A label-free quantitative shotgun proteomics analysis of rice grain developmentReport as inadecuate




A label-free quantitative shotgun proteomics analysis of rice grain development - Download this document for free, or read online. Document in PDF available to download.

Proteome Science

, 9:61

First Online: 30 September 2011Received: 23 March 2011Accepted: 30 September 2011

Abstract

BackgroundAlthough a great deal of rice proteomic research has been conducted, there are relatively few studies specifically addressing the rice grain proteome. The existing rice grain proteomic researches have focused on the identification of differentially expressed proteins or monitoring protein expression patterns during grain filling stages.

ResultsProteins were extracted from rice grains 10, 20, and 30 days after flowering, as well as from fully mature grains. By merging all of the identified proteins in this study, we identified 4,172 non-redundant proteins with a wide range of molecular weights from 5.2 kDa to 611 kDa and pI values from pH 2.9 to pH 12.6. A Genome Ontology category enrichment analysis for the 4,172 proteins revealed that 52 categories were enriched, including the carbohydrate metabolic process, transport, localization, lipid metabolic process, and secondary metabolic process. The relative abundances of the 1,784 reproducibly identified proteins were compared to detect 484 differentially expressed proteins during rice grain development. Clustering analysis and Genome Ontology category enrichment analysis revealed that proteins involved in the metabolic process were enriched through all stages of development, suggesting that proteome changes occurred even in the desiccation phase. Interestingly, enrichments of proteins involved in protein folding were detected in the desiccation phase and in fully mature grain.

ConclusionThis is the first report conducting comprehensive identification of rice grain proteins. With a label free shotgun proteomic approach, we identified large number of rice grain proteins and compared the expression patterns of reproducibly identified proteins during rice grain development. Clustering analysis, Genome Ontology category enrichment analysis, and the analysis of composite expression profiles revealed dynamic changes of metabolisms during rice grain development. Interestingly, we detected that proteins involved in glycolysis, TCA-cycle, lipid metabolism, and proteolysis accumulated at higher levels in fully mature grain compared to grain developing stages, suggesting that the accumulation of these proteins during the desiccation stage may be associated with the preparation of proteins required in germination.

KeywordsMudPIT Rice Spectral Counts Shotgun proteomics Electronic supplementary materialThe online version of this article doi:10.1186-1477-5956-9-61 contains supplementary material, which is available to authorized users.

Download fulltext PDF



Author: Joohyun Lee - Hee-Jong Koh

Source: https://link.springer.com/







Related documents