July 16, 2021

Animal Breeding and Genetics Symposium I

Animal Breeding and Genetics Symposium I

By: Dr. Emily Taylor
Awardee Talk: Implications of the Gut Microbiome for Genetic Improvement of Swine – Dr. Christian Maltecca – North Carolina State University

Dr. Maltecca started the Animal Breeding and Genetics Symposium I, accepting the American Society of Animal Science Rockefeller Prentice Award in Animal Breeding and Genetics. His presentation began by introducing how feed costs, amount, and quality of lean products, improving diets, exploiting livestock genetic variability and focusing on individual variation all play a role in producing protein efficiently.

His research group focuses on applying the gut microbiome in swine production, with a particular focus on growth and feed efficiency. While the intestinal microbiome and different gut microbiome compositions have been heavily researched in the previous years, Dr. Maltecca wanted to investigate how the microbiome shapes other production systems by comparing the microbiome composition of growing/finishing pigs raised in bio-secure nucleus farms and commercial facilities. Direct and mediated genomic variants were identified and were found to be affecting the host trait expression. Highlighting the potential for the ‘second genome’ will contribute to the recovery of genetic variance.

Opportunities to Apply and Learn from Deep Phenotyping in Dairy Cattle – Dr. James Koltes, Iowa State University.

Dr. Koltes began his presentation defining deep phenotyping – providing a more complete and comprehensive picture of a phenotype. As an example, what pieces make up feed efficiency? This would include feed intake, which is influenced by milk production, body weight, time at the bunk, feeding behavior, and activity. How we obtain the data needed for deep phenotyping is by utilizing technology and automated systems. These systems include sensors, cameras, and high-throughput assays, such as milk testing, which generate large amounts of valuable data for research and on-farm applications. Ongoing research to evaluate the ability of various sensor data to predict trait phenotypes continues. Dr. Koltes identified a potential to learn more about trait relationships and underlying genetics of behavior by developing a precision management tool from the sensors for producers. Therefore, the future of sensing technologies will require transdisciplinary research to develop these new types of sensor measurements and data analytics to identify hidden information within the data that may lead to new actionable applications on farms.

Using GPS and Genomic Technology to Provide a More Accurate Estimate of Bull Power in Western Intermountain Beef Systems – Dr. Matthew Garcia, Utah State University

Dr. Garcia began his presentation by discussing the incorporation of new or replacement animals in the herd. His focus was placed on the bull, as he is the vector of genetic change into the herd. Dr. Garcia discussed the multiple tools available to aid in increasing the accuracy of selection for replacements. The ultimate goal is compatibility to maximize productivity/profitability. Therefore, the study's objective was to utilize GPS technology and genomic parentage testing to provide a more accurate measurement of bull power in the intermountain west beef production system. GPS collars were used, and hair samples for future DNA extraction were taken prior to the breeding season. The collars could track the total distance traveled per day and distance traveled away from water and geocoordinates. Parentage testing of calves was taken at breeding, and the ranch's bulls sired only 69% of them. It was found that bulls sired 31% of the calves from herds that grazed nearby. The results validate the importance of verifying bull-power (the number of cows serviced by each bull) and sire identification to critically evaluate sire performance and increase selection accuracy in breeding replacements. Therefore, these tools may be helpful as a future selection tool to identify bulls that are high-performing during the breeding season.

Phenotyping of Individual Pigs Utilizing Computer Vision Offers Insights for Novel Trait Generation – Dr. Benny Mote, University of Nebraska – Lincoln

Dr. Mote began his presentation by continuing the discussion of phenotyping. We have many tools at our disposal used for phenotyping; however, there are lots of unknown or underutilized phenotypes for pig behavior. He also described some challenges facing swine production, like profit margins for health and well-being and tight labor costs. Therefore, the study's objective was to monitor activity in a noninvasive manner – specifically trying to improve genetics, health, well-being, and efficiency of the animal. Identification activity was over 96% accurate within the study and provided a large amount of data. This technology will help provide extra eyes on pigs and help teach us how pigs behave.

Genetics Reloaded: Large-scale Collection of Novel Phenotypes in Turkey – Dr. Christine Baes, University of Guelph

Dr. Baes began her presentation by stating that it is essential to blend both applied (focusing on phenotypes; reproduction, health, and welfare) and theoretical (focusing on methodology; relatedness, genomic evaluation, models, TRD) aspects. Moreover, selection programs are needed to increase breeding values' accuracy, therefore improving the ability to estimate genetic potential in animals. She outlined the improvement of traits such as livability, disease resistance, fertility, and other health and welfare traits in turkeys may aid in advancing breeding programs. The study presented used different methodologies to collect traits in commercial turkey lines. More accurate selection of parent stock for applied poultry breeding programs will be more easily obtained with improved methods, more detailed phenotypic information, and comprehensive data collection and integration.