Analysis of Hi-C data using SIP effectively identifies loops in organisms from C. elegans to mammals

• Type of Material: Article
• Authors: M. Jordan Rowley, Emory University; Axel Poulet, Emory University; Michael H. Nichols, Emory University; Brianna J. Bixler, Emory University; Adrian L. Sanborn, Baylor College of Medicine; Elizabeth A. Brouhard, University of Michigan; Karen Hermetz, Emory University; Hannah Linsenbaum, Emory University; Gyorgyi Csankovszki, University of Michigan; Erez Lieberman Aiden, Baylor College of Medicine; Victor Corces, Emory University
• Language: English
• Date: 2020-03-01
• Publisher: Cold Spring Harbor Laboratory Press
• Publication Version: Final Published Version
• Copyright Statement: © 2020 Rowley et al.; Published by Cold Spring Harbor Laboratory Press
• License: Creative Commons Attribution-NonCommercial 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1101/gr.257832.119
• Title of Journal or Parent Work: Genome Research
• Volume: 30
• Issue: 3
• Start Page: 447
• End Page: 458
• Grant/Funding Information: This work was supported by National Institutes of Health (NIH) Pathway to Independence Award K99/R00 GM127671 (M.J.R.) and U.S. Public Health Service Award R01 GM035463 (V.G.C.) from the National Institutes of Health.; B.J.B. was supported by NIH T32 GM008490.
• Keywords: Genetics & Heredity; Science & Technology; Principles; Biotechnology & Applied Microbiology; Cohesin; Genome; Biochemistry & Molecular Biology; CTCF; Topology; Chromatin; Life Sciences & Biomedicine
• Research Categories: Biology, Genetics; Biology, Microbiology; Chemistry, Biochemistry; Biology, Molecular

Abstract

Chromatin loops are a major component of 3D nuclear organization, visually apparent as intense point-to-point interactions in Hi-C maps. Identification of these loops is a critical part of most Hi-C analyses. However, current methods often miss visually evident CTCF loops in Hi-C data sets from mammals, and they completely fail to identify high intensity loops in other organisms. We present SIP, Significant Interaction Peak caller, and SIPMeta, which are platform independent programs to identify and characterize these loops in a time- and memory-efficient manner. We show that SIP is resistant to noise and sequencing depth, and can be used to detect loops that were previously missed in human cells as well as loops in other organisms. SIPMeta corrects for a common visualization artifact by accounting for Manhattan distance to create average plots of Hi-C and HiChIP data. We then demonstrate that the use of SIP and SIPMeta can lead to biological insights by characterizing the contribution of several transcription factors to CTCF loop stability in human cells. We also annotate loops associated with the SMC component of the dosage compensation complex (DCC) in Caenorhabditis elegans and demonstrate that loop anchors represent bidirectional blocks for symmetrical loop extrusion. This is in contrast to the asymmetrical extrusion until unidirectional blockage by CTCF that is presumed to occur in mammals. Using HiChIP and multiway ligation events, we then show that DCC loops form a network of strong interactions that may contribute to X Chromosome-wide condensation in C. elegans hermaphrodites.