Sample Submission Guidelines
Turn CAR/vector integration questions into sequencing-ready evidence
In vivo CAR-T and in vivo immune-cell engineering studies often raise questions that a basic sequencing file cannot answer on its own. Your team may need to know whether CAR/vector-related sequences are integrated, where candidate integration sites are located, whether certain sites are enriched, and how the integration profile changes across samples.
Our in vivo CAR-T integration site analysis solution helps you move from raw sequencing output to a clearer integration profile. The goal is not only to detect sites, but to organize them into genomic coordinates, annotation tables, clone-abundance summaries, QC notes, and review-ready figures.
What this solution helps you answer
- Are CAR/vector-related sequences integrated into the host genome?
- Where are candidate integration sites located?
- Which nearby genes or genomic features are associated with those sites?
- Are some integration sites supported by higher read or fragment counts?
- Do integration profiles differ across tissues, timepoints, or groups?
- What QC and bioinformatics outputs are needed for internal project review?
For many projects, the most useful result is not a site list alone. It is a structured integration profile that links sequence evidence with genomic context.
Why an integration-site list is not enough
A basic integration-site table may show genomic coordinates, but that does not always tell your team how to review the result. A useful report often needs nearby gene annotation, chromosomal distribution, genomic feature categories, clone abundance, sample-level QC, and cross-sample comparison.
We help you plan those outputs before sequencing begins. This makes the final results easier to review and reduces the risk of generating data that are technically valid but difficult to interpret.
Our service capabilities for in vivo CAR-T integration studies
We support in vivo CAR-T integration-site projects as integrated sequencing and bioinformatics studies, not as isolated data-generation tasks. Before the project starts, our team can review your CAR/vector design, sample source, genomic DNA status, expected integration biology, and reporting goals.
That early review matters. The best strategy for a purified engineered-cell sample may not be the same as the strategy for tissue-derived cells, sorted immune cells, or low-input genomic DNA from an in vivo study.
Vector and CAR construct contexts we can support
- In vivo CAR engineering research
- CAR-T or engineered immune-cell research
- Lentiviral or retroviral vector integration profiling
- Vector-host junction analysis
- CAR/vector construct-related sequencing support
- Multi-sample integration profile comparison
Integration-site sequencing and annotation modules
- CAR/vector sequence information review
- Genomic DNA QC and feasibility review
- Integration junction enrichment or targeted library strategy
- NGS-based integration-site detection
- Candidate site calling and genomic coordinate assignment
- Nearby gene and genomic feature annotation
- Clone abundance or site-support summary where supported
- Cross-sample comparison
- Report-ready visualization and bioinformatics notes
Project execution support from sample review to report delivery
A strong project starts with the right information. Before sequencing, we help you review CAR/vector sequence or LTR information, sample type and collection format, genomic DNA amount and concentration, sample grouping and timepoints, expected integration signal, control sample availability, desired annotation categories, and required output tables and figures.
This helps your team align the experimental question with the assay design and bioinformatics plan.
Choose the right integration-site detection strategy
There is no single integration-site method that fits every in vivo CAR-T project. Method choice depends on vector biology, sample quality, DNA input, target sequence information, and whether your team needs sensitivity, genomic context, clone abundance, or structural detail.
| Method | Best-fit Question | Input Need | Strength | Limitation | Suggested Use |
|---|---|---|---|---|---|
| LAM-PCR | Where are vector-host junctions? | Known LTR/vector sequence; genomic DNA | Enriches integration junctions from known vector ends | May introduce amplification bias | Known integrating vectors with defined junction design |
| nrLAM-PCR | Can junction detection be improved with reduced restriction bias? | Known vector sequence; genomic DNA | Useful for recovering junctions with less dependence on restriction sites | Still amplification-dependent | Integration-site discovery when junction enrichment is needed |
| Targeted Capture NGS | Can known CAR/vector regions be captured and mapped? | CAR/vector sequence; genomic DNA | Flexible target design and useful sequence support | Depends on probe or target design | CAR/vector confirmation plus junction evidence |
| Whole Genome Sequencing | Is broader genomic context needed? | Higher-quality genomic DNA | Genome-wide context and broader variant-level information | Lower sensitivity for rare integration events | Selected samples with adequate DNA and broader genomic questions |
| Long-read Sequencing | Is long-range structure or complex insertion context important? | High-quality DNA | Can support longer-range structural context | Higher input and DNA quality requirements | Complex insertion or structure-related questions |
| Hybrid Strategy | Do we need both sensitivity and genomic context? | Case-specific | Combines targeted and broader evidence | More complex design and interpretation | Multi-readout integration projects |
For related CD Genomics services, see our Lentiviral/Retroviral Integration Site Sequencing, Integration Site Analysis for Transgene Integration, Targeted Region Sequencing, and Whole Genome Sequencing pages.
