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dc.contributor.authorDi Pierro, Michele
Cheng, Ryan R.
Aiden, Erez Lieberman
Wolynes, Peter G.
Onuchic, José N.
dc.date.accessioned 2017-12-21T18:21:51Z
dc.date.available 2017-12-21T18:21:51Z
dc.date.issued 2017
dc.identifier.citation Di Pierro, Michele, Cheng, Ryan R., Aiden, Erez Lieberman, et al.. "De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture." PNAS, 114, no. 46 (2017) National Academy of Sciences: 12126-12131. https://doi.org/10.1073/pnas.1714980114.
dc.identifier.urihttps://hdl.handle.net/1911/98912
dc.description.abstract Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from chromatin immunoprecipitation-sequencing (ChIP-Seq). We exploit the idea that chromosomes encode a 1D sequence of chromatin structural types. Interactions between these chromatin types determine the 3D structural ensemble of chromosomes through a process similar to phase separation. First, a neural network is used to infer the relation between the epigenetic marks present at a locus, as assayed by ChIP-Seq, and the genomic compartment in which those loci reside, as measured by DNA-DNA proximity ligation (Hi-C). Next, types inferred from this neural network are used as an input to an energy landscape model for chromatin organization [Minimal Chromatin Model (MiChroM)] to generate an ensemble of 3D chromosome conformations at a resolution of 50 kilobases (kb). After training the model, dubbed Maximum Entropy Genomic Annotation from Biomarkers Associated to Structural Ensembles (MEGABASE), on odd-numbered chromosomes, we predict the sequences of chromatin types and the subsequent 3D conformational ensembles for the even chromosomes. We validate these structural ensembles by using ChIP-Seq tracks alone to predict Hi-C maps, as well as distances measured using 3D fluorescence in situ hybridization (FISH) experiments. Both sets of experiments support the hypothesis of phase separation being the driving process behind compartmentalization. These findings strongly suggest that epigenetic marking patterns encode sufficient information to determine the global architecture of chromosomes and that de novo structure prediction for whole genomes may be increasingly possible.
dc.language.iso eng
dc.publisher National Academy of Sciences
dc.rights This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.title De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture
dc.type Journal article
dc.citation.journalTitle PNAS
dc.subject.keywordHi-C
energy landscape theory
epigenetics
genomic architecture
machine learning
dc.citation.volumeNumber 114
dc.citation.issueNumber 46
dc.identifier.digital PNAS-2017-DiPierro-12126-31
dc.type.dcmi Text
dc.identifier.doihttps://doi.org/10.1073/pnas.1714980114
dc.identifier.pmcid PMC5699090
dc.identifier.pmid 29087948
dc.type.publication publisher version
dc.citation.firstpage 12126
dc.citation.lastpage 12131


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This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
Except where otherwise noted, this item's license is described as This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).