Design qPCR primers and TaqMan/molecular beacon probes using primer3-py. Configure probe Tm, primer-probe spacing, and hydrolysis probe constraints for real-time PCR assays. Use when designing qPCR primers and probes.
Scanned 9/4/2026
Install to Claude Code
npx -y skills add gabrielmoreira/agent-skills-mirror --skill qpcr-primers --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Qpcr Primers?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/gabrielmoreira-qpcr-primers)More formats (shields.io, HTML) on the badges page.
---
name: bio-primer-design-qpcr-primers
description: Design qPCR primers and TaqMan/molecular beacon probes using primer3-py. Configure probe Tm, primer-probe spacing, and hydrolysis probe constraints for real-time PCR assays. Use when designing qPCR primers and probes.
tool_type: python
primary_tool: primer3-py
---
## Version Compatibility
Reference examples tested with: BioPython 1.83+, pandas 2.2+, primer3-py 2.0+
Before using code patterns, verify installed versions match. If versions differ:
- Python: `pip show <package>` then `help(module.function)` to check signatures
If code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.
# qPCR Primer and Probe Design
Design primers and internal probes for quantitative PCR using primer3-py.
**"Design qPCR primers with probe"** → Generate primer pairs plus internal TaqMan/molecular beacon probes with constrained Tm and spacing.
- Python: `primer3.design_primers(seq_args, global_args)` with `PRIMER_PICK_INTERNAL_OLIGO=1` (primer3-py)
## Required Imports
```python
import primer3
from Bio import SeqIO
```
## Design Primers with TaqMan Probe
```python
sequence = 'ATGCGTACGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCG' * 3
result = primer3.design_primers(
seq_args={'SEQUENCE_TEMPLATE': sequence},
global_args={
'PRIMER_PICK_LEFT_PRIMER': 1,
'PRIMER_PICK_RIGHT_PRIMER': 1,
'PRIMER_PICK_INTERNAL_OLIGO': 1, # Design internal probe
'PRIMER_PRODUCT_SIZE_RANGE': [[70, 150]], # Short amplicons for qPCR
'PRIMER_OPT_TM': 60.0,
'PRIMER_MIN_TM': 58.0,
'PRIMER_MAX_TM': 62.0,
'PRIMER_INTERNAL_OPT_TM': 70.0, # Probe Tm ~10C higher
'PRIMER_INTERNAL_MIN_TM': 68.0,
'PRIMER_INTERNAL_MAX_TM': 72.0,
'PRIMER_INTERNAL_MIN_SIZE': 18,
'PRIMER_INTERNAL_OPT_SIZE': 25,
'PRIMER_INTERNAL_MAX_SIZE': 30,
}
)
```
## Extract Probe Results
```python
num_returned = result['PRIMER_PAIR_NUM_RETURNED']
print(f'Found {num_returned} primer/probe sets')
for i in range(num_returned):
left = result[f'PRIMER_LEFT_{i}_SEQUENCE']
right = result[f'PRIMER_RIGHT_{i}_SEQUENCE']
probe = result[f'PRIMER_INTERNAL_{i}_SEQUENCE']
probe_tm = result[f'PRIMER_INTERNAL_{i}_TM']
left_tm = result[f'PRIMER_LEFT_{i}_TM']
right_tm = result[f'PRIMER_RIGHT_{i}_TM']
product_size = result[f'PRIMER_PAIR_{i}_PRODUCT_SIZE']
print(f'Set {i}:')
print(f' Forward: {left} (Tm: {left_tm:.1f}C)')
print(f' Reverse: {right} (Tm: {right_tm:.1f}C)')
print(f' Probe: {probe} (Tm: {probe_tm:.1f}C)')
print(f' Product: {product_size}bp')
```
## qPCR-Optimized Parameters
```python
result = primer3.design_primers(
seq_args={
'SEQUENCE_TEMPLATE': sequence,
'SEQUENCE_TARGET': [100, 30], # Target region for probe
},
global_args={
'PRIMER_PICK_INTERNAL_OLIGO': 1,
'PRIMER_PRODUCT_SIZE_RANGE': [[60, 100], [100, 150]], # Prefer short
'PRIMER_NUM_RETURN': 5,
# Primer parameters
'PRIMER_OPT_SIZE': 20,
'PRIMER_MIN_SIZE': 18,
'PRIMER_MAX_SIZE': 25,
'PRIMER_OPT_TM': 60.0,
'PRIMER_MIN_TM': 58.0,
'PRIMER_MAX_TM': 62.0,
'PRIMER_OPT_GC_PERCENT': 50.0,
'PRIMER_MIN_GC': 35.0,
'PRIMER_MAX_GC': 65.0,
# Probe parameters (TaqMan: Tm 8-10C higher than primers)
'PRIMER_INTERNAL_OPT_SIZE': 25,
'PRIMER_INTERNAL_MIN_SIZE': 18,
'PRIMER_INTERNAL_MAX_SIZE': 30,
'PRIMER_INTERNAL_OPT_TM': 70.0,
'PRIMER_INTERNAL_MIN_TM': 68.0,
'PRIMER_INTERNAL_MAX_TM': 72.0,
'PRIMER_INTERNAL_MIN_GC': 30.0,
'PRIMER_INTERNAL_MAX_GC': 70.0,
# Avoid G at 5' end of probe (quenches FAM)
'PRIMER_INTERNAL_MAX_SELF_ANY': 8,