Start with the vector biology and the CAR construct information. If your main goal is vector-host junction detection, a junction-enrichment strategy may be appropriate. If your team also needs to verify CAR/vector regions, targeted sequencing can be added. If the question involves broader genomic context, whole-genome or long-read sequencing may be considered for selected samples.
Clone abundance analysis should be planned only when the sample design and sequencing strategy support meaningful comparison. Annotation categories should also be chosen before sequencing begins, so the final output can include nearby genes, genomic features, chromosomal distribution, and sample-level summaries.
Sample-to-report workflow with QC checkpoints
Our workflow connects the technical assay with the service process. Once samples enter the project, we keep checking whether each step still supports the original research question.
Step 1: Project intake and vector information review
We start by reviewing CAR construct or vector sequence, LTR/vector-end information where available, vector system and expected integration biology, sample type and source, tissue, cell, or timepoint groups, genomic DNA amount and quality, and desired outputs and comparison groups.
This step helps us decide whether the project should focus on junction enrichment, targeted sequencing, broader genomic analysis, or a hybrid design.
Step 2: Sample receipt, identity check, and gDNA QC
After sample receipt, we check sample identity, labeling, and available QC information. For extracted genomic DNA, we review amount, concentration, purity, degradation, and compatibility with the selected strategy.
If samples are submitted as PBMC, sorted immune cells, tissue-derived cells, cell pellets, or low-input material, a feasibility review may be needed before the final assay plan is confirmed.
Step 3: Integration junction enrichment or library strategy
The technical workflow depends on the chosen method. For junction-enrichment strategies, vector-host junctions are selectively enriched from genomic DNA. For targeted capture approaches, CAR/vector-related regions can be captured and sequenced. For whole-genome or long-read approaches, library preparation is designed around broader genomic context or structural information.
The goal is to generate data that can support integration-site calling, not just general sequencing output.
Step 4: Sequencing and junction-read processing
Sequencing data are processed to identify reads or fragments that support vector-host junctions. This may include read filtering, alignment, trimming of vector-derived sequences, mapping to a reference genome, duplicate review, and removal of likely artifacts depending on the method.
QC checkpoints can include read yield, mapping quality, junction-read support, sample-level consistency, and the number of candidate integration sites detected.
Step 5: Integration-site calling, annotation, and report delivery
Candidate integration sites are organized into a structured output package. Depending on the project, the report may include genomic coordinates, supporting read or fragment counts, nearby gene annotation, genomic feature distribution, chromosomal distribution, clone-abundance summaries, and cross-sample comparison.
The final deliverable is built to help your team review integration profiles and decide whether additional experiments are needed.
Sample requirements for CAR/vector integration-site projects
Sample needs depend on method, vector type, expected integration level, and DNA quality. The table below gives practical starting points. Exact requirements should be confirmed during project review.
| Sample Type | Recommended Input | Concentration | Container | Shipping | QC Checkpoints | Notes |
|---|---|---|---|---|---|---|
| Extracted genomic DNA | ≥100 ng | ≥10 ng/μl | DNase-free tube | Ice packs or dry ice | OD260/OD280 1.8-2.0, purified, not degraded | Provide CAR/vector sequence or LTR information |
| PBMC / sorted immune cells | Project-specific; gDNA extraction required | TBD after extraction | Cryotube or approved tube | Dry ice | Cell identity, viable/frozen status, DNA yield | Provide target cell type and enrichment method |
| Tissue-derived cells | Project-specific; feasibility review recommended | TBD after extraction | Cryotube | Dry ice | Tissue origin, cell fraction, DNA quality | Useful for in vivo distribution-related samples |
| Cell pellets / cultured engineered cells | Project-specific; sufficient cells for gDNA extraction | TBD after extraction | Cryotube or approved tube | Dry ice | Cell count, sample identity, extraction yield | Useful for engineered immune-cell studies |
| Low-input genomic DNA | Feasibility review required | Case-by-case | Low-bind tube | Ice packs or dry ice | Concentration, degradation, expected integration level | May require adapted library or amplification strategy |
Before submission, it is helpful to share the CAR/vector map, LTR or vector-end sequence, sample groups, target cell type, expected integration status, and any existing DNA QC data.
Bioinformatics analysis and deliverables
Bioinformatics is central to this solution. The key question is not only whether integration sites can be detected, but whether the results can be reviewed, filtered, annotated, and compared in a useful way.
Minimum deliverables
- Raw sequencing data and clean data where applicable
- Sample-level sequencing QC summary
- Junction-read or vector-host read support summary
- Candidate integration-site table
- Genomic coordinate annotation
- Nearby gene annotation
- Genomic feature distribution
- Chromosomal distribution visualization
- Clone abundance or site-support summary where supported
- Analysis report notes
For custom analysis support, see our Bioinformatics services.
