Confirming Copy Number, Zygosity, and Junction Integrity for T-DNA Lines

For plant breeders and gene banks, three checks determine whether a line deserves another season: copy number, zygosity, and junction integrity. This practical guide shows what to measure, how to measure it, and how to decide—confidently—what moves forward.

The Check That Saves a Season

Every breeding program has seen it: a promising T0 or T1 looks great in the greenhouse, only to unravel in field trials. Traits drift, segregation does not match expectations, or regulators flag vector backbone risk. The root cause is often the same—advancement without robust confirmation of the insertion.

Before you put acres, budget, or reputation behind a line, you need three answers:

• How many T-DNA copies were inserted?
• What is the zygosity of each insertion?
• Are the left and right junctions clean and free of vector backbone?

These questions are the backbone of responsible t-dna insertion site analysis. Getting them right keeps lines on a predictable path and protects downstream work. Throughout this article, we will refer to t-dna insertion site mapping and confirmation methods that are proven in real breeding pipelines.

What can go wrong if you skip confirmation

• Unstable trait expression: Multi-copy insertions or partial repeats complicate expression and can trigger silencing.
• Breeding delays: Miscalled zygosity wastes generations as you chase fixation that never arrives.
• Regulatory roadblocks: Junctions that include vector backbone derail release or distribution plans.
• Lost seasons: Field plots are too expensive to allocate to lines that have not cleared basic checks.

Why These Three Metrics Matter

Each metric connects directly to a breeding or bank management decision.

• Copy number → Stability and predictability

  Single-copy insertions are generally easier to track and more predictable in expression. Multi-copy or tandem arrays can behave variably. Knowing copy number early informs whether to advance, split, or remap.

• Zygosity → Fixation speed

  A homozygous line fixes the trait and simplifies seed increase. Heterozygous or segregating lines require careful selection and larger population sizes. Calling zygosity correctly helps you size cohorts and plan the next generation efficiently.

• Junction integrity → Safety and readiness

  Clean left/right borders without vector backbone are essential for many distribution contexts. Junction mapping also anchors the t-dna insertion site in the reference genome, helping you monitor linked traits and avoid confounders.

Go/No-Go rules of thumb

Use these simple patterns to triage lines:

• Advance with confidence: Single-copy, backbone-free, homozygous (or heterozygous with clean segregation on track).
• Advance with monitoring: Two copies in different loci, clean junctions, segregation as expected; plan extra checks.
• Remediate or retire: Multiple tandem copies, truncated borders, or vector backbone detected across one or more junctions.

The principle is straightforward: align investment with genetic clarity. Cohorts with clean, single-copy insertions and verified zygosity deserve more plots; ambiguous cohorts deserve more lab time before more field time.

How to Confirm: Fast, Reliable Workflows

There is no single assay that answers everything. The art is combining complementary tools to cross-check calls while keeping cost and turnaround practical. Below is a pragmatic menu that we and many clients use to design confirmation packages.

Copy number confirmation

qPCR:

• Use when: You need a quick, cost-effective screen on many lines.
• How it works: Compares amplification of the transgene to a single-copy endogenous control.
• Pros: Fast, scalable, compatible with modest DNA quality.
• Watch-outs: Requires carefully validated reference genes and PCR efficiency calibration; less robust for complex arrays.

ddPCR (digital droplet PCR):

• Use when: You need higher precision on copy number, especially around 1–2 copies.
• Pros: Absolute quantification without standard curves; narrower confidence intervals.
• Watch-outs: Slightly higher per-sample cost; still assumes intact target regions and suitable reference loci.

Detection and quantification of 1SST-6G-FFT construct (FAM in blue) using ddPCR. (Giraldo P.A. et al., 2019, Frontiers in Plant Science)

Low-coverage WGS ("WGS-light"):

• Use when: You suspect complex insertions or want copy-number and junction context in one run.
• Pros: Genome-wide signal; can support both CNV estimation and t-dna insertion site analysis.
• Watch-outs: Requires good library quality and bioinformatics; coverage must be adequate for reliable CNV inference.

Zygosity determination

Segregation analysis (T1/T2):

• Use when: You have seed and time for Mendelian ratios to reveal zygosity.
• Pros: Simple, cost-effective, biologically grounded.
• Watch-outs: Requires clear selectable markers or robust genotyping calls; chimerism in founders complicates ratios.

