10x Single-Cell V(D)J Sequencing Service
The adaptive immune system relies on an extraordinarily diverse repertoire of T cell receptors (TCRs) and B cell receptors (BCRs) generated through V(D)J recombination. CD Genomics delivers end-to-end 10x single-cell V(D)J sequencing services — capturing paired-chain TCR/BCR sequences alongside 5' gene expression from each individual lymphocyte — for immunology, oncology, and therapeutic development teams seeking to decode clonal dynamics, antigen specificity, and immune cell states in a single experiment.
What our 10x V(D)J sequencing service delivers:
- Paired-chain TCR α/β and BCR heavy/light chain reconstruction at true single-cell resolution
- Simultaneous 5' gene expression profiling with optional surface protein detection via CITE-seq
- Full-length V(D)J assembly with IMGT reference annotation and clonotype grouping
- Integrated bioinformatics pipeline covering clonal diversity, expansion, chain pairing, isotype analysis, and clonotype–phenotype correlation
- Publication-ready deliverables: UMAP with clonotype overlay, chain-pairing Sankey diagrams, clonal expansion landscapes, and isotype distribution analyses
Technology Overview: 10x Chromium Single-Cell Immune Profiling
The 10x Genomics Chromium Single Cell Immune Profiling platform uses droplet-based microfluidics to encapsulate individual cells with barcoded gel beads in nanoliter-scale droplets. The 5' capture chemistry enriches the V(D)J regions of TCR and BCR transcripts while retaining mRNA for gene expression analysis. Each gel bead carries oligonucleotides containing a cell-specific barcode, a transcript-specific molecular tag, and a poly-dT primer. This design enables simultaneous recovery of paired receptor sequences and transcriptome-wide gene expression data from the same single cell.
Unlike bulk immune repertoire sequencing — which pools millions of TCR or BCR reads and loses native α–β (or heavy–light) chain pairing — the 10x Chromium workflow preserves chain pairing at the individual cell level. Every assembled TCR α/β pair or BCR heavy/light chain pair can be traced to a specific lymphocyte, enabling direct identification of clonally expanded receptor pairs and correlation of paired-chain sequences with cell-type annotations from gene expression data.
| Capability | Specification |
|---|---|
| Platform | 10x Genomics Chromium Single Cell Immune Profiling |
| Throughput | 500–10,000 cells per sample |
| Receptor coverage | TCR α/β and BCR heavy/light paired chains |
| Modalities | V(D)J + 5' gene expression; optional surface protein (CITE-seq) |
| Species | Human, mouse (default); other species upon consultation |
| Sequencing | Illumina NovaSeq platform |
For projects requiring paired-chain immune repertoire data without full transcriptome coverage, targeted V(D)J-only library preparation is also available. For comprehensive multi-modal immune profiling needs, see our 10x single-cell RNA-seq and BD Rhapsody scWTA service pages.
V(D)J Immune Repertoire Sequencing Workflow
The single-cell V(D)J sequencing workflow proceeds through six integrated stages with quality control at each checkpoint.
- Sample preparation
Single-cell suspensions are prepared from fresh or cryopreserved tissue, PBMCs, or sorted lymphocyte populations. QC checkpoint: Viability assessment (target ≥85%), cell counting, and debris evaluation under microscopy.
- Single-cell encapsulation
Cells are loaded onto the 10x Chromium microfluidic chip, where individual cells are co-encapsulated with barcoded gel beads in nanoliter-scale droplets. Each gel bead carries a cell-specific barcode, a molecular tag, and a poly-dT primer for mRNA capture.
- Reverse transcription and barcoding
Within each droplet, cells are lysed and mRNA is reverse-transcribed. The resulting cDNA molecules carry both a cell barcode and a transcript-specific molecular tag, enabling unambiguous assignment of each read to its cell of origin. QC checkpoint: Post-GEM RT cDNA yield assessment.
- V(D)J enrichment
cDNA is split into two portions. One is used to construct a standard 5' gene expression library. The other undergoes targeted PCR enrichment using primers specific to the constant regions of TCR and BCR transcripts, selectively amplifying full-length V(D)J sequences. QC checkpoint: Enrichment efficiency verification by fragment analysis.
