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ARS Home Plains Area Clay Center, Nebraska U.S. Meat Animal Research Center Genetics and Animal Breeding Research





- Rohrer, Gary
- Nonneman, Danny - Dan
- Keel, Brittney
- 2023
- Publications
- Food Animal Production (101)

Research Project: Multi-Dimension Phenotyping to Enhance Prediction of Performance in Swine **Location:
                            Genetics and Animal Breeding** 2023 Annual Report **Objectives**
                                

Objective 1.  Identify proteins, genes, and quantitative trait loci associated with important phenotypes to improve efficiency of swine production.

Sub-objective 1.A: Improving methodologies to enhance the analysis of gene expression
data.
Sub-objective 1.B: Improve nutrient utilization and conversion of feed to muscle.
Sub-objective 1.C: Improve lifetime reproductive performance.

Objective 2.  Develop machine learning methods and artificial intelligence models that incorporate production data, biological assays, and data acquired via electronic monitoring.

Sub-objective 2.A: Enable prediction of animal performance to inform management decisions in real-time.
Sub-objective 2.B: Enhance selection decisions to improve performance of future generations. **Approach**
                                

Demand for pork products continues to grow, while producers are being asked to reduce their environmental impact; therefore, commercial swine production needs to reduce inefficiencies while continuing to improve product quality and quantity. Inefficiencies are magnified by a pig’s response to stressors encountered, whether these stressors are environmental (temperature), health (pathogens) or social interactions with pen-mates. The greatest opportunities for increased efficiency are to improve nutrient utilization and increase sow lifetime reproductive performance, by reducing reproductive failure and culling associated with lameness. These challenges are complex and require novel approaches to rapidly identify solutions. The proposed research will contribute to the development of more accurate computational tools for incorporating production data, biological assays, and data acquired via electronic monitoring into selection decisions. These tools will be crucial to create a catalogue of genetic variants that alter gene function (either in amount or function of protein) and trait expression. Putative functional genetic variants identified in our research population will be used to inform selection decisions in commercial populations once their effects have been validated. Our research will focus on identification of genetic markers responsible for variation in conversion of feed to pork product and lifetime reproductive performance in commercial sows. In addition to genetic variant discovery, tools developed in the proposed research will allow early identification of sick or stressed animals via real-time monitoring through electronic systems. This will improve animal welfare and reduce associated mitigation costs. The unique swine resources at USMARC will be coupled with our genomic capabilities to permit more accurate prediction of phenotypes or breeding values, contributing to the goals of National Program 101’s Action Plan. These predictions will inform herd management decisions, resulting in improved performance in current pigs as well as enhance selection decisions to create more productive pigs in future generations. **Progress Report**
                                

