{ "id": "ep6eqs4jcs", "slug": "pore-c", "title": "Pore-C", "updated": "2026-10-15", "topic_path": [ { "id": "life", "label": "Life and health", "api_url": "https://www.edgepedia.org/api/v1/topics/life" }, { "id": "life.biology", "label": "Biological foundations", "api_url": "https://www.edgepedia.org/api/v1/topics/life.biology" }, { "id": "life.biology.genetics", "label": "Genetics and genomic reference", "api_url": "https://www.edgepedia.org/api/v1/topics/life.biology.genetics" }, { "id": "life.biology.genetics.genomics_projects_databases", "label": "Genomics, sequencing, and genome resources", "api_url": "https://www.edgepedia.org/api/v1/topics/life.biology.genetics.genomics_projects_databases" }, { "id": "life.biology.genetics.genomics_projects_databases.genome-structure-and-conformation-methods", "label": "Genome structure and conformation methods", "api_url": "https://www.edgepedia.org/api/v1/topics/life.biology.genetics.genomics_projects_databases.genome-structure-and-conformation-methods" } ], "geo": [ { "id": "geo.nongeo.t2001.life.biology.genetics.genomics_projects_databases", "label": "Non-geographic · 2001 to 2020: Genomics, sequencing, and genome resources", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001.life.biology.genetics.genomics_projects_databases", "path": [ { "id": "geo.nongeo", "label": "Non-geographic", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo" }, { "id": "geo.nongeo.t2001", "label": "Non-geographic · 2001 to 2020", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001" }, { "id": "geo.nongeo.t2001.life", "label": "Life and health", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001.life" }, { "id": "geo.nongeo.t2001.life.biology", "label": "Biological foundations", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001.life.biology" }, { "id": "geo.nongeo.t2001.life.biology.genetics", "label": "Genetics and genomic reference", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001.life.biology.genetics" }, { "id": "geo.nongeo.t2001.life.biology.genetics.genomics_projects_databases", "label": "Genomics, sequencing, and genome resources", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001.life.biology.genetics.genomics_projects_databases" } ] } ], "excerpt": "Pore-C is a chromatin conformation capture method combining proximity ligation with Oxford Nanopore long-read sequencing to read multi-way chromatin contacts directly, introduced in Nature Biotechnology in 2022.", "snippet": "Pore-C is a chromatin conformation capture method combining proximity ligation with Oxford Nanopore long-read sequencing to read multi-way chromatin contacts directly, introduced in Nature Biotechnology in 2022.", "node": "life.biology.genetics.genomics_projects_databases.genome-structure-and-conformation-methods", "markdown": "# Pore-C\n\nPore-C is a chromatin conformation capture method that combines proximity ligation with Oxford Nanopore long-read sequencing to read multi-way chromatin contacts directly, as concatemers, at genome scale. Where Hi-C reports only pairwise contacts between two loci, a single Pore-C read can carry fragments from many interacting loci in one molecule, so the assay outputs both standard pairwise contact maps and higher-order, single-molecule interaction data without amplification.