End-to-End Spatial Transcriptomics Services
Understanding the cellular landscape of complex tissues requires knowing exactly where genes are expressed. At CD Genomics, we provide premium, end-to-end spatial transcriptomics services for global research. From fresh frozen sections to challenging FFPE blocks, our workflows unlock precise spatial heterogeneity without sacrificing native tissue architecture.
- High-Resolution Mapping: Achieve cellular to subcellular precision across diverse tissue types, overcoming the physical data loss associated with bulk sequencing.
- End-to-End Delivery: Seamlessly transition from rigorous wet-lab sample quality control (QC) to in situ capturing and high-throughput sequencing.
- Deep Bioinformatics: Integrate single-cell data with spatial coordinates using advanced deconvolution algorithms for custom multi-omics insights.
Beyond Standard Assays: Subcellular Precision, FFPE Compatibility & Multi-Omics
The true potential of spatial biology cannot be realized with a one-size-fits-all approach. Standard spatial assays often struggle with poor-quality clinical samples or lack the resolution required for single-cell insights. We elevate your research by moving beyond standard boundaries, focusing on three core operational advantages:
- Subcellular Precision: Standard spatial platforms often capture multiple cells within a single sequencing spot, obscuring the boundaries between distinct cellular phenotypes. Our advanced workflows break through this barrier, offering ultra-high resolution mapping. By enabling single-cell and even single-molecule detection, we allow researchers to pinpoint exact transcript locations within the cytoplasm or nucleus, capturing true cellular heterogeneity without the blur of neighborhood averaging.
- Robust FFPE Compatibility: Formalin-fixed paraffin-embedded (FFPE) tissues represent a massive, invaluable archive of disease pathology, yet they are notoriously difficult to sequence due to severe RNA cross-linking and degradation. We have optimized proprietary extraction and capturing protocols specifically designed to rescue and sequence highly degraded RNA, guided by rigorous DV200 quality control metrics. This unlocks the ability to conduct retrospective spatial studies on historical tissue cohorts.
- Spatial Multi-Omics Integration: Gene expression alone only tells half the story. We bridge the gap between the transcriptome and the proteome. By multiplexing spatial RNA detection with highly multiplexed protein imaging, we provide a unified view of biological function, allowing researchers to observe post-transcriptional regulations and complex structural matrices within the exact same tissue section.
Explore Our Specialized Spatial Omics Solutions
To meet the diverse demands of modern biomarker discovery and developmental biology, we have engineered a versatile portfolio of specialized pipelines. Explore our focused service hubs below to find the exact methodology that aligns with your sample types and resolution requirements:
Core Platform & Resolution Offerings
- 10x Genomics Visium: Discover our foundational spatial gene expression solutions for comprehensive tissue profiling.
- 10µm spatial transcriptomics service: Leverage high-resolution capabilities (such as Visium HD) to achieve single-cell scale mapping across entire tissue sections without targeting gaps.
- subcellular spatial transcriptomics: Push the boundaries of imaging-based spatial biology to resolve transcripts at the true single-molecule, intracellular level.
Complex Sample Processing Pipelines
- FFPE spatial transcriptomics service: Tailored probe-based capture workflows designed exclusively to bypass the challenges of degraded RNA in archived pathology blocks.
- spatial transcriptome sequencing of frozen samples: Optimized cryosectioning and poly-A capture protocols for pristine fresh frozen tissues to guarantee maximum transcript recovery.
Targeted & Multi-Omics Integrations
- integrated spatial transcriptomics and proteomics solution: Simultaneously profile spatially resolved mRNA and proteins to uncover multi-layered biological networks.
- neuro spatial multiomics targeted panel: Dive deep into complex brain architecture with our highly sensitive, targeted panels specifically curated for neurobiology and neurodegeneration research.
Key Applications in Complex Disease Research
The ability to simultaneously visualize histology and high-dimensional transcriptomics opens unprecedented avenues for translational research and therapeutic development.
- Tumor Microenvironment (TME) & Immuno-Oncology: Solid tumors are not homogeneous masses; they are complex ecosystems consisting of malignant cells, stroma, vasculature, and infiltrating immune cells. Spatial transcriptomics allows for the precise mapping of immune exclusion zones, the identification of exhausted T-cell neighborhoods, and the discovery of localized resistance mechanisms that dictate a patient's response to immunotherapy.
