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Integrating probabilistic maps and 3C-based data for determining high-resolution 3D structure of yeast chromosomes
Perspectives of extension of this common project to a more ambitious proposal to be submitted to funding agencies : Short term Added value of the cooperation : The Gadal group has developed an imaging technology , which allows for deciphering loci probabilistic maps (or territories) in living yeast cells. Such technology will be leveraged with its integration with recent 3C-based data  though our Integrative Modeling Platform  from the Marti-Renom group. Thus, the results for this collaboration would not be possible without the active participation of the proposed researches from both groups.
1. A. B. Berger et al., Nat Methods 5, 1031 (Dec, 2008).
2. Z. Duan et al., Nature 465, 363 (May 2, 2010).
3. F. Alber et al., Nature 450, 683 (Nov 29, 2007).
Summary of the proposal :
The three-dimensional (3D) organization of the genome plays important but still poorly understood roles in the regulation of gene expression. Up to now there has not been a technique to visualize at the nanometer resolution the 3D organization of the genome within nuclei. It has become clear that the spatial organization of chromosomes is reflected in, and driven by, cis- and trans-interactions between genomic elements. For instance, enhancers directly touch target genes resulting in the formation of chromosomal loops. Thus, comprehensive mapping of interactions between loci throughout the genome, combined with microscopy imaging of the spatial distances between a limited set of loci, could provide a powerful approach to gain insight into the spatial organization of chromosomes. This proposal aims at implementing the Integrative Modeling Platform to explore this unique approach.
The Gadal lab has developed a software to automatically extract gene localization in yeast from about 1000 nuclei1. We compute the 3-D coordinates of gene from each cell and assembled the positions extracted into a single probabilistic representation of the gene’s localization in nuclear space. We could construct a two-dimensional map of the probability density of gene localization.
The Marti-Renom lab has developed computational approaches for 3D modeling of proteins, RNA and more recently chromosomal domains using the Integrative Modeling Platform (IMP, http://www.integrativemodeling.org). IMP’s framework for structure determination is similar to NMR spectroscopy, in which the conformation of a polypeptide chain is determined by satisfying distance restraints between atom pairs.
Here we propose to combine comprehensive chromatin interaction mapping, probabilistic maps, and with 3D modeling to generate high-resolution (Kb-scale) models of yeast chromosomes. We believe that our approach will potentially unravel the relationship between structure and function of chromatin in yeast.
Antonio PINEDA-LUCENA, Valencia Claudio GOMES, Lisboa
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