[1](https://doi.org/10.1038/s41587-022-01289-z) • [2](https://www.biorxiv.org/content/10.1101/833590v1.full.pdf)\n\n| Key fact | Detail |\n|---|---|\n| Output | Concatemer reads, each carrying multiple ligated fragments; a read with n fragments decomposes into C(n, 2) virtual pairwise contacts[3](https://www.nature.com/articles/s41467-023-36899-x) |\n| Contact order | Median contact order 7; 78.09%, 10.23%, and 1.04% of reads carry order greater than 2, 10, and 20[2](https://www.biorxiv.org/content/10.1101/833590v1.full.pdf) |\n| Contact density | NlaIII libraries average 6.5 million contacts per Gbp sequenced, close to Hi-C made with 100 bp paired-end reads[2](https://www.biorxiv.org/content/10.1101/833590v1.full.pdf) |\n| Per-run yield | A single PromethION run of an NlaIII library can yield a contact map with more than 1 billion virtual pairwise contacts[2](https://www.biorxiv.org/content/10.1101/833590v1.full.pdf) |\n| Fragment length | Contact fragments are roughly 600–1000 bp, versus Hi-C reads of usually ≤150 bp[4](https://www.biorxiv.org/content/10.1101/2023.08.29.555243v1) |\n| Higher-order efficiency | 18.5-fold higher efficiency and greater fidelity than SPRITE, with more than 12-fold enrichment of contacts of order greater than 3[2](https://www.biorxiv.org/content/10.1101/833590v1.full.pdf) |\n| Main failure mode | Crosslinked proteins clog nanopore pores; protease digestion (proteinase K plus pronase) raises yield about 80%[3](https://www.nature.com/articles/s41467-023-36899-x) |\n\n## How it works\n\nPore-C rests on the 3C principle: crosslinked chromatin is digested, and DNA ends that were near each other in the nucleus are ligated together. In conventional Hi-C the ligation products are read as short paired-end reads, so each molecule yields at most one pairwise contact. In Pore-C the ligation is allowed to join multiple proximal monomers into a single chimeric polymer, a concatemer, which is then sequenced natively end-to-end on a nanopore flow cell.[2](https://www.biorxiv.org/content/10.1101/833590v1.full.pdf) • [5](https://nanoporetech.com/document/restriction-enzyme-pore-c)\n\nEach concatemer read is decomposed into its constituent fragments, and the ordered alignment of those fragments to the reference is called a \"walk\". A read with n ligated fragments generates C(n, 2) pairwise contacts when decomposed, so one molecule contributes many entries to a contact matrix while also preserving which fragments co-occurred on the same DNA molecule. That co-occurrence is what makes multi-way, or higher-order, contacts observable: Pore-C can profile interactions involving more than 10 loci, and the statistical method Chromunity identifies sets of loci whose high-order contact frequencies exceed background, termed \"synergies\".[1](https://doi.org/10.1038/s41587-022-01289-z) • [3](https://www.nature.com/articles/s41467-023-36899-x) • [4](https://www.biorxiv.org/content/10.1101/2023.08.29.555243v1)\n\n## How it is done\n\nThe wet-lab workflow proceeds in order: crosslinking, nuclear permeabilization, chromatin denaturation with detergent and gentle heat, restriction digestion, enzyme inactivation, proximity ligation of proximal monomers into chimeric polymers, overnight proteinase K digestion, and phenol:chloroform extraction with [ethanol precipitation](https://www.edgepedia.org/ethanol-precipitation). The protocol uses an in-nucleus 3C approach, performing digestion and ligation inside permeabilized nuclei to preserve cis-chromosomal contacts and reduce trans-chromosomal contacts. ONT primarily used the 4-cutters DpnII and NlaIII, and also compared the 6-cutters [HindIII](https://www.edgepedia.org/hindiii) and SphI; in situ digestion with DpnII or NlaIII yields average fragment lengths of approximately 7 kb after SPRI size selection, and native extracts average under 10 kbp. PCR is not required, and native sequencing preserves base modifications, though a PCR-based Rapid PCR Barcoding Kit fallback exists for low-yield extracts at the cost of a higher cis:trans ratio.