De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture

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dc.citation.firstpage12126
dc.citation.issueNumber46
dc.citation.journalTitlePNAS
dc.citation.lastpage12131
dc.citation.volumeNumber114
dc.contributor.authorDi Pierro, Michele
dc.contributor.authorCheng, Ryan R.
dc.contributor.authorAiden, Erez Lieberman
dc.contributor.authorWolynes, Peter G.
dc.contributor.authorOnuchic, José N.
dc.contributor.orgCenter for Theoretical Biological Physics
dc.date.accessioned2017-12-21T18:21:51Z
dc.date.available2017-12-21T18:21:51Z
dc.date.issued2017
dc.description.abstractInside 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.identifier.citationDi Pierro, Michele, Cheng, Ryan R., Aiden, Erez Lieberman, et al.. "De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture." <i>PNAS,</i> 114, no. 46 (2017) National Academy of Sciences: 12126-12131. https://doi.org/10.1073/pnas.1714980114.
dc.identifier.digitalPNAS-2017-DiPierro-12126-31
dc.identifier.doihttps://doi.org/10.1073/pnas.1714980114
dc.identifier.urihttps://hdl.handle.net/1911/98912
dc.language.isoeng
dc.publisherNational Academy of Sciences
dc.rightsThis 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.subject.keywordHi-C
dc.subject.keywordenergy landscape theory
dc.subject.keywordepigenetics
dc.subject.keywordgenomic architecture
dc.subject.keywordmachine learning
dc.titleDe novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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