Reconstruction of protein networks from an atlas of maize seed proteotypes

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 110; no. 49; pp. E4808 - E4817
• Main Authors: Walley, Justin W, Shen, Zhouxin, Sartor, Ryan, Wu, Kevin J, Osborn, Joshua, Smith, Laurie G, Briggs, Steven P
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 03.12.2013; National Acad Sciences
• Series: PNAS Plus
• Subjects: Agriculture - methods; Biological Sciences; Correlation analysis; Mass Spectrometry; Phosphorylation; Plant Proteins - genetics; Plant Proteins - metabolism; PNAS Plus; Protein Kinases - genetics; Protein Kinases - metabolism; Proteins; Proteome - genetics; Proteome - metabolism; Proteomics; Proteomics - methods; Ribonucleic acid; RNA; RNA, Messenger - genetics; RNA, Messenger - metabolism; Seeds - genetics; Signal Transduction - genetics; Systems Biology - methods; Tissues; Transcription Factors - genetics; Transcription Factors - metabolism; Zea mays - genetics; systems biology; quantitative proteomics; protein phosphorylation
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1319113110

A comprehensive knowledge of proteomic states is essential for understanding biological systems. Using mass spectrometry, we mapped an atlas of developing maize seed proteotypes comprising 14,165 proteins and 18,405 phosphopeptides (from 4,511 proteins), quantified across eight tissues. We found that many of the most abundant proteins are not associated with detectable levels of their mRNAs, and we provide evidence for three potential explanations: transport of proteins between tissues; diurnal, out-of-phase accumulation of mRNAs and cognate proteins; and differential lifetimes of mRNAs compared with proteins. Likewise, many of the most abundant mRNAs were not associated with detectable levels of their proteins. Across the entire dataset, protein abundance was poorly correlated with mRNA levels and was largely independent of phosphorylation status. Comparisons between proteotypes revealed the quantitative contribution of specific proteins and phosphorylation events to the spatially and temporally regulated starch and oil biosynthetic pathways. Reconstruction of signaling networks established associations of proteins and phosphoproteins with distinct biological processes acting during seed development. Additionally, a protein kinase substrate network was reconstructed, enabling the identification of 762 potential substrates of specific protein kinases. Finally, examination of 694 transcription factors revealed remarkable constraints on patterns of expression and phosphorylation within transcription factor families. These results provide a resource for understanding seed development in a crop that is the foundation of modern agriculture.