The precise regulation of the immune system depends on the synergistic effect of clonal identity, functional state, and regulatory potential of lymphocytes, but it is difficult to completely analyze this complex network using traditional single-omics technology. As the core tool to analyze the characteristics of T cell receptor (TCR) and B cell receptor (BCR) clones, Immune repertoire sequencing can clarify the distribution of T cell clones through TCR-seq, capture the high-frequency mutation and clone amplification of B cell somatic cells through BCR-seq, and accurately answer which immune clones exist. Still, it cannot reveal the functional status (such as activation and depletion) and differentiation potential of these clones.

Transcriptomics can detect gene expression patterns and clarify the functional phenotype of immune cells; Epigenomics can analyze the characteristics of chromatin accessibility and methylation, and mine the regulatory network and pedigree history of cells. Integrating immune repertoire sequencing with them can not only lock antigen-specific clones through TCR-seq/BCR-seq, but also judge the functional state of clones with the help of transcriptomics, and trace their differentiation origin and response potential through epigenetics, thus forming a complete research chain of clone identity-functional state-regulatory mechanism. This multi-omics integration strategy completely breaks through the limitation of single technology, and provides key technical support for deeply understanding the immune response mechanism in infection, tumor, and autoimmune diseases, and promoting the development of precision immunotherapy.

The article discusses integrating immune repertoire sequencing with transcriptomics and epigenetics to analyze lymphocyte clonal identity, functional states, and regulatory mechanisms, supporting immune research and precision immunotherapy.

The Need for a Multi-Dimensional View of Immunity

The function of the immune system depends on the regulation of lymphocytes, and the traditional immune repertoire sequencing technology has limitations, which can not meet the needs of in-depth research. In the study of tumor immunity, its limitations are particularly obvious.

Under this background, integrating V (D) J sequence data with transcriptome and epigenetics data has become the core strategy to break through this limitation. The core argument is that through the linkage analysis of multi-omics data, an unprecedented and integrated map of immune cell function, differentiation, and fate can be constructed. The three core components of this integrated research system have irreplaceable values:

• Immune Repertoire Sequencing: Focusing on clone specificity, by analyzing the V (D) J recombination sequence of TCR/BCR and the characteristics of the CDR3 region, the unique clone identity of each lymphocyte is defined, which is a molecular fingerprint to track clone amplification, migration, and evolution.
• Transcriptomics: Reveal the state and activity of cells, and judges whether cells are in functional states such as activation, exhaustion, and memory by detecting the gene expression level of the whole genome. For example, T cells with high expression of PDCD1(PD-1) and LAG3 can be defined as exhausted T cells.
• Epigenomics: Excavate the regulatory potential and pedigree history, identify the gene expression regulatory network of cells (such as transcription factor binding sites) by analyzing the apparent modification characteristics such as chromatin accessibility and DNA methylation, and trace back its differentiation origin and future response potential. For example, memory T cells have a higher degree of chromatin opening at the IL-7Rα locus, which determines their long-term survival and rapid activation.

The organic integration of the three can realize the complete chain analysis from cloned identity to functional state to "regulatory mechanism", and provide a new perspective for basic research and clinical transformation of immunity.

Analysis of CD8+ antigen-specific T cells sampled from Donor 1 (Samir et al., 2020)

Technological Frameworks for Multi-Omic Integration

In traditional immune research, immune repertoire sequencing, transcriptome, and epigenetics are often carried out separately, which leads to the separation of information such as clone identity, cell state, and regulatory potential, and it is difficult to fully analyze the immune mechanism. Multiomics integration technology came into being, from single-cell synchronous capture to bulk sample cross-modal alignment, which broke through the limitation of a single dimension and realized the accurate correlation of different omics data, providing systematic technical support for revealing the function, differentiation, and fate of immune cells.

Single-cell Omics

The emergence of single-cell multimethology technology has completely broken the limitations of traditional sample detection and data fragmentation, and achieved the synchronous capture of immune repertoire sequencing, transcriptome, epigenome, and protein expression information of the same cell, among which 10x genomics multiome combined with Feature Barcoding technology has become the mainstream platform for multi-dimensional immune research.

