Chromatin conformation
Chromatin conformation capture (3C) techniques reveal genomic interactions in three dimensions. This can provide key information on the effect of chromatin structure on transcriptional regulation; the data can also be utilised to orient contigs, producing highly contiguous scaffolded assemblies. However, the traditionally used short-read 3C methodology limits the number of contacts available to analyse per read. Combining chromatin conformation capture with long-read nanopore sequencing, Pore-C provides long-range contact information, shedding light on higher-order structure. The technique is PCR-free, allowing the characterisation of base modifications in the same dataset.
Use long sequencing reads to generate enhanced, multi-way chromatin interaction data
Pore-C offers a complete, end-to-end chromosome conformation capture workflow — from sample to results
Generate new insights into gene expression, investigate modified bases, and enhance genome assembly contiguity
A complete, end-to-end workflow for chromosome conformation capture
Oxford Nanopore provides the complete solution for investigating chromatin conformation: Pore-C is an end-to-end workflow, from sample preparation to analysis. Pore-C is provided as a comprehensive sample preparation and sequencing protocol (see the Pore-C protocols in the Prepare Documentation section of the Community), and an analysis pipeline available in GitHub (Figure 1). The workflow is suitable for multiple sample types, including whole blood, animal tissue, and plant tissue (see Community case study).
With long nanopore sequencing reads, you can obtain long-range, multi-way contact information; this cannot be achieved using Hi-C — the commonly used short-read-based 3C method, which produces pairwise data, limiting its utility for generating higher-order structural information. Furthermore, Pore-C requires no amplification step. Therefore, combined with the direct detection of modifications alongside nucleotide sequence, you can achieve an even more comprehensive understanding of the regulation of gene expression.
Figure 1: Pore-C laboratory workflow (a), multi-contact reads (b), and bioinformatics workflow (c). Pore-C virtual pairwise contacts derived from concatemeric reads show good concordance with Hi-C pairwise data (d).
Figure 2: Haplotype-resolved assemblies with ultra-long nanopore reads and Pore-C data. Schematic outlining the concept of haplotype-resolved assemblies (a), collapsed assembly, where each contig/scaffold has k-mers from both parents (b), trio-binned assemblies, where assemblies are produced for each haplotype (c), bioinformatic pipeline using a combination of long nanopore reads and Pore-C data for haplotype-resolved assembly (d), including phasing (e), and resolving haplotypes (f) and (g). Dot plots for both assembled haplotypes compared to the T2T CHM13 assembly (h) and (i).
Enhanced genome assemblies using long-range Pore-C data
As well as investigating chromatin architecture, the long reads obtained from the Pore-C workflow enable users to scaffold genome assemblies and correct genomes. Assembly contiguity can be substantially improved with the inclusion of Pore-C data (Figure 2). The Oxford Nanopore GitHub Pore-C analysis pipeline includes an assembly and scaffolding workflow, in addition to processing and outputting pairwise contact data. The data also allow resolution of entire megabase-sized structural variants (SVs), and an understanding of their association with chromatin conformation (see case study below).
From the same sample, and the same sequencing run, the following can therefore be obtained with Pore-C:
- Higher-order, multi-way contact data
- Epigenetic modifications
- Whole-genome sequence data for downstream assembly
- SV detection and resolution — including highly-complex, megabase-spanning variants
Together, these provide an unprecedented understanding of the regulation of gene expression.
Obtaining higher-order features of chromatin structure
...our results establish Pore-C as the most simple and scalable assay for the genome-wide assessment of combinatorial chromatin interactions, with additional applications for cancer rearrangement reconstruction and de novo genome
Deshpande et al. investigated high-order genome structure in human cells with Pore-C, using this technique to additionally gain a greater understanding of complex cancer genomic rearrangements and improve assembly scaffolding. The team determined that Pore-C assesses high-order contacts with substantially greater efficiency than other approaches. Using novel algorithms (Chromunity), they uncovered loci of cooperativity in the genome, and determined the methylation status of DNA participating in such high-order interactions relative to pairwise interactions occurring at the same loci. In addition, in the breast cancer cell line HCC1954, Pore-C data identified the presence of a complex amplification and rearrangement, connecting chromosomes 9, 12, and 20 (Figure 3). This result was confirmed using fluorescence in situ hybridisation. Lastly, the team also demonstrated that Pore-C enables ‘chromosome-scale de novo human genome assembly’.
Figure 3: Resolving complex genomic rearrangements using Pore-C-derived high-order chromatin contact data: a complex, multi-chromosomal arrangement between chromosomes 9, 12, and 20 was identified. From top: contact map of concatemers contributing to the allele; Pore-C concatemers; targets used for input to Chromunity (algorithm used for de novo discovery of high-order chromatin contacts); constructed rearranged allele; and lastly, the corresponding subgraph using JaBba (see software on GitHub). Contact map legends are in units of virtual pairwise contacts. (Adapted from Deshpande et al., 2022).
View the Pore-C protocols
Get detailed information on Pore-C sample preparation and sequencing.
How can I investigate chromatin conformation with Oxford Nanopore?
For a comprehensive investigation into chromatin conformation with Oxford Nanopore sequencing technology, we recommend following the Pore-C extraction protocol, and sequencing your library on a single PromethION Flow Cell as a starting point. Depending on the resolution desired, additional sequencing runs can be performed. The Pore-C info sheet provides advice regarding cell number and restriction enzyme usage, as well as other considerations that need to be made prior to commencing your Pore-C experiment.
The Pore-C sample preparation and sequencing protocols are available on the Extraction Protocols page of the Prepare Documentation section of the Nanopore Community website.
We recommend following one of the two Pore-C pipelines from the Oxford Nanopore GitHub resource for analysis of your Pore-C data:
- Pore-C-Snakemake: a more comprehensive analysis pipeline — recommended. This pipeline also aligns reads against the genome and converts pairwise contacts to contact matrices, enabling you to then view the data as a contact map (as seen above in Figure 1c).
- Pore-C: analysis of Pore-C sequencing data, adapted to deal with multi-contact reads. This pipeline deconstructs the multiway contacts into pairwise contacts in standard format (.pairs, .bed), for downstream analysis.
Note: both analysis pipelines require familiarity with the command line. Further advice and support can be found in the Nanopore Community.
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