Advanced qPCR Features Tutorial

Tutorial: Advanced qPCR Features Tutorial

Learn how to use PrimerLab’s advanced qPCR simulation features.

What You’ll Learn

1. TaqMan probe binding simulation
2. SYBR Green melt curve prediction
3. qPCR amplicon quality assessment

Prerequisites

• PrimerLab v0.5.0+
• Basic qPCR understanding

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1. TaqMan Probe Binding Simulation

Objective

Simulate probe-template binding to ensure optimal annealing.

Step 1: Prepare Your Probe

probe = "ATGCGATCGATCGATCGATCG"  # Your TaqMan probe sequence

Step 2: Run Simulation

from primerlab.api import simulate_probe_binding_api

result = simulate_probe_binding_api(
    probe_sequence=probe,
    min_temp=55.0,
    max_temp=72.0,
)

print(f"Probe Tm: {result['probe_tm']:.1f}°C")
print(f"Optimal annealing: {result['optimal_temp']:.1f}°C")
print(f"Grade: {result['grade']}")

Step 3: Analyze Position (Optional)

amplicon = "NNNNN" + probe + "NNNNN"  # Your amplicon

result = simulate_probe_binding_api(
    probe_sequence=probe,
    amplicon_sequence=amplicon,
)

if "position" in result:
    print(f"Probe start: {result['position']['probe_start']}")
    print(f"Position score: {result['position']['position_score']}")

Expected Output

Probe Tm: 68.5°C
Optimal annealing: 60.0°C
Grade: A

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2. SYBR Green Melt Curve Prediction

Objective

Predict melt curve to check for non-specific products.

Step 1: Prepare Amplicon

amplicon = "ATGCGATCGATCGATCGATCG" * 5  # 100bp amplicon

Step 2: Predict Melt Curve

from primerlab.core.qpcr import predict_melt_curve

result = predict_melt_curve(amplicon)

print(f"Predicted Tm: {result.predicted_tm:.1f}°C")
print(f"Single peak: {result.is_single_peak}")
print(f"Grade: {result.grade}")

Step 3: Generate Report

from primerlab.core.qpcr import generate_melt_markdown

md_report = generate_melt_markdown(result)
print(md_report)

Expected Output

Predicted Tm: 81.5°C
Single peak: True
Grade: A

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3. qPCR Amplicon Quality Check

Objective

Validate amplicon for qPCR suitability.

Step 1: Check Amplicon

from primerlab.core.qpcr import validate_qpcr_amplicon

amplicon = "ATGC" * 25  # 100bp

result = validate_qpcr_amplicon(amplicon)

print(f"Length OK: {result.length_ok}")
print(f"GC OK: {result.gc_ok}")
print(f"Quality: {result.quality_score:.1f}")

Step 2: Check Warnings

if result.warnings:
    print("Warnings:")
    for w in result.warnings:
        print(f"  - {w}")

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Complete Workflow

TaqMan qPCR Design Validation

from primerlab.api import simulate_probe_binding_api
from primerlab.core.qpcr import (
    validate_qpcr_amplicon,
    score_qpcr_efficiency,
)

# Your sequences
fwd_primer = "ATGCGATCGATCGATCG"
rev_primer = "CGATCGATCGATCGATC"
probe = "GATCGATCGATCGATCGATC"
amplicon = "..."  # Full amplicon sequence

# 1. Check amplicon quality
amp_result = validate_qpcr_amplicon(amplicon)
print(f"Amplicon Grade: {amp_result.grade}")

# 2. Simulate probe binding
probe_result = simulate_probe_binding_api(probe, amplicon)
print(f"Probe Grade: {probe_result['grade']}")

# 3. Estimate efficiency
efficiency = score_qpcr_efficiency(
    amplicon_length=len(amplicon),
    primer_tm_diff=0.5,  # |Fwd Tm - Rev Tm|
    probe_tm_diff=probe_result['probe_tm'] - 60.0,
)
print(f"Efficiency: {efficiency:.1f}%")

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Tips

1. Probe Tm: Should be 8-10°C higher than primers
2. Amplicon Length: 70-150 bp optimal for qPCR
3. GC Content: 40-60% for reliable amplification
4. 5’ G Rule: Avoid G at probe 5’ end

Troubleshooting

Issue	Solution
Low probe score	Check Tm, length, 5’ base
Multiple melt peaks	Redesign primers
Low efficiency	Shorten amplicon, balance Tms

See Also

• Probe Binding Feature
• Melt Curve Feature