- Sequencing
Both the gene expression and V(D)J-enriched libraries are sequenced on the Illumina NovaSeq platform with paired-end reads. Sequencing depth is adjusted per project goals. QC checkpoint: Raw sequencing QC (Q30 scores, barcode/molecular tag/RNA read quality metrics from Cell Ranger output).
- Data processing and analysis
Raw sequencing data are processed through the Cell Ranger pipeline for alignment, V(D)J assembly, clonotype grouping, and gene expression quantification. Downstream analyses are performed using a curated bioinformatics pipeline (see Bioinformatics section below). QC checkpoint: Cell Ranger web summary metrics — estimated number of cells, mean reads per cell, V(D)J detection rate, chain pairing rate.
Our 10x V(D)J Sequencing Advantages
Multi-modal profiling from one cell
Capture TCR/BCR sequences, 5' gene expression, and optional surface protein markers (CITE-seq) from the same single cell. No need to run separate experiments to connect clonotype identity with cellular phenotype — one experiment, one data structure.
Full-length paired-chain assembly
Assemble complete V(D)J sequences with correct α/β and heavy/light chain pairing at single-cell resolution, validated against IMGT reference databases. Chain pairing rate is reported as a key QC metric for every project.
Deep bioinformatics integration
Our analysis pipeline goes beyond standard Cell Ranger output, offering integrated clonotype–transcriptome analysis, subpopulation-level immune repertoire characterization, clonal tracking, and cross-sample comparative analysis.
Scalable throughput
Process 500 to 10,000 cells per sample, accommodating both focused studies on rare lymphocyte populations and broad surveys of complex immune infiltrates.
Publication-ready deliverables
Receive analysis reports with publication-quality visualizations including UMAP embeddings with clonotype overlays, clonal expansion landscapes, chain-pairing Sankey diagrams, and isotype distribution analyses. Methods documentation is provided for manuscript preparation.
Bioinformatics Analysis Pipeline
Core immune repertoire analysis (included)
- V(D)J assembly and annotation: V, D, J gene segment usage; CDR3 sequence and length distribution; productive sequence ratio
- Clonotype identification: Clonotype frequency table; dominant clone identification; cells-per-clonotype distribution
- Clonal diversity assessment: Shannon diversity index; Simpson index; clonality score; rarefaction curves
- Chain pairing analysis: TCR α/β and BCR heavy/light chain pairing rates; chain-pairing Sankey diagrams
- Clonal expansion quantification: Clonal expansion categories (single, small, medium, large, hyperexpanded); expansion proportion per sample
- V/J gene usage profiling: Gene segment usage frequency by sample; differential V/J gene usage between conditions
- BCR isotype analysis: Isotype distribution (IgM, IgD, IgG, IgA, IgE) by sample and by B cell subpopulation
Integrated scRNA-seq + V(D)J analysis
- Clonotype overlay on UMAP: Visualize clonal expansion patterns directly on gene expression-based dimensionality reduction maps
- Subpopulation-level IR analysis: Quantify clonal diversity, expansion, and V/J gene usage within each annotated T/B cell subpopulation
- Clonotype–phenotype correlation: Identify which transcriptional states are associated with clonal expansion within CD8+ T, CD4+ T, and B cell compartments
- Clonal tracking across compartments: Trace individual clonotypes between blood and tissue, or across time points and treatment conditions
- Public clonotype analysis: Identify shared clonotypes (same or highly similar CDR3 sequences) across samples or patient groups
Advanced custom analysis options are available for projects requiring deeper investigation: epitope/antigen specificity prediction via CDR3 sequence alignment against immune receptor databases, BCR somatic hypermutation (SHM) analysis for affinity maturation quantification, class-switch recombination (CSR) trajectory analysis, and multi-omics integration with ATAC-seq or spatial transcriptomics data. For project-specific analysis design, contact our team.
Demo Results
The following figures represent the types of analysis outputs delivered with each 10x V(D)J sequencing project. Actual results are tailored to your experimental design and biological questions.
