β‐lactamase (ESBL/AmpC)‐producing E. coli. In addition, 260 broiler and 15 turkey samples were screened for carbapenemase‐producing E. coli. Susceptibility to different class of cephalosporins and meropenem was determined with disc diffusion tests according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST). Determination of ESBL/AmpC production was performed with a combination disc diffusion test according to the recommendations of the European Food Safety Authority (EFSA). Plasmidic bla_ESBL/AmpC genes were characterized by polymerase chain reaction and sequencing. A collection of isolates producing AmpC enzyme but not carrying plasmidic bla_AmpC was analysed by PCR and sequencing for possible chromosomal ampC promoter area mutations. Altogether ESBL/AmpC‐producing E. coli was recovered from five cattle (0.8%), eight pig (1.5%) and 40 broiler samples (8.1%). No ESBL/AmpC‐producing E. coli was found in turkey samples. Carbapenem resistance was not detected. Altogether ESBL/AmpC‐producing E. coli was found on 4 (2.0%), 3 (4.5%) and 14 (25%) cattle, pig and broiler farms, respectively. From cattle samples 3 (27%) bla_CTX‐M‐1 and from broiler samples 13 (33%) bla_CTX‐M‐1 and 22 (55%) bla_CMY‐2 gene‐carrying isolates were detected. In pigs, no plasmidic bla_ESBL/AmpC gene‐carrying isolates were found. In all analysed isolates, the same mutations in the promoter region of chromosomal ampC were detected. The results showed low occurrence of ESBL/AmpC‐producing E. coli in Finnish food‐producing animals. In pigs, plasmidic bla_ESBL/AmpC‐carrying E. coli was not detected at all.     

Accuracy of genomic prediction using imputed whole‐genome sequence data in white layers

There is an increasing interest in using whole‐genome sequence data in genomic selection breeding programmes. Prediction of breeding values is expected to be more accurate when whole‐genome sequence is used, because the causal mutations are assumed to be in the data. We performed genomic prediction for the number of eggs in white layers using imputed whole‐genome resequence data including ~4.6 million SNPs. The prediction accuracies based on sequence data were compared with the accuracies from the 60 K SNP panel. Predictions were based on genomic best linear unbiased prediction (GBLUP) as well as a Bayesian variable selection model (BayesC). Moreover, the prediction accuracy from using different types of variants (synonymous, non‐synonymous and non‐coding SNPs) was evaluated. Genomic prediction using the 60 K SNP panel resulted in a prediction accuracy of 0.74 when GBLUP was applied. With sequence data, there was a small increase (~1%) in prediction accuracy over the 60 K genotypes. With both 60 K SNP panel and sequence data, GBLUP slightly outperformed BayesC in predicting the breeding values. Selection of SNPs more likely to affect the phenotype (i.e. non‐synonymous SNPs) did not improve the accuracy of genomic prediction. The fact that sequence data were based on imputation from a small number of sequenced animals may have limited the potential to improve the prediction accuracy. A small reference population (n = 1004) and possible exclusion of many causal SNPs during quality control can be other possible reasons for limited benefit of sequence data. We expect, however, that the limited improvement is because the 60 K SNP panel was already sufficiently dense to accurately determine the relationships between animals in our data.     

Hepatic Ethoxy‐, Methoxy‐ and Pentoxyresorufin O‐Dealkylase Activities in Landrace and Duroc Pigs Stimulated with hCG

