Validate 3D genome hypotheses with confocal z-stack imaging and per-cell 3D distance quantification—not projected 2D proximity. IA Analysis delivers publication-ready 3D reconstructions, distance distributions, and spatial context for mechanism-focused research.
3D-FISH is an in situ hybridization approach performed under conditions that maintain three-dimensional nuclear structure, followed by z-stack imaging and 3D reconstruction. Unlike 2D imaging that can compress nuclear geometry, 3D-FISH quantifies where targets reside in intact nuclei and how spatial relationships change across conditions.
Use 3D-FISH when you need to:
Successful 3D-FISH projects begin with a clear question and a metric that answers it. We commonly support studies such as:
3D structure-aware execution
We scope fixation, permeabilization, hybridization, and imaging around nuclear architecture, reducing artifacts that distort 3D distance metrics.
Quantification-first reporting
You receive distributions and statistics (distance and positioning), not only curated images—so conclusions are supported by data structure.
Probe strategy tailored to the decision
BAC and oligo-based approaches are selected to match resolution, multiplexing needs, and feasibility for your genomic targets.
Reproducible, documented analysis rules
We standardize segmentation, spot calling, thresholds, and QC flags so results remain comparable across batches and conditions.
Built for multi-omics validation
Reporting is structured to complement Hi-C/Capture-C and other chromatin datasets, enabling coherent "discovery → validation → mechanism" workflows.
Best for: enhancer–promoter validation • locus repositioning • SV-driven spatial shifts
Outputs: 3D locus coordinates • per-cell distance distributions • optional radial positioning
Options: single/dual/multi-locus • BAC or oligo probes • multiplex channel planning
Best for: transcript localization in 3D • nuclear retention • RNA foci & heterogeneity
Outputs: 3D localization maps • project-defined quant metrics • optional DNA–RNA co-detection
Options: pattern-level profiling or spot-based readouts • multiplex (project-dependent)
Best for: linking loci/RNAs to chromatin state or nuclear architecture
Outputs: co-localization frequency • distance-to-marker metrics • figure-ready overlays
Options: marker selection & channel planning • controls for background and specificity
Probe type selection (BAC vs oligo) • target feasibility check • multiplex/channel plan • ordering coordination or client-supplied probes
Client z-stacks → standardized 3D segmentation & spot calling • distance/positioning stats • group comparisons & plots
| What clients want to know | 3D-FISH (Confocal z-stack) | 2D-FISH (Single-plane / projection) | Hi-C / Capture-C (Sequencing-based) |
| Primary output | Single-cell 3D spot coordinates and 3D distance distributions | 2D spot positions in flattened nuclei; 2D distances | Genome-wide or targeted contact frequency (population average) |
| Best for answering | "Are loci physically closer in cells?" "Does positioning shift?" "How heterogeneous is the effect?" | "Where is the locus roughly?" "Is there a large localization difference?" | "Which regions contact each other?" "Which candidates should we validate?" |
| What you can quantify | 3D distances, radial positioning, co-localization (rule-based) | Approximate proximity; limited 3D claims | Contact matrices, loops/peaks, interaction scores |
| Single-cell vs population | Single-cell (cell-to-cell heterogeneity visible) | Single-cell but geometry compressed | Mostly population average (cell states mixed) |
| Spatial realism | Preserves nuclear architecture (3D) | Higher risk of geometric distortion from flattening | Not an image; spatial distance inferred indirectly |
| Throughput | Medium (dozens–hundreds of cells per condition; project-dependent) | Higher than 3D-FISH | High (genome-scale discovery; many loci) |
| Resolution drivers | Probe design + optics + z-step; practical distance precision is project-dependent | Optics + imaging plane; limited z information | Sequencing depth + restriction/enrichment design |
| Typical turnaround drivers | Probe availability, sample prep, imaging & quant analysis | Probe availability, imaging | Library prep, sequencing, bioinformatics |
| Common failure points (what we mitigate) | Fixation/3D preservation, background, spot calling thresholds, Z-axis chromatic aberration | Flattening artifacts, ambiguous overlaps in projection | Complex interpretation; false positives from averaging; batch effects |
| Where it fits in a workflow | Validation & mechanism visualization for selected candidates | Quick screen or localization check | Discovery & prioritization (then validate by FISH) |
| When to choose it | You need decision-ready, image-based 3D evidence | Budget/time constrained; effect expected to be large | You need to find candidates genome-wide or across many loci |
Use Hi-C/Capture-C to discover and prioritize candidates, then use 3D-FISH to validate physical proximity and quantify cell-level distance shifts; choose 2D-FISH for rapid screening when large effects are expected.
