Evaluation of Precision Livestock Technology and Human Scoring of Nursery Pigs in a Controlled Immune Challenge Experiment.

The objectives were to determine the sensitivity, specificity, and cutoff values of a visual-based precision livestock technology (NUtrack), and determine the sensitivity and specificity of sickness score data collected with the live observation by trained human observers. At weaning, pigs (n = 192; gilts and barrows) were randomly assigned to one of twelve pens (16/pen) and treatments were randomly assigned to pens. Sham-pen pigs all received subcutaneous saline (3 mL). For LPS-pen pigs, all pigs received subcutaneous lipopolysaccharide (LPS; 300 µg/kg BW; E. coli O111:B4; in 3 mL of saline). For the last treatment, eight pigs were randomly assigned to receive LPS, and the other eight were sham (same methods as above; half-and-half pens). Human data from the day of the challenge presented high true positive and low false positive rates (88.5% sensitivity; 85.4% specificity; 0.871 Area Under Curve, AUC), however, these values declined when half-and-half pigs were scored (75% sensitivity; 65.5% specificity; 0.703 AUC). Precision technology measures had excellent AUC, sensitivity, and specificity for the first 72 h after treatment and AUC values were >0.970, regardless of pen treatment. These results indicate that precision technology has a greater potential for identifying pigs during a natural infectious disease event than trained professionals using timepoint sampling.

Evaluation of a novel computer vision-based livestock monitoring system to identify and track specific behaviors of individual nursery pigs within a group-housed environment.

Animal behavior is indicative of health status and changes in behavior can indicate health issues (i.e., illness, stress, or injury). Currently, human observation (HO) is the only method for detecting behavior changes that may indicate problems in group-housed pigs. While HO is effective, limitations exist. Limitations include HO being time consuming, HO obfuscates natural behaviors, and it is not possible to maintain continuous HO. To address these limitations, a computer vision platform (NUtrack) was developed to identify (ID) and continuously monitor specific behaviors of group-housed pigs on an individual basis. The objectives of this study were to evaluate the capabilities of the NUtrack system and evaluate changes in behavior patterns over time of group-housed nursery pigs. The NUtrack system was installed above four nursery pens to monitor the behavior of 28 newly weaned pigs during a 42-d nursery period. Pigs were stratified by sex, litter, and randomly assigned to one of two pens (14 pigs/pen) for the first 22 d. On day 23, pigs were split into four pens (7 pigs/pen). To evaluate the NUtrack system's capabilities, 800 video frames containing 11,200 individual observations were randomly selected across the nursery period. Each frame was visually evaluated to verify the NUtrack system's accuracy for ID and classification of behavior. The NUtrack system achieved an overall accuracy for ID of 95.6%. This accuracy for ID was 93.5% during the first 22 d and increased (P < 0.001) to 98.2% for the final 20 d. Of the ID errors, 72.2% were due to mislabeled ID and 27.8% were due to loss of ID. The NUtrack system classified lying, standing, walking, at the feeder (ATF), and at the waterer (ATW) behaviors accurately at a rate of 98.7%, 89.7%, 88.5%, 95.6%, and 79.9%, respectively. Behavior data indicated that the time budget for lying, standing, and walking in nursery pigs was 77.7% ± 1.6%, 8.5% ± 1.1%, and 2.9% ± 0.4%, respectively. In addition, behavior data indicated that nursery pigs spent 9.9% ± 1.7% and 1.0% ± 0.3% time ATF and ATW, respectively. Results suggest that the NUtrack system can detect, identify, maintain ID, and classify specific behavior of group-housed nursery pigs for the duration of the 42-d nursery period. Overall, results suggest that, with continued research, the NUtrack system may provide a viable real-time precision livestock tool with the ability to assist producers in monitoring behaviors and potential changes in the behavior of group-housed pigs.

Genetic diversity and detection of atypical porcine pestivirus infections.