The effect of human chorionic gonadotropin (hCG) stimulation on the activities of ethoxyresorufin O‐deethylase (EROD), methoxyresorufin O‐demethylase (MROD) and pentoxyresorufin O‐depentylase (PROD) was studied in intact male pigs of purebred Landrace and Duroc breeds. Pigs were divided into four groups: two control groups of each breed, without hCG stimulation (n = 20 for each breed), and two experimental groups (n = 18 for each breed), with hCG stimulation (Pregnyl^®; N.V. Organon, Oss, The Netherlands, 30 IU/kg live weight). Pigs were slaughtered 3 days after hCG stimulation and enzyme activities were measured in hepatic microsomes using two approaches. First, only one substrate concentration was used for the analysis of each enzyme activity. We found that EROD activity was suppressed by hCG‐stimulation in Landrace (p = 0.004), but not Duroc pigs (p > 0.05). Generally, EROD activity was higher in Duroc pigs compared with Landrace (p = 0.017). Methoxyresorufin O‐demethylase and PROD activities did not differ between groups (p > 0.05). To further characterize EROD, MROD and PROD, enzyme kinetic studies were performed. V_max values for EROD and MROD in both breeds were lower after hCG stimuation (p < 0.001 for Landrace and p < 0.05 for Duroc). Additionally, V_max values for EROD significantly differed between Landrace and Duroc pigs being higher in Duroc pigs (p < 0.05). We concluded that both hCG stimulation and breed differences may be important in the regulation of EROD and MROD activities. This study provides the first data on the effect of hCG stimulation and thus high testicular steroids, on EROD, MROD and PROD activities. Further studies are needed to investigate individual CYP450 enzymes and their regulation in porcine tissues.     

Influence of Bacillus subtilis GCB‐13‐001 on growth performance,nutrient digestibility,blood characteristics,faecal microbiota and faecal score in weanling pigs

The present study investigated the influence of Bacillus subtilis GCB‐13‐001 on growth performance, nutrient digestibility, blood characteristics, faecal microbiota and faecal score in weanling pigs. A total of 120 weaning pigs [(Landrace × Yorkshire) × Duroc; 7.73 ± 0.75 kg (28 days of age)] were randomly allotted into three treatments according to their initial body weight (BW) and gender in a 6‐week experiment. There were 8 replication pens in each treatment, with five pigs/pen. Dietary treatment groups were as follows: (a) basal diet (CON), (b) CON + 0.1% Bacillus subtilis GCB‐13‐001 1 × 10⁸ CFU/kg (T1) and (c) CON + 0.1% Bacillus subtilis GCB‐13‐001 1 × 10⁹ CFU/kg (T2). Days 1 to 7, the BW and ADG with T2 treatment were higher (p < .05) than CON treatment, as well as F:G showed trends in linear reduction (p < .1). Days 8 to 21, the BW and ADG were improved (p < .05) in pigs offered T1 and T2 diets compared with CON diet. Days 22 to 42, BW and ADG were higher (p < .05) in pigs fed T2 diet than CON and T1 diets, and the pigs fed T1 diet had higher BW than CON treatment. Overall, the ADG with the T2 treatment was higher (p < .05) than that with the T1 and CON treatments, and pigs offered T1 treatment had higher (p < .05) ADG than CON treatment. Moreover, F:G ratio were significantly decreased (p < .05) by T2 treatment compared with CON treatment. The faecal Lactobacillus counts were improved, and E. coli counts were reduced (p < .05) in pigs fed T2 diet compared with CON at the end of the experiment. In conclusion, supplementation of 0.1% Bacillus subtilis GCB‐13‐001 1 × 10⁹ CFU/kg has shown a beneficial effect in improving BW, increase ADG, decrease F:G ratio.     

Accounting for genetic architecture in single‐ and multipopulation genomic prediction using weights from genomewide association studies in pigs

We studied the effect of including GWAS results on the accuracy of single‐ and multipopulation genomic predictions. Phenotypes (backfat thickness) and genotypes of animals from two sire lines (SL1, n = 1146 and SL3, n = 1264) were used in the analyses. First, GWAS were conducted for each line and for a combined data set (both lines together) to estimate the genetic variance explained by each SNP. These estimates were used to build matrices of weights (D), which was incorporated into a GBLUP method. Single population evaluated with traditional GBLUP had accuracies of 0.30 for SL1 and 0.31 for SL3. When weights were employed in GBLUP, the accuracies for both lines increased (0.32 for SL1 and 0.34 for SL3). When a multipopulation reference set was used in GBLUP, the accuracies were higher (0.36 for SL1 and 0.32 for SL3) than in single‐population prediction. In addition, putting together the multipopulation reference set and the weights from the combined GWAS provided even higher accuracies (0.37 for SL1, and 0.34 for SL3). The use of multipopulation predictions and weights estimated from a combined GWAS increased the accuracy of genomic predictions.     

