Model IDs potential pathways to improve plant oil production
“This approach allowed us to narrow down the large list of enzyme reactions to the relatively few ones that might be good candidates to be manipulated in future experimental studies,” Schwender said. “Our major goal is to computationally predict the least possible number of enzymes that have most control over the tradeoff between oil and protein production.”
Of the 572 reactions included in the model, the scientists identified 149 reactions as “protein-responsive” and 116 as “oil-responsive.”
“In addition, the model helps us evaluate how sensitive the reactions are in a quantitative way, so we can see which of these are the ‘most sensitive’ reactions,” Schwender said. “This allows us to identify a relatively few possible targets for future genetic manipulation to tip the balance in favor of greater seed oil production.”
Some of the reactions identified by the model confirm pathways pointed out in previous research as important for oil synthesis. “But some of the reactions identified by our model have not really been implied so far to be important in the oil/protein tradeoff,” Schwender said, suggesting that this could be new ground for discovery.
“These simulation tools may therefore point the way to new strategies for re-designing bioenergy crops for improved production,” he concluded.
This research was funded by the DOE Office of Science.
DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov
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