Identifying Early-Life Behavior to Predict Mothering Ability in Swine Utilizing NU\u3ci\u3etrack\u3c/i\u3e System

Early indicator traits for swine reproduction and longevity support economical selection decision-making. Activity is a key variable impacting a sow’s herd life and productivity. Early-life activities could contribute to farrowing traits including gestation length (GL), number born alive (NBA), and number weaned (NW). Beginning at 20 weeks of age, 480 gilts were video recorded for 7 consecutive days and processed using the NUtrack system. Activity traits included angle rotated (radians), average speed (m/s), distance traveled (m), time spent eating (s), lying lateral (s), lying sternal (s), standing (s), and sitting (s). Final daily activity values were averaged across the period under cameras. Parity one data were collected for all gilts considered. Data were analyzed using linear regression models (R version 4.0.2). GL was significantly impacted by angle rotated (p = 0.03), average speed (p = 0.07), distance traveled (p = 0.05), time spent lying lateral (p = 0.003), and lying sternal (0.02). NBA was significantly impacted by time spent lying lateral (p = 0.01), lying sternal (p = 0.07), and time spent sitting (p = 0.08). NW was significantly impacted by time spent eating (p = 0.09), time spent lying lateral (p = 0.04), and time spent sitting (p = 0.007). This analysis suggests early-life gilt activities are associated with sow productivity traits of importance. Further examination of the link between behaviors compiled utilizing NUtrack and reproductive traits is necessitated to further isolate behavioral differences for potential use in selection decisions

Porcine Genomic Sequencing Initiative

Rationale and Objectives. Completion of the human genome sequence provides the starting point for understanding the genetic complexity of humans and how genetic variation contributes to diverse phenotypes and disease. It is clear that model organisms have played an invaluable role in the synthesis of this understanding. It is also noted that additional species must be sequenced to resolve the genetic complexity of human evolution and to effectively extrapolate genetic information from comparative (veterinary) medicine to human medicine. Certainly the pig has been a valuable biomedical model organism and its role will expand in the future. The pig also represents an evolutionary clade distinct from primates or rodents, and thus, provides considerable power in the analysis of human genomic sequences. The pig, a domesticated eutherian mammal, has co-evolved with humans and represents a taxa with diverse selected phenotypes [Rothschild and Ruvinsky, 1998]. The pig has a central position in the scientific and veterinary medical communities that supports the utility of securing genome sequence information. Thus, this white paper provides scientific justification for sequencing the porcine genome (6X coverage) to identify new genes and novel regulatory elements in the pig and in humans, mice and rats. The porcine genome will serve as a reference non-primate, non-rodent, eutherian genome. The recent ability to genetically modify the porcine genome, genetically manipulate embryonic fibroblasts, and �clone� genetically modified somatic cells through nuclear transfer attests to how the pig can provide relevant genetic models (of appropriate phenotypes). This further demonstrates the unique role the pig will play in biomedical research, hence warranting the value for genomic sequencing. The porcine genome is uniquely positioned for genomic sequencing because of the advanced stage of the necessary reagents. A porcine BAC map with 20X coverage, constructed via an international consortium, will be fingerprinted and all fingerprinted clones end-sequenced by June, 2003. This resource will permit selection of the minimum tilling path of BAC clones to be sequenced and complement a whole-genome shotgun sequencing approach. This approach was selected since its affords increased efficiency, saving time and money, and yields a better product since the BAC map will be completed prior to initiation of genomic sequencing. Linking the sequence to the BAC clone map allows for subsequent targeted closure of the genomic sequence in regions of particular interest. This strategy is justified through the outcomes associated with the human, mouse, and rat sequencing efforts that were done in parallel with the BAC map development

Determining the Presence and Size of Shoulder Lesions in Sows Using Computer Vision