Optional add-ons
- Cross-sample integration profile comparison
- Multi-tissue or multi-timepoint integration profile analysis
- Dominant clone or enriched site visualization
- Gene-category proximity annotation where appropriate for research review
- Repeat region, TSS, CpG island, or promoter-proximal annotation
- Long-read structural context analysis
- Custom figure-ready visualization
- Pipeline parameter record
A well-planned project can provide both data files and summary visuals. These may include integration-site tables, annotation files, chromosomal plots, feature distribution charts, clone-abundance summaries, and report notes.
For expression-level follow-up, our RNA Sequencing service may be considered. For vector-specific integration questions, our AAV Integration Site Analysis page may also be useful as a related reference.
Application scenarios for in vivo CAR-T and vector integration research
These study scenarios show how integration-site analysis can support CAR/vector research when genomic context, clonal profile, or cross-sample comparison is needed.
In vivo CAR engineering studies
In vivo CAR engineering studies may require evidence that CAR/vector-related sequences are integrated and can be reviewed in genomic context. Integration-site analysis can help your team examine candidate insertion sites, annotation patterns, and sample-level differences.
Lentiviral or retroviral CAR vector integration profiling
Lentiviral and retroviral vectors are common contexts for integration-site analysis. In these studies, vector-host junction detection, clone abundance, and genomic feature annotation may be important outputs.
Multi-tissue or longitudinal integration-profile comparison
For in vivo studies with multiple tissues or timepoints, integration profiles can be compared across samples when the study design supports it. This may help your team review whether candidate integration patterns differ across tissue sources, collection times, or experimental groups.
Engineered immune-cell research and construct confirmation
Some studies may need both construct-related sequence support and integration-site mapping. In those cases, targeted sequencing, vector sequence review, and integration-site analysis can be combined into a broader evidence package.
References
- Tagmentation-based analysis reveals the clonal behavior of CAR-T cells in association with lentivector integration sites
- Joint profiling of chromatin accessibility and CAR-T integration site analysis at population and single-cell levels
- IS-Seq: a bioinformatics pipeline for integration sites analysis with comprehensive abundance quantification methods
- VISA - Vector Integration Site Analysis server: a web-based server to rapidly identify retroviral integration sites from next-generation sequencing
- Ub-ISAP: a streamlined UNIX pipeline for mining unique viral vector integration sites from next generation sequencing data
Demo results: what your integration profile may include
Demo results help your team understand how integration-site data can be organized. The examples below show common result formats that may be included when they match the study design.
Demo 1: Chromosomal distribution of integration sites
A chromosomal distribution view can show how candidate integration sites are distributed across chromosomes and samples. This can help your team review whether sites appear broadly distributed or concentrated in selected regions. A typical output may include chromosome ID, genomic coordinate, sample ID, supporting read or fragment count, and visualization by chromosome.
Demo 2: Nearby gene and genomic feature annotation
A gene annotation table can show which genes or genomic features are near candidate integration sites. Depending on the selected annotation categories, the report may include gene body, intronic, intergenic, promoter-proximal, repeat-associated, transcription-unit, or other feature labels. This output helps turn coordinates into a more useful genomic context.
Demo 3: Clone abundance and sample comparison
When supported by the assay design, clone abundance or site-support summaries can help compare integration profiles across samples. For example, a report may show candidate clonal patterns across tissues, timepoints, or treatment groups. A typical visualization may include a heatmap, stacked bar chart, or ranked site-support table.
FAQ: planning an in vivo CAR-T integration-site project
1. Do I need integration-site analysis for every in vivo CAR-T study?
Not always. Integration-site analysis is most useful when the vector system can integrate, when insertion-site location matters, or when your team needs clonal profile information. If the main question is vector presence, expression, or biodistribution, another readout may be more appropriate or may need to be combined with integration-site analysis.
2. What sample type is best for CAR/vector integration-site detection?
Extracted genomic DNA is usually the most direct input. PBMC, sorted immune cells, tissue-derived cells, cell pellets, or cultured engineered cells may also be suitable if enough genomic DNA of acceptable quality can be obtained.
3. Can low-input DNA be used?
Low-input DNA may be possible, but it requires feasibility review. The expected integration level, DNA quality, vector sequence information, and selected method all affect whether the project can proceed.
4. What vector or CAR construct information should I provide?
Useful information includes the CAR/vector map, LTR or vector-end sequence, transgene region, expected integration mechanism, sample groups, and any known target sequences for assay design.
5. What is the difference between vector sequence confirmation and integration-site mapping?
Vector sequence confirmation checks whether expected CAR/vector regions are supported by sequencing. Integration-site mapping looks for vector-host junctions and assigns candidate insertion sites to genomic coordinates. Some projects need both.
