Sample Submission Guidelines
Introduction
Traditional Hi-C sequencing has been the cornerstone for studying 3D genome architecture, but its limitation to pairwise interactions leaves many higher-order chromatin structures unresolved. As genome projects advance to telomere-to-telomere (T2T) assemblies, polyploid organisms, and complex plant and animal genomes, researchers face a growing challenge: How can we accurately anchor contigs, resolve centromeres, and capture true chromatin complexity?
Pore-C sequencing, a long-read Nanopore-based chromatin conformation capture method, provides the solution. By directly sequencing ultra-long concatemers, Pore-C nanopore technology simultaneously reveals multi-way chromatin interactions and DNA methylation, offering insights beyond the reach of Hi-C. For researchers in biochemistry labs, CRO collaborations, and academic institutions, Pore-C opens a new dimension in genome assembly and epigenetic discovery.
Technology Overview: What is Pore-C Sequencing?
Pore-C sequencing is an advanced Nanopore-based chromatin conformation capture technology that overcomes the limitations of Hi-C. By combining chromatin crosslinking and ligation with Oxford Nanopore long-read sequencing, Pore-C enables direct detection of multi-way chromatin interactions along single DNA molecules.
How It Works
- Crosslinking & Digestion: Chromatin interactions are preserved through formaldehyde fixation and restriction enzyme cutting.
- Ligation: DNA fragments in close spatial proximity are ligated into concatemers, retaining their 3D contact information.
- Nanopore Sequencing: Ultra-long concatemers are sequenced directly, capturing multiple interacting loci within a single read.
- Integrated Data: In addition to 3D chromatin interactions, Pore-C sequencing preserves native DNA methylation signals, providing both structural and epigenetic insights in one workflow.
Why It Matters
- Unlike Hi-C, which is restricted to pairwise interactions, Pore-C nanopore sequencing delivers higher-order contact maps that reflect the true complexity of chromatin folding.
- Multi-way interaction data improve the accuracy of telomere-to-telomere genome assembly, centromere resolution, and polyploid scaffolding.
- Built-in methylation detection adds a new dimension for epigenetic research.
Pore-C vs Hi-C: A New Dimension in Genome Analysis
| Feature | Hi-C | Pore-C |
|---|---|---|
| Interaction Type | Pairwise only (two loci at a time) | Multi-way interactions (3+ loci in a single read) |
| Read Length | Short-read Illumina | Ultra-long Nanopore concatemers |
| Epigenetic Information | Not captured | Direct DNA methylation detection |
| Genome Anchoring Depth | Requires ~100× coverage | Comparable results with ~30× coverage |
| Complex Regions | Limited centromere resolution | Strong signals in centromeres and repeats |
| Polyploid Assembly | Higher risk of mis-joins between homologs | Reduced false joins, higher scaffolding accuracy |
| Data Output | Contact heatmaps | Contact heatmaps + multi-way networks + methylation tracks |
Why Pore-C Outperforms Hi-C
- Stronger interaction signals across entire genomes, including centromeres.
- More complete genome assemblies in both diploid and polyploid species.
- Dual insights: 3D chromatin structure and epigenetic modifications.
- Efficient sequencing depth: 30× Pore-C can match 100× Hi-C anchoring power.
Service Workflow
Applications of Pore-C Sequencing
Pore-C sequencing provides a powerful solution for research teams seeking to go beyond the limitations of Hi-C. With the ability to capture multi-way chromatin interactions and detect DNA methylation simultaneously, pore-c nanopore analysis supports a broad spectrum of applications across life sciences and agriculture.
Genome Assembly and Scaffolding
- Strengthens contig anchoring in telomere-to-telomere (T2T) genome projects.
- Improves resolution of centromeres, repetitive regions, and structural variants.
- Delivers superior scaffolding accuracy for complex or large genomes.
Polyploid Genome Research
- Reduces misassemblies by minimizing homologous chromosome cross-signals.
- Provides clearer separation of subgenomes in polyploid plants and animals.
- Supports accurate haplotype phasing and evolutionary studies.
3D Genome Architecture
- Enables mapping of higher-order chromatin structures beyond pairwise contacts.
- Reveals multi-way interaction networks that govern gene regulation.
- Advances fundamental understanding of nuclear organization.
Epigenetics and Chromatin Biology
- Detects DNA methylation patterns along with structural interactions.
- Offers an integrated view of epigenetic regulation in 3D space.
- Facilitates research into gene expression control, imprinting, and silencing.
Plant and Animal Breeding
- Accelerates pan-genome construction and diversity studies.
- Supports identification of structural features linked to agronomic and disease-resistance traits.
- Provides high-value insights for genetic improvement programs.
