Exploiting native forces to capture chromosome conformation in mammalian cell nuclei

Abstract

Mammalian interphase chromosomes fold into a multitude of loops to fit the confines of cell nuclei, and looping is tightly linked to regulated function. Chromosome conformation capture (3C) technology has significantly advanced our understanding of this structure‐to‐function relationship. However, all 3C‐based methods rely on chemical cross‐linking to stabilize spatial interactions. This step remains a “black box” as regards the biases it may introduce, and some discrepancies between microscopy and 3C studies have now been reported. To address these concerns, we developed “i3C”, a novel approach for capturing spatial interactions without a need for cross‐linking. We apply i3C to intact nuclei of living cells and exploit native forces that stabilize chromatin folding. Using different cell types and loci, computational modeling, and a methylation‐based orthogonal validation method, “ TALE ‐ iD ”, we show that native interactions resemble cross‐linked ones, but display improved signal‐to‐noise ratios and are more focal on regulatory elements and CTCF sites, while strictly abiding to topologically associating domain restrictions. image i3C captures chromatin folding in intact nuclei without a need for cross‐linking and reveals that native interactions resemble cross‐linked ones, yet they display improved signal‐to‐noise ratios and highlight how cis ‐elements and TAD s contribute to 3D genomic organization. i3C addresses the issue of potential biases introduced in 3C‐based studies by formaldehyde cross‐linking and harsh treatments. This protocol is robust, sensitive, and significantly faster than the conventional approach, and relies on native forces to preserve spatial interactions in uncross‐linked nuclei. Overall, i3C interaction profiles resemble conventional ones and highlight the contribution of both active and inactive regulatory regions in chromatin looping, as well as that of the restrictions imposed by topologically associating domain boundaries. i3C complements the existing toolkit and can prove especially useful for analyzing dense interaction matrices at high resolution.