Dosage-sensitive assays (qPCR/ddPCR):

• Use when: You need early calls on T0/T1 without full segregation data.
• Pros: Quantitative dosage differences can indicate homozygous vs. heterozygous states.
• Watch-outs: Must control for copy number first; two copies in trans complicate dosage reads.

Marker panels (PCR or amplicon sequencing):

• Use when: You have mapped the t-dna insertion site and can track flanking markers.
• Pros: Direct, locus-specific tracking; scalable for cohorts.
• Watch-outs: Repeats or structural variants near the locus may reduce marker informativeness.

Junction integrity and backbone screening

TES-NGS (Target Enrichment Sequencing for borders):

• Use when: You want high-throughput capture of left/right borders at scale.
• Pros: Efficient for dozens to thousands of lines; multiplexed; detects truncated borders and backbone presence.
• Watch-outs: Probe design matters; repetitive flanks may need alternate strategies.

Paired-end mapping of T-DNA. (Inagaki et al., 2015, PLOS ONE)

TAIL-PCR / Border-PCR:

• Use when: You need a quick, line-by-line border check with basic lab infrastructure.
• Pros: Low cost per line; useful for initial mapping.
• Watch-outs: Can miss complex or long insertions; lower sensitivity to small backbone fragments.

WGS-light (again):

• Use when: TES or PCR results are ambiguous; you suspect complex concatenations or partial vector sequences.
• Pros: Provides broader context of the insertion and any rearrangements.
• Watch-outs: Bioinformatics must filter repeats and transposon-rich regions carefully.

Picking the right combination

For most cohorts, an efficient workflow is:

Overview of Targeted Genomic Sequencing. (Lepage et al., 2013, PLOS ONE)

1. Copy number screen by qPCR/ddPCR → triage lines.
2. Junction mapping by TES-NGS or TAIL-PCR → confirm left/right borders and backbone status.
3. Zygosity by segregation or dosage assays → plan fixation and seed scale-up.
4. Escalate tricky cases to WGS-light for resolution.

This balances certainty with cost. The result is a crisp report that rolls up to Go/No-Go calls you can defend.

Reading results & edge cases

• Single-copy insertion: qPCR/ddPCR near 1×; TES-NGS shows clean L/R junctions; no backbone. Advance.
• Two copies in trans: Dosage ~2×; distinct junction pairs; segregation suggests independent loci. Advance with monitoring.
• Tandem array: Dosage >1× with shared flanks; border reads collapse; possible internal repeats. Consider remapping; watch for silencing.
• Backbone detected: Any vector backbone at a junction is a red flag. Remediate or retire line.
• Mosaic founders: Mixed calls across tissues or siblings; inconsistent segregation. Re-derive from clean progeny; avoid premature scale-up.

SALK_059379 T-DNA insertions are T-strand and backbone conglomerations. (Jupe et al., 2019, PLOS Genetics)

Common pitfalls & quick fixes

• DNA quality: Degraded DNA inflates variability. Set clear A260/280 and DIN/RIN targets; repeat extraction if needed.
• Repeats near borders: Primers or probes fall inside repeats. Shift targets outward; consider capture-based methods.
• Barcode cross-talk in multiplexing: Sample misassignment blurs calls. Use robust index sets with adequate edit distance; include spike-in controls.
• Over-reliance on a single method: Every assay has blind spots. Design orthogonal confirmation for high-stakes decisions.

From Mixed T1s to a Clean Line: A Mini Case

A public gene bank submitted a batch of T1 lines derived from a single transformation event. Early greenhouse observations looked good, but staff reported erratic trait strength and inconsistent segregation. The objective was to select one or more lines suitable for seed increase and distribution.

Step 1 — Copy number screen (ddPCR):

• Results indicated a mix of single-copy and apparent multi-copy individuals. Two siblings suggested ~2× dosage.

Step 2 — Junction mapping (TES-NGS):

• Most single-copy candidates showed clean left/right borders with precise genomic anchors for the t-dna insertion site.
• Two individuals flagged low-level vector backbone at the right junction.

Step 3 — Zygosity calls (dosage + segregation):

• For three clean candidates, dosage hinted homozygosity. Segregation counts in the next generation confirmed fixation in one line and near-fixation in another.

Step 4 — Resolution of edge cases (WGS-light):

• One line with ambiguous border reads resolved to a short tandem duplication within the insert, explaining earlier variability.

Outcome:

• The gene bank advanced a single-copy, backbone-free, homozygous line to seed increase. Two additional lines were archived as backups with clear annotations. The program reduced downstream field plots by 40% and cut re-testing cycles in half.