Panel A — Clonal expansion landscape
UMAP visualization of single T cells colored by clonal expansion category (single, small, medium, large, hyperexpanded). Dominant clones are highlighted, revealing which transcriptional clusters exhibit the strongest clonal outgrowth — a key indicator of antigen-driven expansion.
Panel B — TCR chain pairing overview
Sankey diagram showing the distribution of TCR chain pairs (α/β, α-only, β-only) across T cell subpopulations. The majority of productive cells yield paired α/β chains, enabling full receptor reconstruction for downstream specificity analysis.
Panel C — BCR isotype distribution by sample
Stacked bar chart of BCR isotype frequencies (IgM, IgD, IgG, IgA, IgE) across patient samples, with subpopulation-level breakdown. Isotype skewing provides insight into class-switch recombination activity and the antibody effector functions active in the tissue microenvironment.
Panel D — Clonal tracking across compartments
Circos plot or alluvial diagram tracing shared clonotypes between peripheral blood and tumor-infiltrating lymphocytes. Recirculating clones are distinguished from tissue-resident clones, revealing patterns of systemic immune surveillance versus local expansion.
These figures are intended as demonstrations of output types. Actual figures delivered with each project reflect the specific biological context, cell populations, and comparative questions defined in the analysis protocol.
Immune Repertoire Sample Requirements
Proper sample preparation is critical for high-quality single-cell V(D)J data. The table below lists general submission guidelines. For project-specific recommendations, contact our scientific team before shipment.
| Sample Type | Minimum Quantity | Viability Requirement | Preservation & Shipping |
|---|---|---|---|
| PBMCs (cryopreserved) | ≥5 × 105 cells | ≥85% | Cryopreserved in freeze medium; ship on dry ice |
| Fresh tissue | 200–400 mg (~0.5 cm³, 2–3 pieces) | ≥85% post-dissociation | Place in tissue preservation solution; cold chain (2–8°C); ship within 48 h |
| Sorted T/B cells | ≥3 × 105 cells | ≥85% | Cryopreserved or fresh in appropriate buffer; cold chain |
| Whole blood | 3–5 mL (EDTA anticoagulant) | N/A | Store at 4°C; cold chain; ship within 12 h for PBMC isolation; or isolate PBMCs on site and cryopreserve |
| Body fluids (ascites, CSF, etc.) | ≥1 × 105 total cells | ≥85% | Crushed ice transport; ship within 4 h |
Important notes:
- T/B cell proportion should ideally be >20% of the total cell population. For samples with lower lymphocyte content, enrichment by FACS or magnetic sorting is recommended prior to submission.
- Nuclei-based preparations are not compatible with V(D)J sequencing, as cytoplasmic mRNA containing V(D)J transcripts is lost during nuclear isolation.
- For CAR-T, TCR-T, or other engineered cell therapy products, please contact our technical team for project-specific guidance.
For detailed shipping instructions and a sample submission kit, contact our team.
Immune Repertoire Applications
Single-cell immune repertoire sequencing powers discovery across a broad range of research domains.
Tumor immunology
Profile TIL clonal expansion; identify tumor-reactive TCR clonotypes; characterize immune subtypes predictive of immunotherapy response. Apply to cancer types where immune infiltration pattern is a known determinant of treatment outcome.
CAR-T / TCR-T cell therapy
Track engineered T cell clonal dynamics; validate TCR pairing and specificity; monitor persistence and exhaustion trajectories in pre-infusion products and post-infusion patient samples.
Antibody and vaccine development
Identify antigen-specific B cell clones; characterize affinity maturation via SHM analysis; map neutralizing antibody repertoires in response to vaccination or natural infection.
Autoimmune disease
Detect expanded autoreactive clones; compare clonal architecture between affected and healthy tissues; study B cell tolerance breakdown in systemic and organ-specific autoimmune conditions.
Transplantation and immune reconstitution
Monitor donor-derived lymphocyte engraftment; track alloreactive T cell clones; assess immune repertoire recovery post-transplant in hematopoietic stem cell and solid organ transplantation.