The core technical principle of this kind of platform is Cell Barcode sharing, that is, a single cell and a Gel Bead with a unique Cell Barcode are wrapped in the same droplet through microfluidic technology, so that all the data of the cell carries the same Barcode, and finally, the accurate correlation of multimodal data is realized through bioinformatics analysis. The specific process can be divided into three steps:

• Single cell capture and Barcode labeling: The treated single cell suspension (such as PBMCs and TILs) is mixed with gel beads, and the single cell-gel bead-droplet complex is formed by a microfluidic chip. Primers coupled to the surface of gel beads include Cell Barcode (cell recognition), molecular marker (correction of PCR amplification deviation), and histocompatibility-specific primers (oligo (dT) of mRNA, V/J primer of TCR/BCR, Tn5 aptamer of open chromatin).
• Multiomics synchronous detection: After cell lysis in the droplet, different types of biomolecules (mRNA, TCR/BCR cDNA, open chromatin fragment) combine with corresponding primers to complete reverse transcription (for RNA) or transposition (for chromatin) reaction. For example, in the 10x Genomics Multiome platform, you can simultaneously:
  a) Gene expression (GEX) detection: mRNA was captured by oligo (dT) primer, and then cDNA was synthesized and amplified to obtain the transcriptome information of cells.
  b) Chromatin accessibility (ATAC-seq) detection: The Tn5 transposon was inserted into the open chromatin region, and the apparent regulatory information was obtained after amplification.
  c) TCR/BCR sequencing: The variable region sequence of TCR/BCR was amplified by V/J region-specific primers, and the cell clone type was confirmed.
  d) Protein expression detection: Combining with Feature Barcoding technology, cell surface proteins (such as CD4, CD8, PD-1) were labeled with antibodies coupled with a Barcode to realize the correlation between protein expression and other omics data.
• Data integration and analysis: The transcriptome, epigenome, Immune repertoire sequencing, and protein data of the same cell were matched by Cell Barcode, and the subsequent analysis was carried out by using special analysis software (such as 10x Genomics Cell Ranger ARC and Seurat).

Multimodal biomarkers of immune cell states (Hao et al., 2021)

Sequential and Polymerization Analysis Methods

In addition to the single-cell synchronous capture technology, sequential analysis and aggregation analysis methods have become an important supplement to the integration of multi-omics, mainly including two strategies: bulk horizontal integration and cross-modal data alignment.

A. Bulk horizontal integration

a) This strategy is suitable for the research that needs in-depth analysis of specific cell subsets, and the core process is cell sorting → sample analysis → data association. Specifically, the target cell subsets (such as CD8+T cells and CD19+B cells) were separated from the bulk samples by flow cytometry or magnetic bead sorting technology, and then the same subset was subjected to Bulk Immunization Repeater Sequencing and bulk RNA-seq, respectively. Finally, the characteristics of clone amplification and the differences in gene expression were correlated by statistical methods.

b) The advantage of this method is that it can achieve in-depth detection of specific subgroups. For example, bulk RNA-seq can detect low-expression genes (such as transcription factor genes), while single-cell technology may miss such information due to the limitation of sequencing depth. However, the disadvantage is that the accurate correlation at the single cell level can not be realized, and it can only reflect the average characteristics at the population level, and the cell sorting process may lead to the change of activation state of some cells, which may affect the authenticity of the data.

B. Cross-modal Data Alignment

a) When the sample size is very small (such as a puncture biopsy tissue), it is impossible to carry out cell sorting or multiple tests. A cross-modal data alignment strategy can solve the contradiction between insufficient sample size and multiple omics requirements by carrying out different omics tests on different aliquots of the same sample, and then using computing tools to realize data integration.

b) The specific process is as follows: Divide an original sample (for example, 10^5 PBMCs) into 2-3 aliquots on average, respectively:

