A TMT-based quantitative proteomic analysis provides insights into the protein changes in the seeds of high- and low- protein content soybean cultivars
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The presence of high amounts of seed storage proteins (SSPs) improves the overall quality of soybean seeds. However, these SSPs pose a major limitation due to their high abundance in soybean seeds. Although various technical advancements including mass-spectrometry and bioinformatics resources were reported, only limited information has been derived to date on soybean seeds at proteome level. Here, we applied a tandem mass tags (TMT)-based quantitative proteomic analysis to identify the significantly modulated proteins in the seeds of two soybean cultivars showing varying protein contents. This approach led to the identification of 5,678 proteins of which 13 and 1,133 proteins showed significant changes in Daewon (low-protein content cultivar) and Saedanbaek (high-protein content cultivar) respectively. Functional annotation revealed that proteins with increased abundance in Saedanbaek were mainly associated with the amino acid and protein metabolism involved in protein synthesis, folding, targeting, and degradation. Taken together, the results presented here provide a pipeline for soybean seed proteome analysis and contribute a better understanding of proteomic changes that may lead to alteration in the protein contents in soybean seeds.
Abstract
The presence of high amounts of seed storage proteins (SSPs) improves the overall quality of soybean seeds. However, these SSPs pose a major limitation due to their high abundance in soybean seeds. Although various technical advancements including mass-spectrometry and bioinformatics resources were reported, only limited information has been derived to date on soybean seeds at proteome level. Here, we applied a tandem mass tags (TMT)-based quantitative proteomic analysis to identify the significantly modulated proteins in the seeds of two soybean cultivars showing varying protein contents. This approach led to the identification of 5,678 proteins of which 13 and 1,133 proteins showed significant changes in Daewon (low-protein content cultivar) and Saedanbaek (high-protein content cultivar) respectively. Functional annotation revealed that proteins with increased abundance in Saedanbaek were mainly associated with the amino acid and protein metabolism involved in protein synthesis, folding, targeting, and degradation. Taken together, the results presented here provide a pipeline for soybean seed proteome analysis and contribute a better understanding of proteomic changes that may lead to alteration in the protein contents in soybean seeds.
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