[5](https://nanoporetech.com/document/restriction-enzyme-pore-c)\n\nOn the computational side, ONT maintains wf-pore-c, a Nextflow EPI2ME workflow that performs virtual digestion, alignment with minimap2 (-x map-ont), ligation junction detection, and fragment assignment, outputting pairs, cooler (mcool), Hi-C format, and Chromunity parquet files. Reads with more than max_monomers (default 250) are excluded as assumed errors. The original paper aligned concatemers with a directed acyclic graph built by partially ordering reference alignments, traversed greedily to produce the final concatemer alignment.[1](https://doi.org/10.1038/s41587-022-01289-z) • [6](https://nanoporetech.com/document/epi2me-workflows/wf-pore-c) The MapPore-C pipeline, developed to address low base-calling accuracy, integrates NGMLR and Minimap2 to map fragments in multiway contact reads and generate virtual pairwise contacts.[3](https://www.nature.com/articles/s41467-023-36899-x)\n\n## Origin\n\nPore-C was introduced by Aditya S. Deshpande, Netha Ulahannan, Matthew Pendleton, and colleagues in \"Identifying synergistic high-order 3D chromatin conformations from genome-scale nanopore concatemer sequencing\", published in [Nature Biotechnology](https://www.edgepedia.org/nature-biotechnology) in 2022.[1](https://doi.org/10.1038/s41587-022-01289-z) The method builds on 3C and on in-nucleus chromatin conformation capture protocols that carry out digestion and ligation inside permeabilized nuclei (Nagano et al., 2015).[5](https://nanoporetech.com/document/restriction-enzyme-pore-c) HiPore-C, a high-throughput variant with a coupled methylation readout and the MapPore-C pipeline, was reported by Jia-Yong Zhong and colleagues in [Nature Communications](https://www.edgepedia.org/nature-communications) in 2023.[3](https://www.nature.com/articles/s41467-023-36899-x)\n\n## Variants\n\n**HiPore-C** simplifies the procedure and adds protease treatment, capturing multiway interactions and [DNA methylation](https://www.edgepedia.org/dna-methylation) in one experiment; its methylation calls correlate with WGBS at Pearson \\( r = 0.8038 \\), and it provides more virtual pairwise interactions than traditional Hi-C and Pore-C for the same cost.[3](https://www.nature.com/articles/s41467-023-36899-x)\n\n**RE-Pore-C** refers to the restriction-enzyme protocol choices documented by ONT. Libraries made with the Ligation Sequencing Kit (SQK-LSK110 or SQK-LSK109) on R9.4.1 flow cells yield 1–2 Gb in 6 hours or 4–8 Gb in 48 hours per MinION Mk1B/GridION flow cell; SQK-LSK114 on R10.4.1 flow cells gives similar output with better resolution of repeat-rich regions such as centromeres, aiding scaffolding of dark genome regions.[5](https://nanoporetech.com/document/restriction-enzyme-pore-c)\n\n**Haplotagging** assigns fragments to parental haplotypes. The wf-pore-c workflow supports haplotagging via Whatshap when a phased VCF is supplied.[6](https://nanoporetech.com/document/epi2me-workflows/wf-pore-c) The Dip3D pipeline uses Falign for mapping, a Pore-C-trained Clair3 model for SNV calling (over 95% recall and precision on ≥30× Pore-C data), and HapCUT2 for phasing, raising the SNV phasing rate 11.9-fold to 72.7% on HG001 data; in [F1 hybrid](https://www.edgepedia.org/f1-hybrid) mice, more than 93% of Pore-C reads were h-cis reads carrying fragments from the same haplotypes.[4](https://www.biorxiv.org/content/10.1101/2023.08.29.555243v1)\n\n**Epi-PoreC** combines Pore-C with [Fiber-seq](https://www.edgepedia.org/fiber-seq) adenine methyltransferase labeling, so that chromatin contacts, 6-methyladenosines, and endogenous 5-methylcytosines are detected on the same DNA molecules; demonstrated in [Arabidopsis thaliana](https://www.edgepedia.org/arabidopsis-thaliana) nuclei, it yields contact maps comparable to standard Pore-C and methylation and accessibility profiles comparable to standard Fiber-seq. Fiber-seq itself was introduced by [Andrew B. Stergachis](https://www.edgepedia.org/andrew-b-stergachis), Brian M. Debo, Eric Haugen, L. Stirling Churchman, and John A. Stamatoyannopoulos in Science in 2020.