High-Sensitivity 10 μm Spatial Transcriptome Sequencing Based on Microbead Array Chip
Our high resolution spatial transcriptomics sequencing service uses a 10 μm microbead array chip on frozen tissue sections.
You obtain dense spatial gene expression maps that link cell types, microenvironments, and pathology in a single dataset.
Why work with us
- 10 μm microbead array chip – resolves neighbouring cell types that standard spot sizes merge.
- End-to-end spatial transcriptomics service – send frozen tissue, receive ready-to-interpret spatial datasets.
- High-sensitivity chemistry – detects more transcripts per spot, supporting deeper biomarker discovery.
What Is High-Resolution (10 μm) Spatial Transcriptomics
High-resolution spatial transcriptomics measures gene expression while preserving tissue structure and coordinates.
Instead of dissociating cells, the tissue section remains intact on the slide.
You obtain whole-transcriptome spatial gene expression maps across thousands of spots in a single experiment.
In this context, "10 μm" refers to the physical size of each measurement spot.
At roughly 10 micrometres, each spot samples a very small area, close to the dimensions of an individual cell.
This high resolution reduces signal mixing from neighbouring cells and microenvironments.
Different researchers may describe the same concept as 10 um spatial transcriptomics, 10 µm spatial transcriptomics, or 10 micron spatial transcriptomics.
All three terms refer to the same idea: genome-wide spatial profiles at near cell-level spatial scale.
Key points for your projects
- Preserved spatial context
Gene expression is linked to exact locations in intact tissue, rather than isolated cells in suspension.
- Near cell-level spatial scale
10 μm spots help you distinguish adjacent cell populations and microenvironments that bulk methods merge.
- Whole-transcriptome, not panel-based
Genome-wide profiles let you test known markers and also discover new genes and pathways in one dataset.
Technology Overview: Chip-Based 10 μm Microbead Array Spatial Transcriptomics
Our platform uses a spatial transcriptomics microbead array chip to measure gene expression directly on the slide at 10 μm resolution. Frozen tissue sections are captured on a 10 μm barcoded bead array, enabling whole-transcriptome spatial maps that can be aligned with histology or immunofluorescence images.
How the 10 μm microbead array works
- A frozen tissue section is placed on the spatial transcriptomics microbead array chip and gently permeabilised.
- Polyadenylated mRNA diffuses a short distance and binds to oligo(dT) probes on nearby barcoded beads.
- On-chip reverse transcription and library preparation generate sequencing reads that carry both gene identity and bead barcodes.
- Reads are mapped back to the genome and to x–y positions on the slide, producing frozen tissue spatial gene expression mapping at 10 μm resolution.
Key technical features
- 10 μm spatially barcoded microbead array
High-density 10 μm capture spots sample many more positions than coarser arrays, revealing fine anatomical domains instead of mixed signals.
- In situ mRNA capture and on-chip cDNA synthesis
Controlled permeabilisation and on-chip reverse transcription keep transcripts tied to their original chip coordinates, supporting stable and quantitative spatial patterns.
- Frozen tissue spatial gene expression mapping
The workflow is tuned for frozen and OCT-embedded tissue, generating whole-transcriptome spatial maps that register directly to tissue morphology.
High-Resolution Spatial Transcriptomics vs Other Platforms
Different spatial transcriptomics platforms balance resolution, implementation effort, and throughput in different ways.
The table below summarises how our 10 μm chip-based spatial transcriptomics compares with commonly used alternatives.