Atypical porcine pestivirus (APPV), an RNA virus member of the Flaviviridae family, has been associated with congenital tremor in newborn piglets. Previously reported quantitative polymerase chain reaction (qPCR)-based assays were unable to detect APPV in novel cases of congenital tremor originated from multiple farms from U.S. Midwest (MW). These assays targeted the viral polyprotein coding genes, which were shown to display substantial variation, with sequence identity ranging from 58.2% to 70.7% among 15 global APPV strains. In contrast, the 5'-untranslated region (5' UTR) was found to have a much higher degree of sequence conservation. In order to obtain the complete 5' UTR of the APPV strains originated from MW, the 5' end of the viral cDNA was obtained by using template switching approach followed by amplification and dideoxy sequencing. Eighty one percent of the 5' UTR was identical across 14 global and 5 MW strains with complete or relatively complete 5' UTR. Notably, some of the most highly conserved 5' UTR segments overlapped with potentially important regions of an internal ribosome entry site (IRES), suggesting their functional role in viral protein translation. A newly designed single qPCR assay, targeting 100% conserved 5' UTR regions across 19 strains, was able to detect APPV in samples of well documented cases of congenital tremor which originated from five MW farm sites (1-18 samples/site). As these fully conserved 5' UTR sequences may have functional importance, we expect that assays targeting this region would broadly detect APPV strains that are diverse in space and time.

Bias in variance component estimation in swine crossbreeding schemes using selective genotyping and phenotyping strategies.

Selective genotyping of crossbred (CB) animals to include in traditionally purebred (PB) dominated genetic evaluations has been shown to provide an increase in the response to selection for CB performance. However, the inclusion of phenotypes from selectively genotyped CB animals, without the phenotypes of their non-genotyped cohorts, could cause bias in estimated variance components (VC) and subsequent estimated breeding values (EBV). The objective of the study was to determine the impact of selective CB genotyping on VC estimates and subsequent bias in EBV when non-genotyped CB animals are not included in genetic evaluations. A swine crossbreeding scheme producing 3-way CB animals was simulated to create selectively genotyped datasets. The breeding scheme consisted of three PB breeds each with 25 males and 450 females, F1 crosses with 1200 females and 12,000 CB progeny. Eighteen chromosomes each with 100 QTL and 4k SNP markers were simulated. Both PB and CB performances were considered to be moderately heritable (h2 = 0.4). Factors evaluated were as follows: 1) CB phenotype and genotype inclusion of 15% (n = 1800) or 35% (n = 4200), 2) genetic correlation between PB and CB performance (rpc = 0.1, 0.5, or 0.7), and 3) selective genotyping strategy. Genotyping strategies included the following: 1) Random: random CB selection, 2) Top: highest CB phenotype, and 3) Extreme: half highest and half lowest CB phenotypes. Top and Extreme selective genotyping strategies were considered by selecting animals in full-sib (FS) families or among the CB population (T). In each generation, 4320 PB selection candidates contributed phenotypic and genotypic records. Each scenario was replicated 15 times. VC were estimated for PB and CB performance utilizing bivariate models using pedigree relationships with dams of CB animals considered to be unknown. Estimated values of VC for PB performance were not statistically different from true values. Top selective genotyping strategies produced deflated estimates of phenotypic VC for CB performance compared to true values. When using estimated VC, Top_T and Extreme_T produced the most biased EBV, yet EBV of PB selection candidates for CB performance were most accurate when using Extreme_T. Results suggest that randomly selecting CB animals to genotype or selectively genotyping Top or Extreme CB animals within full-sib families can lead to accurate estimates of additive genetic VC for CB performance and unbiased EBV.

Selective genotyping and phenotypic data inclusion strategies of crossbred progeny for combined crossbred and purebred selection in swine breeding.

