Recipient Organization
UNIVERSITY OF ILLINOIS
2001 S. Lincoln Ave.
URBANA,IL 61801
Performing Department
(N/A)
Non Technical Summary
Increasing the yield of soybean allows farmers to maximize profit and has the potential to increase output without expanding the area of land under cultivation. This is important for efforts directed at the sustainable intensification of agriculture. It is commonly assumed that soybean yield is limited by the amount of carbon fixed through photosynthesis, which is seen in high rates of flower abortion during seed production. It follows that plants bred to have greater rates of photosynthesis may have increased yield. However, there is no consensus over the extent to which this assumption is valid, and the genetic basis of variation in photosynthesis is poorly understood. Therefore, we aim to test whether a specific aspect of photosynthesis - the rate at which it is turned on during sunflecks - has a significant impact on soybean yield, and gain insight into the genetic cause of variation in this trait. This will be achieved by (1) generating soybean lines with variable rates of photosynthesis through editing of a gene known to be related to this process, (2) comparing rates of photosynthesis under field conditions of two lines of soybean for which yield data is available and (3) development of a high-throughput method to test rates of activation of photosynthesis for future genetic mapping studies.The resources, information and methods developed during this proposal will provide fundamental understanding of the link between an aspect of photosynthesis and yield that can inform future efforts to improve soybean.
Animal Health Component
(N/A)
Research Effort Categories
Basic
100%
Applied
(N/A)
Developmental
(N/A)
Goals / Objectives
The goal of this proposal is to develop resources to characterize the physiological basis of variation in rates of photosynthetic induction in soybean under greenhouse and field conditions. We aim to test the central hypothesis that increasing rates of photosynthetic induction can improve the efficiency of photosynthesis and boost crop yield. Thisgoal will be achieved through three objectives:Objective 1: Createelite lines of soybean with variation in rates of photosynthetic induction. This objective will generate lines of soybean with variable expression levels of the gene rubisco activase, abundance of which has been shown to linearly correlate with rates of photosynthetic induction in other species. This will be achieved by 8x multiplex CRISPR-Cas9 genome editing of the promoter region of the major form of rubisco activase, generating lines with variable deletions in the promoterleading to altered expression, and subsequent genotyping and phenotyping through immunoblot.Objective 2: Identifythe physiological basis of variation in induction rates between genotypes. Previous studies identified two genotypes of soybean with a >6-fold variation in rates of photosynthetic induction using gas exchange analysis. First we will validate these results in greenhouse using gas-exchange analysis and perform measurements to narrow down the cause, including biochemical assay testing rubisco activation state, metabolite analysis testing concentration of rubisco inhibitor CA1P, and comparative RNA-SEQ analysis. Second we will test that variation in observedrates of photosynthetic induction persist under field conditions at two developlmental time-points (vegetative and reproductive stage), and three canopy layers, using gas exchange analysis.Objective 3: Developing a chlorophyll fluorescence assay for high-throughput screening of rates of photosynthetic induction. Gas exchange and biochemical analyses are low throughput and time consuming. We will therefore develop a chlorophyll fluorescence based leaf disk assay to assess rates of photosynthetic induction through monitoring changes in the efficiency of photochemical quenching, to validate the assay samples will be taken in parallel to measure gas exchange and metabolite accummulation.