}
)
```
## TaqMan Probe Constraints
```python
# Additional considerations for TaqMan probes
global_args = {
'PRIMER_PICK_INTERNAL_OLIGO': 1,
'PRIMER_PRODUCT_SIZE_RANGE': [[70, 150]],
# Probe Tm should be 8-10C higher than primers
'PRIMER_OPT_TM': 60.0,
'PRIMER_INTERNAL_OPT_TM': 70.0,
# Probe should be closer to forward primer
'PRIMER_INTERNAL_MIN_SIZE': 18,
'PRIMER_INTERNAL_MAX_SIZE': 30,
# Avoid long poly-X runs in probe
'PRIMER_INTERNAL_MAX_POLY_X': 3,
}
```
## SYBR Green Primers (No Probe)
```python
# For SYBR Green, design primers without probe
result = primer3.design_primers(
seq_args={'SEQUENCE_TEMPLATE': sequence},
global_args={
'PRIMER_PICK_LEFT_PRIMER': 1,
'PRIMER_PICK_RIGHT_PRIMER': 1,
'PRIMER_PICK_INTERNAL_OLIGO': 0, # No probe
'PRIMER_PRODUCT_SIZE_RANGE': [[70, 200]], # Short for qPCR
'PRIMER_OPT_TM': 60.0,
'PRIMER_MIN_TM': 58.0,
'PRIMER_MAX_TM': 62.0,
'PRIMER_MAX_SELF_ANY': 4, # Strict for SYBR specificity
'PRIMER_MAX_SELF_END': 2,
'PRIMER_PAIR_MAX_COMPL_ANY': 4,
'PRIMER_PAIR_MAX_COMPL_END': 2,
}
)
```
## Design for Exon-Spanning (Avoid Genomic DNA)
```python
# For cDNA-specific amplification, target exon junction
# Mark the exon junction position
exon_junction = 150 # Position where exons meet
result = primer3.design_primers(
seq_args={
'SEQUENCE_TEMPLATE': sequence,
'SEQUENCE_OVERLAP_JUNCTION_LIST': [exon_junction], # Primer must span
},
global_args={
'PRIMER_PRODUCT_SIZE_RANGE': [[70, 150]],
'PRIMER_OPT_TM': 60.0,
'PRIMER_MIN_3_PRIME_OVERLAP_OF_JUNCTION': 4, # Min bases on each side
}
)
```
## Multiplex Primer Design
```python
# Design primers for multiple targets with compatible Tms
targets = [
{'name': 'gene1', 'seq': sequence1, 'target': [100, 30]},
{'name': 'gene2', 'seq': sequence2, 'target': [150, 30]},
]
results = []
for target in targets:
result = primer3.design_primers(
seq_args={
'SEQUENCE_TEMPLATE': target['seq'],
'SEQUENCE_ID': target['name'],
'SEQUENCE_TARGET': target['target'],
},
global_args={
'PRIMER_PICK_INTERNAL_OLIGO': 1,
'PRIMER_PRODUCT_SIZE_RANGE': [[70, 150]],
'PRIMER_OPT_TM': 60.0, # Same Tm for all
'PRIMER_MAX_TM': 61.0,
'PRIMER_MIN_TM': 59.0,
'PRIMER_INTERNAL_OPT_TM': 70.0,
}
)
results.append(result)
```
## Validate Tm Calculations
```python
# Verify Tm with primer3's thermodynamic calculations
primer_seq = 'ATGCGATCGATCGATCGATC'
# Standard Tm
tm = primer3.calc_tm(primer_seq)
print(f'Standard Tm: {tm:.1f}C')
# Tm with specific salt conditions (match your qPCR master mix)
tm_adjusted = primer3.calc_tm(
primer_seq,
mv_conc=50.0, # Monovalent cation (K+, Na+) mM
dv_conc=3.0, # Divalent cation (Mg2+) mM
dntp_conc=0.8, # dNTP mM (reduces free Mg2+)
dna_conc=250.0, # Primer concentration nM
)
print(f'Adjusted Tm: {tm_adjusted:.1f}C')
```
## Format qPCR Results
```python
import pandas as pd
def qpcr_results_to_df(result):
rows = []
for i in range(result['PRIMER_PAIR_NUM_RETURNED']):
row = {
'pair': i,
'forward': result[f'PRIMER_LEFT_{i}_SEQUENCE'],
'reverse': result[f'PRIMER_RIGHT_{i}_SEQUENCE'],
'fwd_tm': result[f'PRIMER_LEFT_{i}_TM'],
'rev_tm': result[f'PRIMER_RIGHT_{i}_TM'],
'product_size': result[f'PRIMER_PAIR_{i}_PRODUCT_SIZE'],
}
if f'PRIMER_INTERNAL_{i}_SEQUENCE' in result:
row['probe'] = result[f'PRIMER_INTERNAL_{i}_SEQUENCE']
row['probe_tm'] = result[f'PRIMER_INTERNAL_{i}_TM']
rows.append(row)
return pd.DataFrame(rows)
df = qpcr_results_to_df(result)
print(df)
```
## qPCR Design Guidelines
| Parameter | Primers | TaqMan Probe |
|-----------|---------|--------------|
| Length | 18-25 bp | 18-30 bp |
| Tm | 58-62C | 68-72C |
| GC% | 35-65% | 30-70% |
| Amplicon | 70-150 bp | - |
| 5' base | Any | Avoid G (quenches FAM) |
## Related Skills
- primer-basics - General PCR primer design
- primer-validation - Check primers for dimers and specificity
- sequence-manipulation - Work with cDNA sequences
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!