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Maximum parsimony interpretation of chromatin capture experiments


Autoři: Dirar Homouz aff001;  Andrzej S. Kudlicki aff004
Působiště autorů: Department of Physics, Khalifa University of Science and Technology, Abu Dhabi, UAE aff001;  Department of Physics, University of Houston, Houston, TX, United States of America aff002;  Center for Theoretical Biological Physics, Rice University, Houston, TX, United States of America aff003;  Institute for Translational Sciences, University of Texas Medical Branch, Galveston, TX, United States of America aff004;  Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, TX, United States of America aff005
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0225578

Souhrn

We present a new approach to characterizing the global geometric state of chromatin from HiC data. Chromatin conformation capture techniques (3C, and its variants: 4C, 5C, HiC, etc.) probe the spatial structure of the genome by identifying physical contacts between genomic loci within the nuclear space. In whole-genome conformation capture (HiC) experiments, the signal can be interpreted as spatial proximity between genomic loci and physical distances can be estimated from the data. However, observed spatial proximity signal does not directly translate into persistent contacts within the nuclear space. Attempts to infer a single conformation of the genome within the nuclear space lead to internal geometric inconsistencies, notoriously violating the triangle inequality. These inconsistencies have been attributed to the stochastic nature of chromatin conformation or to experimental artifacts. Here we demonstrate that it can be explained by a mixture of cells, each in one of only several conformational states, contained in the sample. We have developed and implemented a graph-theoretic approach that identifies the properties of such postulated subpopulations. We show that the geometrical conflicts in a standard yeast HiC dataset, can be explained by only a small number of homogeneous populations of cells (4 populations are sufficient to reconcile 95,000 most prominent impossible triangles, 8 populations can explain 375,000 top geometric conflicts). Finally, we analyze the functional annotations of genes differentially interacting between the populations, suggesting that each inferred subpopulation may be involved in a functionally different transcriptional program.

Klíčová slova:

Functional genomics – Genetic loci – Genome annotation – Genomic signal processing – Chromatin – Structural genomics – Transcriptional control – Yeast


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