Recommended Pore-C Strategies for Different Genome Levels
To maximize the benefits of Pore-C sequencing in genome assembly, different strategies are recommended depending on the target genome level. These combinations ensure optimal balance between read accuracy, long-range interactions, and sequencing depth.
| Genome Level | Recommended Strategy |
|---|---|
| Chromosome-level Genome | 30× HiFi + 30× Pore-C + 50× NGS |
| T2T Genome | 30× HiFi + 30× ONT ultra-long + 30× Pore-C + 50× NGS |
| Perfect T2T Genome | 40–60× HiFi + 60–100× ONT ultra-long + 30× Pore-C + 50× NGS |
| Haploid Perfect T2T Genome | 80–120× HiFi + 120–200× ONT ultra-long + 60× Pore-C + 50× NGS |
Data Analysis & Bioinformatics
The true value of Pore-C sequencing lies not only in generating long-read concatemer data but also in extracting accurate and efficient interaction signals. At CD Genomics, we employ optimized pore-c analysis pipelines to ensure high-quality results for genome assembly and 3D genome research.
Optimized Analysis Strategy
Traditional Hi-C pipelines rely on a cut-first, align-later method, which often underestimates the unique power of Pore-C. Instead, we use an align-first, cut-later approach tailored for Nanopore data:
- Full-read alignment to the reference genome preserves long-range context.
- Post-alignment fragment parsing avoids over-splitting and reduces multi-mapping errors.
- Accurate valid pairs extraction increases usable data rates and interaction resolution.
This strategy significantly improves the valid data rate compared with conventional methods, ensuring that each Pore-C read contributes more effectively to downstream analysis.
New QC Metrics for Pore-C
Beyond standard contact map generation, our bioinformatics workflow evaluates Pore-C datasets with specialized metrics, including:
- Mean Fragment Count – average number of loci captured per read.
- Contacts/Reads Ratio – efficiency of interaction capture per read.
- Valid Size/Total Size – proportion of data effectively used.
- Mean Valid Pairs Length – distance spanned by valid interactions.
These metrics provide deeper insights into both data quality and biological signal strength, ensuring reliable interpretation.
Deliverables
Clients receive a complete data package that can be directly integrated into genome and epigenetic studies:
- Raw Nanopore sequencing data (FASTQ/FAST5)
- Processed interaction pairs (multi-way contacts)
- Chromatin contact maps and 3D interaction networks
- DNA methylation profiles alongside structural data
- Comprehensive bioinformatics report with QC statistics and visualizations
Sample Requirements for Pore-C Sequencing
To ensure high-quality results, please follow the guidelines below when preparing and shipping your samples. All samples must be snap-frozen in liquid nitrogen, stored at −80 °C, and shipped on dry ice to avoid degradation.
| Sample Type | Input Requirements | Preparation Notes | Shipping Conditions |
|---|---|---|---|
| Human Blood (Leukocytes / PBMCs) | ≥ 1×10⁷ fixed cells per sample | Follow leukocyte isolation and 1% formaldehyde crosslinking protocol; aliquot into cryovials | Snap-freeze in liquid nitrogen; store at −80 °C; ship on dry ice |
| Plant Tissue (Young Leaves) | ≥ 3 g young, disease-free tissue | Select fresh, tender leaves; surface sterilize (75% ethanol, sterile water rinse); freeze immediately | Pre-chilled tubes or foil packs; snap-freeze in liquid nitrogen; ship on dry ice |
| Animal Samples (Cells) | ≥ 6×10⁷ fixed cells per sample | Wash in PBS; crosslink using same workflow as blood leukocytes | Store at −80 °C; ship on dry ice |
| Animal Blood (mammals) | ≥ 7 mL whole blood (fixed) | Isolate and fix leukocytes prior to freezing | Store at −80 °C; ship on dry ice |
| Nucleated Blood (fish, reptiles, amphibians, birds) | ≥ 100 µL fixed blood | Adjust input based on cell count; follow fixation protocol | Store at −80 °C; ship on dry ice |
| Animal Tissues (Muscle / Viscera) | ≥ 3 g muscle, ≥ 0.5 g organ tissue | Process quickly on ice; cut into small pieces; freeze immediately | Store at −80 °C; ship on dry ice |
Important Notes:
- Label each tube clearly with sample ID (letters + numbers) and ensure it matches the Sample Information Form.
- Avoid freeze–thaw cycles.
- Do not exceed 5× the recommended input amounts, unless otherwise specified for low-yield samples.
Frequently Asked Questions (FAQ)
Q: What is Pore-C, and how is it different from Hi-C?
Pore-C is a chromatin conformation capture method that uses long-read Nanopore sequencing instead of short reads; it captures multi-way (3 or more loci) chromatin interactions in single reads, preserves DNA methylation, simplifies library prep by eliminating biotin labeling and PCR steps, and resolves complex regions that are challenging for Hi-C.
Q: Can Pore-C detect epigenetic modifications and interactions at the same time?
Yes, because Pore-C uses Nanopore sequencing which is PCR-free and retains native DNA base modifications; thus both chromatin interaction networks and methylation signatures (for example 5mC) can be obtained from the same dataset.
Q: What types of samples are suitable for Pore-C sequencing?
Samples including crosslinked cells, tissues from plants or animals, fresh or frozen biological material that can preserve chromatin structure are suitable; Pore-C has been used successfully for human cell lines, plant leaf tissues, animal tissue types, often needing appropriate fixation and purification to retain interaction signals.
