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

Genome Research
M Jordan RowleyVictor G Corces

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 bidire...Continue Reading

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Citations

Nov 11, 2020·ELife·Lorenzo CostantinoDouglas Koshland
Mar 21, 2021·Epigenetics & Chromatin·Beoung Hun Lee, Suhn K Rhie
Mar 20, 2021·Scientific Reports·Artem V LuzhinOmar L Kantidze
May 7, 2021·Nature Reviews. Molecular Cell Biology·Ivana Jerkovic, Giacomo Cavalli
May 18, 2021·Computational and Structural Biotechnology Journal·Haiyan GongXiaotong Zhang
Aug 14, 2021·Nature Communications·Hua-Jun WuFranziska Michor

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