- Neuroanatomy & Neurodegenerative Diseases: The mammalian brain possesses the most intricate spatial organization of any organ. Our spatial mapping services allow researchers to chart cortical layers, map the progression of amyloid plaques, and analyze localized neuroinflammation in models of Alzheimer's and Parkinson's diseases.
- Developmental Biology: Tracking the spatial and temporal gradients of gene expression is vital for understanding organogenesis and embryogenesis. Spatial technologies map the precise morphogen gradients that dictate cell fate during development.
- Immunology & Infectious Disease: Visualize the architecture of secondary lymphoid organs, track the spatial distribution of host-pathogen interactions, and understand how localized inflammatory responses propagate through healthy tissues.
Our Comprehensive Spatial Transcriptomics Workflow
We provide a seamless, truly end-to-end laboratory workflow. From the moment your tissue arrives at our facility to the final delivery of publication-ready bioinformatics data, every step is governed by strict Quality Control (QC) checkpoints.
- Sample Preparation & Sectioning: Your samples (Fresh Frozen or FFPE) are sectioned onto specialized spatially barcoded capture slides. We adhere strictly to recommended thickness parameters (typically 5-10µm) to prevent overlapping cell layers while ensuring sufficient RNA yield.
- Staining & High-Resolution Imaging: The tissue sections are stained (e.g., H&E or Immunofluorescence) and imaged using high-resolution microscopy. This creates the foundational morphological map that will later be merged with the sequencing data.
- Tissue Permeabilization & Spatial Barcoding: The tissue is carefully permeabilized, allowing intracellular mRNA to migrate downwards and bind to the millions of spatially barcoded oligonucleotide probes covering the capture area of the slide.
- cDNA Synthesis & NGS Library Construction: The captured RNA acts as a template for in situ cDNA synthesis. The spatial barcodes are permanently incorporated into the cDNA, and the libraries are amplified and optimized for high-throughput Next-Generation Sequencing (NGS).
- Data Processing & Visualization: Post-sequencing, our bioinformatics pipelines demultiplex the data, align the sequences to the reference genome, and map the spatial barcodes directly back to the original tissue image, generating multidimensional expression overlays.
Sample Requirements & Submission Guidelines
Proper sample preparation is the most critical variable in spatial transcriptomics. To minimize risks and ensure optimal library construction, we enforce rigorous sample intake protocols. Our platform is highly versatile and capable of analyzing a wide variety of samples:
Species We Analyze:
Human, mouse, rat, and other common preclinical models.
Tissue Types We Analyze:
Heart, lung, eyes, liver, kidney, spleen, stomach, testis, ovary, breast, lymph node, brain, intestine, thyroid, skin, pancreas, bone tissue, etc.
| Sample Type | Recommended Size / Input | Fixation & Container | Shipping Condition | Primary QC Checkpoint | Notes |
|---|---|---|---|---|---|
| Fresh Frozen Tissue | 6mm × 6mm, ~10μm thickness | OCT Embedded Block | Dry Ice | RNA RIN > 8 | Please provide at least 2 backup aliquots for initial RNA extraction and protocol optimization. |
| FFPE Tissue | Standard pathology blocks | Cassette / Slide | Room Temperature | DV200 Assessment | Requires specialized probe-based workflows. Ensure blocks are properly sealed to prevent oxidation. |
Advanced Bioinformatics: Single-Cell & Spatial Integration
Raw sequencing data holds little value without expert interpretation. Our dedicated bioinformatics team employs advanced analytical frameworks, moving far beyond standard pipeline outputs to deliver customized, actionable insights.
Minimum Core Deliverables
For every spatial transcriptomics project, we provide comprehensive foundational data packages, ensuring you have the baseline needed for visualization:
- Standard pipeline processing (e.g., Space Ranger outputs)
- Accurate spot identification and background noise filtering
- Unsupervised spatial clustering of distinct morphological zones
- Complete gene expression matrices and basic visualization plots
Optional Advanced Add-On Analyses
For researchers requiring deeper biological mechanistic insights, we offer highly specialized computational interventions:
- Custom Deconvolution (e.g., MultiGATE Integration): Since standard 55µm spots may contain multiple cells, we leverage proprietary algorithms and external scRNA-seq reference data to "deconvolve" the spatial spots. This predicts the exact proportion and placement of distinct cell sub-types within a single spot.
- Cell-Cell Communication Networks: We map ligand-receptor interaction networks and project them onto the physical tissue space, revealing how adjacent cell populations actively signal to one another.
- Spatial Trajectory Inference: Analyzing transitional cellular states across physical tissue gradients, highly relevant for studying tumor invasive margins or developmental zones.