Including an additional systematic environmental effect within a generation in an evaluation model improves accuracy of prediction of breeding values in a closed herd of pigs

The present study evaluated the advantage of mixed‐model techniques over a selection index under different magnitudes of an additional systematic environmental effect (ASEE) in terms of accuracy of prediction and expected genetic gain. The data attempted to simulate a closed herd in a pig breeding program. The base population (G₀) consisted of 10 males and 50 females. Six generations (G₀ to G₅) were selected by using a selection index of three traits without overlapping. Additional systematic environmental constants with four levels in a generation were assigned from a uniform distribution at different ranges. Breeding values of animals in the last generation (G₅) were estimated on the basis of an index of individual phenotype (SI‐U), SI‐U adjusted for ASEE using a least‐squares mean (SI‐A), best linear unbiased prediction using an animal model excluding ASEE (AM‐E), and an animal model including ASEE (AM‐I). Accuracy of prediction and expected genetic gain were larger by the animal model than by the selection index, even if heritability of the traits selected was high and ASEE was set to zero. When ASEE was zero, the accuracy of prediction and expected genetic gain given by SI‐U and AM‐I were similar to those given by SI‐A and AM‐E, respectively. However, the differences in accuracy and expected gain between SI‐U and AI‐A and between AM‐I and AM‐E increased as the range of ASEE increased. It was concluded that selection based on an animal model was more effective than index selection, even if the herd environment was uniform and traits with high heritability were selected, and that it should be always included in an evaluation model, however slight any systematic environmental effect may be in a closed herd.     

Determining the stability of accuracy of genomic estimated breeding values in future generations in commercial pig populations

Genomic information has a limited dimensionality (number of independent chromosome segments [M_e]) related to the effective population size. Under the additive model, the persistence of genomic accuracies over generations should be high when the nongenomic information (pedigree and phenotypes) is equivalent to M_e animals with high accuracy. The objective of this study was to evaluate the decay in accuracy over time and to compare the magnitude of decay with varying quantities of data and with traits of low and moderate heritability. The dataset included 161,897 phenotypic records for a growth trait (GT) and 27,669 phenotypic records for a fitness trait (FT) related to prolificacy in a population with dimensionality around 5,000. The pedigree included 404,979 animals from 2008 to 2020, of which 55,118 were genotyped. Two single-trait models were used with all ancestral data and sliding subsets of 3-, 2-, and 1-generation intervals. Single-step genomic best linear unbiased prediction (ssGBLUP) was used to compute genomic estimated breeding values (GEBV). Estimated accuracies were calculated by the linear regression (LR) method. The validation population consisted of single generations succeeding the training population and continued forward for all generations available. The average accuracy for the first generation after training with all ancestral data was 0.69 and 0.46 for GT and FT, respectively. The average decay in accuracy from the first generation after training to generation 9 was −0.13 and −0.19 for GT and FT, respectively. The persistence of accuracy improves with more data. Old data have a limited impact on the predictions for young animals for a trait with a large amount of information but a bigger impact for a trait with less information.     

Ketoprofen pharmacokinetics of R‐ and S‐isomers in juvenile loggerhead sea turtles (Caretta caretta) after single intravenous and single‐ and multidose intramuscular administration

Ketoprofen is a nonsteroidal anti‐inflammatory and analgesic agent that nonselectively inhibits cyclooxygenase, with both COX‐1 and COX‐2 inhibition. Recent studies on COX receptor expression in reptiles suggest that nonselective COX inhibitors may be more appropriate than more selective inhibitors in some reptiles, but few pharmacokinetic studies are available. The goal of this study was to determine single‐ and multidose (three consecutive days) pharmacokinetics of racemic ketoprofen administered intravenously and intramuscularly at 2 mg/kg in healthy juvenile loggerhead turtles (Caretta caretta). The S‐isomer is the predominant isomer in loggerhead sea turtles, similar to most mammals, despite administration of a 50:50 racemic mixture. Multidose ketoprofen administration demonstrated no bioaccumulation; therefore, once‐daily dosing will not require dose adjustment over time. S‐isomer pharmacokinetic parameters determined in this study were C_max of 10.1 μg/ml by IM injection, C₀ of 13.4 μg/ml by IV injection, AUC of 44.7 or 69.4 μg*hr/ml by IM or IV injection, respectively, and T½ of 2.8 or 3.6 hr by IM or IV injection, respectively. Total ketoprofen plasma concentrations were maintained for at least 12 hr above concentrations determined to be effective for rats and humans. A dose of 2 mg/kg either IM or IV every 24 hr is likely appropriate for loggerhead turtles.     