This case illustrates the power of a tiered workflow. Start broad and fast, then focus resources on the winners. It is the essence of efficient t-dna insertion site analysis for breeding operations.

Time & budget planning

Turnaround and cost depend on cohort size, DNA quality, and the depth of analysis:

• Screening tier (qPCR or ddPCR):
  • Use: First-pass copy number across dozens to hundreds of lines.
  • Drivers: Plate count, controls per run, replicate strategy.
• Mapping tier (TES-NGS or TAIL-PCR):
  • Use: Junction integrity, backbone screening, locus anchoring.
  • Drivers: Probe set breadth, multiplex level, read depth.
• Resolution tier (WGS-light):
  • Use: Complex or contradictory cases requiring structural clarity.
  • Drivers: Coverage target, library type, bioinformatics complexity.

For gene banks and breeding programs, batching is your friend. Group lines by construct and developmental stage. Share controls across plates. Align sampling schedules with sequencing runs to avoid idle capacity. These steps reduce per-line cost without compromising certainty.

Ready to Confirm? Your Next Steps

If you want decisions you can stand behind, treat confirmation as a small, focused experiment with a big payoff. Here is a short preparation checklist to ensure clean execution and clear results:

Sample & data checklist

• Tissue and DNA: Specify tissue type and growth stage. Target DNA yield/quality thresholds (e.g., >1 µg, A260/280 ~1.8–2.0, DIN ≥7 if available).
• Construct map: Provide the final vector map, including T-DNA borders and any selectable markers.
• Expected borders: Note expected left/right border sequences and any known restriction sites.
• Line IDs & plate map: Supply stable identifiers and a plate layout. Reserve wells for positive and negative controls.
• Reporting format: Choose your preferred format for calls and evidence (summary table + IGV snapshots + assay QC).
• Decision criteria: Define what qualifies as "advance," "monitor," or "retire" in your context.

Choose a confirmation bundle

• Standard: ddPCR copy number + TES-NGS borders + segregation-ready marker panel.
• Express: qPCR copy number + TAIL-PCR borders for early triage.
• Resolution: WGS-light for complex or high-value candidates.

Where to deepen next

• Compare methods and pick the best fit with our method selection guide: Choosing the Right Method: TAIL-PCR, TES-NGS, or WGS for T-DNA Insertion Site Mapping
• Align your pass/fail thresholds using the quality criteria in our genotyping guide: Quality Metrics that Matter in T-DNA Insertion Genotyping
• For experimental design nuances and research-grade detail, explore our research deep dive: Bioinformatics Pipeline for T-DNA Insertion Position Analysis: From Reads to Genotypes

Call to action

Ready to move your best candidates forward with confidence? Share your cohort size, timeline, and construct map. We will recommend a right-sized confirmation package, provide a sample report, and schedule the first batch. The goal is simple: fewer surprises in the field, more lines you can trust.

References

1. Edwards, B., Hornstein, E.D., Wilson, N.J. et al. High-throughput detection of T-DNA insertion sites for multiple transgenes in complex genomes. BMC Genomics 23, 685 (2022).
2. Inagaki, S., Henry, I.M., Lieberman, M.C., Comai, L. High-Throughput Analysis of T-DNA Location and Structure Using Sequence Capture. PLOS ONE 10(10), e0139672 (2015).
3. Giraldo, P.A., Cogan, N.O.I., Spangenberg, G.C., Smith, K.F., Shinozuka, H. Development and Application of Droplet Digital PCR Tools for the Detection of Transgenes in Pastures and Pasture-Based Products. Frontiers in Plant Science 9, 1923 (2019).
4. Jupe, F., Rivkin, A.C., Michael, T.P. et al. The complex architecture and epigenomic impact of plant T-DNA insertions. PLOS Genetics 15(1), e1007819 (2019).
5. Lepage, É., Zampini, É., Boyle, B., Brisson, N. Time- and Cost-Efficient Identification of T-DNA Insertion Sites through Targeted Genomic Sequencing. PLOS ONE 8(8), e70912 (2013).
6. Collier, R., Dasgupta, K., Xing, Y.P. et al. Accurate measurement of transgene copy number in crop plants using droplet digital PCR. The Plant Journal 90(5), 1014–1025 (2017).
7. Shilo, S., Tripathi, P., Melamed-Bessudo, C., Tzfadia, O., Muth, T.R., Levy, A.A. T-DNA-genome junctions form early after infection and are influenced by the chromatin state of the host genome. PLOS Genetics 13(7), e1006875 (2017).