Quantitative prediction of enhancer–promoter interactions

Recent experimental and computational efforts provided large datasets describing 3-dimensional organization of mouse and human genomes and showed interconnection between expression profile, epigenetic status and spatial interactions of loci. These interconnections were utilized to infer spatial organization of chromatin, including enhancer-promoter contacts, from 1-dimensional epigenetic marks. Here we showed that predictive power of some of these algorithms is overestimated due to peculiar properties of biological data. We proposed an alternative approach, which gives high-quality predictions of chromatin interactions using only information about gene expression and CTCF-binding. Using multiple metrics, we confirmed that our algorithm could efficiently predict 3-dimensional architecture of normal and rearranged genomes.

[1]  Simon J. van Heeringen,et al.  GimmeMotifs: a de novo motif prediction pipeline for ChIP-sequencing experiments , 2010, Bioinform..

[2]  Neva C. Durand,et al.  A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping , 2014, Cell.

[3]  Benjamin L. Moore,et al.  Integrative modeling reveals the principles of multi-scale chromatin boundary formation in human nuclear organization , 2015, Genome Biology.

[4]  A. Visel,et al.  Disruptions of Topological Chromatin Domains Cause Pathogenic Rewiring of Gene-Enhancer Interactions , 2015, Cell.

[5]  M. Martí-Renom,et al.  Chromatin and RNA Maps Reveal Regulatory Long Noncoding RNAs in Mouse , 2015, Molecular and Cellular Biology.

[6]  In This Issue , 2015, Cell.

[7]  Jean-Philippe Vert,et al.  HiC-Pro: an optimized and flexible pipeline for Hi-C data processing , 2015, Genome Biology.

[8]  Dariusz M Plewczynski,et al.  CTCF-Mediated Human 3D Genome Architecture Reveals Chromatin Topology for Transcription , 2015, Cell.

[9]  Dmitry A Afonnikov,et al.  Comparison of the three-dimensional organization of sperm and fibroblast genomes using the Hi-C approach , 2015, Genome Biology.

[10]  S. Mundlos,et al.  Formation of new chromatin domains determines pathogenicity of genomic duplications , 2016, Nature.

[11]  Michael Q. Zhang,et al.  De novo deciphering three-dimensional chromatin interaction and topological domains by wavelet transformation of epigenetic profiles , 2016, Nucleic acids research.

[12]  W. Huber,et al.  The Shh Topological Domain Facilitates the Action of Remote Enhancers by Reducing the Effects of Genomic Distances , 2016, Developmental cell.

[13]  James T. Robinson,et al.  Juicebox Provides a Visualization System for Hi-C Contact Maps with Unlimited Zoom. , 2016, Cell systems.

[14]  Simona Bianco,et al.  Polymer physics of chromosome large-scale 3D organisation , 2016, Scientific Reports.

[15]  Sharon R Grossman,et al.  Systematic mapping of functional enhancer–promoter connections with CRISPR interference , 2016, Science.

[16]  K. Pollard,et al.  Enhancer–promoter interactions are encoded by complex genomic signatures on looping chromatin , 2016, Nature Genetics.

[17]  M. Cecchini,et al.  Ultrastructural Characterization of the Lower Motor System in a Mouse Model of Krabbe Disease , 2016, Scientific Reports.

[18]  A. Tanay,et al.  Multiscale 3D Genome Rewiring during Mouse Neural Development , 2017, Cell.

[19]  R. David Hawkins,et al.  Three-dimensional genome architecture and emerging technologies: looping in disease , 2017, Genome Medicine.

[20]  Fowzan S Alkuraya,et al.  Computational Prediction of Position Effects of Apparently Balanced Human Chromosomal Rearrangements. , 2017, American journal of human genetics.

[21]  Michele Di Pierro,et al.  De Novo Prediction of Human Chromosome Structures: Epigenetic Marking Patterns Encode Genome Architecture , 2017, bioRxiv.

[22]  Leonid A. Mirny,et al.  Emerging Evidence of Chromosome Folding by Loop Extrusion , 2018, bioRxiv.

[23]  Erez Lieberman Aiden,et al.  De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture , 2017, Proceedings of the National Academy of Sciences.

[24]  William Stafford Noble,et al.  HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient , 2017, bioRxiv.

[25]  Edwin Cuppen,et al.  The genomic landscape of balanced cytogenetic abnormalities associated with human congenital anomalies , 2016, Nature Genetics.

[26]  Keith Nykamp,et al.  Pathogenic variant burden in the ExAC database: an empirical approach to evaluating population data for clinical variant interpretation , 2017, Genome Medicine.

[27]  N. Matveeva,et al.  Allele-Specific Biased Expression of the CNTN6 Gene in iPS Cell-Derived Neurons from a Patient with Intellectual Disability and 3p26.3 Microduplication Involving the CNTN6 Gene , 2018, Molecular Neurobiology.

[28]  K. Brennand,et al.  Kmt1e regulates a large neuron-specific topological chromatin domain , 2017, Nature Genetics.

[29]  William Stafford Noble,et al.  HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient , 2017, bioRxiv.

[30]  Michael P Snyder,et al.  Static and dynamic DNA loops form AP-1 bound activation hubs during macrophage development , 2017, bioRxiv.

[31]  Weiqun Peng,et al.  Predicting CTCF-mediated chromatin interactions by integrating genomic and epigenomic features , 2017, Nature Communications.

[32]  D. Marenduzzo,et al.  Polymer Simulations of Heteromorphic Chromatin Predict the 3D Folding of Complex Genomic Loci , 2018, bioRxiv.

[33]  Jian Ma,et al.  Predicting CTCF-mediated chromatin loops using CTCF-MP , 2018, bioRxiv.

[34]  V. Fishman,et al.  Interpreting Chromosomal Rearrangements in the Context of 3-Dimentional Genome Organization: A Practical Guide for Medical Genetics , 2018, Biochemistry (Moscow).

[35]  S. Mundlos,et al.  Polymer physics predicts the effects of structural variants on chromatin architecture , 2018, Nature Genetics.

[36]  E. Furlong,et al.  Developmental enhancers and chromosome topology , 2018, Science.

[37]  S. Mundlos,et al.  Structural variation in the 3D genome , 2018, Nature Reviews Genetics.

[38]  Deborah Chasman,et al.  In silico prediction of high-resolution Hi-C interaction matrices , 2018, Nature Communications.

[39]  M. Andrade-Navarro,et al.  7C: Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs , 2018, BMC Genomics.

[40]  De Novo Prediction of Human Chromosome Structures: Epigenetic Marking Patterns Encode Genome Architecture , 2018 .

[41]  R. Jiang,et al.  Prediction of enhancer-promoter interactions via natural language processing , 2018, BMC Genomics.

[42]  M. Andrade-Navarro,et al.  7C: Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs , 2019, BMC Genomics.

[43]  Jesse M. Engreitz,et al.  Activity-by-Contact model of enhancer specificity from thousands of CRISPR perturbations , 2019, bioRxiv.

[44]  K. Plath,et al.  Promoter-Enhancer Communication Occurs Primarily within Insulated Neighborhoods. , 2019, Molecular cell.