Abstract
BackgroundThe availability of high throughput experimental methods has made possible to observe the relationships between proteome and transcirptome. The protein abundances show a positive but weak correlation with the concentrations of their cognate mRNAs. This weak correlation implies that there are other crucial effects involved in the regulation of protein translation, different from the sole availability of mRNA. It is well known that ribosome and tRNA concentrations are sources of variation in protein levels. Thus, by using integrated analysis of omics data, genomic information, transcriptome and proteome, we aim to unravel important variables affecting translation.ResultsWe identified how much of the variability in the correlation between protein and mRNA concentrations can be attributed to the gene codon frequencies. We propose the hypothesis that the influence of codon frequency is due to the competition of cognate and near-cognate tRNA binding; which in turn is a function of the tRNA concentrations. Transcriptome and proteome data were combined in two analytical steps; first, we used Self-Organizing Maps (SOM) to identify similarities among genes, based on their codon frequencies, grouping them into different clusters; and second, we calculated the variance in the protein mRNA correlation in the sampled genes from each cluster. This procedure is justified within a mathematical framework.ConclusionsWith the proposed method we observed that in all the six studied cases most of the variability in the relation protein-transcript could be explained by the variation in codon composition.
Highlights
The availability of high throughput experimental methods has made possible to observe the relationships between proteome and transcirptome
Molecular mechanisms of translation Translation in yeast starts by the formation of the PIC which is formed in three steps: first, binding of the specific initiation Met-tRNA to the small ribosomal subunit; second, the resulting complex binds to the mRNA molecules localizing the start codon; and third, the attachment of large ribosomal subunit to generate the polysome structure
More details of the experimental techniques of the datasets shown in Additional File 1 can be seen elsewhere [31,32,33,34,35]. It has been demonstrated by Najafabadi et al [14] that the codon usage content provides direct information about the translation elongation rate based on the demand of tRNA, which affects the fold change of the protein levels
Summary
The availability of high throughput experimental methods has made possible to observe the relationships between proteome and transcirptome. It is well known that ribosome and tRNA concentrations are sources of variation in protein levels. By using integrated analysis of omics data, genomic information, transcriptome and proteome, we aim to unravel important variables affecting translation. The integration of large scale transcriptome and proteome data along with genome-wide sequence information can give insights into the molecular mechanisms that control cellular functions. If all the mRNAs were translated at a constant rate the correlation between mRNA and protein concentration would be high. The observed lack of correlation is due to the particularities of the translation study by the same authors [10], it was found that initiation is a controlling step, and the elongation phase, which is function of the of tRNA concentration. The mentioned authors reformulated their mathematical model to include the competition between the different aminoacyl-tRNA’s
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