Project Methods
Methods:CRISPR-Cas9 gene editing. A CRISPR construct will be generated using the Golden Gate assembly toolkit for genome engineering targeting the major isoform of Rca. Eight guide RNAs will be expressed from a single construct using the tRNA processing system targeting locations between the translational start site and 3kb upstream. sgRNAs will be designed using the algorithm CROSPR, which is optimized for use with crop species, and constructs introduced into an elite soybean Asgrow genotype by the Wisconsin Crop Innovation Center, to create six independent T1 transformation events.Genotyping: Genomic DNA will be extracted from lines and PCR used to amplify the promoter region of Rca. Amplicons will be sent for sequencing and the data analyzed for the presence of indels. In addition a PAT/bar ELISA kit (Gold Standard diagnostics) will be used to screen for segregation of the Cas9 transgene, allowing identify fixed genotypes for further analysis in the T2 generation. Up to 8 lines showing a range of variation in Rca abundance will be selected for physiological analysis at the T2 generation.Molecular phenotyping: Plants will be grown in the greenhouse rooms in the Plant Care Facility at UIUC for analysis, 28 oC, with supplemental lighting 16h/8h day/night. Samples will be taken from the youngest fully expanded leaf of 3-week-old seedlings between 11-11:30AM to control for potential variation in protein and RNA abundance due to circadian rhythms. Quantitative immunoblot analysis and qPCR will be used to assess the relative abundance of Rca and plants showing variable expression levels (increased or decreased) will be progressed for further analysis.Biochemical analysis: To directly test the activation state of Rubisco in Objectives 2 and 3, leaf disks will be harvested and processed before analysis of incorporation of 14CO2 into 3-phosphoglycerate.Infra-red gas exchange analysis (IRGA): LI6800 fitted with a fluorescence head will be used to measure rates of photosynthesis and photosynthetic induction, monitoring CO2 assimilation, stomatal conductance and chlorophyll fluorescence parameters.Gene-expression analysis: Comparative RNA-SEQ will be performed to identify genes differentially expressed between NAM12 and NAM23. Samples will be taken with 5 biological replicates for each genotype. RNA will be extracted using QIAGEN RNeasy Plant RNA extraction kit, checked for integrity using a bioanalyzer, and sent for sequencing at the Roy J Carver Biotechnology Center at UIUC using Illumina NovaSeq to generate 10-15 million 2x150 paired end reads per sample. Differential gene expression analysis will be used to identify significantly up and down regulated genes between genotypes.Metabolic analysis: Analysis of CA1P contents will be performed using an indirect assay, where inhibition of rubisco activity (purified, Mg2+ activated) by CA1P is compared to a standard curve. These data will address whether differences occur due to differences in the relative abundance of known Rubisco inhibitors.Evaluation of success and key milestones:Objective 1:3-to-6 months: Completion of design and synthesis of plasmid for CRISPR-Cas9 gene editing. Evaluated by whole plasmid sequencing and comparison against designed plasmid looking for perfect match.12-15 months: Generation of six elite soybean lines transformed with CRISPR-Cas9 construct. Evaluated by screening of transgenic lines for selection marker (herbicide or antibiotic resistance), keeping some null lines.15-20 months: Isolation of up to 25 elite soybean lines with gene edited promoter region of the major form of Rca. Evaluated through sequencing of genomic DNA PCR amplicons spanning the Rca promoter region and identifying those lines with indels relative to the reference sequence, a minimum of 5 lines and maximum of 25 showing different deletions would be considered success.20-24 months: Generation of elite soybean lines with varying abundance of Rca. Evaluation: Perform quantitative immunoblot and qPCR on lines with validated indels in Rca promoter region, statistical analysis using ANOVA with post-hoc Dunnett's test to compare against wild-type protein and RNA level will determine whether lines with variable gene expression have been generated. Generation of lines with >20% differences in abundance of Rca protein or RNA will be considered successful.20-24 months: Perform preliminary gas exchange analysis to assess the impact on rates of photosynthetic induction on candidate lines shown. Generation of lines displaying >20% differences in induction (faster or slower) will be considered successful.Objective 2:6-9 months: Completion of greenhouse analysis of rates of photosynthetic induction in two lines previously reported to show variation through gas exchange and metabolite analysis to serve as the basis for future QTL mapping. Evaluated: Production of reliable data, success will be if we can reproduce previous findings showing a statistically significant difference between rates of photosynthetic induction in RC, NAM12 and NAM23.9-12 months: RNA-SEQ comparison of gene expression between lines showing varying rates of photosynthetic induction. Evaluated by identifying one or more candidate genes showing differential expression between genotypes.18 months: Completion of two-years analysis of rates of photosynthetic induction of field grown NAM12, RC and NAM23 using gas-exchange and biochemical analysis during vegetative and reproductive stages. Evaluated: Creation of a reliable data set. Effort: Results will be written up and submitted for publication in a plant science journal (target 18 months).Objective 3:9-12 months: Create a chlorophyll-fluorescence assay that can differentiate between lines with varying rates of photosynthetic induction by analyzing changes in PhiPSII. An exponential decay function will be fit to calculate rates of photosynthetic induction using R. Evaluation: by comparing rates of photosynthetic induction in genotypes known to vary, calculated by chlorophyll fluorescence assay and conventional gas exchange measurements. If the two different measurements agree on the relative differences between lines in rates of photosynthetic induction.12-15 months: Determining the underlying cause of signal measured in chlorophyll fluorescence assay will be achieved by comparing fluorescence data with direct measurement of rubisco activation state, tracking incorporation of 14CO2 and gas exchange data on intact leaves. Evaluation: correlation between biochemical, gas exchange and chlorophyll fluorescence data will be performed, and success will be to provide an estimate of the relative contribution of each component to the chlorophyll fluorescence signal.Effort to inform target audience: A methods paper will be written up describing the assay, uploaded as a pre-print and published in an appropriate journal. The article will be promoted through social media (Bluesky and LinkedIn).