| Aspect | 10 μm chip-based spatial transcriptomics (this service) | Visium-style arrays | Slide-seq | DBiT-seq |
|---|---|---|---|---|
| Typical spatial scale | ~10 μm spots (near cell-level scale) | ~55 μm spots | Bead-sized features (high density) | Fine grid defined by microfluidic channels |
| Resolution category | High resolution spatial transcriptomics | Moderate resolution | High resolution | High resolution |
| Sample type focus | Frozen / OCT tissue, targeted cohorts | Broad tissue types, larger cohorts | Often method development / in-house | Often method development / in-house |
| Implementation | Provided as a service on a microbead array spatial transcriptomics platform | Commercial kit plus in-house lab | Custom bead arrays and protocols | Microfluidic setup and barcoding hardware |
| Infrastructure required | No special equipment at client site; outsourced spatial transcriptomics sequencing | Standard NGS lab and instruments | Specialised preparation and strong in-house expertise | Microfluidics, imaging, and advanced workflows |
| Throughput | Moderate sample numbers with deep characterisation | High sample throughput at moderate resolution | Typically lower throughput, method dependent | Typically lower throughput, method dependent |
| Ideal use cases | Projects where fine boundaries, niches, or layers are central; cost-effective high resolution spatial transcriptomics | Large surveys, screening across many samples or conditions | Groups wanting in-house control of high resolution spatial methods | Groups with strong engineering capacity and custom protocol needs |
| Delivery model | End-to-end spatial transcriptomics service with analysis and reporting | Mainly reagents and protocols; analysis often in-house | Research protocol and infrastructure-driven | Research protocol and infrastructure-driven |
How to choose a spatial transcriptomics platform
- For broad screening across many samples, Visium-style platforms remain attractive.
- For detailed, high resolution spatial transcriptomics vs Visium comparisons, 10 μm approaches help resolve small structures and boundaries.
- Spatial transcriptomics vs Slide-seq vs DBiT-seq is often a choice between service-based convenience and building complex in-house methods.
- Our 10 μm service is positioned for teams that want high resolution spatial data without investing in custom platform development.
Advantages of Our High-Sensitivity 10 μm Spatial Transcriptomics Service
Our high-sensitivity spatial transcriptomics platform is built for frozen tissue studies that need clear, interpretable data without building an in-house spatial lab.
High-sensitivity spatial transcriptomics for frozen tissue
Capture chemistry and workflow are optimised for frozen and OCT-embedded sections, so each 10 μm spot detects more transcripts and genes than standard-resolution approaches.
This higher sensitivity supports robust pathway analysis and biomarker discovery, even in challenging regions such as necrotic cores or fibrotic areas.
Cost-effective high resolution spatial transcriptomics
Each slide provides many thousands of 10 μm capture spots, delivering high resolution comparable to research-grade platforms in a service format.
You gain detailed views of small niches and microenvironments without purchasing hardware or maintaining a dedicated spatial transcriptomics team.
End-to-end spatial transcriptomics service from a single partner
We run a sample-to-analysis spatial transcriptomics workflow: chip processing, sequencing, and spatial transcriptomics data analysis service under one project manager.
Your team receives ready-to-interpret spatial datasets and figures from one CRO partner, simplifying communication and reducing the risk of hand-off errors.
Applications of High-Resolution 10 μm Spatial Transcriptomics
High-resolution 10 μm spatial transcriptomics is most valuable when spatial context changes biology.
It supports cancer, immunology, neuroscience, and developmental studies where microenvironments matter as much as cell identity.
Tumor Microenvironment and Oncology
High resolution cancer spatial transcriptomics allows you to profile the tumor microenvironment in situ.
You can map malignant cells, stromal populations, and immune infiltrates at 10 μm resolution across whole sections.
Researchers use oncology spatial transcriptomics to:
- Separate tumor cores, invasive margins, and peritumoral regions.
- Characterise immune microenvironment states under different therapies.
- Study resistance niches that are invisible in bulk RNA-seq.
Immunology and Inflammation
Spatial transcriptomics for immunology helps dissect how immune cells organise within tissues.
You can position T cells, B cells, myeloid cells, and cytokine signals in their native immune microenvironment.
Typical questions include:
- Where effector and regulatory cells accumulate in chronic inflammation.
- How spatial patterns of chemokines relate to immune cell recruitment.
- How infection foci shape local gene expression programs.
Brain Tissue and Neuroscience
Brain tissue spatial transcriptomics captures layered and regional organisation that dissociated methods lose.
