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Nucleic Acids Research 2005 33(20):6587-6592; doi:10.1093/nar/gki967
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Published online 24 November 2005

© The Author 2005. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oxfordjournals.org

Article

A thermodynamic model of transcriptome formation

Tomokazu Konishi*

Faculty of Bioresource Sciences, Akita Prefectural University Shimoshinjyo Nakano, Akita 010-0195, Japan

*Tel: +81 18 872 1603; Fax: +81 18 872 1677; Email: konishi{at}akita-pu.ac.jp

Received October 2, 2005. Revised November 2, 2005. Accepted November 2, 2005.

The genome supplies information on both the quality and quantity of the transcriptome. However, as it remains unknown how a cell determines transcript levels from the genome sequences, despite comprehensive knowledge of the cellular components involved, the quantity information held by the genome cannot as yet be derived from nucleotide sequences. The model presented here explains on a thermodynamic basis how the components decode the genome to form and maintain the transcriptome. The model describes the level of a transcript as a pseudo-equilibrium between velocities of synthesis and degradation, both of which are controlled by sequence-specific interactions between protein factors and nucleic acids. Each of the transcript levels can be described by a single equation expressing a function of the activity concentrations of the protein factors. Quantitative information in the genome can thus be transformed into constants determined from the nucleotide sequences. Using this model, the transcriptome can be traced back to the protein factors and the state of chromosome packaging. The total description of transcript levels allows the model to be verified through comparison of derived hypotheses with comprehensive measurements of the transcriptome. The hypotheses thus derived in the present study are well supported by experimental microarray data, confirming the appropriateness of the model.


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