ExperimentTypesci-Hi-C

released
   March 28th, 2019 at 5:41pm
Reference Publication
Ramani V et al. (2017) PMID:28135255
Ramani V, Deng X, et al., Nature methods 2017

Overview


Experiment Category 
Sequencing
Assay Classification 
3C via Ligation
Experimental Purpose 
DNA-DNA Pairwise Interactions - Single Cell
Raw Files Available 
Reads (fastq) provided by lab

Assay Description

Sci-Hi-C

Sci-Hi-C is a method to detect and quantify chromatin interactions in large numbers of single cells. This massively multiplexed method was developed in 2017 and it enables characterization of 3D genome architecture in thousands of single cells in parallel without requiring compartmentalization of each cell or microfluidic manipulation.

This protocol involves cross-linking the cells with formaldehyde. The cells are then permeabilized with their nuclei intact. A 4-cutter restriction enzyme DpnII is used to fragment the chromatin. Nuclei are then distributed to 96 wells, wherein the first barcode is introduced through ligation of barcoded biotinylated double-stranded bridge adaptors. Intact nuclei are then pooled and subjected to proximity ligation, followed by dilution and redistribution to a second 96-well plate. Importantly, this dilution is carried out such that each well in this second plate contains at most 25 nuclei. Following lysis, a second barcode is introduced through ligation of barcoded Y-adaptors. As the number of barcode combinations (96 × 96) exceeds the number of nuclei (96 × 25), the vast majority of single nuclei are tagged by a unique combination of barcodes. All material is once again pooled, and biotinylated junctions are purified with streptavidin beads, restriction digested, and further processed to Illumina sequencing libraries. Sequencing these molecules with relatively long paired-end reads (i.e., 2 × 250 base pairs) allows one to identify not only the genome-derived fragments of conventional Hi-C, but also external and internal barcodes, which enable decomposition of the Hi-C data into single-cell contact probability maps.

See Ramani et al 2017 for more details on in sci-Hi-C.



Image source: Ramani et. al. Nature Methods 2017, Figure 1a