[7](https://doi.org/10.64898/2026.09.15.751767) • [8](https://doi.org/10.1126/science.aaz1646) Epi-PoreC was reported by Anastasia McKinlay, Wei Zong, and Craig S. Pikaard in bioRxiv in 2026.[7](https://doi.org/10.64898/2026.09.15.751767)\n\n## Applications\n\n**Genome assembly.** For HG002 scaffolding, HindIII-derived Pore-C data yielded the longest scaffold (216 Mbp) with a nearly 10-fold NG50 increase (98.6 Mbp) over the WGS assembly, while NlaIII gave a 3.2-fold improvement (33.2 Mbp), and Pore-C generated a chromosome-scale de novo assembly of HG002.[2](https://www.biorxiv.org/content/10.1101/833590v1.full.pdf) Dip3D on 190× HG001 Pore-C data achieved 6.9-fold higher haplotype-assigned contact density (1.80 vs 0.26 M/Gb), 10-fold higher resolution (5 kb vs 50 kb), and 63.9% fewer gap regions than a 531× Hi-C matrix, with an ungapped haplotype contact block N50 of 14.5 Mb versus 2.9 kb.[4](https://www.biorxiv.org/content/10.1101/2023.08.29.555243v1)\n\n**Structural variation and cancer.** In HCC1954 breast cancer cells, Pore-C contacts enable reconstruction of complex aneuploid rearranged alleles spanning multiple megabases and chromosomes; Chromunity synergies in breast cancer cells were associated with tyfonas DNA amplicons, and in prostate cancer cells with androgen-regulated genes in active chromatin.[2](https://www.biorxiv.org/content/10.1101/833590v1.full.pdf) • [1](https://doi.org/10.1038/s41587-022-01289-z)\n\n**Single-allele topology and bacteria.** Applied to GM12878 and K562 cells, fragments in multi-contact reads generally coexist in the same TAD, while a significant proportion span multiple compartments of the same chromatin type over megabase distances, and single-allele topology clusters are cell type-specific even inside conserved TADs.[3](https://www.nature.com/articles/s41467-023-36899-x) Pore-C has also been applied to [Streptococcus pneumoniae](https://www.edgepedia.org/streptococcus-pneumoniae), with NlaIII or MluCI digestion and 12-plex native barcoding (SQK-NBD114.24) at roughly 400 ng DNA per replicate.[9](https://journals.plos.org/plospathogens/article?id=10.1371%2Fjournal.ppat.1013392)\n\n## Limitations and alternatives\n\nThe dominant failure mode is pore clogging: DNA-bound proteins as small as 2 kD can clog nanopore pores, and incomplete removal of crosslinked proteins during library preparation causes clogging. HiPore-C solved this with proteinase K digestion plus pronase, raising output to an average of 128 Gbase (two rounds of proteinase K with reverse crosslinking) or 144 Gbase (three rounds) per PromethION cell; a pronase protocol achieved 128 Gbase with fewer steps, and the pronase step has been adopted in bacterial Pore-C work.[3](https://www.nature.com/articles/s41467-023-36899-x) • [9](https://journals.plos.org/plospathogens/article?id=10.1371%2Fjournal.ppat.1013392) Even so, average Pore-C throughput is relatively low, and the method is more expensive than traditional Hi-C for generating the same number of pairwise contacts.[3](https://www.nature.com/articles/s41467-023-36899-x)\n\nAgainst other higher-order methods, Pore-C detects higher-order structure at 18.5-fold higher efficiency and greater fidelity than SPRITE, whose clusters have a median order of 4, and unlike ChIA-Drop it does not suffer from barcode collisions.[2](https://www.biorxiv.org/content/10.1101/833590v1.full.pdf) Among short-read methods, Hi-C and Micro-C differ in crosslinking chemistry and fragmentation strategy, Micro-C captures more local detail such as loops, and Hi-C 3.0 was developed to detect both loops and compartments relatively effectively; contact maps from all these assays are 2D matrices of pairwise frequencies normalized with ICE iterative correction and observed-over-expected transformation.