6. Can clone abundance be estimated from integration-site data?
Clone abundance or site-support summaries may be included when the assay design and sequencing data support it. The result should be interpreted as a research profile, not as a standalone conclusion.
7. Can integration profiles be compared across tissues or timepoints?
Yes, if the study design includes comparable samples and sufficient data quality. Cross-sample comparison may show differences in candidate integration-site patterns, site support, or clonal profile across tissues, timepoints, or groups.
8. What bioinformatics outputs can be included?
Outputs may include candidate integration-site tables, genomic coordinates, nearby gene annotation, genomic feature distribution, chromosomal distribution plots, clone-abundance summaries, sample-level QC summaries, and report notes.
9. Can this solution support lentiviral and retroviral vector studies?
Yes. Lentiviral and retroviral vector studies are common contexts for integration-site analysis because vector-host junction detection and clonal profile review may be important for research interpretation.
10. Can CD Genomics help decide which method is appropriate?
Yes. We can review your vector type, CAR construct, sample source, DNA amount, expected integration profile, and reporting goals to help select a fit-for-purpose strategy.
Case Study: CAR-T clonal behavior revealed by integration-site analysis
Open-access literature case
Journal: Molecular Therapy - Oncolytics
Published: 2023
DOI: 10.1016/j.omto.2023.05.004
Background
This open-access study focused on integration-site analysis in lentivector-engineered CAR-T cells. The authors developed DIStinct-seq, a tagmentation-based method for detecting integration sites and analyzing clonal behavior from sequencing data.
The study is relevant to this solution because it shows how integration-site analysis can provide more than a list of insertion coordinates. When the data are connected with clone size, diversity measures, genomic annotation, and timepoint comparison, they can help researchers review how CAR-T cell populations change after infusion in an in vivo model.
Methods
The authors used a bead-linked Tn5 transposome to prepare libraries for integration-site analysis. They first validated DIStinct-seq using clones with known integration sites, then applied the method to ex vivo CAR-T products and to CAR-T cells collected from mice after infusion.
The bioinformatics workflow focused on reads containing long terminal repeat sequences, trimming of vector-derived sequence portions, mapping to a human/vector fusion reference genome, artifact filtering, and identification of vector-human genome junction sites. The study also used clonal abundance measures based on raw fragment counts and deduplicated fragment counts.
Results
The study detected a total of 17,695 integration sites from three CAR-T products using 500 ng DNA per sample. For in vivo samples, the authors analyzed CAR-T cells collected at day 30 and day 60 after infusion. They detected 4,055-4,473 integration sites for CAR-T products, 2,650-6,233 integration sites at day 30, and 1,034-4,895 integration sites at day 60.
Figure 4 shows how CAR-T cells expanded polyclonally with decreased diversity in vivo, and how persistence was associated with integration into genomic safe harbors. The figure includes the mouse study design, vector-specific qPCR trend, Shannon entropy index, top-clone proportion, and genomic safe harbor distribution across clone groups.
The authors observed that CAR-T products had greater clonal diversity than in vivo samples. The in vivo samples showed decreased diversity from day 30 to day 60. They also reported that the proportion of clones in the top 1 percentile by size was lower in the CAR-T product and higher in in vivo samples at day 30 and day 60.
Figure 4 from the open-access study shows how integration-site analysis can connect clonal behavior, timepoint comparison, and genomic-context review in CAR-T research.
Conclusion
This study supports a key point for in vivo CAR-T integration-site projects: integration-site data become more useful when they are connected to clonal behavior, genomic annotation, and cross-sample comparison.
For a service project, the practical lesson is clear. A useful integration-site analysis plan should define the sample groups, integration-junction strategy, clone-abundance approach, annotation categories, and reporting outputs before sequencing begins.
Reference
Related customer publications
The publications below are relevant to CAR-T, immune-cell engineering, in vivo genetic medicine, or immune-response research contexts. They are listed as related customer publications, not as full case studies.
| Publication | Journal / Year | Related Service Tag | Why It Is Relevant |
|---|---|---|---|
| IL-4 drives exhaustion of CD8+ CART cells | Nature Communications, 2024 | Multi-Omics Services | CAR-T research context; useful customer publication support for immune-cell functional profiling |
| In vivo base editing rescues ADPKD in a humanized mouse model | Nature Communications, 2025 | RNA-seq / RNA-seq Library Construction and Sequencing | Relevant to in vivo genetic medicine and RNA-seq-supported analysis |
| The HLA class I immunopeptidomes of AAV capsid proteins | Frontiers in Immunology, 2023 | HLA Typing | Relevant to vector immunogenicity and immune-response research context |
| Unlocking novel T cell-based immunotherapy for hepatocellular carcinoma through neoantigen-driven T cell receptor isolation | Gut, 2025 | Bulk TCR Sequencing | Relevant to T-cell immunotherapy and immune repertoire research |
See more articles published by our clients.