IL‐12p40 gene expression in lung and hilar lymph nodes of MPS‐resistant pigs

Mycoplasma pneumonia of swine (MPS) is caused by Mycoplasma hyopneumoniae (M.hp) and is a common chronic respiratory disease of pigs. Recently, a genetically selected variant of the Landrace pig (Miyagino L2) has a lower incidence of pulmonary MPS lesions. We investigated the pathological and immunological characteristics of MPS resistance in these pigs (n = 24) by comparing with the normal landrace pig (control: n = 24). The pathological MPS lung lesion score in MPS‐selected landrace pigs was significantly lower than in the control. The gene expression of interleukin (IL)‐12p40, which acts as a chemoattractant and a component of the bioactive cytokines IL‐12 and IL‐23, was significantly higher at the hilar lymph nodes, lung, and spleen in MPS‐selected landrace pigs than in control landrace pigs, and these were negatively correlated with the macroscopic MPS lung lesion score. In summary, we demonstrate that resistance against MPS in Miyagino L2 pigs is associated with IL‐12p40 up‐regulation, in comparison with normal landrace pigs without the MPS vaccine. In addition, a comparative study of macroscopic MPS lung lesions and IL‐12p40 gene expression in lung and hilar lymph nodes may lead to beneficial selection traits for the genetic selection for MPS resistance in pigs.     

Use of molecular markers to improve relationship information in the genetic evaluation of beef cattle tick resistance under pedigree‐based models

The selection of genetically superior individuals is conditional upon accurate breeding value predictions which, in turn, are highly depend on how precisely relationship is represented by pedigree. For that purpose, the numerator relationship matrix is essential as a priori information in mixed model equations. The presence of pedigree errors and/or the lack of relationship information affect the genetic gain because it reduces the correlation between the true and estimated breeding values. Thus, this study aimed to evaluate the effects of correcting the pedigree relationships using single‐nucleotide polymorphism (SNP) markers on genetic evaluation accuracies for resistance of beef cattle to ticks. Tick count data from Hereford and Braford cattle breeds were used as phenotype. Genotyping was carried out using a high‐density panel (BovineHD ‐ Illumina^® bead chip with 777 962 SNPs) for sires and the Illumina BovineSNP50 panel (54 609 SNPs) for their progenies. The relationship between the parents and progenies of genotyped animals was evaluated, and mismatches were based on the Mendelian conflicts counts. Variance components and genetic parameters estimates were obtained using a Bayesian approach via Gibbs sampling, and the breeding values were predicted assuming a repeatability model. A total of 460 corrections in relationship definitions were made (Table 1) corresponding to 1018 (9.5%) tick count records. Among these changes, 97.17% (447) were related to the sire's information, and 2.8% (13) were related to the dam's information. We observed 27.2% (236/868) of Mendelian conflicts for sire–progeny genotyped pairs and 14.3% (13/91) for dam–progeny genotyped pairs. We performed 2174 new definitions of half‐siblings according to the correlation coefficient between the coancestry and molecular coancestry matrices. It was observed that higher‐quality genetic relationships did not result in significant differences of variance components estimates; however, they resulted in more accurate breeding values predictions. Using SNPs to assess conflicts between parents and progenies increases certainty in relationships and consequently the accuracy of breeding value predictions of candidate animals for selection. Thus, higher genetic gains are expected when compared to the traditional non‐corrected relationship matrix.     

