TCR Sequencing: Key Insights into Single-Cell and Bulk Methods

T-cell receptor (TCR) sequencing is a powerful tool for studying immune responses, offering insights into how T cells recognize and respond to pathogens, cancer cells, and other antigens. By analyzing TCR genetic sequences, researchers can track clonal expansions, assess immune diversity, and investigate disease mechanisms with unprecedented resolution.

Advancements in sequencing technology have enabled both bulk and single-cell approaches, each suited to different research needs. Understanding these methods and their applications is essential for leveraging TCR sequencing in immunology and clinical research.

T Cell Receptor Structure And Diversity

T-cell receptors (TCRs) enable T cells to recognize antigenic peptides presented by major histocompatibility complex (MHC) molecules. Each TCR consists of two polypeptide chains—either an α and β chain (in αβ T cells) or a γ and δ chain (in γδ T cells)—forming a heterodimer anchored in the T cell membrane. The extracellular portion contains variable (V), diversity (D, in β and δ chains), joining (J), and constant (C) regions, with the V region playing a key role in antigen recognition. The immense variability in the V region allows TCRs to recognize a broad array of antigens, making them indispensable for adaptive immunity.

This diversity arises through V(D)J recombination, a gene rearrangement process during T cell development in the thymus. The recombination activating genes RAG-1 and RAG-2 mediate the excision and rejoining of V, D, and J gene segments, generating unique TCR sequences. Additional diversity comes from junctional modifications, including nucleotide insertions and deletions by terminal deoxynucleotidyl transferase (TdT), creating an almost limitless TCR repertoire.

Beyond genetic recombination, thymic selection further shapes TCR diversity. During positive selection, T cells that weakly recognize self-MHC molecules receive survival signals, while those failing to interact with MHC are eliminated. Negative selection removes T cells with high affinity for self-antigens, reducing the risk of autoimmunity. This dual selection process refines the TCR repertoire, ensuring only functional and self-tolerant T cells enter circulation.

Core Steps In TCR Sequencing

TCR sequencing involves key steps to ensure accurate analysis of T-cell receptor repertoires, including sample collection, amplification, and sequencing library preparation.

Sample Collection

The quality of TCR sequencing data depends on proper sample collection and handling. Peripheral blood mononuclear cells (PBMCs) are commonly used, but tumor-infiltrating lymphocytes (TILs), lymph node biopsies, and bone marrow samples can also be analyzed. Whole blood samples require immediate processing to isolate PBMCs using density gradient centrifugation. Tissue samples are processed using enzymatic or mechanical dissociation to obtain viable T cells.

RNA-based TCR sequencing requires preserving RNA integrity with stabilization reagents like TRIzol or RNAlater. DNA-based approaches analyze TCR rearrangements at the genomic level and require high-quality genomic DNA. Single-cell TCR sequencing necessitates additional precautions, such as immediate cryopreservation or processing with microfluidic platforms to prevent RNA degradation. Standardized protocols, such as those from the Human Cell Atlas project, help ensure reproducibility.

Amplification

After nucleic acid extraction, TCR sequences must be selectively amplified to enrich for variable regions. RNA-based methods use reverse transcription polymerase chain reaction (RT-PCR), while DNA-based approaches rely on multiplex PCR. Primer design is critical, targeting conserved regions flanking the V(D)J junctions while minimizing amplification bias.

To improve accuracy, some protocols incorporate unique molecular identifiers (UMIs), short barcode sequences added during reverse transcription that help correct for PCR bias and sequencing errors. High-fidelity polymerases like Q5 or KAPA HiFi are preferred to minimize errors. For single-cell sequencing, whole-transcriptome amplification (WTA) may be performed before targeted TCR amplification to capture TCR sequences alongside gene expression data.

Sequencing Libraries

Library preparation converts amplified TCR products into formats compatible with next-generation sequencing (NGS) platforms. This includes adapter ligation, indexing, and size selection. Illumina platforms, such as NovaSeq and MiSeq, are widely used for their high accuracy and read depth, while Oxford Nanopore and PacBio long-read sequencing offer advantages in resolving complex TCR rearrangements.