Project scoping & feasibility
Define targets, sample type, groups, resolution goals, and success metrics.
Probe strategy & panel design
Choose probe type (BAC vs oligo), channel planning, multiplex feasibility, and controls.
Sample QC & pre-treatment plan
Confirm fixation approach, nuclear integrity considerations, and pilot checks if needed.
3D-FISH execution
Hybridization and post-wash conditions optimized for signal-to-background and structural preservation.
3D imaging (z-stack acquisition)
Confocal z-stacks acquired with consistent settings aligned to quantification requirements.
3D reconstruction & quantification
Nuclear segmentation, spot calling, artifact screening, and metric computation.
Reporting & delivery
Quantitative outputs, figures, and QC/method summaries delivered in a project-ready package.
Our platform is built around confocal z-stack imaging, enabling volumetric capture of FISH signals within intact nuclei. Imaging settings are controlled to support 3D spatial fidelity rather than presentation-focused visualization.
Probe strategies are selected to balance target specificity, spatial resolution, and multiplex compatibility, with BAC- and oligo-based designs applied as appropriate. Fluorophore and channel planning prioritize signal separability under 3D acquisition conditions.
Image stacks are processed using structure-aware reconstruction workflows that preserve nuclear geometry. Spatial metrics are derived under consistent analytical rules, enabling reproducible interpretation across samples and study groups.
STELLARIS Confocal Microscope Platform (Fig from Leica Microsystems)
3D reconstruction and distance-based quantification of FISH signals across intact nuclei.
| What clients care about | BAC Probes | Oligo / Oligopaint-Style Probes |
| Best use cases | Single- or dual-locus validation • robust positioning studies | Multi-locus panels • refined targeting • scalable multiplex projects |
| Target region size | Large genomic inserts (kb–Mb scale) | Custom-defined regions (flexible length and density) |
| Design flexibility | Limited customization once BAC is selected | High—probe density, spacing, and composition are adjustable |
| Multiplex potential | Low to moderate | High, suitable for multi-color and panel expansion |
| Spatial resolution | Adequate for locus-level positioning | Higher effective resolution for closely spaced targets |
| Background risk | Generally low, but repeat content may vary | Design-dependent; repeat masking is critical |
| Turnaround drivers | BAC availability and validation | Design complexity, synthesis, and QC |
| Typical project complexity | Lower (straightforward validation) | Higher (design, optimization, multiplex planning) |
| When to choose | You need a robust, fast path to confirm locus positioning | You need flexibility, scalability, or fine spatial discrimination |
Choose BAC probes for robust, low-complexity locus validation, and oligo/Oligopaint-style probes when multiplexing, refined targeting, or panel scalability is required.
Below are common sample formats for research 3D-FISH workflows. Final requirements depend on target type, sample matrix, and whether immunostaining is included.
| Sample Type | Recommended Format | Handling Notes |
| Cultured cells | Fixed cells on coverslips or fixed suspension | Avoid freeze–thaw; fixation consistency is critical |
| Isolated nuclei | Pre-fixed nuclei aliquots | Provide buffer composition and processing details |
| Frozen tissue sections | Cryosections (thickness per design) | Ship on dry ice; minimize moisture exposure |
| FFPE sections (optional) | FFPE slides (project-dependent) | Feasibility check recommended due to background and accessibility |
Information to include with samples
Validation of candidate loci from chromatin-contact studies
Used to confirm selected loci from Hi-C or Capture-C experiments with image-based spatial evidence.
