RESEARCH-PGR: Understanding proteome plasticity in the soybean seed using multi-omic integration.

The soybean seed delivers proteins, oils, and carbohydrates for a wide variety of agricultural and industrial uses. However, the protein and amino acid composition that has evolved to be most adaptive to the soybean itself is less than ideal for the nutrition of humans and their livestock. For example, most soybean seed storage proteins are poor in the essential, sulfur-containing amino acids, methionine and cysteine. Attempts to modify the amino acid and protein content of the soybean seed by means of agricultural biotechnology have encountered a phenomenon termed 'rebalancing', where the plant compensates for the forced reduction of one type of seed storage protein by increasing expression of other proteins, such that the overall protein content and amino acid composition is maintained within tight margins. Rebalancing has been observed in many crop species including pulses, oilseeds, and cereals. This team of four investigators seeks to better understand how the plant genome guides the protein and amino acid composition of its seeds. To this end the gene expression will be measured over the time course of soybean seed development with a panel of complementary techniques. The data will be analyzed using a mathematical representation and machine learning techniques. The success of this project may allow molecular biologists and breeders to better predict which genetic changes can deliver the desired effects on the nutritional quality of seed crops. The regulatory mechanism that underlies the rebalancing of the seed proteome is not well understood. The project is guided by the hypothesis that rebalancing is due to homeostatic constraints at multiple levels, including transcription and amino acid supply, but experimental data as well as theoretical considerations suggest that translational control deserves special attention. Using CRISPR gene editing, the Stacey lab recently engineered a new, genetically robust model system for rebalancing, with modifications in both a major soybean seed storage protein (beta-conglycinin) and amino acid synthesis (methionine). The project will collect multi-omic datasets over the developmental time course of soybean seed development. In Aim 1, data from the transcriptome, translatome, proteome, and metabolome will be compared between wild type and rebalanced seeds. Data will be integrated by mathematical modeling to identify potential drivers of rebalancing and their developmental timing. Aim 2 implements experiments and machine learning to pinpoint potential, nonintuitive mechanisms of rebalancing. This includes a novel test of the intellectually intriguing but controversial 'specialized ribosome' hypothesis, which states that translational control is exerted by biochemically distinct types of ribosomes. The broader impacts of this project include training of researchers in multi-omic data integration, including undergraduates participating in a program for deaf and hard-of-hearing students, a population underrepresented in science. The US is one of the two largest producers of soybeans in the world, and a deeper mechanistic understanding of seed storage protein production may increase its nutritional quality, sustainability of production, and diversity of uses. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.