Technology Comparison: Choosing the Right Spatial Assay
Navigating the landscape of spatial technologies can be complex. Below is an evaluation framework to help you choose the ideal methodology for your study:
| Technology | Spatial Resolution | Sample Compatibility | Best For... |
|---|---|---|---|
| Visium HD | ~2µm (High-resolution grid) | FFPE / Fresh Frozen | Unbiased whole-transcriptome discovery at a near single-cell scale across large, complex sections. |
| Subcellular Profiling | Single-molecule / <1µm | Fresh / Fixed Tissues | Ultra-precise mapping of pre-selected gene panels, subcellular transcript localization, and precise cell boundary segmentation. |
| Standard Visium | 55µm spots (Center-to-center 100µm) | Fresh Frozen / FFPE | Cost-effective, whole-transcriptome spatial mapping for broad tissue profiling and large anatomical zones. |
| scRNA-seq (Non-Spatial) | True Single Cell | Fresh / Dissociated | High-throughput cellular census and rare cell discovery where physical tissue context is not strictly required. |
Solution Selection Strategy:
- Choose Subcellular Profiling if your project requires identifying exactly where an mRNA transcript resides within a cell (e.g., nucleus vs. soma), or if you demand absolute single-cell segmentation without the need for computational deconvolution.
- Choose Visium HD if you are conducting unbiased, whole-transcriptome discovery on complex FFPE blocks and need high-resolution mapping without limiting yourself to targeted gene panels.
- Opt for our Integrated Spatial Multi-omics solution when your hypothesis relies on correlating both protein abundance and RNA expression to fully define a tissue's functional state.
Typical Deliverables & Multi-omics Demo Results
When you partner with CD Genomics, the final deliverable is designed to be highly intuitive, interactive, and directly applicable to your manuscript or patent filing. Typical visual outputs include:
- Spot Identification & Quality Filtering: Visual overlays demonstrating the accurate identification of tissue-covered spots and the successful computational removal of low-quality background noise or artifactual signals.
- Unsupervised Spatial Clustering: Colorful spatial mapping graphs that categorize discrete tissue regions based on their comprehensive, multidimensional gene expression signatures, often mirroring underlying histological structures.
- Cell Type Deconvolution: High-accuracy prediction maps showing the estimated proportions of various cell types within each spatial spot, visualized through localized pie charts or specialized heatmaps.
- Spatially Variable Gene (SVG) Expression: Targeted heatmaps overlaid directly onto the brightfield H&E morphology, explicitly showing the active expression zones and gradients of your specific biomarkers of interest.
Case Study: Spatial Mapping of the Mouse Brain
Spatial transcriptomics has proven to be a game-changer in mapping highly organized anatomical structures. Below is a summary of how spatial techniques are applied in advanced neurobiology, referencing recent high-impact peer-reviewed literature.
Background: The mammalian brain exhibits profound regional complexity, with distinct functional cell types organized into precise anatomical layers extending from the cortex and hippocampus down to the cerebellum and olfactory bulb. Understanding how these diverse layers develop, function, and age is critical for treating neurological disorders. However, standard tissue dissociation methods destroy this vital topographic information, leading to a loss of architectural context.
Methods: Researchers utilized high-resolution spatial transcriptomics to profile coronal sections of the mouse brain across various stages of development and aging. The physical tissue slices were mapped onto spatial capture arrays, preserving the anatomical context of the captured mRNA. The methodology involved rigorous cryosectioning followed by tissue permeabilization, ensuring that transcripts bound correctly to spatial barcodes without lateral diffusion, which is critical for maintaining spatial fidelity across densely packed neuronal layers.
Results: The spatial analysis successfully identified discrete molecular boundaries corresponding to known anatomical regions. High-resolution clustering effectively demarcated the dentate gyrus from the surrounding hippocampal fields and identified distinct molecular signatures within the cortical layers. Furthermore, by analyzing spatially variable genes across multiple time points, researchers uncovered localized temporal dynamics—revealing specific gene clusters that were activated in restricted brain regions only during specific developmental windows.
Conclusion: This spatial approach provided a comprehensive spatio-temporal atlas of the mouse brain, proving the technology's unmatched utility in resolving regional dynamics that would be completely obscured by traditional bulk or non-spatial single-cell methods. For a visual representation of these findings, refer to the representative spatial mapping figures in Spatial Transcriptomics Reveals Regional and Temporal Dynamics of Gene Expression in the Mouse Brain Across Development and Aging (2025).
