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ARS Home » Plains Area » Fargo, North Dakota » Edward T. Schafer Agricultural Research Center » Weed and Insect Biology Research » Research » Research Project #443819

Research Project: Improving Freezing Tolerance and Weed Suppression in Canola

Location: Weed and Insect Biology Research

Project Number: 3060-21220-033-023-T
Project Type: Trust Fund Cooperative Agreement

Start Date: Jul 1, 2022
End Date: Jun 30, 2025

The objectives of this study are to: 1) Identify alleles of SENSITIVE TO FREEZING 2 (SFR2) associated with enhanced freezing tolerance in canola and transform this version of the gene into an elite spring genotype that is freezing sensitive such as Regina II. 2) Use CRISPR technology to knock out the VERNALIZATION INDEPENDENCE 3 (VIP3) gene in Regina II to make it less sensitive to cold deacclimation. 3) Identify the most effective canola planting densities for repressing growth of kochia without impacting yield potential. 4) Identify genes induced in canola when detecting nearby kochia plants under both field and greenhouse conditions. 5) Identify genes and processes that can be modified to enhance competitiveness and reduce yield loss in canola growing in the presence of weeds.

1) We will first identify the allelic form of SFR2 that is present in our most freezing tolerant lines of canola. Using procedures described by Ding et al. (2017) we will clone the SFR2 gene into dsRED-derived constructs and transform the elite spring line 'Regina II' and the freezing sensitive winter line 'ARS110'. Transgenic plants will be detected by screening their resulting seeds for expression of the DsRED gene. Transgenic plants will be grown and self-pollinated lines homozygous for the transgene will be identified by screening T1 lines that produce 100% offspring expressing the DsRED gene. Twelve individuals, each independent transgenic lines, along with twelve non-transgenic controls will be tested for freezing tolerance according to established protocols. 2) To confirm the role of VIP3 in cold deacclimation and associated freezing tolerance of winter canola, we will use gene editing CRISPR technology to knock out all copies of this gene in the same canola varieties described above. For knockout vectors, different constructs containing a single guide RNA or two guide RNAs will be generated using standard cloning procedures that target the VIP3 gene of canola. Lines that have deletions in all copies of the VIP3 genes of canola will be screened for deacclimation resistance using our established protocols. 3) Under field conditions, 2-meter square plots will be planted at densities of ~9 seeds per foot and row spacing of 3, 6, 9, 12, 24 inches in a random complete block design with 6 replicates per treatment. Approximately100 kochia seeds will be broadcast into each plot at the same time as canola planting. Additionally, a kochia free treatment (with a 9 inch row spacing) and a kochia alone treatment will be included. Kochia germination and growth rate (as determined by plant height canopy coverage) and dry and fresh weight at the time of canola harvest will be measured. Additionally, yield of canola per plot will be determined (based on total seed yield, 100 seed weight, and fresh and dry weight of above ground biomass) at the end of the season. 4) We will collect leaf and root tissue from canola plants field grown in 9 inch rows with and without kochia from objective 3, as well as tissue from greenhouse studies where a single potted canola plant will be grown with 0, 2, 4, or 6 kochia plants. The same measures for canola growth and yield described for field studies will be used to determine the impact of kochia on canola. Collected tissue samples will be stored at -80 C prior to being used for extraction of mRNA, construction of RNAseq libraries, and next-generation sequencing. 5) We will use the most up-to-date bioinformatics tools to analyze sequence data and to identify gene networks and over-represented developmental, physiological, and biochemical processes among sets of differentially and coordinately expressed genes. We will use programs such as WGCNA for network analysis in conjunction with known regulatory interactions available in the program CYTOSCAPE, as-well-as predictive programs such as SC-ION designed to identify probable transcription factors regulating specific clusters of coordinately regulated genes.