iTRAQ-Based Proteomics Analysis and Network Integration for Kernel Tissue Development in Maize
AbstractGrain weight is one of the most important yield components and a developmentally complex structure comprised of two major compartments (endosperm and pericarp) in maize (Zea mays L.), however, very little is known concerning the coordinated accumulation of the numerous proteins involved. Herein, we used isobaric tags for relative and absolute quantitation (iTRAQ)-based comparative proteomic method to analyze the characteristics of dynamic proteomics for endosperm and pericarp during grain development. Totally, 9539 proteins were identified for both components at four development stages, among which 1401 proteins were non-redundant, 232 proteins were specific in pericarp and 153 proteins were specific in endosperm. A functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the tissue development. Three and 76 proteins involved in 49 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were integrated for the specific endosperm and pericarp proteins, respectively, reflecting their complex metabolic interactions. In addition, four proteins with important functions and different expression levels were chosen for gene cloning and expression analysis. Different concordance between mRNA level and the protein abundance was observed across different proteins, stages, and tissues as in previous research. These results could provide useful message for understanding the developmental mechanisms in grain development in maize. View Full-Text
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Zhang, L.; Dong, Y.; Wang, Q.; Du, C.; Xiong, W.; Li, X.; Zhu, S.; Li, Y. iTRAQ-Based Proteomics Analysis and Network Integration for Kernel Tissue Development in Maize. Int. J. Mol. Sci. 2017, 18, 1840.
Zhang L, Dong Y, Wang Q, Du C, Xiong W, Li X, Zhu S, Li Y. iTRAQ-Based Proteomics Analysis and Network Integration for Kernel Tissue Development in Maize. International Journal of Molecular Sciences. 2017; 18(9):1840.Chicago/Turabian Style
Zhang, Long; Dong, Yongbin; Wang, Qilei; Du, Chunguang; Xiong, Wenwei; Li, Xinyu; Zhu, Sailan; Li, Yuling. 2017. "iTRAQ-Based Proteomics Analysis and Network Integration for Kernel Tissue Development in Maize." Int. J. Mol. Sci. 18, no. 9: 1840.
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