Using Big Data and Global Partnerships to Accelerate Rates of Genetic Gain In Wheat

Sunday, February 14, 2016: 8:00 AM-9:30 AM
Marshall Ballroom East (Marriott Wardman Park)
Jessica Rutkoski, Cornell University, Ithaca, NY
To help meet growing food demands, continual genetic improvement of crops is needed. In the case of wheat, genetic gain must be achieved for several traits including stable grain yield and disease resistance across years in the face of fluctuating temperatures, erratic rainfall, and rapidly-changing pathogen populations. Currently, rates of genetic gain in wheat are not sufficient to meet projections of future demand. Major advances in genomics enable us to inexpensively generate thousands DNA markers on individual breeding lines. In addition, high-throughput aerial phenotyping now allows thousands of phenotypes to be recorded in a matter of minutes for low cost at virtually any location as long as equipment is available. Linking the DNA marker data with data on disease resistance, grain yield, and aerially collected phenotypes from cooperators at various sites across the world, will enable us to develop prediction models that can identify the top performing breeding lines for a range of environments, even at very early stages of breeding without observing the traits of interest. Effective data management, data sharing, and cultural changes in the way we do research and crop breeding will be needed. However, the potential pay-off is well worth facing the challenges. Early results indicate that harnessing this big data-driven approach on a large scale could dramatically accelerate rates of genetic gain- ultimately leading to faster improvements in yield and disease resistance on farmers’ fields.