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Beyond pairwise DNA contacts: exploring higher-order genome structure using proximity ligation

$404,611U01FY2017HLNIH

Baylor College Of Medicine, Houston TX

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Abstract

?Project Summary The roughly two meters of DNA in the human genome is intricately packaged to form the chromatin and chromosomes in each cell nucleus. In addition to its structural role, this organization has critical regulatory functions. In particular, the formation of hubs in the human genome plays an essential role in regulating genes in different cell types. We recently demonstrated the ability to create reliable maps of loops, using an in situ Hi-C method for three-dimensional genome sequencing. Hi-C characterizes the three-dimensional configuration of the genome by determining the frequency of physical contact between all pairs of loci, genome-wide. The proposed project will develop more sophisticated technologies that can identify not only loops - which involve a pair of genomic positions - but hubs, which can involve many interacting DNA positions (often five or more such positions). We will examine the dynamics of these hubs in the setting of differentiating embryonic stem (ES) cells in humans and mice. Aim 1 will develop COLA, a variant of the in situ Hi-C protocol that can identify contacts between large numbers of loci at once in intact nuclei. Aim 2 will develop split-pool barcoding, which can identify contacts between unlimited numbers of loci, but which requires disruption of the nucleus. The results of both methods will be integrated and compared to one another and, in Aim 3, will be independently validated using microscopy. The proposed project will advance our understanding of the determinants and functions of chromatin hubs, and present a technological framework for comprehensive analysis of higher-order genome structure in any cell type. All methods and data will be freely and rapidly released to the scientific community.

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Beyond pairwise DNA contacts: exploring higher-order genome structure using proximity ligation · GrantIndex