Location: Genetics and Animal Breeding
Project Number: 3040-31000-106-000-D
Project Type: In-House Appropriated
Start Date: Sep 8, 2022
End Date: Sep 7, 2027
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.
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.