The fleshy taproot of radish is an important storage organ determining its yield and quality. Taproot thickening is a complex developmental process in radish. However, the molecular mechanisms governing this process remain unclear at the proteome level. In this study, a comparative proteomic analysis was performed to analyze the proteome changes at three developmental stages of taproot thickening using iTRAQ approach. In total, 1862 differentially expressed proteins (DEPs) were identified from 6342 high-confidence proteins, among which 256 up-regulated proteins displayed overlapped accumulation in S1 (pre-cortex splitting stage) vs. S2 (cortex splitting stage) and S1 vs. S3 (expanding stage) pairs, whereas 122 up-regulated proteins displayed overlapped accumulation in S1 vs. S3 and S2 vs. S3 pairs. Gene Ontology (GO) and pathway enrichment analysis showed that these DEPs were mainly involved in several processes such as "starch and sucrose metabolism", "plant hormone signal transduction", and "biosynthesis of secondary metabolites". A high concordance existed between iTRAQ and RT-qPCR at the mRNA expression levels. Furthermore, association analysis showed that 187, 181, and 96 DEPs were matched with their corresponding differentially expressed genes (DEGs) in S1 vs. S2, S1 vs. S3, and S2 vs. S3 comparison, respectively. Notably, several functional proteins including cell division cycle 5-like protein (CDC5), expansin B1 (EXPB1), and xyloglucan endotransglucosylase/hydrolase protein 24 (XTH24) were responsible for cell division and expansion during radish taproot thickening process. These results could facilitate a better understanding of the molecular mechanism underlying taproot thickening, and provide valuable information for the identification of critical genes/proteins responsible for taproot thickening in root vegetable crops.
Pubmed ID: 30302255 RIS Download
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Web server to identify statistically enriched pathways, diseases, and GO terms for a set of genes or proteins, using pathway, disease, and GO knowledge from multiple famous databases. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). A standalone command line version is also available
View all literature mentionsSoftware R package. Methods for Cluster analysis. Performs variety of types of cluster analysis and other types of processing on large microarray datasets.
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