Massively multiplex single-cell Hi-C

Abstract

We present single-cell combinatorial indexed Hi-C (sciHi-C), a method that applies combinatorial cellular indexing to chromosome conformation capture. In this proof of concept, we generate and sequence six sciHi-C libraries comprising a total of 10,696 single cells. We use sciHi-C data to separate cells by karyotypic and cell-cycle state differences and identify cell-to-cell heterogeneity in mammalian chromosomal conformation. Our results demonstrate that combinatorial indexing is a generalizable strategy for single-cell genomics.

Figure 1. Single-cell combinatorial indexed Hi-C integrates the in situ Hi-C protocol with combinatorial cellular indexing to generate signal-rich bulk Hi-C maps that can be decomposed into single cell Hi-C maps

a.) sciHi-C follows the traditional paradigm of fixation, digestion, and re-ligation shared by all Hi-C assays (Steps 1 – 4), but uses a biotinylated bridge adaptor to incorporate a first round of barcodes prior to proximity ligation (Step 3), and custom barcoded Illumina Y-adaptors (Step 5) to incorporate a second round of barcodes prior to affinity purification and library amplification (Steps 5 – 6). b.) Bulk data generated by this protocol can be decomposed to single cell Hi-C maps. c.) sciHi-C libraries demonstrate a high cis:trans ratio, measured as the ratio of intrachromosomal contacts > 20 kb apart to interchromosomal contacts. d.) The high cis:trans ratio observed in bulk data is maintained after libraries are decomposed to ~1800 cellular indices (each with >= 1,000 unique reads).

Figure 2. The large number of cellular indices generated through combinatorial single cell Hi-C are overwhelmingly species-specific, and can be separated by cell type

a.) In libraries ML1 and ML2, similar levels of collision (defined as any cellular index with at least 1,000 unique reads, but <95% species purity) are observed, and fall within the expected range. b.) Species contamination visualized as a histogram of the fraction of reads mapping to the human genome (only cellular indices with >= 1000 reads shown). c.) Projection onto the first two principal components from PCA analysis of interchromosomal contact matrices results in separation of HeLa S3 and HAP1, two karytoypically different cell lines (n = 3,609 cells). Percentages shown are the percentage of variance explained by each plotted component. d.) Principal component 2 loadings represent the contribution of each feature (interchromosomal contact) to the observed cell type separation. Known translocations for each cell type are mirrored against the loading heatmap.

Figure 3. sciHi-C of nocadazole arrested HeLa S3 cells enable in silico sorting by cell cycle progression

a.) Mean contact probability and standard deviation as a function of genomic distance for single HeLa S3 cells from a population treated with nocadazole (n = 588 cells containing at least 5,000 contacts and harboring nocadazole experiment-specific programmed barcodes). As a control, untreated cells were processed simultaneously (data not shown). b.) Scaling coefficients for 588 single HeLa S3 cells follow a bimodal distribution. c.) Cells can be “sorted” in silico to generate two distinct contact probability maps, shown here for HeLa chromosome 12.