Shoulder sores predominantly arise in breeding sows and often result in untimely culling. Reported prevalence rates vary significantly, spanning between 5% and 50% depending upon the type of crate flooring inside a farm, the animal’s body condition, or an existing injury that causes lameness. These lesions represent not only a welfare concern but also have an economic impact due to the labor needed for treatment and medication. The objective of this study was to evaluate the use of computer vision techniques in detecting and determining the size of shoulder lesions. A Microsoft Kinect V2 camera captured the top-down depth and RGB images of sows in farrowing crates. The RGB images were collected at a resolution of 1920 × 1080. To ensure the best view of the lesions, images were selected with sows lying on their right and left sides with all legs extended. A total of 824 RGB images from 70 sows with lesions at various stages of development were identified and annotated. Three deep learning-based object detection models, YOLOv5, YOLOv8, and Faster-RCNN, pre-trained with the COCO and ImageNet datasets, were implemented to localize the lesion area. YOLOv5 was the best predictor as it was able to detect lesions with an [email protected] of 0.92. To estimate the lesion area, lesion pixel segmentation was carried out on the localized region using traditional image processing techniques like Otsu’s binarization and adaptive thresholding alongside DL-based segmentation models based on U-Net architecture. In conclusion, this study demonstrates the potential of computer vision techniques in effectively detecting and assessing the size of shoulder lesions in breeding sows, providing a promising avenue for improving sow welfare and reducing economic losses

Rapid Communication: Genetic Linkage and Physical Mapping of the Porcine Androgen Receptor (AR) Gene

Source and Description of Primers. Primers were designed from published bovine and human androgen receptor (AR) sequences (GenBank accession number Z75315 and M27430, respectively). These primers were used to obtain a porcine sequence (submitted to GenBank: accession number AF079783). A total of 247 bp out of the entire 793-bp PCR product shared 90.3% identity with sections of exons 7 and 8 of the human AR gene. Porcine specific primers (AR-3 and AR-4) were then designed to amplify a 160-bp fragment in intron 7 of the AR gene region from porcine genomic DNA

Characterization of the aldo-keto reductase 1C gene cluster on pig chromosome 10: possible associations with reproductive traits

BACKGROUND: The rate of pubertal development and weaning to estrus interval are correlated and affect reproductive efficiency of swine. Quantitative trait loci (QTL) for age of puberty, nipple number and ovulation rate have been identified in Meishan crosses on pig chromosome 10q (SSC10) near the telomere, which is homologous to human chromosome 10p15 and contains an aldo-keto reductase (AKR) gene cluster with at least six family members. AKRs are tissue-specific hydroxysteroid dehydrogenases that interconvert weak steroid hormones to their more potent counterparts and regulate processes involved in development, homeostasis and reproduction. Because of their location in the swine genome and their implication in reproductive physiology, this gene cluster was characterized and evaluated for effects on reproductive traits in swine. RESULTS: Screening the porcine CHORI-242 BAC library with a full-length AKR1C4 cDNA identified 7 positive clones and sample sequencing of 5 BAC clones revealed 5 distinct AKR1C genes (AKR1CL2 and AKR1C1 through 4), which mapped to 126–128 cM on SSC10. Using the IMpRH(7000rad )and IMNpRH2(12000rad )radiation hybrid panels, these 5 genes mapped between microsatellite markers SWR67 and SW2067. Comparison of sequence data with the porcine BAC fingerprint map show that the cluster of genes resides in a 300 kb region. Twelve SNPs were genotyped in gilts observed for age at first estrus and ovulation rate from the F8 and F10 generations of one-quarter Meishan descendants of the USMARC resource population. Age at puberty, nipple number and ovulation rate data were analyzed for association with genotypes by MTDFREML using an animal model. One SNP, a phenylalanine to isoleucine substitution in AKR1C2, was associated with age of puberty (p = 0.07) and possibly ovulation rate (p = 0.102). Two SNP in AKR1C4 were significantly associated with nipple number (p ≤ 0.03) and another possibly associated with age at puberty (p = 0.09). CONCLUSION: AKR1C genotypes were associated with nipple number as well as possible effects on age at puberty and ovulation rate. The estimated effects of AKR1C genotypes on these traits suggest that the SNPs are in incomplete linkage disequilibrium with the causal mutations that affect reproductive traits in swine. Further investigations are necessary to identify these mutations and understand how these AKR1C genes affect these important reproductive traits. The nucleotide sequence data reported have been submitted to GenBank and assigned accession numbers [GenBank:DQ474064–DQ474068, GenBank:DQ494488–DQ494490 and GenBank:DQ487182–DQ487184]

Effects of Farrowing Stall Layout and Number of Heat Lamps on Sow and Piglet Production Performance