A comparison of accuracy validation methods for genomic and pedigree‐based predictions of swine litter size traits using Large White and simulated data

The objective of this study was to compare and determine the optimal validation method when comparing accuracy from single‐step GBLUP (ssGBLUP) to traditional pedigree‐based BLUP. Field data included six litter size traits. Simulated data included ten replicates designed to mimic the field data in order to determine the method that was closest to the true accuracy. Data were split into training and validation sets. The methods used were as follows: (i) theoretical accuracy derived from the prediction error variance (PEV) of the direct inverse (iLHS), (ii) approximated accuracies from the accf90(GS) program in the BLUPF90 family of programs (Approx), (iii) correlation between predictions and the single‐step GEBVs from the full data set (GEBV_Full), (iv) correlation between predictions and the corrected phenotypes of females from the full data set (Y_c), (v) correlation from method iv divided by the square root of the heritability (Y_ch) and (vi) correlation between sire predictions and the average of their daughters' corrected phenotypes (Y_cs). Accuracies from iLHS increased from 0.27 to 0.37 (37%) in the Large White. Approximation accuracies were very consistent and close in absolute value (0.41 to 0.43). Both iLHS and Approx were much less variable than the corrected phenotype methods (ranging from 0.04 to 0.27). On average, simulated data showed an increase in accuracy from 0.34 to 0.44 (29%) using ssGBLUP. Both iLHS and Y_ch approximated the increase well, 0.30 to 0.46 and 0.36 to 0.45, respectively. GEBV_Full performed poorly in both data sets and is not recommended. Results suggest that for within‐breed selection, theoretical accuracy using PEV was consistent and accurate. When direct inversion is infeasible to get the PEV, correlating predictions to the corrected phenotypes divided by the square root of heritability is adequate given a large enough validation data set.     

Pulmonary pharmacokinetics of tulathromycin in swine. Part 2: Intra‐airways compartments

The objective of this study was to assess the pharmacokinetics of tulathromycin in pulmonary and bronchial epithelial lining fluid (PELF and BELF) from pigs. Clinically healthy pigs were allocated to two groups of 36 animals each. All animals were treated with tulathromycin (2.5 mg/kg/i.m). Animals in group 2 were also challenged intratracheally with lipopolysaccharide from Escherichia coli 3 h prior to tulathromycin administration. Both PELF and BELF samples were harvested using bronchoalveolar lavage fluid and bronchial micro‐sampling probes, respectively. Samples were taken for 17 days post‐tulathromycin administration. No statistical differences in the concentration of tulathromycin were observed in PELF between groups. The concentration vs. time profile in BELF was evaluated only in Group 1. Tulathromycin distributed rapidly and extensively into the airway compartments. The time to maximal (T_max) concentration was 6 h postdrug administration in PELF but 72 h post‐tulathromycin administration for BELF. In group 2, the T_max was seen at 24 h post‐tulathromycin administration. The area under the concentration time curve (h*ng/mL) was 522 000, 348 000 and 1 290 000 for PELF_Group‐1, PELF_Group‐2, and BELF_Group‐1, respectively. Tulathromycin not only distributed rapidly into intra‐airway compartments at relatively high concentrations but also resided in the airway lining fluid for a long time (>4 days).     

Integration of pharmacokinetic–pharmacodynamic for dose optimization of doxycycline against Haemophilus parasuis in pigs

The aims of this study were to establish optimal doses of doxycycline (dox) against Haemophilus parasuis on the basis of pharmacokinetic–pharmacodynamic (PK‐PD) integration modeling. The infected model was established by intranasal inoculation of organism in pigs and confirmed by clinical signs, blood biochemistry, and microscopic examinations. The recommended dose (20 mg/kg b.w.) was administered in pigs through intramuscular routes for PK studies. The area under the concentration 0‐ to 24‐hr curve (AUC_0–24), elimination half‐life (T_½ke), and mean residence time (MRT) of dox in healthy and H. parasuis‐infected pigs were 55.51 ± 5.72 versus 57.10 ± 4.89 μg·hr/ml, 8.28 ± 0.91 versus 9.80 ± 2.38 hr, and 8.43 ± 0.27 versus 8.79 ± 0.18 hr, respectively. The minimal inhibitory concentration (MIC) of dox against 40 H. parasuis isolates was conducted through broth microdilution method, the corresponding MIC₅₀ and MIC₉₀ were 0.25 and 1 μg/ml, respectively. The Ex vivo growth inhibition data suggested that dox exhibited a concentration‐dependent killing mechanism. Based on the observed AUC_24 hr/MIC values by modeling PK‐PD data in H. parasuis‐infected pigs, the doses predicted to obtain bacteriostatic, bactericidal, and elimination effects for H. parasuis over 24 hr were 5.25, 8.55, and 10.37 mg/kg for the 50% target attainment rate (TAR), and 7.26, 13.82, and 18.17 mg/kg for 90% TAR, respectively. This study provided a more optimized alternative for clinical use and demonstrated that the dosage 20 mg/kg of dox by intramuscular administration could have an effective bactericidal activity against H. parasuis.     