Several projects conducted have targeted improvement of methodologies for analyzing gene expression data (Objective 1A). It is well-known that livestock RNA-sequencing (RNA-Seq) experiments are often limited to a small number of replicates due to cost. This limitation hinders the statistical power of the experiments, which in turn decreases the robustness of the results. One way to improve reproducibility of RNA-Seq is by integrating data from multiple independent studies via meta-analysis. In FY2018, we reported the first livestock RNA-Seq meta-analysis for differential gene expression. Our proposed approach has begun to gain traction in the livestock genomics field.
A gene classification algorithm was generated to classify genes according to their expression distribution (Objective 1A). Collaborators from the Farm Animal Genotype-Tissue Expression (FarmGTEx; https://www.researchgate.net/project/FarmGTEx-Project) effort have provided us with gene expression data from 77 porcine tissues. Application of our classification algorithm to this data set is underway, which will result in a gene expression distribution library for each tissue. These expression libraries will be the basis for a novel approach for identifying differentially expressed genes, which is to be developed in the upcoming fiscal year (Objective 1A). 
Whole blood samples were taken at days 0 and 42 from 178 pigs that were monitored for individual feed intakes and body weight gain during a 6-week study. In FY2019 we reported generation of RNA-Seq data for these blood samples, and in FY2022 we reported analysis of blood cell parameters including white blood cell, neutrophil, lymphocyte, monocyte, eosinophil and basophil counts, red blood cell counts, hemoglobin, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin, platelet count, and mean platelet volume. Initial processing of the RNA-Seq data was performed. A total of 375 libraries were successfully sequenced, with an average of 38.4 million reads per library. An average of 91.5% per library mapped to the porcine reference genome. RNA-Seq data is currently being utilized to identify efficient and effective selection strategies for identifying quantitative trait-associated genes (Objective 1A).
We continue to collect feed intake and feeding behavior data to understand feed utilization in growing pigs (Objective 1B). Data collection was suspended during a disease outbreak, but we are on schedule to complete data collection on 4 groups of 196 pigs this year. Collection of genotypic data for all animals phenotyped prior to the disease outbreak has been completed to facilitate a genome wide association study (GWAS) for feed utilization.
For Objective 1C considerable progress has been made. Phenotypic data collection for the prediction of sow lameness has been completed along with collecting RNA-Seq and metabolomic data from whole blood on over 500 samples. Blood samples are from 176 sows and 324 gilts in two separate case-control experiments evaluating sow structural soundness. Cases for this study are animals that became lame while in the swine breeding herd and control animals are contemporary sows who remained sound during their production tenure. Individual and joint analyses of the transcriptomic and metabolomic data for prediction of early sow lameness is currently underway to determine if blood samples contain key biomarkers predictive of future sow lameness. Analysis of electronically captured data collected on gilts at 20 weeks of age have been completed resulting in several interesting findings. Activity and length of stride of gilts at 20 weeks of age is associated with their current structural soundness score and at least one activity measure was associated with future lameness. In addition, the phenotypes electronically collected were all heritable with most estimates of heritability between 0.2 and 0.3. 
We continue to utilize geophones to study sow behavior and piglet activity in farrowing pens. In addition, we have begun to evaluate the use of geophones as an objective method to measure animal mobility. Data have been collected on 26 animals and we plan to conduct another session of data collection in the near future (Objective 1C).
Finally, a significant proportion of sows have ovulation rates too low to meet the litter size goals of commercial producers today. In a study to identify genes that affect litter size, RNA-seq libraries were constructed and sequenced from ovarian tissue of sows that were most extreme for differences in ovulation rate at harvest and litter size through four parities. These data were analyzed for differential gene expression and to detect biological pathways related to litter size and ovulation rate (Objective 1C). Four hundred sixty-two genes comprised of 520 transcripts were differentially expressed in the ovary with most genes and transcripts being more highly expressed in more productive sows with larger litter size and ovulation rate. These genes are primarily involved in neural signaling pathways. There were 71 quantitative trait loci associations for litter traits (total number born or born alive and ovulation rate) found within 65 of these differentially expressed genes, some of which are known to affect litter size or ovulation rate (BMP4 and BMPR1B).
Clay Center, Nebraska, currently possesses feeding behavior data for more than 12,000 pigs and continues to add data for approximately 1,900 pigs every year. For pigs in the grow-finish phase of production, we have two different computer automated feeding systems capable of capturing individual animal feeding behavior, the single animal Osborne FIRE feeder system and an in-house designed multi-animal feeder. In FY2022, feeding behavior data from twelve contemporary groups, collected from the in-house designed feeder, were collated and analyzed (Objective 2A). Four modeling frameworks were developed and evaluated for predicting individual animal feeding behavior. Analyses to identify deviations in feeding behavior associated with health conditions is currently underway. Additional data collection has continued to facilitate model development to predict animal behaviors. We have begun to collect environmental data inside barns to improve our ability to model effects of air temperature and humidity. Also, a new experiment has been designed to expand our data collection and include monitoring a pig’s access to water and determine how animal-animal interactions alter animal behavior and well-being. **Accomplishments**
                                

