Plants, including soybean, extract carbon dioxide (CO2) from the atmosphere as they grow, and pathways for carbon capture and partitioning, such as photosynthesis and fatty acid synthesis, directly affect the biomass, seed yields, and oil content. While it is apparent that the carbon capture and partitioning has direct effect on the soybean yield and oil content, the linkage between carbon capture/partitioning and their corresponding phenotypes is poorly understood in transgenic soybeans, carrying some key genes involved in photosynthesis and/or fatty acid synthesis. Therefore, we propose a study to apply a systems approach by analyzing transcriptomic sequencing data for variant transgenic lines to uncover the intricate interactions among the genes involved in carbon capture and partitioning pathways, and to develop a predictive model by constructing a gene co-expression network to link them to the corresponding phenotypes, such as seed size and oil content.

Objective One: Identify the transcriptomic profiles of transgenic soybeans with carbon capture and partitioning pathway modifications.
Objective Two: Systematically discover carbon capture and partitioning pathways, genes, and their interactions by a statistical model for co-expression gene networks and linkage to phenotyping data.

The project will generate an online database of gene expression profiles and co-expression networks of soybeans for public use. The database will be posted on the Pl's lab website (http://sysbio.unl.edu/). This database will be valuable to experimentalists in guiding the research on carbon capture and partitioning in soybeans. All transcriptomic data generated by this project will be deposited to the NCBl databases. To reach broader audience by taking full advantage of our solid skills and expertise in computer related technology, we plan to develop a webpage, which will have biology related quizzes, pictures, and cartoons to broadcast knowledge about carbon capture and partitioning in soybeans. At the same time, results from the proposed research will be disseminated broadly; we will present our results to the scientific community through meeting reports, invited lectures, and peer-reviewed publications. Those media will also be online, including in NebGuides database. Special seminars for soybean producers will be held at the UNL.

Updated May 19, 2023:

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The proposed study is expected to reveal interactions among the genes involved in carbon capture and partitioning pathways and to link gene functions to phenotypes, such as seed size and oil content. The discovery from this study can guide the generation of optimally transgenic soybeans with enhanced carbon capture and partitioning pathways for yield and oil content improvement since the careful manipulation of these pathways in soybeans can directly increase both seed yield and oil content. For example, redirecting flux to fatty acids by manipulating carbon partitioning pathways increases more than 20% of the oil content in soybean seeds. This can substantially impact to the soybean industry in the US and the entire world, because currently about 30 million tons of soybean oil is produced worldwide, constituting about half of worldwide edible vegetable oil production.