Location: Sunflower and Plant Biology Research
Project Number: 3060-21220-029-05-T
Project Type: Trust Fund Cooperative Agreement
Start Date: May 1, 2017
End Date: Jul 1, 2019
The overall goal of our research is to develop effective, environmentally sound weed control strategies in northern regions of the United States, using winter cover crops that will also produce a crop with cash value to the farmer. We have identified canola as having good potential for this purpose, but winter hardiness can be an issue in northern regions. Thus, the objectives of this grant proposal are to: 1) Characterize the environmental conditions (light and temperature) that impact the rate and intensity of cold acclimation and deacclimation in winter canola; 2) Use this information to develop a robust protocol for screening 400 lines of a winter canola diversity panel for variation in cold acclimation/deacclimation processes; and 3) Use the genotypic information from the 400 lines to associate genetic differences with cold acclimation/deacclimation processes using a GWAS-based approach.
Three freezing tolerant, intolerant, and intermediate tolerant lines will be characterized for light and temperature conditions optimal for deacclimation following cold acclimation, which will be used on all 413 previously genotyped lines of our diversity panel to identify phenotypic differences in regards to deacclimation. Plants will be grown to the 6 leaf stage under greenhouse conditions and then cold acclimated using previously defined conditions (8 weeks of 5C under 12 hr day/night with full spectrum LED lighting in our chilling chamber). Identifying optimal temperature regimes for deacclimation Five plants of each line will be grown and deacclimated under 14 different treatment regimes. Following deacclimation, plants will be subjected to freezing stress (ramp down in temperature of 3 C/hr to a low of -15 C for 4 hrs, followed by return to 20 C at 3 C/hr in the dark). Plants will be moved to the greenhouse and scored for damage and survival based on our previously defined arbitrary scale. Experiments will be replicated at least 2 times. Determining if alternating day night conditions impacts deacclimation intensity Five plants of each line will be grown and cold acclimated and then deacclimated under 8 different treatment regimes. Following deacclimation, plants will be subjected to freezing stress and rated as previously described. Experiments will be repeated at least 2 times. Determine optimal time for deacclimation Five plants of each line will be grown and acclimated as described for each course of treatment. Based on experiments that produced the most variable results among the cultivars, we will treat plants to deacclimating conditions for 0 - acclimated control, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 7.0 days, and a non-acclimated control. Following deacclimation, plants will be subjected to freezing stress and rated as previously described. Experiments will be repeated at least 2 times. Identifying deacclimation rate differences between lines in our diversity panel We will subject 2 plants each from the 413 lines to our previously established acclimation protocol (see above). Plants will be then be subjected to the optimal deacclimation conditions for distinguishing differences between lines. Following deacclimation, plants will be subjected to freezing stress and scored for damage survival as previously described. GWAS analysis will be used to identify mapped SNPs associated with freezing tolerance following deacclimation treatments. Appropriate models will be used to identify markers associated with the phenotypes determined above. Although not all genes involved in controlling the rate of deacclimation may be differentially expressed, differential expression of genes associated with altered deacclimation phenotypes would provide supporting data. Thus, we will prepare RNA from shoot tips of canola showing variable responsiveness to deacclimation based on the experiments described above. Time permitting, we may also functionally confirm the role of any identified deacclimation-associated genes using CRISPER technologies.