Quantification of DNA cleavage specificity in Hi-C experiments.
Abstract
Hi-C experiments produce large numbers of DNA sequence read pairs that are typically
analyzed to deduce genomewide interactions between arbitrary loci. A key step in these
experiments is the cleavage of cross-linked chromatin with a restriction endonuclease.
Although this cleavage should happen specifically at the enzyme's recognition sequence,
an unknown proportion of cleavage events may involve other sequences, owing to the
enzyme's star activity or to random DNA breakage. A quantitative estimation of these
non-specific cleavages may enable simulating realistic Hi-C read pairs for validation
of downstream analyses, monitoring the reproducibility of experimental conditions
and investigating biophysical properties that correlate with DNA cleavage patterns.
Here we describe a computational method for analyzing Hi-C read pairs to estimate
the fractions of cleavages at different possible targets. The method relies on expressing
an observed local target distribution downstream of aligned reads as a linear combination
of known conditional local target distributions. We validated this method using Hi-C
read pairs obtained by computer simulation. Application of the method to experimental
Hi-C datasets from murine cells revealed interesting similarities and differences
in patterns of cleavage across the various experiments considered.
Type
Journal articleSubject
AlgorithmsChromosomes
Computer Simulation
DNA Cleavage
DNA Restriction Enzymes
Datasets as Topic
Humans
Models, Biological
Nucleic Acid Conformation
Reproducibility of Results
Substrate Specificity
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https://hdl.handle.net/10161/15625Published Version (Please cite this version)
10.1093/nar/gkv820Publication Info
Meluzzi, Dario; & Arya, Gaurav (2016). Quantification of DNA cleavage specificity in Hi-C experiments. Nucleic Acids Res, 44(1). pp. e4. 10.1093/nar/gkv820. Retrieved from https://hdl.handle.net/10161/15625.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Gaurav Arya
Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science
My research laboratory uses physics-based computational tools to provide fundamental,
molecular-level understanding of a diverse range of biological and soft-material systems,
with the aim of discovering new phenomena and developing new technologies. The methods
we use or develop are largely based on statistical mechanics, molecular modeling and
simulations, stochastic dynamics, coarse-graining, bioinformatics, machine learning,
and polymer/colloidal physics. Our current resear

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