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J Biomol Struct Dyn. 2010 Jun;27(6):747-64.

Prediction of nucleosome positioning in genomes: limits and perspectives of physical and bioinformatic approaches.

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1
Dipartimento di Chimica, Sapienza Universita di Roma, P.le A.Moro, 5, I-00185 Roma, Italy. pasquale.desantis@uniroma1.it

Abstract

Nucleosomes, the fundamental repeating subunits of all eukaryotic chromatin, are responsible for packaging DNA into chromosomes inside the cell nucleus and controlling gene expression. While it has been well established that nucleosomes exhibit higher affinity for select DNA sequences, until recently it was unclear whether such preferences exerted a significant, genome-wide effect on nucleosome positioning in vivo. For this reason, an increasing interest is arising on a wide-ranging series of experimental and computational analyses capable of predicting the nucleosome positioning along genomes. Toward this goal, we propose a theoretical model for predicting nucleosome thermodynamic stability in terms of DNA sequence. Based on a statistical mechanical approach, the model allows the calculation of the sequence-dependent canonical ensemble free energy involved in nucleosome formation. The theoretical free energies were evaluated for 90 single nucleosome DNA tracts and successfully compared with those obtained with nucleosome competitive reconstitution. These results, obtained for single nucleosomes, could in principle allow the calculation of the intrinsic affinity of nucleosomes along DNA sequences virtually opening the possibility of predicting the nucleosome positioning along genomes on physical basis. The theoretical nucleosome distribution was compared and validated with that of yeast and human genome experimentally determined. The results interpret on a physical basis the experimental nucleosome positioning and are comparable with those obtained adopting models based on the identification of some recurrent sequence features obtained from the statistical analysis of a very large pool of nucleosomal DNA sequences provided by the positioning maps of genomes.

PMID:
20232931
DOI:
10.1080/07391102.2010.10508583
[Indexed for MEDLINE]
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