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3D Genomics Multi-omics Integration Service

3D Genomics Multi-omics Integration Service integrates chromatin contact maps with RNA-seq, ATAC-seq, and histone ChIP-seq (optionally methylation) to build reviewable enhancer–promoter and variant-to-gene evidence. Deliverables include QC summaries, normalized matrices, browser tracks, and figure-ready visualizations that support downstream experimental validation. Research Use Only (RUO).

  • Evidence integration: Connect structure, activity, and gene output.
  • QC-first reporting: Metric types and audit trail sections.
  • Analysis-ready outputs: Matrices, tracks, and annotations.
  • Figure-ready views: IGV-style composite locus panels.
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Diagram of 3D genomics multi-omics integration service linking contact maps with RNA/ATAC/ChIP evidence.

What this service is and when it's the right fit

What "multi-omics integration" means in 3D genomics

In 3D genomics, multi-omics integration is a structured way to connect:

  1. 3D genome features (contact maps, loops, TADs, A/B compartments)
  2. Regulatory activity (ATAC-seq peaks; histone ChIP-seq such as H3K27ac/H3K4me1; optional methylation)
  3. Gene output (RNA-seq expression)

The goal is a reviewable evidence chain for enhancer–promoter linking and variant-to-gene (V2G) prioritization, especially when "nearest gene" assumptions are not reliable (RUO).

When teams choose this service

This service is a strong fit when your team needs to prioritize enhancer–promoter links, connect noncoding variants to plausible targets using 3D contact context, and convert existing datasets into an audit-friendly package for cross-team review (RUO).

What you get (audit-ready outputs, not just raw reads)

Deliverables are organized to be usable by both computational and experimental teams and to support figure-ready genome browser visualization (RUO).

  • Processed, normalized contact matrices (resolution appropriate to the data)
  • Interaction/loop outputs where applicable, plus evidence summaries
  • TAD and A/B compartment outputs as track-ready annotations
  • Browser-ready tracks aligned across assays (coordinate-consistent)
  • Candidate enhancer–promoter / variant–gene link tables with evidence fields

RUO boundary & interpretation scope

This service is provided for Research Use Only (RUO). We do not provide clinical interpretations, diagnostic conclusions, or treatment recommendations. Outputs are presented as research evidence and hypotheses to support downstream experimental validation.

Why integrate 3D genomics with multi-omics?

  • Reduce ambiguity: go beyond nearest-gene assignment.
  • Align evidence: structure + activity + expression.
  • Review-ready: locus panels for stakeholder inspection.
  • Audit-friendly: QC sections and reusable outputs.

Integration layers and evidence types

Multi-omics integration is framed as a reviewable evidence model rather than a single opaque score. Depending on your use case, evidence can include structural context, regulatory state, and gene output aligned to the same coordinate system (RUO).

Layer What it contributes Examples of outputs
3D contacts Contact neighborhoods and candidate regulatory routes Contact maps, loop candidates, locus heatmaps/arcs
Chromatin activity Evidence of regulatory element activity in context ATAC-seq peaks, H3K27ac/H3K4me1 tracks
Gene output Functional alignment to target gene expression RNA-seq expression tracks and gene-level summaries
Integrated interpretation Reviewable evidence chain for enhancer–promoter and V2G Candidate link tables, IGV-style composite track views

When additional data types are relevant, integration can incorporate promoter-anchored interaction assays such as HiChIP or PLAC-seq, or long-read multi-contact approaches such as Pore-C (RUO).

Use cases mapped to decisions

Use cases below are expressed as decision points and the evidence packages required to support them (RUO).

1. GWAS-to-Gene (V2G) and enhancer–promoter linking

Prioritize candidate variant–enhancer–gene links using contact context from Hi-C sequencing and/or Micro-C, aligned with ATAC/ChIP activity and RNA-seq output (RUO).

2. Locus interpretation beyond proximity

Resolve ambiguous "nearest gene" assignments by aligning local contact heatmaps/arcs with regulatory activity and expression evidence to create review-ready locus panels (RUO).

3. Perturbation planning (CRISPRi/a)

Select candidate regulatory elements and define readouts using multi-layer evidence (3D contact context + ATAC/ChIP activity + RNA-seq output alignment) (RUO).

4. Structural variation context (when relevant)

Interpret how rearrangements may alter contact neighborhoods and regulatory logic by integrating 3D context with functional layers at the affected loci (RUO).

5. RNA–chromatin adjacency extensions (optional)

Extend integration to RNA–chromatin adjacency assays such as RADICL-seq, ChAR-seq, or iMARGI when required by the biological question (RUO).

6. R-loop or hybrid context (optional)

If the hypothesis involves R-loops, integration can incorporate signals from R-loop sequencing, DRIP-seq, or RDIP-seq alongside 3D contacts (RUO).

