Originally published as Genetics Published Articles Ahead of Print on October 8, 2006.

Genetics, Vol. 174, 2229-2243, December 2006, Copyright © 2006
doi:10.1534/genetics.106.065862

Correlation of mRNA Expression and Protein Abundance Affected by Multiple Sequence Features Related to Translational Efficiency in Desulfovibrio vulgaris: A Quantitative Analysis

Lei Nie^*,1, Gang Wu^,1 and Weiwen Zhang^,2

^* Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University, Washington, DC 20057, Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, Maryland 21250 and Microbiology Department, Pacific Northwest National Laboratory, Richland, Washington 99352

² Corresponding author: Microbiology Department, Pacific Northwest National Laboratory, P.O. Box 999, Mail Stop P7-50, Richland, WA 99352.
E-mail: weiwen.zhang{at}pnl.gov

The modest correlation between mRNA expression and protein abundance in large-scale data sets is explained in part by experimental challenges, such as technological limitations, and in part by fundamental biological factors in the transcription and translation processes. Among various factors affecting the mRNA–protein correlation, the roles of biological factors related to translation are poorly understood. In this study, using experimental mRNA expression and protein abundance data collected from Desulfovibrio vulgaris by DNA microarray and liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) proteomic analysis, we quantitatively examined the effects of several translational-efficiency-related sequence features on mRNA–protein correlation. Three classes of sequence features were investigated according to different translational stages: (i) initiation, Shine–Dalgarno sequences, start codon identity, and start codon context; (ii) elongation, codon usage and amino acid usage; and (iii) termination, stop codon identity and stop codon context. Surprisingly, although it is widely accepted that translation initiation is the rate-limiting step for translation, our results showed that the mRNA–protein correlation was affected the most by the features at elongation stages, i.e., codon usage and amino acid composition (5.3–15.7% and 5.8–11.9% of the total variation of mRNA–protein correlation, respectively), followed by stop codon context and the Shine–Dalgarno sequence (3.7–5.1% and 1.9–3.8%, respectively). Taken together, all sequence features contributed to 15.2–26.2% of the total variation of mRNA–protein correlation. This study provides the first comprehensive quantitative analysis of the mRNA–protein correlation in bacterial D. vulgaris and adds new insights into the relative importance of various sequence features in prokaryotic protein translation.

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