Genome‐wide association studies reveal additional related loci for fatty acid composition in a Duroc pig multigenerational population

The aim of the present study was to detect quantitative trait loci affecting fatty acid composition in back fat and intramuscular fat in a Duroc pig population comprising seventh‐generation pedigrees using genome‐wide association studies (GWAS). In total, 305 animals were genotyped using single nucleotide polymorphisms (SNPs) array and five selected SNPs from regions containing known candidate genes related to fatty acid synthesis or metabolism. In total, 24 genome‐wide significant SNP regions were detected in 12 traits, and 76 genome‐wide suggestive SNP regions were detected in 33 traits. The Sus scrofa chromosome (SSC) 7 at 10.3 Mb was significantly associated with C17:0 in intramuscular fat, while the SSC9 at 13.6 Mb was significantly associated with C14:0 in intramuscular fat. The SSC12 at 1.0 Mb was significantly associated with C14:0 in back fat and the SSC14 at 121.0 Mb was significantly associated with C18:0 in intramuscular fat. These regions not only replicated previously reported loci containing some candidate genes involved in fatty acid composition (fatty acid synthase and stearoyl‐CoA desaturase) but also included several additional related loci.     

Influence of On‐farm pig Salmonella status on Salmonella Shedding at Slaughter

The risk of Salmonella shedding among pigs at slaughter with regard to their previous on‐farm Salmonella status was assessed in a group of pigs from a farm from NE of Spain. A total of 202 pigs that had been serologically monitored monthly during the fattening period and from which mesenteric lymph nodes (MLN) and faecal (SFEC) samples were collected at slaughter for Salmonella isolation were included. A repeated‐measures anova was used to assess the relationship between mean OD% values during the fattening period and sampling time and bacteriology on MLN and SFEC. Pigs were also grouped into four groups, that is pigs seronegative during the fattening period and Salmonella negative in MLN (group A; n = 69); pigs seronegative during the fattening period but Salmonella positive in MLN (B; n = 36); pigs seropositive at least once and Salmonella positive in MLN (C; n = 50); and pigs seropositive at least once but Salmonella negative in (D; n = 47). Pigs shedding at slaughter seroconverted much earlier and showed much higher mean OD% values than non‐shedders pigs. The proportion of Salmonella shedders in groups A and D was high and similar (26.1% and 29.8%, respectively), but significantly lower than that for groups B and C. The odds of shedding Salmonella for groups B and C were 4.8 (95% CI = 1.5–15.5) and 20.9 (3.7–118) times higher, respectively, when compared to A. It was concluded that a large proportion of Salmonella seronegative pigs may shed Salmonella at slaughter, which would be likely associated to previous exposure with contaminated environments (i.e. transport and lairage). For pigs already infected at farm, the likelihood of shedding Salmonella was much higher and may depend on whether the bacterium has colonized the MLN or not. The odds of shedding Salmonella spp. were always much higher for pigs in which Salmonella was isolated from MLN.     

