Hi-C 2.0: An optimized Hi-C procedure for high-resolution genome-wide mapping of chromosome conformation.

Chromosome conformation capture-based methods such as Hi-C have become mainstream techniques for the study of the 3D organization of genomes. These methods convert chromatin interactions reflecting topological chromatin structures into digital information (counts of pair-wise interactions). Here, we describe an updated protocol for Hi-C (Hi-C 2.0) that integrates recent improvements into a single protocol for efficient and high-resolution capture of chromatin interactions. This protocol combines chromatin digestion and frequently cutting enzymes to obtain kilobase (kb) resolution. It also includes steps to reduce random ligation and the generation of uninformative molecules, such as unligated ends, to improve the amount of valid intra-chromosomal read pairs. This protocol allows for obtaining information on conformational structures such as compartment and topologically associating domains, as well as high-resolution conformational features such as DNA loops.

[1]  J. Dekker,et al.  Capturing Chromosome Conformation , 2002, Science.

[2]  J. Sedat,et al.  Spatial partitioning of the regulatory landscape of the X-inactivation centre , 2012, Nature.

[3]  Neva C. Durand,et al.  Juicer Provides a One-Click System for Analyzing Loop-Resolution Hi-C Experiments. , 2016, Cell systems.

[4]  Giorgio Bernardi,et al.  Chromosome Architecture and Genome Organization , 2015, PloS one.

[5]  L. Mirny,et al.  Iterative Correction of Hi-C Data Reveals Hallmarks of Chromosome Organization , 2012, Nature Methods.

[6]  Geoffrey Fudenberg,et al.  Micro-C XL: assaying chromosome conformation from the nucleosome to the entire genome , 2016, Nature Methods.

[7]  A. Tanay,et al.  Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture , 2011, Nature Genetics.

[8]  Jesse R. Dixon,et al.  Topological Domains in Mammalian Genomes Identified by Analysis of Chromatin Interactions , 2012, Nature.

[9]  Philip A. Ewels,et al.  HiCUP: pipeline for mapping and processing Hi-C data , 2015, F1000Research.

[10]  Job Dekker,et al.  Invariant TAD Boundaries Constrain Cell-Type-Specific Looping Interactions between Promoters and Distal Elements around the CFTR Locus. , 2016, American journal of human genetics.

[11]  Philip A. Ewels,et al.  Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C , 2015, Nature Genetics.

[12]  Yan Li,et al.  A high-resolution map of three-dimensional chromatin interactome in human cells , 2013, Nature.

[13]  Neva C. Durand,et al.  Chromatin extrusion explains key features of loop and domain formation in wild-type and engineered genomes , 2015, Proceedings of the National Academy of Sciences.

[14]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[15]  I. Amit,et al.  Comprehensive mapping of long range interactions reveals folding principles of the human genome , 2011 .

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

[17]  William Stafford Noble,et al.  Fine-scale chromatin interaction maps reveal the cis-regulatory landscape of human lincRNA genes , 2014, Nature Methods.

[18]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[19]  P. Fraser,et al.  Comparison of Hi-C results using in-solution versus in-nucleus ligation , 2015, Genome Biology.

[20]  K. Sandhu,et al.  Circular chromosome conformation capture (4C) uncovers extensive networks of epigenetically regulated intra- and interchromosomal interactions , 2006, Nature Genetics.

[22]  J. Dekker,et al.  Condensin-Driven Remodeling of X-Chromosome Topology during Dosage Compensation , 2015, Nature.

[23]  A. Tanay,et al.  Single cell Hi-C reveals cell-to-cell variability in chromosome structure , 2013, Nature.

[24]  Noam Kaplan,et al.  The Hitchhiker's guide to Hi-C analysis: practical guidelines. , 2015, Methods.

[25]  B. Steensel,et al.  Nuclear organization of active and inactive chromatin domains uncovered by chromosome conformation capture–on-chip (4C) , 2006, Nature Genetics.

[26]  Josée Dostie,et al.  From cells to chromatin: capturing snapshots of genome organization with 5C technology. , 2012, Methods.

[27]  E. Liu,et al.  An Oestrogen Receptor α-bound Human Chromatin Interactome , 2009, Nature.

[28]  C. Glass,et al.  Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. , 2010, Molecular cell.

[29]  Elzo de Wit,et al.  Determining long-range chromatin interactions for selected genomic sites using 4C-seq technology: from fixation to computation. , 2012, Methods.

[30]  Yaniv Lubling,et al.  Single-cell Hi-C for genome-wide detection of chromatin interactions that occur simultaneously in a single cell , 2015, Nature Protocols.

[31]  M. Gobbi,et al.  Analysis of hundreds of cis-regulatory landscapes at high resolution in a single, high-throughput experiment , 2014, Nature Genetics.

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

[33]  J. Dekker,et al.  The long-range interaction landscape of gene promoters , 2012, Nature.

[34]  Sergey V. Razin,et al.  In vivo formaldehyde cross-linking: it is time for black box analysis , 2014, Briefings in functional genomics.

[35]  Nir Friedman,et al.  Mapping Nucleosome Resolution Chromosome Folding in Yeast by Micro-C , 2015, Cell.

[36]  J. Dekker,et al.  Hi-C: a comprehensive technique to capture the conformation of genomes. , 2012, Methods.

[37]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[38]  Yijun Ruan,et al.  Chromatin Interaction Analysis Using Paired‐End Tag Sequencing , 2010, Current protocols in molecular biology.

[39]  Job Dekker,et al.  TAD disruption as oncogenic driver. , 2016, Current opinion in genetics & development.