For long-read multi-contact contexts, integration can incorporate outputs from Pore-C or HiPore-C when appropriate (RUO).

End-to-end integration workflow (RUO)

The workflow is designed to generate coordinate-consistent outputs and an audit-friendly QC narrative that supports review and reuse (RUO).

  1. Data inventory & design lock: confirm genome build, groups, replicates, and available assays.
  2. 3D processing: generate contact maps and context annotations (TADs/compartments; loops where applicable).
  3. Multi-omics alignment: align ATAC/ChIP and RNA-seq layers to consistent coordinates.
  4. Evidence linking: assemble reviewable evidence packages for enhancer–promoter and V2G candidates.
  5. QC reporting: provide metric-type sections such as valid-pair summaries, cis/trans reporting, and P(s) curve reporting.
  6. Deliverables: export matrices, tracks, locus panels, and candidate link tables for downstream use (RUO).

Report mock showing QC sections and deliverable file types for a 3D genome plus multi-omics integration workflow.

Sample Requirements

Input requirements vary by organism, tissue complexity, and the selected assay layers. The table below provides a concise starting point (RUO).

Sample type Minimum input Recommended input Shipping
Cells / nuclei ≥ 2×105 5×105–1×106 Ice (fresh) / Dry ice (frozen)
Fresh tissue ≥ 20 mg 50–100 mg On ice
Frozen tissue ≥ 20 mg 50–100 mg Dry ice

Note: Final feasibility depends on project goals, genome build, and assay selection (RUO).

Case study: integrative 3D + multi-omics visualization

Note: This case study references peer-reviewed literature and illustrates a deliverable-style visualization pattern (RUO).

A Nature Communications (2024) study integrated genomic, epigenomic, 3D genomic, and transcriptomic data to prioritize functional variant–gene links in chickens.

Source: https://doi.org/10.1038/s41467-024-53692-6
PDF: https://www.nature.com/articles/s41467-024-53692-6.pdf

The integration logic combines 3D chromatin contacts (Hi-C) with epigenomic activity (ATAC-seq and histone marks such as H3K27ac/H3K4me1) and transcriptomic evidence (RNA-seq) to build a locus-level evidence stack for variant–gene prioritization (RUO).

A key deliverable pattern is an IGV-style composite view that aligns activity (ATAC/ChIP), contact context (3D arcs or local heatmap), and gene output alignment (RNA-seq) in one reviewable panel.

Service-page demo note: The image below is a CD Genomics-created demo composite that follows this evidence structure and is not reproduced from the paper.

Integrated multi-omics track view showing a candidate regulatory variant within an active enhancer, supported by ATAC/ChIP signals and linked to target genes through 3D chromatin interactions.An integrative genome browser view combining 3D chromatin contacts (Hi-C) with epigenomic activity (ATAC-seq, histone ChIP-seq) and transcriptomic evidence to prioritize functional variant–gene links.

This style of locus panel supports internal review and downstream validation planning by making the evidence chain explicit. Licensing for the referenced PDF includes Creative Commons Attribution-NonCommercial-NoDerivatives language; reproducing published figures on commercial pages may require separate permission (RUO).

License source: https://www.nature.com/articles/s41467-024-53692-6.pdf

Demo Results & Deliverables

Deliverables are structured as reusable outputs for analysis, review, and figure generation (RUO).

Raw Data & QC
QC report sections describing metric types, including mapping/valid-pair summaries, cis/trans reporting, and P(s) curve reporting (RUO).

Composite Locus View
IGV-style composite panels combining ATAC/ChIP tracks with local 3D contact context and RNA-seq evidence to support reviewable enhancer–gene linking (RUO).

Candidate Link Outputs
Candidate enhancer–promoter and variant-to-gene link tables with evidence fields and locus annotations to guide validation planning (RUO).

Genome-wide Summary
Summary panels for compartments, domains, and interaction context, aligned to project design and documented for reuse (RUO).

To discuss integration scope, please contact us.

Decision-blocking FAQs

References

  1. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing and analysis
    https://link.springer.com/article/10.1186/s13059-015-0831-x
  2. Galaxy HiCExplorer 3: a web server for reproducible Hi-C, capture Hi-C and single-cell Hi-C data analysis
    https://academic.oup.com/nar/article/48/W1/W177/5821269
  3. MAPS: Model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments
    https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006982
  4. Integrative 3D genomics with multi-omics analysis and functional validation of genetic regulatory mechanisms of abdominal fat deposition in chickens
    https://doi.org/10.1038/s41467-024-53692-6
    https://www.nature.com/articles/s41467-024-53692-6.pdf

For Research Use Only. Not for use in diagnostic procedures. CD Genomics does not provide clinical diagnosis or treatment recommendations.

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