Single-Cell TCR Immune Repertoire Sequencing

Single-Cell TCR Immune Repertoire Sequencing

1. Background

T-cell receptor (TCR) diversity is the molecular foundation of adaptive immune responses. The clonal composition and functional status of TCRs are closely associated with tumor immunity, autoimmune diseases, and infectious diseases, as well as disease progression and therapeutic outcomes. Conventional bulk TCR sequencing characterizes the overall clonal lineage of mixed cell populations but cannot determine the native α-chain and β-chain pairing of individual T cells, nor directly link clonotypes to cell phenotypes, limiting in-depth analysis of T-cell functional heterogeneity.

Single-cell TCR sequencing is based on droplet or microwell single-cell platforms. At single-cell resolution, each T cell is loaded with a unique cell barcode and UMI to achieve native paired capture of full-length TCR α-chain (V-J rearrangement) and β-chain (V-D-J rearrangement) V(D)J sequences. When integrated with single-cell transcriptome sequencing (scRNA-seq) on the same platform, clonal identity can be mapped to cell phenotype, functional status, and differentiation trajectory, providing unprecedented resolution for T-cell immunology research.

In the frontier of drug development, the value of single-cell TCR sequencing has gained broad recognition. The FDA Considerations for the Development of CAR T Cell Products (2024) and China's CDE Guiding Principles for Pharmaceutical Research and Evaluation of Immune Cell Therapy Products (Trial) (2022, Announcement No. 30) have set forth explicit requirements for clonal composition and receptor chain pairing characterization of TCR-T/CAR-T products. The FDA Long-Term Follow-Up After Administration of Human Gene Therapy Products (2020) also highlights refined monitoring of risks such as clonal expansion and delayed adverse events. Single-cell paired technology can provide higher-precision data support for the aforementioned research and product characterization.

ZhuHai GeneRulor provides a full-process service spanning sample quality control, single-cell capture and library construction, high-throughput sequencing, and systematic bioinformatics analysis, empowering clients to precisely dissect T-cell clonal dynamics and functional heterogeneity at single-cell resolution.

2. Technical Principles

Single-cell TCR sequencing is based on a 5' V(D)J capture approach, utilizing droplet microfluidics or microwell single-cell platforms to achieve efficient amplification and native paired sequencing of full-length TCR V(D)J sequences at the single-cell level. The technical workflow comprises the following core steps:

（1）Single-Cell Suspension Preparation and Capture

A high-viability single-cell suspension is prepared, and individual T cells are captured via droplet or microwell platforms. Each cell is loaded with a unique cell barcode and UMI, ensuring accurate deduplication and single-cell traceability of downstream data.

（2）Reverse Transcription and V(D)J Enrichment Library Construction

A 5'-end template-switching strategy is employed for reverse transcription to target-enrich TCR V(D)J sequences, covering the full-length variable regions of α-chains (V-J region) and β-chains (V-D-J region) as well as γ/δ chains (optional). scRNA-seq libraries can be simultaneously constructed on the same platform, enabling concurrent capture of clonal and transcriptomic information. Library construction is completed after library preparation and sample indexing.

（3）High-Throughput Sequencing and Data Analysis

Library sequencing is performed on Illumina platforms. After quality control filtering, UMI deduplication, and VDJ sequence alignment (referencing the IMGT database), TCR α/β chain sequence reconstruction and clonotype annotation are completed, outputting the native paired TCR information for each cell, followed by systematic multidimensional immune repertoire analysis (see Section 5 for details).

Figure 1. Single-Cell TCR Sequencing Technical Workflow

3. Technical Features and Advantages

（1）Native α–β Pairing

Precisely captures the native paired α-chain and β-chain sequences of each individual T cell at single-cell resolution, overcoming the fundamental limitation of bulk TCR-seq in resolving native α–β chain pairing, and providing a precise molecular basis for TCR specificity validation, functional studies, and engineering.

（2）Full-Length V(D)J Sequence Coverage

Provides complete coverage of TCR variable regions (α-chain V-J region, β-chain V-D-J region), encompassing CDR1–CDR3 full-region information. This is superior to short-fragment approaches that cover only CDR3, facilitating sequence reconstruction, database alignment, and downstream functional validation.

（3）Precise Clonotype–Phenotype Integration

Can be combined with scRNA-seq libraries from the same platform for joint analysis, directly mapping TCR clonotype information to cell phenotypes (such as CD4⁺/CD8⁺ subsets, exhaustion, activation, memory, and differentiation states), enabling multidimensional integrated analysis of "clonotype–phenotype–function."

