Location: Sunflower and Plant Biology Research
Project Number: 3060-21220-033-09-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Jul 1, 2020
End Date: Jun 30, 2023
Previous studies indicated that sunflowers respond to weed exposure (winter canola in this case) by changing gene expression in above and below-ground tissues. However, it is unknown if changes in sunflower gene expression observed under greenhouse conditions would be observed under field conditions, or with other weeds or cover-crops as competitors. It is also unknown if the gene expression changes only occur during interspecies competition or if they occur during intraspecies competition as well. The objectives of this study are to determine gene expression changes in sunflower growing under field conditions in competition with itself, with canola, or with natural weed populations.
Sunflower will be grown in a random complete block design with four replicates in 8M x 4M plots for each of the following treatments 1) sunflower growing at standard spacing (control conditions), 2) sunflower at 1/2X standard spacing (double density), 3) sunflower grown at standard spacing with canola inter seeded between rows, 4) sunflower grown at standard spacing with uncontrolled natural weed populations. Leaf samples (the distal 10 cm of the top-most fully expanded leaf) from 4 randomly chosen plants from the middle rows of each plot will be collected into liquid N2 when 50% of the control plants have reached the R5 stage of growth (a point in development marking the end of the critical period for weed control in sunflower). Likewise, root material from the same plants will be dug up, shaken mostly clean of dirt and also flash frozen in liquid N2. Total RNA from all samples will be extracted and subjected to RNAseq analysis using standard approaches. De novo and reference-based assembly of the resulting sequences will be mined to identify genes that are differentially expressed. These results will be compared to those studies of genes differentially expressed under greenhouse conditions. Cluster analysis will be used to identify coordinately-expressed, competition-responsive genes suitable for identifying likely regulatory factors. Testable hypotheses regarding the role of specific of regulatory factors and weed-generated or plant density-generated signals will be developed for future analysis. Additionally, the phenological measures of plant growth, development and yield will be collected as will the impact of canola as a weed-suppressing treatment through assessing weed biomass in the various treatments.