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A model for the process of translation in gene expression is proposed. The model is based on the assumption that the ribosome decodes the mRNA sequences using consecutive subsequences of the 3 ′ -end of its 16S rRNA subunit. The biological consistency of the model is validated by successful detection of the Shine-Dalgarno signal and the start codon. Furthermore, implications on the role of the 3 ′ -end in the complete process of prokaryotic translation are presented and discussed. Interestingly, the results obtained support the possibility of an involvement of this part of the ribosome in the process of translation termination. Subsequently, results obtained via the proposed model are compared with published experimental results for different mutations of the last 13 bases of the 16S rRNA molecule. Agreement between predictions and experimental results validate the biological relevance of the proposed model. By means of simulated nucleotide mutations, a global analysis of this part of the ribosome in the process of translation is conducted.

We present a computational model of DNA-binding by sigma70 in Escherichia coli which allows us to extract the functional characteristics of the wider promoter environment. Our model is based on a measure for the binding energy of sigma70 to the DNA, which is derived from promoter strength data and used to build up a non-standard weight matrix. Opposed to conventional approaches, we apply the matrix to the environment of 3765 known promoters and consider the average matrix scores to extract the common features. In addition to the expected minimum of the average binding energy at the exact promoter site, we detect two minima shortly upstream and downstream of the promoter. These are likely to occur due to correlation between the two binding sites of sigma70. Moreover, we observe a characteristic energy landscape in the 500 bp surrounding the transcription start sites, which is more pronounced in groups of strong promoters than in groups of weak promoters. Our subsequent analysis suggests that the characteristic energy landscape is more likely an influence on target search by the RNA polymerase than a result of nucleotide biases in transcription factor binding sites.

The DNA sequencing efforts of the past years together with rapid progress in sequencing technology have generated a huge amount of sequence data available in public molecular databases. This recent development makes it statistically feasible to apply universal concepts from Shannon’s information theory to problems in molecular biology, e.g to use mutual information for gene mapping and phylogenetic classification. Additionally, the genetic information in the cell is continuously subject to mutations. However, it has to be passed from generation to generation with high fidelity, raising the question of existence of error protection and correction mechanisms similar to those used in technical communication systems. Finally, better understanding of genetic information processing on the molecular level in the cell can be acquired by looking for parallels to well established models in communication theory, e.g. there exist analogies between gene expression and frame synchronization.

SUMMARY This paper gives a brief overview of several applications from the emerging interdisciplinary field of genomic coding theory that aims at applying concepts and techniques from the field of coding theory to problems from the field of molecular biology. This is motivated by the high precision and robustness found in genomic processes in addition to the increase in the availability of genomic data for a wide range of species. The considered applications include source coding for DNA classification, channel coding for modelling gene expression with emphasis on the process of translation, existence of error correcting codes in the DNA and channel coding structure in the genetic code. Example results are presented that demonstrate the relevance of the proposed approaches and open questions are formulated to suggest future research work. Copyright © 2007 John Wiley & Sons, Ltd.

International audience; We present a biophysical model of promoter search by E. coli RNA polymerase. We use an unconventional weight matrix derived from promoter strength data to extract the energy landscape common to a large set of known promoters. This exhibits a continuous strengthening of the binding energy when approaching the transcription start site from either side. During promoter search, the RNA polymerase slides along the DNA double helix (one-dimensional diffusion) after randomly binding to it. We discuss the possibility that the sliding has a sequence-dependent component, which implies that the energy landscape influences the movement with respect to speed, direction and efficiency. Based on this assumption, we relate the obtained energy landscape around the promoters to the one-dimensional diffusion of the RNA polymerase. Our analytical results suggest that the sequence-dependent random walk slows down and gets directed upon entering a region of 500 bp around the transcription start site, which significantly increases the efficiency of promoter search. These results may explain how the RNA polymerase is able to find the promoter in biologically relevant times out of a vast excess of non-target sites. Moreover, they provide evidence for a sequence-dependent component of one-dimensional diffusion.

A model for the process of translation in gene expression is proposed. The model is based on the assumption that the ribosome decodes the mRNA sequences using consecutive subsequences of the 3(')-end of its 16S rRNA subunit. The biological consistency of the model is validated by successful detection of the Shine-Dalgarno signal and the start codon. Furthermore, implications on the role of the 3(')-end in the complete process of prokaryotic translation are presented and discussed. Interestingly, the results obtained support the possibility of an involvement of this part of the ribosome in the process of translation termination. Subsequently, results obtained via the proposed model are compared with published experimental results for different mutations of the last 13 bases of the 16S rRNA molecule. Agreement between predictions and experimental results validate the biological relevance of the proposed model. By means of simulated nucleotide mutations, a global analysis of this part of the ribosome in the process of translation is conducted.