Design PCR primers for a target sequence using primer3-py. Specify target regions, product size, melting temperature, and other constraints. Returns ranked primer pairs with quality metrics. Use when designing standard PCR primers.
Scanned 9/5/2026
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---
name: bio-primer-design-primer-basics
description: Design PCR primers for a target sequence using primer3-py. Specify target regions, product size, melting temperature, and other constraints. Returns ranked primer pairs with quality metrics. Use when designing standard PCR primers.
tool_type: python
primary_tool: primer3-py
measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.
allowed-tools:
- read_file
- run_shell_command
---
<!--
# COPYRIGHT NOTICE
# This file is part of the "Universal Biomedical Skills" project.
# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>
# All Rights Reserved.
#
# This code is proprietary and confidential.
# Unauthorized copying of this file, via any medium is strictly prohibited.
#
# Provenance: Authenticated by MD BABU MIA
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# PCR Primer Design
Design PCR primers using primer3-py, the Python binding for Primer3.
## Required Imports
```python
import primer3
from primer3 import p3helpers
from Bio import SeqIO
from Bio.Seq import Seq
```
## Sequence Preparation (p3helpers)
```python
# Sanitize sequence (uppercase, remove whitespace)
raw_seq = ' atgc gatc GATC '
clean_seq = p3helpers.sanitize_sequence(raw_seq)
print(f'Cleaned: {clean_seq}') # 'ATGCGATCGATC'
# Reverse complement for designing reverse primers
seq = 'ATGCGATCGATC'
rc_seq = p3helpers.reverse_complement(seq)
print(f'Reverse complement: {rc_seq}') # 'GATCGATCGCAT'
# Ensure valid DNA sequence (ACGT only, uppercase)
valid_seq = p3helpers.ensure_acgt_uppercase('atgcNNgatc') # Raises error if invalid
```
## Basic Primer Design
```python
sequence = 'ATGCGTACGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCG'
result = primer3.design_primers(
seq_args={'SEQUENCE_TEMPLATE': sequence},
global_args={
'PRIMER_PRODUCT_SIZE_RANGE': [[100, 300]],
'PRIMER_MIN_TM': 57.0,
'PRIMER_OPT_TM': 60.0,
'PRIMER_MAX_TM': 63.0,
'PRIMER_MIN_GC': 40.0,
'PRIMER_MAX_GC': 60.0,
}
)
```
## Extract Primer Results
```python
num_returned = result['PRIMER_PAIR_NUM_RETURNED']
print(f'Found {num_returned} primer pairs')
for i in range(num_returned):
left = result[f'PRIMER_LEFT_{i}_SEQUENCE']
right = result[f'PRIMER_RIGHT_{i}_SEQUENCE']
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'Pair {i}: {left} / {right}')
print(f' Tm: {left_tm:.1f}C / {right_tm:.1f}C, Product: {product_size}bp')
```
## Target a Specific Region
```python
# Target a specific region: [start, length]
result = primer3.design_primers(
seq_args={
'SEQUENCE_TEMPLATE': sequence,
'SEQUENCE_TARGET': [100, 50], # Target region at position 100, length 50
},
global_args={
'PRIMER_PRODUCT_SIZE_RANGE': [[150, 300]],
'PRIMER_OPT_TM': 60.0,
}
)
```
## Primers Must Span a Region
```python
# Primers must span this region (e.g., exon junction)
result = primer3.design_primers(
seq_args={
'SEQUENCE_TEMPLATE': sequence,
'SEQUENCE_INCLUDED_REGION': [50, 200], # Primers within this region
},
global_args={'PRIMER_PRODUCT_SIZE_RANGE': [[100, 250]]}
)
```
## Exclude Regions
```python
# Exclude regions (e.g., SNP positions, repeats)
result = primer3.design_primers(
seq_args={
'SEQUENCE_TEMPLATE': sequence,
'SEQUENCE_EXCLUDED_REGION': [[150, 20], [300, 15]], # Regions to avoid
},
global_args={'PRIMER_PRODUCT_SIZE_RANGE': [[100, 300]]}
)
```
## Constrain Primer Positions
```python
# Force primer to overlap a specific position
result = primer3.design_primers(
seq_args={
'SEQUENCE_TEMPLATE': sequence,
'SEQUENCE_FORCE_LEFT_START': 50, # Left primer must start here
'SEQUENCE_FORCE_RIGHT_START': 250, # Right primer must start here
},
global_args={'PRIMER_PRODUCT_SIZE_RANGE': [[150, 250]]}
)
```
## Design for Sequencing
```python
# Single primer for sequencing
result = primer3.design_primers(
