Journal of Molecular Evolution

, Volume 48, Issue 2, pp 133–141 | Cite as

Relationships Between Transcriptional and Translational Control of Gene Expression in Saccharomyces cerevisiae: A Multiple Regression Analysis

  • Angelo  Pavesi


Natural selection for an increased translation efficiency has been proposed as the main determinant for the bias in codon usage observed in many genes of Saccharomyces cerevisiae. Recently, the efficiency of transcription of a large number of yeast genes has been determined, based on the cellular content of the respective mRNAs: this provides an additional dimension to the study of the multisep process of gene expression. Using a representative set of yeast genes with a known level of transcription, the relationship between transcriptional and translational steps was evaluated by a multiple linear regression model. This analysis demonstrated a positive correlation between the amount of transcript, given as the number of mRNA copies per cell for each individual gene, and indices evaluating the effects of translational selection on the corresponding codon usage pattern. This finding suggests a close association of the cellular mRNA content, regulated also at the transcriptional level, to its efficiency of translation, mediated by a fine-tuning of codon usage strategy. Moreover, multiple regression analysis demonstrated that the transcription level of a gene can be approximately predicted using indices of bias deriving from its nucleotide sequence. This allowed for an extensive investigation of uncharacterized regions of the complete genome sequence of S. cerevisiae, to detect new potential short protein coding genes that were not considered by previous searching procedures. Several small open reading frames exhibiting a statistically significant coding potential were thus identified as good candidates for functional analysis.

Key words: Yeast genome — mRNA sequence evolution — Codon usage bias — Gene expression — Statistical model — Small open reading frames 


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Copyright information

© Springer-Verlag New York Inc. 1999

Authors and Affiliations

  • Angelo  Pavesi
    • 1
  1. 1.Department of Evolutionary and Functional Biology, University of Parma, Viale delle Scienze, I-43100 Parma, ItalyItaly

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