Infectious disease
Characterize pathogen-specific TCR/BCR responses; compare clonal diversity between acute and convalescent phases; identify broadly neutralizing antibody lineages for therapeutic development.
Case Study: Immune Subtyping in Pancreatic Cancer via Single-Cell TCR/BCR Profiling
This independently published study demonstrates the power of single-cell V(D)J sequencing in decoding tumor immune microenvironments. It is presented as a representative example of the analytical depth achievable with this technology — it is not a CD Genomics client project.
Source: Sivakumar S, Jainarayanan A, Arbe-Barnes E, et al. Distinct immune cell infiltration patterns in pancreatic ductal adenocarcinoma (PDAC) exhibit divergent immune cell selection and immunosuppressive mechanisms. Nature Communications 16, 1397 (2025).
Background: Pancreatic ductal adenocarcinoma (PDAC) has one of the poorest prognoses among solid tumors, with a 5-year survival rate below 10%. Despite the success of immunotherapy in melanoma and lung cancer, PDAC has remained largely refractory to checkpoint blockade, and the underlying immunological barriers are poorly understood.
Methods: The study profiled tumor-infiltrating CD45+ immune cells from 12 treatment-naïve PDAC patients alongside matched peripheral blood, using the 10x Genomics Chromium Single Cell Immune Profiling platform (v1.1). The experimental design simultaneously captured 5' gene expression (GEX), surface protein markers (CITE-seq), and paired V(D)J sequences for both TCR α/β chains and BCR heavy/light chains. Data were integrated with two publicly available PDAC single-cell datasets (combined cohort: 47 patients) and validated against the APACT phase III clinical trial cohort (n = 486).
Results: PDAC tumors segregated into two fundamentally distinct immune archetypes: Adaptive-Enriched (AE) tumors — dominated by B and T lymphocytes with high CD8 EM clonal expansion, active germinal center B cell selection, and systemic tumor-reactive clone expansion — and Myeloid-Enriched (ME) tumors — characterized by high macrophage/DC infiltration, elevated Treg expansion with TIGIT/CTLA4/CCR8 expression, and enriched immunosuppressive axes (TIGIT/PVR, SIRPA/CD47). In the APACT validation cohort, patients with a myeloid-enriched, CD8-depleted phenotype had a median overall survival below 30 months versus over 43 months for those with high CD8+ and low CD163+ macrophage infiltration (p = 0.0016).
Conclusion: This study demonstrates that single-cell V(D)J sequencing — applied to both TCR and BCR repertoires — can resolve clinically meaningful immune subtypes invisible to bulk sequencing or histology alone. The integrated clonal expansion, chain pairing, isotype distribution, and blood–tumor clonal tracking analysis provided a systems-level view of adaptive immunity in PDAC, offering a blueprint for rational immunotherapy design applicable to immune profiling across cancer types.
Frequently Asked Questions
References
- Sivakumar S, Jainarayanan A, Arbe-Barnes E, et al. Distinct immune cell infiltration patterns in pancreatic ductal adenocarcinoma (PDAC) exhibit divergent immune cell selection and immunosuppressive mechanisms. Nature Communications. 2025;16:1397. DOI: 10.1038/s41467-024-55424-2.
- Zheng GXY, Terry JM, Belgrader P, et al. Massively parallel digital transcriptional profiling of single cells. Nature Communications. 2017;8:14049. DOI: 10.1038/ncomms14049.
- Peng J, Sun BF, Chen CY, et al. Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma. Cell Research. 2019;29(9):725-738. DOI: 10.1038/s41422-019-0195-y.
- Yost KE, Satpathy AT, Wells DK, et al. Clonal replacement of tumor-specific T cells following PD-1 blockade. Nature Medicine. 2019;25(8):1251-1259. DOI: 10.1038/s41591-019-0522-3.
- Azizi E, Carr AJ, Plitas G, et al. Single-cell map of diverse immune phenotypes in the breast tumor microenvironment. Cell. 2018;174(5):1293-1308. DOI: 10.1016/j.cell.2018.05.060.
