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Combinatorial Modeling of Chromatin Features Quantitatively Predicts DNA Replication Timing in Drosophila

Overview of attention for article published in PLoS Computational Biology, January 2014
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Title
Combinatorial Modeling of Chromatin Features Quantitatively Predicts DNA Replication Timing in Drosophila
Published in
PLoS Computational Biology, January 2014
DOI 10.1371/journal.pcbi.1003419
Pubmed ID
Authors

Federico Comoglio, Renato Paro

Abstract

In metazoans, each cell type follows a characteristic, spatio-temporally regulated DNA replication program. Histone modifications (HMs) and chromatin binding proteins (CBPs) are fundamental for a faithful progression and completion of this process. However, no individual HM is strictly indispensable for origin function, suggesting that HMs may act combinatorially in analogy to the histone code hypothesis for transcriptional regulation. In contrast to gene expression however, the relationship between combinations of chromatin features and DNA replication timing has not yet been demonstrated. Here, by exploiting a comprehensive data collection consisting of 95 CBPs and HMs we investigated their combinatorial potential for the prediction of DNA replication timing in Drosophila using quantitative statistical models. We found that while combinations of CBPs exhibit moderate predictive power for replication timing, pairwise interactions between HMs lead to accurate predictions genome-wide that can be locally further improved by CBPs. Independent feature importance and model analyses led us to derive a simplified, biologically interpretable model of the relationship between chromatin landscape and replication timing reaching 80% of the full model accuracy using six model terms. Finally, we show that pairwise combinations of HMs are able to predict differential DNA replication timing across different cell types. All in all, our work provides support to the existence of combinatorial HM patterns for DNA replication and reveal cell-type independent key elements thereof, whose experimental investigation might contribute to elucidate the regulatory mode of this fundamental cellular process.

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Geographical breakdown

Country Count As %
United States 3 6%
United Kingdom 1 2%
Germany 1 2%
Switzerland 1 2%
Unknown 44 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 36%
Researcher 10 20%
Student > Master 4 8%
Student > Postgraduate 3 6%
Professor 3 6%
Other 6 12%
Unknown 6 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 46%
Biochemistry, Genetics and Molecular Biology 15 30%
Physics and Astronomy 2 4%
Computer Science 1 2%
Mathematics 1 2%
Other 2 4%
Unknown 6 12%