PMID- 29087948 OWN - NLM STAT- MEDLINE DCOM- 20180619 LR - 20191210 IS - 1091-6490 (Electronic) IS - 0027-8424 (Print) IS - 0027-8424 (Linking) VI - 114 IP - 46 DP - 2017 Nov 14 TI - De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture. PG - 12126-12131 LID - 10.1073/pnas.1714980114 [doi] AB - 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. CI - Copyright (c) 2017 the Author(s). Published by PNAS. FAU - Di Pierro, Michele AU - Di Pierro M AD - Center for Theoretical Biological Physics, Rice University, Houston, TX 77005; michele.dipierro@rice.edu jonuchic@rice.edu. FAU - Cheng, Ryan R AU - Cheng RR AD - Center for Theoretical Biological Physics, Rice University, Houston, TX 77005. FAU - Lieberman Aiden, Erez AU - Lieberman Aiden E AD - Center for Theoretical Biological Physics, Rice University, Houston, TX 77005. AD - Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030. FAU - Wolynes, Peter G AU - Wolynes PG AD - Center for Theoretical Biological Physics, Rice University, Houston, TX 77005. AD - Department of Chemistry, Rice University, Houston, TX 77005. AD - Department of Physics & Astronomy, Rice University, Houston, TX 77005. FAU - Onuchic, Jose N AU - Onuchic JN AD - Center for Theoretical Biological Physics, Rice University, Houston, TX 77005; michele.dipierro@rice.edu jonuchic@rice.edu. AD - Department of Physics & Astronomy, Rice University, Houston, TX 77005. LA - eng GR - U01 HL130010/HL/NHLBI NIH HHS/United States GR - UM1 HG009375/HG/NHGRI NIH HHS/United States GR - DP2 OD008540/OD/NIH HHS/United States GR - P50 HG006193/HG/NHGRI NIH HHS/United States GR - RM1 HG006193/HG/NHGRI NIH HHS/United States PT - Journal Article PT - Research Support, N.I.H., Extramural PT - Research Support, Non-U.S. Gov't PT - Research Support, U.S. Gov't, Non-P.H.S. DEP - 20171031 PL - United States TA - Proc Natl Acad Sci U S A JT - Proceedings of the National Academy of Sciences of the United States of America JID - 7505876 RN - 0 (Chromatin) SB - IM MH - Animals MH - Cell Nucleus/chemistry/ultrastructure MH - Chromatin/*chemistry/ultrastructure MH - Chromosomes, Human/*chemistry/ultrastructure MH - *Epigenesis, Genetic MH - *Genome, Human MH - Humans MH - In Situ Hybridization, Fluorescence MH - Molecular Conformation MH - *Neural Networks, Computer MH - Phase Transition MH - Thermodynamics PMC - PMC5699090 OTO - NOTNLM OT - Hi-C OT - energy landscape theory OT - epigenetics OT - genomic architecture OT - machine learning COIS- The authors declare no conflict of interest. EDAT- 2017/11/01 06:00 MHDA- 2018/06/21 06:00 PMCR- 2017/10/31 CRDT- 2017/11/01 06:00 PHST- 2017/11/01 06:00 [pubmed] PHST- 2018/06/21 06:00 [medline] PHST- 2017/11/01 06:00 [entrez] PHST- 2017/10/31 00:00 [pmc-release] AID - 1714980114 [pii] AID - 201714980 [pii] AID - 10.1073/pnas.1714980114 [doi] PST - ppublish SO - Proc Natl Acad Sci U S A. 2017 Nov 14;114(46):12126-12131. doi: 10.1073/pnas.1714980114. Epub 2017 Oct 31.