• Aliquot 1: single cell Immune repertoire sequencing (detection of clonal type and cell grouping)
• Aliquot 2: Single Cell RNA-seq (Detection of Transcriptome Characteristics)
• Aliquot 3: single cell ATAC-seq (detection of epigenetic characteristics)

c) Then, using computational integration algorithms (such as CCA integration of Seurat, Harmony, LIGER), the cells of different aliquots were matched based on cell clustering markers or similarity of gene expression/apparent characteristics.

d) The key to this method is to choose an appropriate integration Anchor to ensure the consistency of cell grouping of different aliquots. In the study of tumor-infiltrating lymphocytes, the expression patterns of surface markers such as "CD3, CD8, CD4, PD-1" can be used as anchor points, which can effectively reduce the cell grouping deviation caused by the difference in sample processing, and the integration accuracy can reach 80%-90%. However, its limitation is that it depends on the reliability of the calculation model. If there is a large heterogeneity among aliquots (such as a high proportion of apoptosis in some aliquots), the integration results may be distorted.

Investigating immune repertoire and transcriptional features of TNFR2-specific BM PCs (Agrafiotis et al., 2023)

Insights from Immune Repertoire Sequencing and Transcriptomics

The integration of immune repertoire sequencing and transcriptomics (cell state) fills the information gap between the identity and functional state of immune clones, and provides key evidence for analyzing antigen-specific immune response, clone differentiation trajectory, and gene regulation network. The following is elaborated from three core directions.

Define the Function of Antigen Cloning

• Tumor immunity: In the TILs study of melanoma, immune repertoire sequencing combined with transcriptome analysis found that the MART-1 antigen-specific TCR clone (TRBV13-1+TRBJ2-3+) highly expressed a depletion marker and low expressed effector gene, which provided a target for PD-1 inhibitor therapy.
• Infection immunity: PBMCs analysis of COVID-19 recovered people showed that the S protein-specific BCR clone (IGHV3-53+IGKJ4+) was enriched in memory B cells, which had both the ability of memory and rapid antibody secretion.
• Autoimmune disease: In patients with systemic lupus erythematosus, the self-reactive BCR clone (IGH4-34+IGLJ3+) is concentrated in a specific cell group, which highly expresses inflammatory factors and can bind to dsDNA, which is the key to the disease.

Immune Clone Differentiation Trajectory

• Dynamic differentiation of T-cell clones: In the mouse virus infection model, immune repertoire sequencing tracked the specific virus clone. Combined with the pseudo-sequence analysis of transcriptome, it was found that the clone showed effector precursor state at the initial stage of infection, developed into effector cells at the middle stage, and differentiated into central memory and effector memory cells at the later stage. The high expression of TCF1 in transitional cells was the key molecule of memory differentiation.
• Affinity maturation of B-cell clones: The study of mice immunized with a vaccine shows that the specific clones undergo SHM with the immune process, go through the stage of germinal center precursor and germinal center B-cell, and finally differentiate into memory B cells and plasma cells, and the affinity of plasma cell BCR is significantly higher.

Mining the Characteristics of Cloned Genes

• Proliferation and metabolism of amplified clones: Immune repertoire sequencing showed that TCR Klonga expressed cell cycle and glycolysis genes in antigen-specific amplification of healthy people after vaccination, and cell cycle inhibitory genes were highly expressed in resting initial clones, which confirmed that proliferation and metabolism reprogramming drove clone amplification.
• Regulation in inflammatory microenvironment: In synovial tissue of patients with rheumatoid arthritis, B cells with BCR clones highly expressed inflammatory transcription factors and related genes, and the expression of the NF-κB pathway was positively correlated with the abundance of clones, indicating that the regulation of inflammatory signals was abnormally amplified.
• Survival in tumor microenvironment: TILs of lung cancer predominantly express TCR Klonga to express anti-apoptosis genes, and the apoptosis inhibition pathway is activated, while low-abundance clones highly express pro-apoptosis genes, indicating that anti-apoptosis ability ensures clone amplification.