Q: What are typical data outputs and file formats from Pore-C analysis?
The Pore-C workflow produces raw long-read FASTQ or BAM/concatemer reads, processed contact pairs, multi-way interaction matrices (cooler/.mcool or HiC style), methylation annotation, and QC metrics such as valid contacts per read, fragment count, inter- versus intra-chromosomal contact ratios.
Q: How much sequencing depth is needed for Pore-C to achieve useful genome assembly or interaction mapping?
Required depth depends on genome size and complexity: for chromosome-level scaffolding moderate coverage combined with Pore-C often suffices; for telomere-to-telomere assemblies or polyploid genomes higher long-read and Pore-C coverage improves results; Pore-C generally achieves scaffolding comparable to much higher depth Hi-C with fewer bases when properly processed.
Q: What bioinformatics workflows are used for Pore-C data analysis?
Typical pipelines use an "align-first, then fragment" approach, mapping full long reads to reference genome, then parsing ligation fragments based on restriction enzyme cut sites, extracting multi-contact information and pairwise contacts, generating contact maps, methylation profiling, QC and visualization; tools such as wf-pore-c are commonly used.
Case Study: Application of HiPore-C to Uncover Allele-Specific 3D Genome Folding
1. Background
Traditional Hi-C captures pairwise chromatin interactions, but it cannot resolve multiway contacts or single-allele topology. This limitation hinders our understanding of higher-order 3D genome structures and their cell-type-specific variation. Pore-C, and its optimized high-throughput version (HiPore-C), allow direct sequencing of concatemers containing multiple ligated DNA fragments, thereby enabling the discovery of multi-fragment interactions and epigenetic information within single long reads.
2. Methods
The authors applied HiPore-C to human GM12878 (B lymphocyte) and K562 (erythroleukemia) cells. Improvements in library preparation (proteinase K + pronase digestion) overcame nanopore pore-clogging and increased sequencing yield. They then integrated Nanopore sequencing with the MapPore-C pipeline, which maps multi-fragment reads to the reference genome and extracts both multiway interactions and DNA methylation patterns.
- Key Technique: HiPore-C with ONT PromethION sequencing.
- Data Analysis: Comparison against Hi-C, clustering of single-allele topologies, and simultaneous methylation profiling.
3. Results
- HiPore-C successfully captured canonical 3D genome structures such as A/B compartments, TADs, and loops, with high concordance to Hi-C (r = 0.958 for eigenvectors; r = 0.868 for insulation scores).
- Higher-Order Interactions: ~38% of reads contained interchromosomal fragments, uncovering active and inactive chromatin hubs (see Figure 3 on page 5).
- Single-Allele Resolution: Reads clustered into cell-type-specific topologies, even in conserved TADs (Figure 5 on page 10).
- Functional Relevance: At the β-globin locus, HiPore-C revealed that enhancer hubs form only in K562 cells, where embryonic and fetal globin genes are expressed. In GM12878, the same locus remained silent (Figure 6 on page 12).
- Epigenetics: HiPore-C accurately captured CpG methylation, consistent with WGBS (r = 0.80), and linked it with chromatin structures (Figure 7 on page 14).
HiPore-C identifies a cell-type-specific enhancer hub at the β-globin locus, revealing simultaneous interactions among enhancers and fetal globin genes in K562 cells, but not in GM12878 cells.
4. Conclusions
HiPore-C provides an end-to-end solution for exploring genome folding at single-allele resolution, while simultaneously profiling DNA methylation. It revealed diverse topology clusters within TADs, cell-type-specific enhancer-promoter hubs, and epigenetic regulation embedded in 3D genome architecture. This demonstrates its potential for functional genomics, disease research, and polyploid genome assembly.
References:
- Sean P. McGinty, Gulhan Kaya, View , Sheina B. Sim et al. CiFi: Accurate long-read chromatin conformation capture with low-input requirements.
- Zhang, Z., Yang, T., Liu, Y. et al. Haplotype-resolved genome assembly and resequencing provide insights into the origin and breeding of modern rose. Nat. Plants 10, 1659–1671 (2024).
- Tianyu Yang, Yifan Cai, Tianping Huang et al., A telomere-to-telomere gap-free reference genome assembly of avocado provides useful resources for identifying genes related to fatty acid biosynthesis and disease resistance, Horticulture Research, Volume 11, Issue 7, July 2024, uhae119,
- Jeon, D., Sung, YJ. & Kim, C. High-quality Chromosomal-Level Genome Assembly of the Wasabi (Eutrema japonicum) 'Magic'. Sci Data 11, 1044 (2024).
- Jonghwan Choi, Taemin Kang, Sun-Jae Park, Seunggwan Shin, A Chromosome-Scale and Annotated Reference Genome Assembly of Plecia longiforceps Duda, 1934 (Diptera: Bibionidae), Genome Biology and Evolution, Volume 16, Issue 10, October 2024, evae205,
- Zhong, JY., Niu, L., Lin, ZB. et al. High-throughput Pore-C reveals the single-allele topology and cell type-specificity of 3D genome folding. Nat Commun 14, 1250 (2023).