（4）High-Resolution Clonal Dynamics Tracking

Through UMI-based error correction and cell-level resolution, supports precise quantitative comparison of clonal expansion dynamics across different time points, tissue origins, and sample sources, suitable for longitudinal analysis of pre- and post-treatment clonal changes.

（5）Standardized Analysis Pipeline with Reproducible Results

Establishes a standardized pipeline spanning upstream data processing (Cell Ranger VDJ) to downstream immune repertoire analysis (scRepertoire and other mainstream tools), with unified diversity index calculation methods and visualization output specifications, ensuring cross-sample and cross-batch result comparability.

Scope of Application: This service requires high-viability single-cell suspensions (viability ≥80%, fresh or cryopreserved in compliance with standards), and is not applicable to FFPE samples, degraded RNA, genomic DNA (gDNA), or fixed cells. Throughput is typically in the range of thousands to tens of thousands of cells, with rare clone detection sensitivity dependent on the number of cells loaded. For high-volume, low-cost overall clonal repertoire screening, bulk TCR-seq may be considered as an alternative.

4. Application Scenarios

Cell Therapy Product Characterization and Research: For CAR-T/TCR-T and other cell therapy products, confirms the completeness of introduced TCR chain pairing at single-cell resolution, analyzes the clonal composition and phenotypic distribution of accompanying T cells in the product, and supports product characterization data packages that meet regulatory requirements.

Antigen-Specific T Cell Identification: Performs single-cell sequencing on antigen-specific T cells enriched via tetramer or other strategies to obtain complete paired TCR sequences, providing evidence for functional validation and TCR-T therapeutic candidate selection.

Tumor-Infiltrating T Cell (TIL) Analysis: Combined with transcriptomic data, dissects the relationship between TIL clonal expansion and functional states (activation, exhaustion, memory), facilitating tumor immune microenvironment research and immune checkpoint therapy mechanism exploration.

Clonality Monitoring and Long-Term Follow-Up: In long-term follow-up settings for cell therapy or gene therapy products, tracks dynamic changes of specific clones to provide refined data for clonal expansion risk assessment.

Autoimmune and Infectious Disease Immunology Research: Analyzes the expansion patterns and specificity of disease-associated T-cell clones, supporting pathogenic clone identification and vaccine response evaluation.

5. Report and Deliverables

The report comprehensively covers sequencing quality control through systematic immune repertoire analysis. Core analysis modules include:

· Sequencing quality control and cell filtering statistics (UMI distribution, valid cell count, α/β chain pairing rate)

· Paired clonotype (α–β) identification, counting, and frequency statistics

· Clonal diversity indices (Shannon entropy, Gini coefficient, clonal expansion index, etc.)

· V/D/J gene usage frequency analysis (frequency distribution and gene combination patterns)

· CDR3 sequence characterization analysis (length distribution, amino acid composition, and sequence motifs)

· Clonal expansion profiles and top expanded clone lists with sequence information

· Inter-sample shared clone analysis and temporal clone tracking (applicable for multiple samples)

· (Optional) Clonotype–phenotype joint analysis: integration of scRNA-seq data, overlaying clonotype information on cell subcluster UMAP projections

Deliverables: Illustrated analysis report (PDF) + detailed clonotype information table (Excel/CSV, containing paired TCR sequences, V/D/J gene annotations, and clone frequencies for each cell) + raw sequencing data (FASTQ)

Figure 2. Overview of Key Analysis Output Examples

6. Service Workflow

*Turnaround time: Standard workflow 25–30 business days

7. Sample Requirements

*Note: Specific viability requirements, target cell counts, and shipping requirements are subject to the latest Sample Submission Form. Viable cell samples are time-sensitive; please schedule in advance and confirm the protocol. If concurrent flow cytometry sorting, antigen-specific enrichment, cell activation, or other pre-processing is required, flexible combinations can be arranged based on project needs.

8. References

[1] U.S. Food and Drug Administration. Considerations for the Development of CAR T Cell Products; Draft Guidance. 2024.

[2] Center for Drug Evaluation (CDE), National Medical Products Administration (NMPA). Guiding Principles for Pharmaceutical Research and Evaluation of Immune Cell Therapy Products (Trial). 2022, Announcement No. 30.

[3] U.S. Food and Drug Administration. Long-Term Follow-Up After Administration of Human Gene Therapy Products; Guidance for Industry. 2020.

[4] Borcherding N, Bormann NL, Kraus G. scRepertoire: An R-based toolkit for single-cell immune receptor analysis. F1000Res. 2020;9:47.

[5] Wu TD, Madireddi S, de Almeida PE, et al. Peripheral T cell expansion predicts tumour infiltration and clinical response. Nature. 2020;579(7798):274–278.