Inclusion of crossbred (CB) data into traditionally purebred (PB) genetic evaluations has been shown to increase the response in CB performance. Currently, it is unrealistic to collect data on all CB animals in swine production systems, thus, a subset of CB animals must be selected to contribute genomic/phenotypic information. The aim of this study was to evaluate selective genotyping strategies in a simulated 3-way swine crossbreeding scheme. The swine crossbreeding scheme was simulated and produced 3-way CB animals for 6 generations with 3 distinct PB breeds each with 25 and 175 mating males and females, respectively. F1 crosses (400 mating females) produced 4,000 terminal CB progeny which were subjected to selective genotyping. The genome consisted of 18 chromosomes with 1,800 QTL and 72k SNP markers. Selection was performed using estimated breeding values (EBV) for CB performance. It was assumed that both PB and CB performance was moderately heritable (h2=0.4). Several scenarios altering the genetic correlation between PB and CB performance (rpc=0.1, 0.3, 0.5, 0.7,or 0.9) were considered. CB animals were chosen based on phenotypes to select 200, 400, or 800 CB animals to genotype per generation. Selection strategies included: (1) Random: random selection, (2) Top: highest phenotype, (3) Bottom: lowest phenotype, (4) Extreme: half highest and half lowest phenotypes, and (5) Middle: average phenotype. Each selective genotyping strategy, except for Random, was considered by selecting animals in half-sib (HS) or full-sib (FS) families. The number of PB animals with genotypes and phenotypes each generation was fixed at 1,680. Each unique genotyping strategy and rpc scenario was replicated 10 times. Selection of CB animals based on the Extreme strategy resulted in the highest (P < 0.05) rates of genetic gain in CB performance (ΔG) when rpc<0.9. For highly correlated traits (rpc=0.9) selective genotyping did not impact (P > 0.05) ΔG. No differences (P > 0.05) were observed in ΔG between top, bottom, or middle when rpc>0.1. Higher correlations between true breeding values (TBV) and EBV were observed using Extreme when rpc<0.9. In general, family sampling method did not impact ΔG or the correlation between TBV and EBV. Overall, the Extreme genotyping strategy produced the greatest genetic gain and the highest correlations between TBV and EBV, suggesting that 2-tailed sampling of CB animals is the most informative when CB performance is the selection goal.

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.

Genomic Analysis of IgG Antibody Response to Common Pathogens in Commercial Sows in Health-Challenged Herds.

Losses due to infectious diseases are one of the main factors affecting productivity in the swine industry, motivating the investigation of disease resilience-related traits for genetic selection. However, these traits are not expected to be expressed in the nucleus herds, where selection is performed. One alternative is to use information from the commercial level to identify and select nucleus animals genetically superior for coping with pathogen challenges. In this study, we analyzed the genetic basis of antibody (Ab) response to common infectious pathogens in health-challenged commercial swine herds as potential indicator traits for disease resilience, including Ab response to influenza A virus of swine (IAV), Mycoplasma hyopneumoniae (MH), porcine circovirus (PCV2), and Actinobacillus pleuropneumoniae (APP; different serotypes). Ab response was measured in blood at entry into gilt rearing, post-acclimation (∼40 days after entering the commercial herd), and parities 1 and 2. Heritability estimates for Ab response to IAV, MH, and PCV2 ranged from 0 to 0.76. Ab response to APP ranged from 0 to 0.40. The genetic correlation (r G ) of Ab response to IAV with MH, PCV2, PRRSV, and APPmean (average Ab responses for all serotypes of APP) were positive (>0.29) at entry. APPmean was negatively correlated with PCV2 and MH at entry and parity 2 but positively correlated with MH at post-acclimation and parity 1. Genomic regions associated with Ab response to different APP serotypes were identified on 13 chromosomes. The region on chromosome 14 (2 Mb) was associated with several serotypes of APP, explaining up to 4.3% of the genetic variance of Ab to APP7 at entry. In general, genomic prediction accuracies for Ab response were low to moderate, except average Ab response to all infectious pathogens evaluated. These results suggest that genetic selection of Ab response in commercial sows is possible, but with variable success depending on the trait and the time-point of collection. Future work is needed to determine genetic correlations of Ab response with disease resilience, reproductive performance, and other production traits.

The effect of varicocele on semen quality in boars exposed to heat stress.

Semen quality has a dramatic impact on reproductive efficiency in the swine industry, influencing both conception rate and litter size. The objective of this study was to assess whether the presence of varicocele hinders semen quality in both thermoneutral and heat stress (HS) conditions. At approximately 6 mo of age, ultrasonography was used to measure left and right pampiniform plexus area in order to detect varicocele in maternal line boars at the University of Nebraska-Lincoln. Between 10 and 12 mo of age, semen was collected from each boar (n = 28) twice weekly. Boars were collected under thermoneutral conditions, were then heat stressed for 7 d to exacerbate any semen quality issues, and semen was collected post-HS for 6 wk. Sperm characteristics were determined by computer-assisted semen analysis. The presence of varicocele had a significant effect on sperm concentration (P = 0.04) and trended toward significance for mean sperm head area (P = 0.06) throughout the duration of the study. An interaction existed between varicocele and collection time point at weeks 2-5 post-HS for distal droplet percentage, suggesting that boars with varicocele were possibly more susceptible to heat-stress-induced semen quality issues than boars without varicocele. Moreover, semen quality was reduced in boars with versus without varicocele under both thermoneutral and HS conditions. Therefore, detection of varicocele by ultrasound could represent a potential marker of fertility in young boars or as a component trait in selection indices for fertility.