Most farrowing facilities in the United States use stalls and heat lamps to improve sow and piglet productivity. This study investigated these factors by comparing production outcomes for three different farrowing stall layouts (traditional, expanded creep area, expanded sow area) and use of one or two heat lamps. Data were collected on 427 sows and their litters over one year. Results showed no statistical differences due to experimental treatment for any of the production metrics recorded, excluding percent stillborn. Parity one sows had fewer piglets born alive (p \u3c 0.001), lower percent mortality (p = 0.001) and over-lay (p = 0.003), and a greater number of piglets weaned (p \u3c 0.001) with lower average daily weight gain (ADG) (p \u3c 0.001) and more uniform litters (p = 0.001) as compared to higher parity sows. Farrowing turn, associated with group/seasonal changes, had a significant impact on most of the production metrics measured. Number of piglets born influenced the percent stillborn (p \u3c 0.001). Adjusted litter size had a significant impact on percent mortality (p \u3c 0.001), percent over-lay (p \u3c 0.001), and number of piglets weaned (p \u3c 0.001). As the number of piglets weaned per litter increased, both piglet ADG and litter uniformity decreased (p \u3c 0.001). This information can be used to guide producers in farrowing facility design

Targeted oligonucleotide-mediated microsatellite identification (TOMMI) from large-insert library clones

BACKGROUND: In the last few years, microsatellites have become the most popular molecular marker system and have intensively been applied in genome mapping, biodiversity and phylogeny studies of livestock. Compared to single nucleotide polymorphism (SNP) as another popular marker system, microsatellites reveal obvious advantages. They are multi-allelic, possibly more polymorphic and cheaper to genotype. Calculations showed that a multi-allelic marker system always has more power to detect Linkage Disequilibrium (LD) than does a di-allelic marker system [1]. Traditional isolation methods using partial genomic libraries are time-consuming and cost-intensive. In order to directly generate microsatellites from large-insert libraries a sequencing approach with repeat-containing oligonucleotides is introduced. RESULTS: Seventeen porcine microsatellite markers were isolated from eleven PAC clones by targeted oligonucleotide-mediated microsatellite identification (TOMMI), an improved efficient and rapid flanking sequence-based approach for the isolation of STS-markers. With the application of TOMMI, an average of 1.55 (CA/GT) microsatellites per PAC clone was identified. The number of alleles, allele size distribution, polymorphism information content (PIC), average heterozygosity (H(T)), and effective allele number (N(E)) for the STS-markers were calculated using a sampling of 336 unrelated animals representing fifteen pig breeds (nine European and six Chinese breeds). Sixteen of the microsatellite markers proved to be polymorphic (2 to 22 alleles) in this heterogeneous sampling. Most of the publicly available (porcine) microsatellite amplicons range from approximately 80 bp to 200 bp. Here, we attempted to utilize as much sequence information as possible to develop STS-markers with larger amplicons. Indeed, fourteen of the seventeen STS-marker amplicons have minimal allele sizes of at least 200 bp. Thus, most of the generated STS-markers can easily be integrated into multilocus assays covering a broader separation spectrum. Linkage mapping results of the markers indicate their potential immediate use in QTL studies to further dissect trait associated chromosomal regions. CONCLUSION: The sequencing strategy described in this study provides a targeted, inexpensive and fast method to develop microsatellites from large-insert libraries. It is well suited to generate polymorphic markers for selected chromosomal regions, contigs of overlapping clones and yields sufficient high quality sequence data to develop amplicons greater than 250 bases

Targeted oligonucleotide-mediated microsatellite identification (TOMMI) from large-insert library clones

Background: In the last few years, microsatellites have become the most popular molecular marker system and have intensively been applied in genome mapping, biodiversity and phylogeny studies of livestock. Compared to single nucleotide polymorphism (SNP) as another popular marker system, microsatellites reveal obvious advantages. They are multi-allelic, possibly more polymorphic and cheaper to genotype. Calculations showed that a multi-allelic marker system always has more power to detect Linkage Disequilibrium (LD) than does a di-allelic marker system [1]. Traditional isolation methods using partial genomic libraries are time-consuming and costintensive. In order to directly generate microsatellites from large-insert libraries a sequencing approach with repeat-containing oligonucleotides is introduced. Results: Seventeen porcine microsatellite markers were isolated from eleven PAC clones by targeted oligonucleotide-mediated microsatellite identification (TOMMI), an improved efficient and rapid flanking sequence-based approach for the isolation of STS-markers. With the application of TOMMI, an average of 1.55 (CA/GT) microsatellites per PAC clone was identified. The number of alleles, allele size distribution, polymorphism information content (PIC), average heterozygosity (HT), and effective allele number (NE) for the STS-markers were calculated using a sampling of 336 unrelated animals representing fifteen pig breeds (nine European and six Chinese breeds). Sixteen of the microsatellite markers proved to be polymorphic (2 to 22 alleles) in this heterogeneous sampling. Most of the publicly available (porcine) microsatellite amplicons range from approximately 80 bp to 200 bp. Here, we attempted to utilize as much sequence information as possible to develop STS-markers with larger amplicons. Indeed, fourteen of the seventeen STS-marker amplicons have minimal allele sizes of at least 200 bp. Thus, most of the generated STS-markers can easily be integrated into multilocus assays covering a broader separation spectrum. Linkage mapping results of the markers indicate their potential immediate use in QTL studies to further dissect trait associated chromosomal regions. Conclusion: The sequencing strategy described in this study provides a targeted, inexpensive and fast method to develop microsatellites from large-insert libraries. It is well suited to generate polymorphic markers for selected chromosomal regions, contigs of overlapping clones and yields sufficient high quality sequence data to develop amplicons greater than 250 base

