Assay decay: a published assay against the sequences circulating now
Check a published PCR assay's primers and probes against the genomes circulating now, and see how often each oligo carries a mismatch today, with the 3′-end mismatches counted apart from the ones a primer can usually carry.
| Reached by | Tools → Analyze |
| Formats | Any DNA records in the project: a multi-record FASTA of current genomes, GenBank, and the other sequence formats the editor opens |
What it does
Tick the file of current genomes, type the assay's primers and probes as they were published
(name=SEQUENCE keeps the name), and run. Each oligo's best binding site is found in each genome on
either strand, and the result reports, per oligo, how many genomes now mismatch it, at which base of
the oligo, and how many of those mismatches sit in the 3′ bases a polymerase has to extend through.
When you’d use this
- An assay you did not design and have been running for years. Its oligos were chosen against the sequences available on the day; nothing tells you when the target has moved under it.
- Before you trust a published assay on a new population. A primer that matches reference genomes can mismatch most of what is actually circulating in the region you are sampling.
- Reading a dropout. A target that stopped amplifying while the others held is the pattern a mismatch at one oligo's 3′ end produces.
- Choosing between two published assays for the same target by how well each still matches.
What this computes
For every oligo against every genome in the corpus:
- best binding site: the window on either strand with the fewest non-matching positions, with its strand and start
- mismatching positions, numbered from the oligo's own 5′ end
- 3′-end mismatch: whether any mismatch falls in the last few bases (five by default, the window Primer-BLAST's specificity rule uses). A probe has none: it is not extended
- scored or not: a site overlapping ambiguous bases in a submitted assembly is missing data, and that genome leaves the oligo's denominator rather than counting as a match or a mismatch
And per oligo over the corpus:
- mismatch rate: genomes with at least one mismatch over the genomes that could be scored
- exact 95% confidence interval on that rate (Clopper–Pearson), so a rate read on forty genomes cannot be mistaken for one read on four hundred
- mismatches at each position of the oligo, which is the shape a manufacturer's own in-silico inclusivity table takes, and what separates one fixed substitution from scattered drift
- 3′-end count per primer, and the oligo whose rate decides the assay
An IUPAC code in an oligo is read as the bases it covers, because a designer who wrote R meant both: a position a code covers is never a mismatch.
A worked example
Twelve published SARS-CoV-2 RT-PCR assays (US CDC N1/N2/N3, Charité RdRP and E, Institut Pasteur IP2 and IP4, HKU ORF1b and N, China CDC ORF1ab and N, NIID Japan N) against 400 complete genomes published in 2026:
- CDC's N1 probe mismatches 395 of 400 genomes (98.8%, 95% CI 97.1 to 99.6), 392 of them at position 3 alone; its forward primer mismatches 320 of 400 (80.0%), 307 of them at position 11. CDC's own in-silico analysis of 615,472 genomes to March 2021 reported every N1 and N2 position below 1%.
- China CDC's N reverse primer mismatches 299 of 400, and every one of them is in the 3′ window — the class that stops a reaction rather than slowing it.
- Charité's E forward primer mismatches 394 of 400 and none of them is: the substitution is at position 2, which a 26-mer carries.
- The pan-Sarbeco oligos are not spared. Charité's RdRP reverse primer mismatches all 400, 399 of them at position 12, and the RdRP probe mismatches every genome it could be scored on, at positions 12 and 21. Designed breadth across species is not breadth across time.
- Three oligos still match all 400 exactly: Charité's E reverse primer and probe, and Pasteur's IP4 forward primer. Nine more mismatch 1% of the corpus or less.
- Where the mismatch sits decides who should care: 60 of RdRP's 61 forward-primer mismatches are in the 3′ window, against 1 of 320 for CDC's N1 forward primer.
Limitations
- A rate is a reading of the genomes in the corpus. Genomes from one country, one month or one lineage answer that narrower question; the panel says what it was given.
- A mismatch is not a failure. Whether an assay still works depends on where the mismatch sits, the oligo's melting temperature and the annealing temperature it is run at, which this does not model.
- Only substitutions are reported this way: an insertion or deletion inside the binding site shows up as several mismatches rather than as an indel.
- Nothing here knows about a lineage's frequency in the world; a corpus is counted as it is given.
Where the numbers come from
Every oligo's best site and its mismatch count are checked against EMBOSS fuzznuc, the pattern
search for a nucleotide motif with IUPAC degeneracy and a mismatch budget, over all 400 genomes of
the example above. The rates' intervals are exact binomial (Clopper–Pearson).
Automation
The same check is a workflow node and a tool the assistant can call, with the same settings as the panel: the oligos as published names and sequences, the corpus as record names.
Related
In this group: Properties · BLAST Search · Search Databases · EMBL-EBI Services · Protein Domains · Protein Analysis · Protease Digest · Antibody Numbering · Mass spectrometry: peptide masses, b ladders, isotopes, spectrum scoring, q-values, protein inference · Codon Usage Analysis · Site avoidance: restriction sites a genome avoids or favors · Codon outliers: genes whose codon usage departs from their own genome · Tree incongruence: genes whose own alignment rejects the species tree · Reference stability: reference genes against genes of their own abundance · Annotation contradictions: UniProt features a predictor scores unlike confirmed ones · Hypothesis ledger: pre-register a hypothesis, attach runs, decide with e-BH · Reagent audit: does each annotated CDS code for what the map says, and are its cryptic promoters, splice sites and repeats worse than chance · Gene incongruence: which loci of a multi-locus alignment have a different history · Target validation: test "gene G drives phenotype P" against gene-level evidence tables · Codon Tables · Enzyme Collections · Virtual Gel Bench · Phylogenetics · Dot Plot · Table · NumPy Array · Structure · PDF · Molecule · Image
Reagent audit: does each CDS code for what the map says?
Check every annotated coding sequence of a vector map against its own bases and genetic code, read on to where translation really stops, and test each map's strongest cryptic promoter, splice site and repeat against shuffles of the same map.
Gene incongruence: which loci have a different history from the rest
Test whether each locus of a multi-locus alignment fits the tree of the other loci worse than chance, by the incongruence length difference test.