PI: Edgar Spalding (University of Wisconsin-Madison) CoPIs: Nathan Springer (University of Minnesota); Irina Makarevitch (Hamline University); Tessa Durham-Brooks (Doane College); A. Mark Settles (University of Florida) Collaborators: Natalia de Leon (University of Wisconsin-Madison); Nathan Miller (University of Wisconsin-Madison); Jeffery Gustin (University of Florida); Gokhan Hacisalihoglu (Florida Agricultural & Mechanical University)
Throughout much of the northern United States, cold spring temperatures can impede the successful transition of planted corn seed into vigorously growing seedlings. Increasingly variable spring weather works against the benefits to the farmer of planting early. This project is designed to identify naturally occurring variations in genes that make some corn plants more resistant to cold than others at this critical period in the life cycle. Genetic variants will be identified first using all-new imaging and computational tools being developed in the laboratory. By imaging and measuring plant responses to cold using computer-based methods, the project will access otherwise obscure information about how seeds take up water, germinate, emerge from the soil and grow under varying cold conditions. Molecular level differences will be identified using genomic methods that associate cold responses to genetic variants. Genetic hypotheses about these cold hardy candidates will then be tested in early-planted corn fields by comparing growth and yield in plants carrying different versions of the identified genetic elements. Undergraduate students from diverse institutions, including rural and urban locations, will be trained through direct participation at all levels of data generation and analysis. The critical role of students will result in a project with highly integrated research and education outcomes. For example, student-lead experiments will be conducted on educational corn field sites, further advancing student learning about scientific methods while at the same time providing critical research data. The project stands to make a positive impact on an important limitation to US agriculture by identifying the genetic basis of cold-resistance in corn and by training the next generation to apply the knowledge to real world situations.
The research plan integrates natural variation in diverse populations, advanced genomics techniques, and custom machine-vision methods to capture a systems-level understanding of the complex responses to cold stress. Populations will include recombinant inbred lines, near isogenic lines and doubled haploids, and includes parents of the Nested Association Mapping population and the Wisconsin Diversity Panel. Cold tolerant alleles in maize will be identified with genome wide association and QTL analyses, and hypotheses about the genetic architecture and inheritance patterns of cold response phenotypes will be rigorously tested. Aim 1 will refine machine vision methods for measuring germination phenotypes, while Aim 2 will focus on chilling stress during seedling growth. Aim 3 will determine transcriptome and chromatin responses associated with cold treatment to identify genes and targets of epigenetic regulation that affect tolerance. Aim 4 will determine the impacts of contrasting alleles for cold stress response on life cycle traits in field experiments to determine if early season cold tolerance translates to improved yield. Data will be available through the project website http://phytomorph.wisc.edu, sequence data will be uploaded to NCBI, and datasets will be accessible through the maize community database http://maizegdb.org and QTL archive http://qtlarchive.org.
