RNA or gDNA: Which Should You Use for Immune Repertoire Sequencing?

A practical look at the tradeoffs between genomic DNA and RNA for TCR and BCR sequencing, and the iRepertoire services built to support each.

Key Takeaways:

• gDNA and RNA are both proven starting materials for TCR and BCR sequencing; the right choice depends on sample availability and your research goals.
• gDNA supports direct, per-cell counting of rearranged V(D)J receptors, and iRepertoire’s RepSeq IQ™ adds quantitative controls to convert reads into DNA copy numbers and cell counts.
• RNA offers greater sensitivity and lower background due to higher per-cell template and expressed-only sequences, and iRepertoire’s RepSeq+ is built to maximize that advantage across all seven adaptive immune chains.
• iRepertoire offers services that support both starting materials, so your sequencing strategy can evolve as your program needs change.

Two Starting Points, One Immune Repertoire

Every immune repertoire sequencing project starts with the same question: what sample do you have, and what do you need it to tell you? Genomic DNA (gDNA) and RNA are both well-established starting materials for TCR and BCR sequencing, and each has been used to generate published, decision-grade immune repertoire data. The right choice depends on your available sample type, your research goals, and how you plan to use the resulting data. Below, we walk through the technical tradeoffs of each starting material and the iRepertoire services built to support them.

gDNA as a Starting Template for Immune Sequencing

gDNA is often the most accessible starting material for immune repertoire sequencing. It is stable, straightforward to extract from PBMCs, whole blood, or FFPE tissue, and it does not require the same handling precautions as RNA. gDNA also offers a distinct quantitative advantage: because each cell carries one successfully rearranged V(D)J segment, sequencing from gDNA lends itself naturally to counting. Detecting a rearranged sequence in a gDNA sample reflects the presence of one cell, independent of that cell’s expression level.

However, this limited template availability is one of the primary disadvantages of gDNA. For a given rearrangement, each lymphocyte contributes only one or a small number of genomic templates, so sequences from rare clones can easily be lost during extraction or fall below the sampling threshold. Using approximately 6.6 pg of diploid DNA per cell, 100 ng of gDNA represents only about 15,000 total nucleated cells, while 1,000 ng represents about 150,000—and T or B cells of interest may account for only a fraction of those cells. PCR inclusivity is therefore constrained by how much gDNA can be loaded into the reaction. In addition, unrearranged V and J segments remain in the genome and can bind primers, generating background amplification that consumes reagent capacity and can obscure rarer clones.

iRepertoire’s RepSeq IQ™ service is designed to quantify the gDNA repertoire actually represented in a sample. It does not eliminate the biological limitation of finite template input, but it makes that limitation measurable. By combining an internal quantitative control with housekeeping gene amplification, RepSeq IQ converts sequencing reads into absolute receptor copy numbers and estimates the total nucleated cell equivalents represented in each library. Researchers can then determine the fraction of T or B cells present and quantify individual clonotypes on a cell-equivalent scale, providing cellular context alongside repertoire diversity. RepSeq IQ supports human TCR β and BCR IgH, κ, and λ chains (as two separate panels) and is compatible with gDNA from a range of sources, including PBMCs and FFPE tissue.

Starting with RNA for Immune Profiling

RNA offers a different set of advantages. Because each cell contains multiple transcript copies of an expressed T cell or B cell receptor, RNA provides substantially more starting template than gDNA. This reduces the risk that a rare clone will be lost and can provide a 5- to 10-fold sensitivity advantage over gDNA. RNA is also inherently cleaner from a background standpoint: only expressed V(D)J segments are present in the starting sample, leaving the unrearranged V- and J-gene sequences that can generate noise in a gDNA reaction out of the amplification reaction. Because RNA primarily represents expressed receptor transcripts, the resulting repertoire is enriched for functional rearrangements and contains fewer non-functional sequences that can complicate interpretation of gDNA data. For B-cell profiling, RNA also preserves constant-region information, allowing each expressed clone to be associated with its antibody isotype—information that is not captured by standard gDNA V(D)J sequencing. RNA does call for more careful handling than gDNA. Because it degrades quickly, RNA samples benefit from immediate stabilization at the point of collection to preserve sample integrity ahead of sequencing.

iRepertoire’s RepSeq+ service is designed to deliver immune insights from an RNA starting template. RepSeq+ performs quantitative, multi-chain amplification across all seven chains of the adaptive immune system in a single reaction, and its UMI-based error correction identifies and removes PCR and sequencing artifacts. The result is a dataset that supports more than 200 immune repertoire metrics, giving researchers the depth needed for biomarker discovery, clonal tracking, and repertoire diversity analysis. RepSeq+ also accepts PBMC, FFPE, whole blood, sorted cells, and bone marrow, so an RNA-based project can expand to additional sample types without switching platforms.

Choosing the Right Starting Material for Your Program

Choosing between gDNA and RNA depends on the biological question, research goals, and sample types available. gDNA is useful when expression-independent, cell-equivalent quantification is the priority, particularly when paired with RepSeq IQ. RNA provides greater sensitivity and a clearer view of the expressed, functional repertoire. For B-cell studies, RNA offers another critical advantage: it preserves antibody isotype information. Standard gDNA V(D)J sequencing identifies the rearranged variable region but does not reveal whether a clone is expressed as IgM, IgD, IgG, IgA, or IgE. That constant-region information can be as important as the variable sequence for distinguishing naïve, memory, class-switched, and antibody-secreting responses. RNA abundance should still be interpreted carefully in B-cell repertoires because antibody-secreting cells can produce disproportionately high numbers of immunoglobulin transcripts.

Whichever starting material fits your program today, iRepertoire’s platform is built to support it, and to grow with your research as your sample strategy evolves. Explore our sequencing technology, or learn more about RepSeq+ and RepSeq IQ, to find the right fit for your next immune repertoire sequencing project.