Hi-CO: 3D genome structure analysis with nucleosome resolution

The nucleosome is the basic organizational unit of the genome. The folding structure of nucleosomes is closely related to genome functions, and has been reported to be in dynamic interplay with binding of various nuclear proteins to genomic loci. Here, we describe our high-throughput chromosome conformation capture with nucleosome orientation (Hi-CO) technology to derive 3D nucleosome positions with their orientations at every genomic locus in the nucleus. This technology consists of an experimental procedure for nucleosome proximity analysis and a computational procedure for 3D modeling. The experimental procedure is based on an improved method of high-throughput chromosome conformation capture (Hi-C) analysis. Whereas conventional Hi-C allows spatial proximity analysis among genomic loci with 1–10 kbp resolution, our Hi-CO allows proximity analysis among DNA entry or exit points at every nucleosome locus. This analysis is realized by carrying out ligations among the entry/exit points in every nucleosome in a micrococcal-nuclease-fragmented genome, and by quantifying frequencies of ligation products with next-generation sequencing. Our protocol has enabled this analysis by cleanly excluding unwanted non-ligation products that are abundant owing to the frequent genome fragmentation by micrococcal nuclease. The computational procedure is based on simulated annealing-molecular dynamics, which allows determination of optimized 3D positions and orientations of every nucleosome that satisfies the proximity ligation data sufficiently well. Typically, examination of the Saccharomyces cerevisiae genome with 130 million sequencing reads facilitates analysis of a total of 66,360 nucleosome loci with 6.8 nm resolution. The technique requires 2–3 weeks for sequencing library preparation and 2 weeks for simulation. The authors describe a step-by-step workflow for generating genome-wide chromatin interaction maps with nucleosome resolution using proximity ligation and deep sequencing followed by modeling optimal nucleosome position and orientation.