Improving Crop Development
In order to develop crops with better yields and increased disease resistance, researchers hybridize crop plants to create lines with favorable genes. One method used is called crossing over, a process where alleles change positions from one chromosome segment to another. While this method is essential, it is not well characterized and there is little control over crossover frequency and location.
PhD candidate Chaochih Liu, in the Department of Plant and Microbial Biology, is developing an algorithm that will help researchers and breeders understand crossover rate variation in breeding populations. The algorithm will be incorporated into a publicly available computational workflow that will help inform breeding decisions and identify plants with favorable characteristics.
Some funding for this project was provided by a 2021 University of Minnesota Informatics Institute MnDRIVE PhD Graduate Assistantship. The UMII MnDRIVE Graduate Assistantship program supports UMN PhD candidates pursuing research at the intersection of informatics and any of the five MnDRIVE areas:
- Robotics, Sensors and Advanced Manufacturing
- Global Food Ventures
- Advancing Industry, Conserving Our Environment
- Discoveries and Treatments for Brain Conditions
- Cancer Clinical Trials
This project is part of the Global Food Ventures MnDRIVE area. Liu also uses MSI resources as a member of the research group of Associate Professor Peter Morrell.
Research Computing partners:
- University of Minnesota Informatics Institute