For bulk TCR sequencing, libraries are pooled and sequenced to generate millions of reads, which are mapped to reference databases such as IMGT (International ImMunoGeneTics). Single-cell TCR sequencing requires additional barcoding to link TCR sequences to individual cells, often using droplet-based platforms like 10x Genomics Chromium or plate-based methods such as SMART-Seq. Quality control measures, including fragment analysis and qPCR quantification, ensure libraries meet concentration and size distribution criteria before sequencing.

Single-Cell And Bulk Sequencing

The choice between single-cell and bulk TCR sequencing depends on the resolution needed for a study. Bulk sequencing provides an overview of the collective TCR repertoire within a sample, capturing overall diversity and clonotype frequency. This approach is effective for analyzing large T cell populations at a lower cost but lacks the ability to link specific TCRs to individual cells.

Single-cell TCR sequencing preserves T cell identity, allowing researchers to determine which α and β (or γ and δ) chains belong to the same receptor. This is valuable for studying rare clonotypes, tracking lineage relationships, and correlating TCR sequences with gene expression profiles. By integrating single-cell RNA sequencing (scRNA-seq) with TCR sequencing, researchers can explore how TCR specificity influences transcriptional programs. However, single-cell approaches require more extensive sample handling, specialized platforms, and come at a higher cost per cell, making them less suitable for large-scale repertoire screenings.

Each method has technical challenges. Bulk sequencing relies on multiplex PCR or 5’ RACE (Rapid Amplification of cDNA Ends) for TCR amplification, but amplification bias can skew clonotype frequency estimates. Single-cell sequencing mitigates this issue with UMIs, which help correct for PCR duplicates and sequencing errors. However, single-cell methods may suffer from incomplete TCR recovery due to RNA degradation or inefficient capture rates. Advances in droplet-based and combinatorial indexing technologies have improved efficiency, but trade-offs between throughput, cost, and resolution remain.

High-Throughput Methods

High-throughput sequencing has transformed TCR analysis, enabling the characterization of millions of TCR sequences in a single experiment. These methods leverage NGS platforms such as Illumina and Pacific Biosciences to generate vast amounts of data with high accuracy and depth. Short-read sequencing, particularly with Illumina technology, is widely used for its low error rates and cost-effectiveness, making it ideal for large-scale repertoire profiling. Meanwhile, long-read platforms like PacBio and Oxford Nanopore allow for full-length TCR sequencing, resolving complex rearrangements.

Recent innovations in barcoding and molecular tagging have further improved sequencing resolution and efficiency. UMIs are commonly integrated into library preparation to correct for PCR bias and sequencing errors, ensuring accurate clonotype frequency estimates. Additionally, combinatorial barcoding techniques, such as those used by 10x Genomics and BD Rhapsody, enable single-cell resolution at high throughput, capturing both TCR sequences and transcriptomic data from thousands of cells in parallel. These advances have expanded the scale at which TCR repertoires can be studied, facilitating applications in immunotherapy and biomarker discovery.

TCR Repertoires In Different T Cell Types

T-cell receptor repertoires vary across different T cell subsets, reflecting their distinct roles in immune response. Naïve T cells, which have not yet encountered antigen, exhibit the highest TCR diversity, ensuring broad recognition of potential threats. In contrast, memory T cells display a more clonally restricted repertoire, characterized by expansions of antigen-specific TCRs selected through prior immune activation. Memory T cells often maintain a stable repertoire over time, with certain clonotypes persisting for years, providing durable immunity.

Regulatory T cells (Tregs), responsible for immune tolerance, exhibit distinct TCR characteristics. Unlike cytotoxic or helper T cells, which expand in response to foreign antigens, Tregs are enriched for self-reactive TCRs selected to suppress excessive immune responses. Bulk and single-cell TCR sequencing studies have shown that Tregs tend to have a more oligoclonal repertoire, with recurrent motifs indicating preferential selection of certain TCR specificities.

Tissue-resident memory T cells (Trm) differ significantly from circulating populations, often exhibiting clonally expanded repertoires specific to local antigens. This adaptation is evident in tumor-infiltrating lymphocytes (TILs), where specific TCR clonotypes dominate, reflecting ongoing immune interactions within the tumor microenvironment. These repertoire variations provide critical insights into T cell function across different physiological and pathological contexts.