Mouse brain spatial transcriptomics can resolve cortical layers, nuclei, and fibre tracts with 10 μm spots.
Neuroscience spatial transcriptomics supports:
- Mapping neurotransmitter and receptor expression across defined circuits.
- Linking gene expression patterns to anatomical regions and connectivity.
- Studying spatial changes in neurodegeneration or injury models.
Developmental Biology and Embryonic Atlases
Developmental biology spatial transcriptomics enables you to follow patterning in space and time.
You can build an embryonic development spatial atlas that shows when and where key regulators switch on.
Use cases include:
- Defining spatial waves of transcription factors during organ formation.
- Comparing normal and perturbed developmental trajectories in whole embryos.
- Linking morphogen gradients to downstream gene expression domains.
Biomarker Discovery and Translational Research
High resolution spatial data supports biomarker discovery with spatial transcriptomics.
Markers are evaluated not only by expression level, but also by location and neighbourhood.
This is especially useful for:
- Identifying spatial biomarkers that predict drug response or resistance.
- Validating targets in the context of human tissue architecture.
- Prioritising regions and cell states for follow-up cell-level or functional studies.
Sample-to-Analysis Spatial Transcriptomics Workflow
Our end-to-end spatial transcriptomics service runs as a single, coordinated workflow.
You send frozen tissue; we return processed spatial datasets and figures.
Study Design and 10 μm Platform Performance
Careful study design ensures that 10 μm spatial transcriptomics delivers the depth and coverage your project needs.
This section outlines recommended inputs, expected performance, and practical design tips.
Input types and tissue handling
- We support frozen and OCT-embedded tissue from common preclinical and translational models, including human, mouse, and rat.
- Consistent freezing procedures and minimal freeze–thaw cycles are important to maintain RNA quality and tissue morphology.
Section thickness and RNA quality
- Sections are typically cut at 10–16 μm, depending on tissue type and architecture.
- We recommend upstream RNA integrity checks on representative material from the same batch.
How many genes and transcripts can be detected per 10 μm spot?
- Under well-optimised conditions, each 10 μm spot in complex tissues can detect on the order of hundreds of genes and a similar scale of transcript counts.
- Exact values depend on tissue type, RNA quality, and chosen sequencing depth, and are refined during study design.
Sequencing depth and capture areas
- Sequencing depth is matched to your question—lighter coverage for broad exploratory screens, deeper coverage for detailed characterisation.
- Multiple capture areas per slide can be dedicated to different regions, donors, or conditions to maximise information from each run.
Reproducibility and experimental design
- We recommend biological replicates per group and balanced allocation of conditions across chips and runs.
- This design supports robust detection of spatial patterns and differential expression while controlling for technical variation.
Bioinformatics for Spatial Transcriptomics and Reporting
Our bioinformatics for spatial transcriptomics turns raw sequencing reads into clear, spatially resolved biology.
This spatial transcriptomics data analysis service includes a standard analysis package plus optional advanced modules.
Standard analysis package
Data preprocessing and quality control
- Overall distribution plots for reads and counts across spatial positions.
- Per-spot metrics, including number of detected genes, total transcript counts, mitochondrial gene fraction, and ribosomal gene fraction.
- Summary of the top 20 most highly expressed genes in each sample or region.
Clustering and dimensionality reduction
- Unsupervised clustering to group spots into cell-type–like or region-specific clusters.
- Mapping of clusters or inferred cell types onto spatial coordinates.
- UMAP and t-SNE embeddings coloured by cluster or cell type.
- Cell cycle phase visualised on UMAP to highlight proliferative regions.
Automatic cell type annotation
- Automatic cell type assignment based on reference signatures or marker genes.
- Annotations projected onto spatial maps, UMAP, and t-SNE plots for intuitive interpretation.
Advanced analysis options
Marker gene functional enrichment
- Functional enrichment analysis for marker genes from selected clusters or regions.
- Pathway- and process-level summaries to support mechanistic interpretation.
Cell trajectory and dynamic state analysis
- Trajectory reconstruction and pseudotime mapping on UMAP for relevant cell populations.