Detection of atypical porcine pestivirus genome in newborn piglets affected by congenital tremor and high preweaning mortality1.

Recently, piglets from a high-health status farm began exhibiting congenital tremors, high preweaning mortality and incidence of splayed legs. Postmortem histological examination identified a small number of scattered white matter vacuoles in the cerebellum and underlying brainstem of affected piglets. Presence of potential viral sources associated with this neurologic condition was initially infirmed using quantitative PCR for atypical porcine pestivirus (APPV), porcine teschovirus, and porcine sapelovirus. Using metagenomic analysis, APPV was identified as the main microbial species in serum obtained from piglets affected by congenital tremor. These piglets had higher preweaning mortality rates (46.4% vs. 15.3%) and incidence of splayed legs (33.0% vs. 0.8 %) compared to unaffected piglets. Piglets affected by congenital tremor had higher viral titer (P < 0.15) and larger birth weights (P < 0.05) compared to normal litter mates. Whole-genome sequencing and genome assembly of the novel APPV strain (MK728876) was carried out using Oxford Nanopore and related bioinformatics pipelines. Phylogenic analysis demonstrated that this strain along with other completely sequenced APPV strains were grouped into 2 clades, both including strains-inducing congenital tremor. Strains appear to cluster based on region but there were still significant differences within regions. Future research needs to address potential underdiagnosis due to genetic diversity but also to understand mode of transmission, variation in virulence, and the role of host genetics in APPV susceptibility.

The heritability of pampiniform plexus vessel size and varicocoele in boars.

Ultrasonography was used to capture a coronal-sagittal image of the veins of the pampiniform plexus (PP) and the testicular artery of 327 maternal-line boars at approximately 6 months of age at the University of Nebraska-Lincoln. Varicocoele was diagnosed by two methods. Method 1 diagnosed varicocoele when the average vessel area on one side of the scrotum was 1.5 times larger than the average vessel area on the other side of the scrotum. Method 2 diagnosed varicocoele when the average vessel area on one side of the scrotum of a boar was 1.5 times larger than the average vessel on the same side of the scrotum of the boar's cohorts (same population and year). Varicocoele was diagnosed in 23.17% and 15.1% of boars measured using method 1 and method 2, respectively. Ultrasonography showed to be an effective means to measure PP vessel size in boars and may even allow for earlier detection of varicocoele than by using palpation. Animal models were employed to estimate the heritability for: average area of right PP vessels (0.52), average area of the left PP vessels (0.46), varicocoele presence using method 1 (0.26) and varicocoele presence using method 2 (0.25). These heritability estimates suggest that vessel size and varicocoele could be selected against in breeding programmes to potentially improve boar semen quality.

Objective evaluation of female feet and leg joint conformation at time of selection and post first parity in swine1.

Feet and legs of replacement females were objectively evaluated at selection, i.e., approximately 150 d of age (n = 319) and post first parity, i.e., any time after weaning of first litter and before second parturition (n = 277) to 1) compare feet and leg joint angle ranges between selection and post first parity; 2) identify feet and leg joint angle differences between selection and first 3 wk of second gestation; 3) identify feet and leg joint angle differences between farms and gestation days during second gestation; and 4) obtain genetic variance components for conformation angles for the two time points measured. Angles for carpal joint (knee), metacarpophalangeal joint (front pastern), metatarsophalangeal joint (rear pastern), tarsal joint (hock), and rear stance were measured using image analysis software. Between selection and post first parity, significant differences were observed for all joints measured (P < 0.05). Knee, front and rear pastern angles were less (more flexion), and hock angles were greater (less flexion) as age progressed (P < 0.05), while the rear stance pattern was less (feet further under center) at selection than post first parity (only including measures during first 3 wk of second gestation). Only using post first parity leg conformation information, farm was a significant source of variation for front and rear pasterns and rear stance angle measurements (P < 0.05). Knee angle was less (more flexion; P < 0.05) as gestation age progressed. Heritability estimates were low to moderate (0.04-0.35) for all traits measured across time points. Genetic correlations between the same joints at different time points were high (>0.8) between the front leg joints and low (<0.2) between the rear leg joints. High genetic correlations between time points indicate that the trait can be considered the same at either time point, and low genetic correlations indicate that the trait at different time points should be considered as two separate traits. Minimal change in the front leg suggests conformation traits that remain between selection and post first parity, while larger changes in rear leg indicate that rear leg conformation traits should be evaluated at multiple time periods.