seq_args={'SEQUENCE_TEMPLATE': sequence},
global_args={
'PRIMER_PICK_LEFT_PRIMER': 1,
'PRIMER_PICK_RIGHT_PRIMER': 0, # Only design left primer
'PRIMER_PICK_INTERNAL_OLIGO': 0,
'PRIMER_OPT_SIZE': 20,
'PRIMER_MIN_SIZE': 18,
'PRIMER_MAX_SIZE': 25,
}
)
```
## Full Parameter Control
```python
result = primer3.design_primers(
seq_args={
'SEQUENCE_TEMPLATE': sequence,
'SEQUENCE_TARGET': [200, 50],
},
global_args={
'PRIMER_PRODUCT_SIZE_RANGE': [[150, 300], [300, 500]], # Multiple ranges
'PRIMER_NUM_RETURN': 5,
'PRIMER_MIN_SIZE': 18,
'PRIMER_OPT_SIZE': 20,
'PRIMER_MAX_SIZE': 25,
'PRIMER_MIN_TM': 57.0,
'PRIMER_OPT_TM': 60.0,
'PRIMER_MAX_TM': 63.0,
'PRIMER_MIN_GC': 40.0,
'PRIMER_OPT_GC_PERCENT': 50.0,
'PRIMER_MAX_GC': 60.0,
'PRIMER_MAX_POLY_X': 4, # Max consecutive identical bases
'PRIMER_MAX_NS_ACCEPTED': 0, # No ambiguous bases
'PRIMER_MAX_SELF_ANY': 8, # Self-complementarity
'PRIMER_MAX_SELF_END': 3, # 3' self-complementarity
'PRIMER_PAIR_MAX_COMPL_ANY': 8, # Pair complementarity
'PRIMER_PAIR_MAX_COMPL_END': 3, # Pair 3' complementarity
'PRIMER_MAX_END_STABILITY': 9.0, # Max 3' end stability (delta G)
}
)
```
## Load Sequence from FASTA
```python
from Bio import SeqIO
record = SeqIO.read('gene.fasta', 'fasta')
sequence = str(record.seq)
result = primer3.design_primers(
seq_args={'SEQUENCE_TEMPLATE': sequence, 'SEQUENCE_ID': record.id},
global_args={'PRIMER_PRODUCT_SIZE_RANGE': [[100, 300]], 'PRIMER_OPT_TM': 60.0}
)
```
## Calculate Tm Directly
```python
# Calculate Tm for an existing primer
tm = primer3.calc_tm('ATGCGATCGATCGATCGATC')
print(f'Tm: {tm:.1f}C')
# With custom salt/DNA concentrations
tm = primer3.calc_tm('ATGCGATCGATCGATCGATC', mv_conc=50.0, dv_conc=1.5, dntp_conc=0.2, dna_conc=50.0)
```
### Tm Calculation Defaults
| Parameter | Default | Description |
|-----------|---------|-------------|
| mv_conc | 50.0 mM | Monovalent cations (Na+, K+) |
| dv_conc | 0.0 mM | Divalent cations (Mg2+) |
| dntp_conc | 0.0 mM | dNTP concentration |
| dna_conc | 50.0 nM | DNA oligo concentration |
## Calculate Hairpin and Dimer Tm
```python
# Hairpin Tm
hairpin = primer3.calc_hairpin('ATGCGATCGATCGATCGATC')
print(f'Hairpin Tm: {hairpin.tm:.1f}C, dG: {hairpin.dg:.1f}')
# Homodimer Tm
homodimer = primer3.calc_homodimer('ATGCGATCGATCGATCGATC')
print(f'Homodimer Tm: {homodimer.tm:.1f}C, dG: {homodimer.dg:.1f}')
# Heterodimer Tm (between two different primers)
heterodimer = primer3.calc_heterodimer('ATGCGATCGATCGATCGATC', 'GCTAGCTAGCTAGCTAGCTA')
print(f'Heterodimer Tm: {heterodimer.tm:.1f}C, dG: {heterodimer.dg:.1f}')
```
## Format Results as DataFrame
```python
import pandas as pd
def primers_to_dataframe(result):
rows = []
for i in range(result['PRIMER_PAIR_NUM_RETURNED']):
rows.append({
'pair': i,
'left_seq': result[f'PRIMER_LEFT_{i}_SEQUENCE'],
'right_seq': result[f'PRIMER_RIGHT_{i}_SEQUENCE'],
'left_tm': result[f'PRIMER_LEFT_{i}_TM'],
'right_tm': result[f'PRIMER_RIGHT_{i}_TM'],
'left_gc': result[f'PRIMER_LEFT_{i}_GC_PERCENT'],
'right_gc': result[f'PRIMER_RIGHT_{i}_GC_PERCENT'],
'product_size': result[f'PRIMER_PAIR_{i}_PRODUCT_SIZE'],
'penalty': result[f'PRIMER_PAIR_{i}_PENALTY'],
})
return pd.DataFrame(rows)
df = primers_to_dataframe(result)
print(df)
```
## Common Global Arguments
| Parameter | Description | Default |
|-----------|-------------|---------|
| PRIMER_PRODUCT_SIZE_RANGE | Allowed product sizes | [[100,300]] |
| PRIMER_NUM_RETURN | Number of primer pairs | 5 |
| PRIMER_MIN/OPT/MAX_SIZE | Primer length | 18/20/27 |
| PRIMER_MIN/OPT/MAX_TM | Melting temperature | 57/60/63 |
| PRIMER_MIN/MAX_GC | GC content percent | 20/80 |
| PRIMER_MAX_POLY_X | Max poly-X run | 5 |
| PRIMER_MAX_SELF_ANY | Self complementarity | 8 |
| PRIMER_MAX_SELF_END | 3' self complementarity | 3 |
## Related Skills
- qpcr-primers - Design primers with internal probes for qPCR
- primer-validation - Check primers for specificity and secondary structures
- sequence-io - Load template sequences
- database-access/local-blast - BLAST primers for specificity checking
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