Project 3: Quantification of the Potential for Epistatic Genomic Loci to Improve Maize Yield

Co-mentors: Luda Mainzer (Institute for Genomic Biology) and Alexander Lipka (Crop Sciences)
Social Impact: Improved crop yields, including corn, through genetic assessment.

Project description: The biological objective of this project is to determine the extent to which epistasis between pairs of genomic loci contribute to variation of yield in maize. The motivation for this research is that it is anticipated that there will not be enough food for the world population by 2050. Thus, there is a critical need to improve the yields of crops including maize. Indeed, critically assessing the genetic sources contributing to maize yield is an essential first step for improving maize yield. Assessing these genetic sources will enable breeders to focus their resources on specific genes (and/or combinations of genes) to select to maximize yield. This project will assess three research questions: 1) How much of yield is explained by epistasis? 2) What are the effect sizes of epistatic loci? And 3) Will considering the identified epistatic loci result in substantially increased yields?

A pair of students, one with a more computational background and the other with a more biological background, will conduct this analysis. These students will conduct stepwise epistatic model selection in the maize nested association mapping panel. The traits to be analyzed will be yield and other related traits. The stepwise epistatic model selection program (which is part of our local version of TASSEL5) was developed by a team lead by Mainzer and Lipka. Since high core-count servers are best for this work, we will use the 46-core Dell system available at NCSA’s Innovative Systems Lab. The dual-threaded cores provide ability to parallelize computation up to 96 threads, which would significantly speed up this analysis. Mainzer and Lipka will supervise this project and ensure that the analysis is completed in a timely manner. To facilitate communication between the students and supervisors, the students will work and have weekly meetings at NCSA. The students will also attend the biweekly Lipka Lab meetings and the HPCBio group meetings. These meetings will give the students the opportunity to ask “big-picture” questions, identify any bottlenecks with the conducting the analysis, and for Mainzer and Lipka to monitor the students’ progress. This project should provide insight into the contribution of epistasis towards variation in yield in maize, and identification of and solutions for computational bottlenecks for running stepwise model selection. In addition, the computational student will learn more about biology, and the biology student will learn more about computational aspects. Both students will learn about conducting statistical analyses and participating in interdisciplinary collaborations.