Chromatin reorganization during cell-state transitions
Applied in differentiation, activation, or stress models to document state-dependent nuclear organization.
Perturbation studies of nuclear architecture regulators
Used as a spatial phenotype readout in RNAi or CRISPR perturbation experiments.
Spatial consequences of genome editing or structural variants
Supports projects assessing whether engineered genomic changes lead to nuclear repositioning.
Nuclear compartment association studies (Immuno-3D-FISH)
Used to map DNA or RNA targets relative to marker-defined nuclear compartments.
3D transcript localization projects
Applied when transcript localization or nuclear retention is a primary research phenotype.
3D-FISH Confocal Z-Stack Reconstruction
Three-dimensional reconstruction of FISH signals from confocal z-stacks, preserving nuclear architecture for quantitative spatial analysis.
3D Distance Measurement Between FISH Signals
Schematic visualization of 3D Euclidean distance measurement between FISH signals within an intact nucleus.
Per-Cell Distribution of 3D FISH Distances
Single-cell distributions of 3D distances between FISH signals across experimental conditions, highlighting cell-to-cell heterogeneity.
Immuno-3D-FISH Overlay for Spatial Context
Immuno-3D-FISH overlay combining DNA-FISH signals, protein marker staining, and nuclear architecture to resolve spatial relationships in three dimensions.
How does 3D-FISH preserve nuclear structure compared to 2D-FISH?
3D-FISH uses fixation and permeabilization strategies designed to prevent nuclear flattening. By combining controlled fixation with confocal z-stack acquisition, the nucleus is captured as a volumetric structure, allowing distance measurements that reflect true 3D genome organization rather than projected 2D geometry.
What is the typical spatial resolution of 3D-FISH measurements?
Optical resolution is diffraction-limited (~200 nm laterally and ~500 nm axially). However, 3D-FISH analysis relies on sub-pixel centroid localization of FISH signals, enabling distance measurements with effective precision in the tens of nanometers for high-quality signals.
Can 3D-FISH validate chromatin interactions identified by Hi-C?
Yes. Hi-C reports contact frequency across a population, whereas 3D-FISH directly measures physical distances between loci in individual cells. This makes 3D-FISH a widely used orthogonal method to validate Hi-C findings and assess cell-to-cell structural heterogeneity.
What are the antibody requirements for Immuno-3D-FISH?
Antibodies must remain reactive after DNA denaturation steps used in FISH. When this is not feasible, a sequential labeling strategy is applied, allowing protein markers to be imaged or stabilized prior to DNA denaturation while preserving nuclear structure.
How many cells are typically analyzed in a 3D-FISH study?
For robust distance distribution analysis, 3D-FISH studies typically analyze 50–150 nuclei per biological condition, providing sufficient statistical power to detect spatial shifts and quantify cell-to-cell variability.
Is 3D-FISH compatible with tissue sections?
Yes. 3D-FISH can be performed on cultured cells as well as frozen or vibratome-cut tissue sections. Thicker sections are preferred to ensure complete nuclei are captured within the z-stack.
What is the difference between BAC and Oligopaint probes in 3D-FISH?
BAC probes (≈150–200 kb) provide strong signals for single-locus positioning. Oligopaint probes offer higher design flexibility and resolution, making them suitable for multi-locus panels or defined chromosomal domains.
Does z-step size affect 3D distance accuracy?
Yes. Z-step size is critical for accurate axial distance measurements. It is typically optimized according to the Nyquist criterion (around 0.2–0.3 µm) to ensure reliable 3D reconstruction and avoid distance artifacts.
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