[10](https://pubmed.ncbi.nlm.nih.gov/34480151/) • [11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11978506/) No published head-to-head benchmark directly compares Pore-C with ChIA-PET or scHi-C, and no true single-cell Pore-C wet-lab protocol has been described.\n\n## References\n\n1. [Aditya S. Deshpande and colleagues (2022). Identifying synergistic high-order 3D chromatin conformations from genome-scale nanopore concatemer sequencing. Nature Biotechnology.](https://doi.org/10.1038/s41587-022-01289-z)\n2. [Nanopore sequencing of DNA concatemers reveals higher-order features of chromatin structure (Pore-C preprint, Deshpande et al. 2019)](https://www.biorxiv.org/content/10.1101/833590v1.full.pdf)\n3. [High-throughput Pore-C reveals the single-allele topology and cell type-specificity of 3D genome folding (HiPore-C, Zhong et al., Nature Communications 2023)](https://www.nature.com/articles/s41467-023-36899-x)\n4. [High-resolution diploid 3D genome reconstruction using Pore-C data (Dip3D)](https://www.biorxiv.org/content/10.1101/2023.08.29.555243v1)\n5. [Restriction enzyme Pore-C (RE-Pore-C) info sheet](https://nanoporetech.com/document/restriction-enzyme-pore-c)\n6. [wf-pore-c | Oxford Nanopore Technologies (EPI2ME workflow documentation)](https://nanoporetech.com/document/epi2me-workflows/wf-pore-c)\n7. [Anastasia McKinlay, Wei Zong, Craig S. Pikaard (2026). Epi-PoreC: a nanopore-based method for simultaneous profiling of chromatin conformation, DNA methylation, and chromatin accessibility. bioRxiv (Cold Spring Harbor Laboratory).](https://doi.org/10.64898/2026.09.15.751767)\n8. [Andrew B. Stergachis and colleagues (2020). Single-molecule regulatory architectures captured by chromatin fiber sequencing. Science.](https://doi.org/10.1126/science.aaz1646)\n9. [Pore-C sequencing identifies episome-driven chromosome conformation perturbations differentiating pneumococcal epigenetic variants (PLOS Pathogens, 2025)](https://journals.plos.org/plospathogens/article?id=10.1371%2Fjournal.ppat.1013392)\n10. [Systematic evaluation of chromosome conformation capture assays (Nature Methods, 2021)](https://pubmed.ncbi.nlm.nih.gov/34480151/)\n11. [Comparing chromatin contact maps at scale: methods and insights (2025)](https://pmc.ncbi.nlm.nih.gov/articles/PMC11978506/)\n\n---\n*Topic: Encyclopedia › Life and health › Biological foundations › Genetics and genomic reference › Genomics, sequencing, and genome resources › Genome structure and conformation methods*\n\n*Initially written Sep 29, 2026 · Edited: Oct 15, 2026*\n\n*Copyright 2026 EdgeChat AI, a subsidiary of Biostate AI.*\n\nLicense: Edgepedia Community License 1.0, https://www.edgepedia.org/edgepedia/license\n", "same_as": [], "url": "https://www.edgepedia.org/pore-c", "markdown_url": "https://www.edgepedia.org/pore-c.md", "license": { "name": "Edgepedia Community License 1.0", "url": "https://www.edgepedia.org/edgepedia/license", "summary": "Free with credit, commercial use included. AI training is open to everyone. For other uses, organizations over USD 100M in revenue or 100M monthly users license separately.", "spdx": "LicenseRef-Edgepedia-Community-1.0" }, "credit": "\"Pore-C\", Edgepedia (EdgeChat), https://www.edgepedia.org/pore-c. Edgepedia Community License 1.0.", "credit_md": "\"[Pore-C](https://www.edgepedia.org/pore-c)\", Edgepedia (EdgeChat), [https://www.edgepedia.org/pore-c](https://www.edgepedia.org/pore-c). [Edgepedia Community License 1.0](https://www.edgepedia.org/edgepedia/license).", "credit_html": "\"Pore-C\", Edgepedia (EdgeChat), https://www.edgepedia.org/pore-c. Edgepedia Community License 1.0.", "speakable": "Pore-C is a chromatin conformation capture method combining proximity ligation with Oxford Nanopore long-read sequencing to read multi-way chromatin contacts directly, introduced in Nature Biotechnology in 2022." }