Genetic and genomic basis of antibody response to porcine reproductive and respiratory syndrome (PRRS) in gilts and sows.

BACKGROUND: Our recent research showed that antibody response to porcine reproductive and respiratory syndrome (PRRS), measured as sample-to-positive (S/P) ratio, is highly heritable and has a high genetic correlation with reproductive performance during a PRRS outbreak. Two major quantitative trait loci (QTL) on Sus scrofa chromosome 7 (SSC7; QTLMHC and QTL130) accounted for ~40 % of the genetic variance for S/P. Objectives of this study were to estimate genetic parameters for PRRS S/P in gilts during acclimation, identify regions associated with S/P, and evaluate the accuracy of genomic prediction of S/P across populations with different prevalences of PRRS and using different single nucleotide polymorphism (SNP) sets. METHODS: Phenotypes and high-density SNP genotypes of female pigs from two datasets were used. The outbreak dataset included 607 animals from one multiplier herd, whereas the gilt acclimation (GA) dataset included data on 2364 replacement gilts from seven breeding companies placed on health-challenged farms. Genomic prediction was evaluated using GA for training and validation, and using GA for training and outbreak for validation. Predictions were based on SNPs across the genome (SNPAll), SNPs in one (SNPMHC and SNP130) or both (SNPSSC7) QTL, or SNPs outside the QTL (SNPRest). RESULTS: Heritability of S/P in the GA dataset increased with the proportion of PRRS-positive animals in the herd (from 0.28 to 0.47). Genomic prediction accuracies ranged from low to moderate. Average accuracies were highest when using only the 269 SNPs in both QTL regions (SNPSSC7, with accuracies of 0.39 and 0.31 for outbreak and GA validation datasets, respectively. Average accuracies for SNPALL, SNPMHC, SNP130, and SNPRest were, respectively, 0.26, 0.39, 0.21, and 0.05 for the outbreak, and 0.28, 0.25, 0.22, and 0.12, for the GA validation datasets. CONCLUSIONS: Moderate genomic prediction accuracies can be obtained for PRRS antibody response using SNPs located within two major QTL on SSC7, while the rest of the genome showed limited predictive ability. Results were obtained using data from multiple genetic sources and farms, which further strengthens these findings. Further research is needed to validate the use of S/P ratio as an indicator trait for reproductive performance during PRRS outbreaks.

Large-scale association study for structural soundness and leg locomotion traits in the pig.

BACKGROUND: Identification and culling of replacement gilts with poor skeletal conformation and feet and leg (FL) unsoundness is an approach used to reduce sow culling and mortality rates in breeding stock. Few candidate genes related to soundness traits have been identified in the pig. METHODS: In this study, 2066 commercial females were scored for 17 traits describing body conformation and FL structure, and were used for association analyses. Genotyping of 121 SNPs derived from 95 genes was implemented using Sequenom's MassARRAY system. RESULTS: Based on the association results from single trait and principal components using mixed linear model analyses and false discovery rate testing, it was observed that APOE, BMP8, CALCR, COL1A2, COL9A1, DKFZ, FBN1 and VDBP were very highly significantly (P < 0.001) associated with body conformation traits. The genes ALOX5, BMP8, CALCR, OPG, OXTR and WNT16 were very highly significantly (P < 0.001) associated with FL structures, and APOE, CALCR, COL1A2, GNRHR, IHH, MTHFR and WNT16 were highly significantly (P < 0.01) associated with overall leg action. Strong linkage disequilibrium between CALCR and COL1A2 on SSC9 was detected, and haplotype -ACGACC- was highly significantly (P < 0.01) associated with overall leg action and several important FL soundness traits. CONCLUSION: The present findings provide a comprehensive list of candidate genes for further use in fine mapping and biological functional analyses.