- Cluster-level trajectory views to show how groups evolve along pseudotime.
- Differential expression along pseudotime and between trajectory-defined states.
Cell–cell interaction analysis
- Quantification of interaction scores or weights between inferred cell types.
- Summary of the number and intensity of putative interactions across the tissue.
Spatially variable and location-specific genes
- Identification of genes whose expression is strongly associated with spatial position.
- Highlighting of region-specific or niche-specific genes for follow-up validation.
Deliverables
- Processed count matrices linked to spatial coordinates and cluster labels.
- Spatial maps, UMAP and t-SNE plots, cell cycle and trajectory visualisations.
- Tables of marker genes, enriched functions, interaction metrics, and spatially variable genes.
- A concise analysis report describing methods, key quality metrics, and main biological findings.
Spatial clustering maps at 100, 50, 20 and 10 μm resolution
Spatial clustering and gene-level expression maps
Joint view of 10 μm spatial transcriptomics clusters:
Sample Requirements: What Types Are Compatible with 10 μm Microbead Array Spatial Transcriptomics
The table below summarises the key requirements for 10 μm microbead array spatial transcriptomics on frozen tissue.
| Item | Requirement / Recommendation |
|---|---|
| Supported species | Human, mouse, rat |
| Sample types | Fresh-frozen or OCT-embedded tissue blocks / sections; FFPE not supported |
| Tissue quality | Rapid, controlled freezing; avoid repeated freeze–thaw cycles; preserve RNA and morphology |
| Storage | Store blocks or slides at ≤ −80°C until shipment |
| Section thickness | Typically 10–16 μm (adjusted by tissue type and architecture) |
| Section size | Sized to the agreed capture area on the 10 μm microbead array chip |
| Extra sections | Provide additional sections for optimisation and potential repeats; number confirmed at study design |
| Companion sections | Reserve consecutive sections for H&E or immunofluorescence if spatial alignment is needed |
| Shipping conditions | Ship on dry ice in secure, clearly labelled containers |
| Documentation | Include manifest with sample ID, species, tissue type, pre-analytical details, and orientation/landmarks if relevant |
This format ensures your samples are compatible with 10 μm microbead array spatial transcriptomics and supports robust spatial mapping.
FAQs on 10 μm High-Resolution Spatial Transcriptomics
Start Your High-Resolution Spatial Transcriptomics Project
Plan a 10 μm chip-based spatial transcriptomics study with an end-to-end, outsourced workflow.
When to contact us
- You need high resolution spatial maps of frozen or OCT-embedded tissue.
- You want to compare 10 μm spatial transcriptomics vs Visium or other platforms for a specific project.
- You prefer a service model rather than building and maintaining your own spatial transcriptomics pipeline.
What you can expect
- Support with study design, including tissue selection, depth planning, and analysis scope.
- A coordinated, sample-to-results workflow with defined milestones.
- Delivery of spatial datasets, figures, and reports ready for internal review and publication.
Next steps
- Request a quote with a brief description of your samples, conditions, and target timelines.
- Talk to a scientist to refine your spatial experiment and integration with existing cell-level or bulk data.
- Upload your project outline if you already have a draft protocol and need execution and analysis support.
Our team will review your information, propose a study design and sequencing plan, and outline how this end-to-end spatial transcriptomics service can be fitted into your broader programme.
References
- Rodriques SG, Stickels RR, Goeva A, et al. Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science. 2019;363(6434):1463–1467.
- Yang M, Ong J, Meng F, et al. Spatiotemporal insight into early pregnancy governed by immune-featured stromal cells. Cell. 2023;186(20):4271–4288.e24.
- Langlieb J, Sachdev NS, Balderrama KS, et al. The molecular cytoarchitecture of the adult mouse brain. Nature. 2023;624(7991):333–342.
- Causer A, Tan X, Lu X, et al. Deep spatial-omics analysis of head and neck carcinomas provides alternative therapeutic targets and rationale for treatment failure. NPJ Precision Oncology. 2023;7(1):89.
