“I DNA’d it, and it didn’t give the right answer.”
If you’ve worked in natural products long enough, you’ve probably heard—or said—some version of that sentence.
It has become shorthand for referring to DNA testing in botanicals. We even at LeafWorks use it to speak in the broad sense about DNA testing. But one thing that we should dive into is that this statement hides a deeper issue and one that we should unpack: DNA testing is not a single method.
It never has been.
DNA Is a Category, Not a Test
When someone says they “DNA’d” a product, what they usually mean is that they used one particular approach, one database and one analytical pipeline.
But like any methods within a category of testing, DNA identification depends entirely on:
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The reference database behind the test
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The genetic markers selected
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The validation of those markers for the species in question
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The ability of the pipeline to handle mixtures, processing and degraded material
Like many analytical technologies, DNA testing has evolved significantly over the past decade. Saying “DNA didn’t work” is like claiming all chemistry methods produce identical results.
Method specificity matters. Fit-for-purpose validation matters. Infrastructure matters.
Change any one of those variables and the result can change.
So when two labs produce different answers, the question isn’t “Does DNA work?”
The better question is: What system was behind the result?
Where Disagreement Comes From
There are several common reasons DNA results may conflict, and all of these are issues in a broader sense are applicable to other analytical methods as well:
1. Incomplete or unauthenticated reference database
If the sequences used for comparison are not built from sufficient, authenticated botanical specimens, errors propagate quickly. For example, if you are using an uncurated blast to NCBI, you may be dealing with inconsistent or possibly even erroneous results. This issue is particularly acute in plants with complex genomes and, or taxonomic nomenclature. Like any method, DNA-based results will vary depending on how well the database has been curated. Curation is key.
2. Markers that lack species-level resolution
Some genetic regions are excellent for broad taxonomic comparison but insufficient for distinguishing closely related species. If a marker cannot reliably separate two taxa, ambiguous or conflicting calls are inevitable. Universal barcodes often have these issues. If your DNA testing lab is limited to only a handful of loci, their platform lacks the flexibility to handle the more complex taxonomic groups. In an industry that relies on testing companies to provide the identity confirmations needed to meet regulatory requirements, as well as consumer expectation of clean, accurate labeling, it is vital to use a DNA testing platform full of truly species-specific markers.
3. Failure to account for processing or degradation
Processed botanicals often contain fragmented DNA. Pipelines designed for intact sequences will struggle unless optimized to deal with these product types. This is one of the largest issues associated with what we call the second generation of DNA testing, and a key area where LeafWorks has ushered in the next generation of DNA test capability.
Bottom line: DNA results disagree when the infrastructure behind them differs. DNA itself is not inherently unreliable. But like any identification method, it only performs as well as the system supporting it.
The Field Has Evolved
In the early years of botanical DNA testing, some laboratories moved quickly to market without building the scientific foundation required for consistent, defensible identification.
Those early experiences shaped industry perception. But the field has evolved: The science has advanced. The infrastructure has matured. The expectations have risen.
Today, evaluating DNA testing based on early implementations is like judging modern analytical chemistry by the limitations of its first-generation instruments.
What To Do Instead
If you’ve had inconsistent DNA results in the past, the solution is not to abandon genomic identification. It’s to ask better questions:
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Was the reference database authenticated and curated?
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Were the markers validated for the taxa in question?
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Has the pipeline been optimized for commercial processed powders, extracts and other products?
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Has the lab validated the method as fit for purpose?
DNA is a powerful identification tool—when it is built correctly.
At LeafWorks, we spent nine years building the infrastructure required to eliminate the inconsistencies that created skepticism in the first place for the complex and nuanced natural products and foods markets.
If you’ve experienced conflicting DNA results, we invite you to try us out.
Because the real issue is rarely DNA itself. It’s whether the system was designed for the job.
