BioSkills bio-primer-design-qpcr-primers
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.
install
source · Clone the upstream repo
git clone https://github.com/GPTomics/bioSkills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/GPTomics/bioSkills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/primer-design/qpcr-primers" ~/.claude/skills/gptomics-bioskills-bio-primer-design-qpcr-primers && rm -rf "$T"
manifest:
primer-design/qpcr-primers/SKILL.mdsource content
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:
thenpip show <package>
to check signatureshelp(module.function)
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:
withprimer3.design_primers(seq_args, global_args)
(primer3-py)PRIMER_PICK_INTERNAL_OLIGO=1
Required Imports
import primer3 from Bio import SeqIO
Design Primers with TaqMan Probe
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
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
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
# 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)
# 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)
# 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
# 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
# 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
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