Repertoire behavior in the vaccination time course (Pavlova et al., 2024)

Combination Immune Repertoire Sequencing with Epigenetics

Immune repertoire sequencing is used to identify the clonal identity of lymphocytes, while epigenetic techniques (such as single-cell ATAC-seq and DNA methylation sequencing) are used to analyze the gene expression regulation mechanism and cell lineage history. The integration of the two provides a core technical means for explaining the mechanism of functional specialization and fate determination mediated by epigenetic regulation of immune clones. The core findings can be expounded from the following three aspects.

Clonal Chromatin Mapping

Prediction of differentiation potential of memory B cell clones after vaccine immunization: immune repertoire sequencing recognizes HPV vaccine-specific BCR clones, and histone modification sequencing shows that the modification level of the antibody secretion gene promoter region H3K4me3 can accurately predict the antibody secretion ability of clones.

Apparent early warning of abnormal differentiation clones in autoimmune diseases: In the high-risk population of rheumatoid arthritis, immune repertoire sequencing detected potentially pathogenic BCR clones, and ATAC-seq showed that chromatin in the enhancer region of pro-inflammatory genes was open, which could be used as an early warning signal of abnormal differentiation of clones.

Traceable Antigen Response Potential

Apparent traceability of tumor antigen through T cell cloning: In PBMCs of lung cancer patients, Immune repertoire sequencing found that specific TCR clones existed in peripheral blood and tumor tissues. Combined with DNA methylation sequencing, it was confirmed that hypomethylation of the tumor antigen response gene promoter from tumor clones was an apparent sign of tumor antigen stimulation, which could trace the infiltration history.

Prediction of differentiation potential of memory B-cell clones after vaccination: immune repertoire sequencing recognizes specific BCR clones among HPV vaccine recipients, and histone modification sequencing shows that the modification level of the antibody secretion gene promoter region H3K4me3 can accurately predict the antibody secretion ability of clones.

Apparent early warning of abnormal differentiation clones in autoimmune diseases: In the high-risk population of rheumatoid arthritis, immune repertoire sequencing detected potentially pathogenic BCR clones, and ATAC-seq showed that chromatin in the enhancer region of pro-inflammatory genes was open, which could be used as an early warning signal of abnormal differentiation of clones.

Apparent Regulation of V (D) J Recombination

• Thymic T cells: immune repertoire sequencing of mouse thymocytes showed that the TCRβ chain V fragment was used preferentially (for example, Vβ8.2 accounted for 15%). Combined with ATAC-seq, it was found that the high-use V fragment locus was more open in RAG-active thymic cortical cells and contained RAG binding motifs.
• Bone marrow B cells: Immune repertoire sequencing of human bone marrow B cells showed that the use of IBR light chain IGK was higher than that of IGL, and methylation sequencing showed that the methylation rate of IGL was higher in the early stage, and the methylation of IGK continued to decrease after maturity, and IGL was still high.
• Immune stress: In mice infected with chronic hepatitis B, IR-seq found that the use of TCR V fragment (such as Vα14) against the virus increased, and ATAC-seq showed that the chromatin opening near its locus was enhanced, enriching the binding sites of NF-κB, and the antigen activated NF-κB to maintain its opening, which promoted the adaptive evolution of the immune library.

Tregs exhibit position-specific TCR sequence features (Kaitlyn et al., 2021)

Conclusion

To sum up, the integration of Immune repetoire sequencing with transcriptomics and Epigenomics breaks through the information limitation of single technology, and constructs a complete research chain of cloning identity-functional state-regulation mechanism: the clone specificity provided by Immune repetoire sequencing anchors the core target of multi-group association, transcriptomics reveals the molecular basis of cell functional phenotype, and Epigenomics analyzes the deep logic and cell lineage history of gene expression regulation.

This multi-dimensional integration not only deepens the understanding of the dynamic evolution of immune response, the specialization of cloning function, and the fate determination mechanism, but also provides a precise control idea for solving clinical problems (such as immunotherapy resistance and the traceability of autoimmune diseases). In the future, with the standardization of technology and the optimization of analytical tools, this integration strategy will further promote the transformation of basic immune research into the clinic, and provide more powerful theoretical and technical support for precise intervention of immune-related diseases.

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