Jason Graham

I am currently a second year PhD student in the field of animal breeding and quantitative genetics in the lab of Dr. Luiz Brito. Our lab focuses on applying quantitative genetics theory to improve novel traits in numerous livestock species. Some of our current studies involve selection for docility in Angus cattle and resiliency in swine. We also have many interesting studies involving domesticated yak and water buffalos. My main interests are genetic improvement for welfare traits and using precision agriculture to generate novel phenotypes. I am also interested in utilizing machine learning to analyze high-throughput phenotypic and genotypic information. My previous research involves determining the transgenerational epigenetic effects of in-utero heat stress in purebred Landrace and Large White populations. The goal of this project is to show that environmental influences can be effect the variation in trait performance several generations later and that controlling the sows environment during pregnancy has an impact on profitability for not only the current generation, but future generations. My current project that I am very excited about is using robotic milking data collected from a large Indiana dairy to determine if certain Holstein lines perform better in automated dairy parlors. We hope to correlate calf performance using an automatic milk feeder with its later performance in a robotic milking system. This may allow us to predict milking ability much earlier in life which would decrease generation intervals and thus increase genetic improvement. My career goals are very much set on working in the livestock industry in the realm of animal breeding and quantitative genetics. I have participated in three different internships during my graduate career working directly with a team of trained geneticists. These include working at ABS Global, The Maschhoffs and Smithfield Premium Genetics. During my time at these internships I learned a lot to prepare me for my career in the industry. I also was able to determine where I may fit in once I leave graduate school. During my time at Smithfield Premium Genetics, I was assisting in a large project that involved collecting growth weight and back fat variables from a production test farm. I then followed those trial animals to the processing plant where we collected meat quality data. The biggest takeaway from this experience is the cost and difficulty of collecting valuable data from research trials even when everything goes right. This set me on the path of understanding the digital tools (e.g. computer vision, automated weight scales, etc.) to collect this information for us. Although new statistical techniques are always needed to better estimate breeding values, current genetic indices are already robust and hard to beat. I believe that precision agriculture is the future and that the new role for geneticists in companies is in developing ways to collect data smarter and more efficiently. This will significantly add value to genetics companies that depend on large quantities of accurate data to perform their routine genetic analyses.