Allelic frequencies of PRKAG3 in several pig breeds and its technological consequences on a Duroc × Landrace‐Large White cross

The allelic frequencies of PRKAG3 gene (the RN gene) have been investigated in several pig breeds. R200Q mutation appear only in Hampshire pigs, whereas V199I mutation is most abundant in Iberian, Porco Celta or Bizaro, and less in breeds selected for muscularity as Duroc, Landrace and Pietrain. A thorough study of phenotypic effects of V1991 has been performed in a Duroc × Landrace‐Large White cross. 199I homozygous pigs show increased pH₂₄ values in ham homogenates and loin (0.14 and 0.16 pH units, respectively) compared to 199V homozygous ones. Meat of 199I homozygous pigs exudates 42.6% less fluid and is darker (2.46 ‘L’‐value units). 199I homozygous pigs are fatter (4.2 mm more backfat thickness) and contain less muscle mass in ham (1.0 percentage points) and shoulder (2.7 percentage points), than 199V homozygous ones. 199I homozygous pigs contain 7.3% less protein in the belly and 8.5% more fat in shoulder muscle mass than 199V homozygous pigs. 199I homozygous pigs have also superior functional properties: better gelling (22.8% larger G′ value) and emulsion capacities (14 percentage points less of total exuded fluid), and higher curing yield in the belly (6 percentage points more). These data support the adipogenic character of the V199I mutation. The advantages and disadvantages of selecting any of the two PRKAG3 alleles for position 199 are discussed.     

Meat Juice Serology and Improved Food Chain Information as Control Tools for Pork‐Related Public Health Hazards

The seroprevalence of Salmonella spp., pathogenic Yersinia spp., Toxoplasma gondii and Trichinella spp. was studied in 1353 finishing pigs from 259 farms that were allocated according to farm types: large fattening farms (≥1000 pig places), small fattening farms (< 1000 pig places) and farrow‐to‐finish farms. The antibodies were analysed with commercial ELISA kits in meat juice samples that were collected at Finnish slaughterhouses. Salmonella antibodies were rare (3% of pigs, 14% of farms) when the cut‐off optical density (OD) value 0.2 was used. Antibodies to pathogenic Yersinia spp. and T. gondii were detected in 57% of pigs and 85% of farms (OD ≥0.3) and in 3% of pigs and 9% of farms (OD ≥0.15), respectively. No antibodies to Trichinella spp. were detected (OD ≥0.3). The European Food Safety Authority (EFSA) considers Salmonella spp., Yersinia enterocolitica, T. gondii and Trichinella spp. as the most relevant biological hazards in the context of meat inspection of pigs. The seroprevalence of these important zoonotic pathogens was low in Finland, except that of Yersinia. The seroprevalence of Toxoplasma was significantly higher in pigs originating from small‐scale fattening farms (P < 0.05). Strong positive correlation was observed at the animal level between Salmonella and Yersinia seropositivity and between Salmonella and Toxoplasma seropositivity (P < 0.05). We suggest that these results reflect the level and importance of biosecurity measures applied on the farms. Meat juice serology at slaughter is a useful tool for targeting measures to control these pathogens. The information obtained from analyses should be used as part of the food chain information (FCI).     

Comparative pharmacokinetics of florfenicol in healthy and Pasteurella multocida‐infected Gaoyou ducks

Pasteurella multocida is the causative agent of fowl cholera, and florfenicol (FF) has potent antibacterial activity against P. multocida and is widely used in the poultry industry. In this study, we established a P. multocida infection model in ducks and studied the pharmacokinetics of FF in serum and lung tissues after oral administration of 30 mg/kg bodyweight. The maximum concentrations reached (C_max) were lower in infected ducks (13.88 ± 2.70 μg/ml) vs. healthy control animals (17.86 ± 1.57 μg/ml). In contrast, the mean residence time (MRT: 2.35 ± 0.13 vs. 2.27 ± 0.18 hr) and elimination half‐life (T_½β: 1.63 ± 0.08 vs. 1.57 ± 0.12 hr) were similar for healthy and diseased animals, respectively. As a result, the area under the concentration curve for 0–12 hr (AUC_0–12 hr) for FF in healthy ducks was significantly greater than that in infected ducks (49.47 ± 5.31 vs. 34.52 ± 8.29 μg hr/ml). The pharmacokinetic differences of FF in lung tissues between the two groups correlated with the serum pharmacokinetic differences. The C_max and AUC_0–12 hr values of lung tissue in healthy ducks were higher than those in diseased ducks. The concentration of FF in lung tissues was approximately 1.2‐fold higher than that in serum both in infected and healthy ducks indicating that FF is effective in treating respiratory tract infections in ducks.     

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

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