Effects of Farrowing Stall Layout and Number of Heat Lamps on Sow and Piglet Production Performance

Most farrowing facilities in the United States use stalls and heat lamps to improve sow and piglet productivity. This study investigated these factors by comparing production outcomes for three different farrowing stall layouts (traditional, expanded creep area, expanded sow area) and use of one or two heat lamps. Data were collected on 427 sows and their litters over one year. Results showed no statistical differences due to experimental treatment for any of the production metrics recorded, excluding percent stillborn. Parity one sows had fewer piglets born alive (p \u3c 0.001), lower percent mortality (p = 0.001) and over-lay (p = 0.003), and a greater number of piglets weaned (p \u3c 0.001) with lower average daily weight gain (ADG) (p \u3c 0.001) and more uniform litters (p = 0.001) as compared to higher parity sows. Farrowing turn, associated with group/seasonal changes, had a significant impact on most of the production metrics measured. Number of piglets born influenced the percent stillborn (p \u3c 0.001). Adjusted litter size had a significant impact on percent mortality (p \u3c 0.001), percent over-lay (p \u3c 0.001), and number of piglets weaned (p \u3c 0.001). As the number of piglets weaned per litter increased, both piglet ADG and litter uniformity decreased (p \u3c 0.001). This information can be used to guide producers in farrowing facility design

Statistical and machine learning approaches to describe factors affecting preweaning mortality of piglets

High preweaning mortality (PWM) rates for piglets are a significant concern for the worldwide pork industries, causing economic loss and well-being issues. This study focused on identifying the factors affecting PWM, overlays, and predicting PWM using historical production data with statistical and machine learning models. Data were collected from 1,982 litters from the U.S. Meat Animal Research Center, Nebraska, over the years 2016 to 2021. Sows were housed in a farrowing building with three rooms, each with 20 farrowing crates, and taken care of by well-trained animal caretakers. A generalized linear model was used to analyze the various sow, litter, environment, and piglet parameters on PWM. Then, different models (beta-regression and machine learning model: a random forest [RF]) were evaluated. Finally, the RF model was used to predict PWM and overlays for all listed contributing factors. On average, the mean birth weight was 1.44 kg, and the mean mortality was 16.1% where 5.55% was for stillbirths and 6.20% was contributed by overlays. No significant effect was found for seasonal and location variations on PWM. Significant differences were observed in the effects of litter lines on PWM (P \u3c 0.05). Landrace-sired litters had a PWM of 16.26% (±0.13), whereas Yorkshire-sired litters had 15.91% (±0.13). PWM increased with higher parity orders (P \u3c 0.05) due to larger litter sizes. The RF model provided the best fit for PWM prediction with a root mean squared errors of 2.28 and a correlation coefficient (r) of 0.89 between observed and predicted values. Features’ importance from the RF model indicated that, PWM increased with the increase of litter size (mean decrease accuracy (MDA) = 93.17), decrease in mean birth weight (MDA = 22.72), increase in health diagnosis (MDA = 15.34), longer gestation length (MDA = 11.77), and at older parity (MDA = 10.86). However, in this study, the location of the farrowing crate, seasonal differences, and litter line turned out to be the least important predictors for PWM. For overlays, parity order was the highest importance predictor (MDA = 7.68) followed by litter size and mean birth weight. Considering the challenges to reducing the PWM in the larger litters produced in modern swine industry and the limited studies exploring multiple major contributing factors, this study provides valuable insights for breeding and production management, as well as further investigations on postural transitions and behavior analysis of sows during the lactation period