1. Measures of activity in growing pigs at 20 weeks of age are associated with performance as a sow. Swine producers would like to select replacement females that will be structurally sound throughout their productive life. Despite close inspection of potential replacements for structural soundness, many females become lame and are prematurely culled from the herd. Culling for lameness is the second most common reason for removal and results in a lame sow having 1.4 fewer litters than her contemporaries. In an attempt to develop objective methods to identify early factors associated with lameness as an adult, ARS researchers in Clay Center, Nebraska, in collaboration with University of Nebraska-Lincoln, used 1 week of continuous video data processed with the NUtrack software to measure activity of each female at 20 weeks of age. These measures were then associated with the animal’s final disposition (culled for other reasons, culled for lameness, or remained sound throughout production). These results indicate that animals that walk a greater distance and change directions more often at 20 weeks of age are more likely to be retained for breeding and have a lesser chance of becoming lame as an adult. Approximately 300,000 sows in the United States are prematurely culled each year for lameness. This assessment could assist producers in selecting replacement animals that will remain mobile and produce more litters resulting in improved lifetime performance, animal well-being and reduce the number of sows prematurely culled prior to achieving a positive net-present value. 2. Development of a reference data set of tissue specific markers for whole blood. Whole blood has become increasingly utilized in RNA-sequencing (RNA-Seq) analysis because it is easily accessible and can be collected from live animals with minimal invasiveness. However, whole blood represents an extremely complex mixture of cell types, and differences in cell types can confound statistical analyses of the data. Statistical approaches have been developed to estimate cell type proportions directly from RNA-Seq data. Statistical estimation procedures require a reference data set for the cell types of interest, but reference data is available for only a small number of blood cell types in pigs. ARS researchers at Clay Center, Nebraska, developed a manually curated reference set of porcine blood cell markers using publicly available swine genomics data and complementary genomics data from human and mouse. The reference data set can be utilized to obtain estimates of cell type proportions of neutrophils, lymphocytes, monocytes, eosinophils, basophils, and red blood cells. Estimates for these cell types can then be used in downstream statistical models analyzing transcriptomic data to adjust for potential confounding effects of cell composition. This reference set will serve as a valuable resource for estimating cell proportions from porcine whole blood when other quantitative measurements are unavailable, improving the power of new experiments that rely on RNA-Seq analyses. 3. Discovery of differences in genes expressed in the hypothalamus are related to feed efficiency. Feed represents two-thirds or more of the cost of swine production and feed is utilized with a relatively low efficiency. Improving the efficiency of the conversion of feed into edible product has the potential to improve the economic efficiency of animal production while also improving the environmental sustainability of animal agriculture. Thus, an understanding of differentially expressed genes and their pathways in pigs of high versus low feed efficiency phenotypes would provide tremendous benefit. ARS researchers in Clay Center, Nebraska, described the expression of genes in the hypothalamus of pigs that differ in efficient feed conversion. Data were collected from 14 gilts and 16 barrows across four cohorts. Using a meta-analysis procedure across the four cohorts, a total of 91 genes were differentially expressed between efficient and inefficient pigs and several of them help to explain, at least in part, efficiency differences. Understanding the relationships between these genes will enable producers to select for more efficient breeding stock that will improve feed efficiency in growing pigs. 4. Relationships between estimated breeding values for age at puberty, birth weight, and adolescent growth in normal cycling and acyclic gilts. Managing replacement gilts to reach optimal body weight and growth rate for early puberty is a key component for sow reproductive longevity and producer profitability. Puberty is metabolically regulated so evaluating phenotypic and genetic relationships between birth weight and growth traits with age at puberty and acyclicity can provide insight for efficient and effective gilt development. ARS researchers at Clay Center, Nebraska, studied litter of origin effects, average daily gain at different stages of development, and age at puberty for age-matched cyclic 4,861 animals and acyclic gilts (578 prepubertal anestrus animals; 428 behavioral anestrus animals). Genomic estimated breeding values were predicted for each trait. First parity sows produced