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pubmed-article:16310166pubmed:abstractTextParallel profiling of mRNA and protein on a global scale and integrative analysis of these two data types could provide additional insights into the metabolic mechanisms underlying complex biological systems. However, because mRNA and protein abundance are affected by many cellular and physical processes, there have been conflicting results on their correlation. Using whole-genome microarray and LC-MS/MS proteomic data collected from Desulfovibrio vulgaris grown under three different conditions, we systematically investigate the relationship between mRNA and protein abundance by a multiple regression approach, in which some of the key covariates that may affect mRNA-protein relationship were included. The results showed that mRNA abundance alone can explain only 20-28% of the total variation of protein abundance, suggesting mRNA-protein correlation can not be determined by mRNA abundance alone. Among various covariates, analytic variation of protein abundance is the major source for the variation of mRNA-protein correlation, which contributes to 34-44% of the total variation of mRNA-protein correlation. The cellular functional category of genes/proteins contributes 10-15% of the total variation of mRNA-protein correlation, with a more pronounced correlation of the two properties was observed for "central intermediary metabolism" and "energy metabolism" categories. In addition, protein stability also contributes 5% of the total variation of mRNA-protein correlation. The study presents the first quantitative analysis of the contributions of various biochemical and physical sources to the correlation of mRNA and protein abundance in D. vulgaris.lld:pubmed
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pubmed-article:16310166pubmed:dateRevised2008-11-21lld:pubmed
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pubmed-article:16310166pubmed:articleTitleCorrelation between mRNA and protein abundance in Desulfovibrio vulgaris: a multiple regression to identify sources of variations.lld:pubmed
pubmed-article:16310166pubmed:affiliationDepartment of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, USA.lld:pubmed
pubmed-article:16310166pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:16310166pubmed:publicationTypeResearch Support, U.S. Gov't, Non-P.H.S.lld:pubmed
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