Tutorial: Tm Gradient Simulation

Tutorial: Tutorial: Tm Gradient Simulation

Learn how to use Tm gradient simulation to find optimal annealing temperatures.

Prerequisites

• PrimerLab v0.4.3+
• Primer JSON file

Step 1: Prepare Primers

Create primers.json:

[
  {
    "name": "BRCA1_Ex10",
    "forward": "ATGCGATCGATCGATCGATCG",
    "reverse": "GCTAGCTAGCTAGCTAGCTAG"
  },
  {
    "name": "TP53_Ex5",
    "forward": "GCGCGCGCGCGCGCGCGCGC",
    "reverse": "ATATATATATATATATATATAT"
  }
]

Step 2: Run Simulation

primerlab tm-gradient -p primers.json -o results/

Step 3: Interpret Results

Optimal Temperature

The optimal annealing temperature is where all primers have good binding efficiency while maintaining specificity.

Recommended Range

The recommended range shows temperatures where efficiency stays above 80%.

Per-Primer Analysis

Primer1_fwd: Tm=62.3°C, Optimal=57.3°C (Grade A)
              ↑           ↑              ↑
              |           |              +-- Overall grade
              |           +-- Best annealing temp (Tm - 5°C)
              +-- Calculated melting temperature

Grades

Grade	Score	Meaning
A	≥90	Excellent - wide temperature tolerance
B	≥80	Good - stable across range
C	≥70	Acceptable - moderate sensitivity
D	≥60	Poor - narrow window
F	<60	Fail - redesign recommended

Step 4: Use in PCR Protocol

Based on results:

1. Set gradient PCR from range_min to range_max
2. Use optimal as starting point
3. Validate with actual amplification

Advanced: Custom Temperature Range

For high-Tm primers (GC-rich):

primerlab tm-gradient -p primers.json --min-temp 55 --max-temp 75 --step 0.5

For low-Tm primers:

primerlab tm-gradient -p primers.json --min-temp 45 --max-temp 65 --step 0.5

Python API Example

from primerlab.api import simulate_tm_gradient_api

result = simulate_tm_gradient_api(
    primers=[{"name": "P1", "forward": "ATGCGATCGATCGATCGATCG"}],
    min_temp=50.0,
    max_temp=72.0
)

# Access efficiency curve for plotting
for primer in result["primers"]:
    print(f"{primer['primer_name']}: Tm={primer['calculated_tm']:.1f}°C")
    for dp in primer["data_points"][:5]:  # First 5 points
        print(f"  {dp['temperature']}°C: {dp['binding_efficiency']:.1f}%")

Next Steps

• Species Specificity Check
• Tm Gradient Feature Docs