significantly more acyclic gilts than later parity sows. Accounting for effects of parity and litter size, prepubertal anestrus gilts were heavier at birth and behaviorally anestrus gilts grew faster during finisher period compared to cyclic gilts, suggesting antagonistic effects between growth and expression of estrus. Genome-wide association for lifetime growth rate identified the melanocortin receptor 4 (MC4R) gene in the quantitative trait loci (QTL) with the largest effect; there was no overlap of QTL for growth with QTL identified for age at puberty. This study identified differences in birth weight and growth rate between cyclic and acyclic gilts. For producers, avoiding the smallest and largest gilts in a cohort will result in gilts with optimal development potential and should reduce the proportion of replacement gilts that are acyclic. 5. Clustering hypothalamic–pituitary–ovarian axis transcriptomes in prepubertal anestrus and cyclic gilts reveals genes related to puberty. Failure to reach puberty is one of the main reasons gilts are culled and cost the industry approximately $100 for each gilt culled, or nearly $20 million annually in the U.S. Although initiation of puberty and first estrus in gilts involves communication between olfactory, neural, anterior pituitary, and ovarian tissues, there have been no studies in which these tissues have been simultaneously examined to better understand collective relationships between them and how differences may be related to delayed puberty. ARS scientists at Clay Center, Nebraska, performed RNA-sequencing gene expression analyses on tissues from neurological regions including olfactory bulb, mediobasal hypothalamus, amygdala, hippocampus, as well as anterior pituitary and ovarian cortex from delayed puberty and age-matched normal cyclic control gilts in midluteal and follicular phases (8 gilts form each reproductive state) of the estrous cycle. A three-way gene x individual x tissue clustering was performed to obtain gene expression modules to simultaneously explore transcriptome variation across individuals and tissues. Networks of genes expressed in pituitary and ovary contributing to regulation of pubertal development were identified. Specifically, OXTR, RUNX2 (ovary), and PRL (pituitary) being less expressed in delayed puberty compared to follicular cyclic gilts and IGF1R (ovary) being more highly expressed in delayed puberty compared to midluteal cyclic gilts. These data provide new insight into complex cross-tissue gene expression and candidate gene pathways to improve both attainment of puberty in gilts and subsequent and sow fertility traits. 6. A pig genotype-tissue expression resource is developed. The Farm animal Genotype-Tissue Expression (FarmGTEx) project has been established by an international consortium to develop a comprehensive public resource of genetic regulatory variants in domestic animal species. This resource, is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biology discovery and exploitation in animal breeding and human biomedicine. ARS researchers in Clay Center, Nebraska, contributed to the pilot phase of PigGTEx, where 9,530 RNA-sequencing and 1,602 whole-genome sequencing samples from pigs have been processed. A pig genotype imputation panel was built, the transcriptional landscape across over 100 tissues were characterized, and millions of genetic variants with five types of transcriptomic phenotypes were identified. Leveraging this resource, regulatory mechanisms underlying about 80% of the genetic associations for 207 pig complex phenotypes were deciphered, and the similarity of pigs to humans in gene expression was demonstrated. The PigGTEx project will serve as a critical genetic/genomic resource for both researchers in the swine genomics community and researchers using pigs as a human biomedical model. **Review Publications**
                            *Rempel, L.A., Keel, B.N., Oliver, W.T., Wells, J.E., Lents, C.A., Nonneman, D.J., Rohrer, G.A. 2022. Dam parity structure and body condition during lactation influence piglet growth and gilt sexual maturation through pre-finishing. Journal of Animal Science. 100(4):1-9. Article skac031. https://doi.org/10.1093/jas/skac031.*
                                *Wijesena, H.R., Nonneman, D.J., Snelling, W.M., Rohrer, G.A., Keel, B.N., Lents, C.A. 2023. gBLUP-GWAS identifies candidate genes, signaling pathways, and putative functional polymorphisms for age at puberty in gilts. Journal of Animal Science. Article skad063. https://doi.org/10.1093/jas/skad063.*
                                *Keel, B.N., Lindholm-Perry, A.K. 2022. Recent developments and future directions in meta-analysis of differential gene expression in livestock RNA-Seq. Frontiers in Genetics. 13. Article 983043. https://doi.org/10.3389/fgene.2022.983043.*
                                *Valez, F., Bosilevac, J.M., Mishra, A., Singh, P. 2023. Universal hydrolysis probe-based approach for specific detection and genotyping of foodborne pathogens. Journal of Microbiological Methods. 204. Article 106632. https://doi.org/10.1016/j.mimet.2022.106632.*


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