Molecular genetics assay planning

Molecular Genetics Assay Planning

Treat the assay as a measurement system, not as a pair of plausible oligos. In-silico design narrows candidates; it never replaces empirical validation.

Define the assay before designing

Record:

• research question and intended readout;
• organism and exact genome assembly/reference build;
• target gene, stable ID, transcript/isoform, exon structure, and strand;
• template type (genomic DNA, cDNA, amplicon, plasmid) and sample matrix;
• assay type (endpoint PCR, RT-PCR, SYBR qPCR, hydrolysis probe, genotyping);
• intended amplicon, required junction/variant/region, and excluded regions;
• known paralogs, pseudogenes, repetitive regions, common variants, and sample population;
• actual reaction chemistry/conditions for thermodynamic calculations.

Do not invent a sequence, accession, assembly, transcript, or reaction condition. Resolve ambiguity against an authoritative database or ask for the missing record.

Route the workflow

1. Candidate design — Read references/primer-design.md; use Primer3/primer3-py as a local candidate optimizer, not a specificity oracle.
2. Genome/transcriptome specificity — Read references/specificity.md; use pair-aware in-silico PCR on the correct assembly. Plain single-primer BLAST is exploratory only.
3. Hairpin and dimer screening — Read references/thermodynamic-validation.md; calculate at the actual monovalent salt, Mg²⁺, dNTP, oligo concentration, and annealing temperature.
4. qPCR/probe design — Read references/qpcr-design.md; treat amplification efficiency, single-product specificity, reference-gene stability, and standard-curve validation as required evidence.

The longer usage notes are in references/primer-basics-usage.md, references/primer-specificity-usage.md, references/primer-validation-usage.md, and references/qpcr-primers-usage.md.

Deterministic examples

Use the bundled scripts only after verifying primer3-py is installed and its API matches the examples:

• scripts/primer_design.py — candidate pair design and ranking;
• scripts/three_prime_anchor.py — illustrates why 3′ anchoring matters;
• scripts/validate_primers.py — hairpin/dimer and pair-Tm checks;
• scripts/qpcr_design.py — primer/probe co-design example.

The scripts contain demo sequences. Replace them only in a working copy; preserve the source accession and all parameters in the result record.

Validation gates

• Verify the intended amplicon sequence and orientation.
• Search the relevant genome and, for RNA assays, the transcriptome; include alternate/unplaced contigs when scientifically relevant.
• Check paralogs, pseudogenes, repetitive regions, and common variants—especially at 3′ primer bases.
• Evaluate the primer pair together: orientation, spacing, product size, and 3′ anchoring.
• Check hairpins, self-dimers, cross-dimers, and 3′-extendable dimers at actual reaction conditions.
• For qPCR, validate a single product, melt curve or probe specificity, efficiency across the intended range, no-template and no-RT controls as applicable, and stable reference genes.
• Confirm performance empirically on representative positive and negative samples before relying on the assay.
• For clinical, regulated, human-subject, recombinant-DNA, or biosafety-sensitive use, route the plan to the appropriate qualified laboratory, IRB/IBC/EHS, QA, and regulatory owners.

Deliverable

Return:

1. target and reference provenance;
2. candidate table with sequences, orientation, Tm, GC, product size, and design penalty;
3. pair-aware specificity results and databases/assemblies searched;
4. thermodynamic flags at stated conditions;
5. common-variant and pseudogene/paralog findings;
6. empirical validation plan and acceptance criteria;
7. assumptions, unresolved risks, and “research use only” boundary where applicable.

Never label an assay diagnostic, validated, specific, or fit for regulated use solely from in-silico output.