Improving Cassava Breeding
Cassava is an important food crop worldwide that can also be used for animal feed and as a source of starch for multiple uses. Researchers are working to develop new varieties of cassava that will be more resistant to disease, pests, and climate change. In order to help speed up the breeding process, the International Center for Tropical Agriculture (CIAT) has sequenced thousands of varieties of cassava to identify genetic markers of beneficial and harmful traits.
MSI staff members Nathan Carlson (Linux Systems Operations Manager, MSI Operations), Dr. Tom Kono (Informatics Analyst, MSI Bioinformatics; currently, University Hospital of Cologne), and Dr. Kevin Silverstein (Scientific Lead Informatics Analyst, MSI Bioinformatics), in a project for GEMS Informatics, used the CIAT sequence data to create a genomics database that can be used by cassava breeders. After identifying genetic sequence variants that change the amino acid sequence of the plants’ proteins, they used a model called BAD_Mutations, which identified the variants that could impact the cassava’s traits. A story about this project appears on the GEMS Informatics website: Weeding out bad mutations to enhance cassava productivity and climate resistance.
GEMS Informatics is a joint initiative led by the College of Food, Agricultural and Natural Resource Sciences and the Research Computing group in the Research and Innovation Office at the University of Minnesota. They produce and enable the creation of research-ready scientific data, and turn that data into actionable information for farmers, scientists, governments, or companies. MSI, which is part of Research Computing, provides computing resources and expertise for GEMS Informatics research.
