Are Viral Genomics Evidence of Spread?

A critical look at genome sequencing, triggered by Clare Craig’s claims.

Are Viral Genomics Evidence of Spread?

A critical look at genome sequencing, triggered by Clare Craig’s claims.

In a recent article, @ClareCraigPath responded to a comment by @Wood_House76, presenting a long list of reasons why she “believes that the virus travels rapidly across the world.”

In my opinion, framing this as a belief already undermines the argument—science should be grounded in verifiable facts, not beliefs. She then lists several claims to support her position. I’ve read the article, and I’d like to focus specifically on point 3, because I believe the topic of sequencing is widely misunderstood—not only by the public but, quite frankly, even by many geneticists. I’ve studied genomics and sequencing in depth, and have run these tools myself. So here’s what I can say based on verifiable facts:

Addressing Point 3: “Whole Genome Sequencing” as the apparent Confirmation of Spread

The term “whole genome sequencing” is problematic. It suggests that we have sequenced an entire genome from end to end. That is factually incorrect. In reality, the claimed genome has never been sequenced in a single read from start to end, and no method has ever produced a truly complete genome using a single approach.

1. The terminal regions of the genome are consistently missing. No existing algorithm has successfully reconstructed a genome in its entirety.

2. Even Sanger sequencing—often held up as the gold standard—has never yielded a complete genome with full raw data. Its assemblies also lack terminal sequences.

3. What is typically referred to as “the genome” is merely a candidate assembly, often derived from the longest contig (e.g., Wu et al., 2020). That assembly is not exactly reproducible from the raw data, and early genome versions even included confirmed human DNA.

4. The origin of many short reads is ambiguous due to unpurified samples that include human and bacterial material.

5. Tools like MEGAHIT use de Bruijn graph algorithms to assemble genomes from k-mers - substrings of sequencing reads. When applied to mixed samples, these tools can accidentally stitch together k-mers from different organisms, leading to chimeric assemblies that don’t even exist in nature.

6. Over 99% of “genomes” in public databases are not de novo assemblies but are instead aligned to the original Wuhan reference. Fewer than 1,000 genomes have ever been assembled de novo directly from patient samples.

7. Crucially, neither alignment nor assembly methods can mathematically verify that a sequence exists in nature. What we call a genome is, at best, a computational model—a hypothetical reconstruction of a pathogen.

8. Due to these limitations, the SARS-CoV-2 genome remains unvalidated. Proper validation steps - such as independent verification of the genome ends - have not been performed or at least publicly documented.

9. Proponents who defend the validity of the SARS-CoV-2 genome often point to the Human Genome as a “verified” benchmark. However, this is a fallacy. The Human Genome itself is not fully verified - it too is a composite model, stitched together from the DNA of multiple individuals, not from a single human or even a single human cell. As such, it is also incomplete and contains unresolved regions. This raises serious concerns about using the human genome as a reference to filter out ‘non-human’ reads, since the line between what is considered human and non-human in sequencing data remains ambiguous and questionable. After all, has any organism ever been fully recreated just from its claimed genome?

It’s also worth noting that some individuals actively dismiss or downplay these verifiable limitations, often while holding significant conflicts of interest. This should not be ignored!

In another part of her list (point 7), Clare claims that detecting viral material (via testing) in remote locations like Antarctica after long delays and without apparent transmission links supports the idea of rapid global spread.

However, reports of infections arising after long periods of isolation - 14 weeks for flu, 7 weeks for COVID, as seen in trips to Antarctica - could also suggest an endogenous origin, where the detected virus or viral-like genetic material is expressed internally without external infection (i.e. a phenomenon originating from the host itself). This raises a serious question: Are these tests detecting an external pathogen, or simply reacting to genetic material produced endogenously by a sick individual? In that case, what we’re calling “spread” might not be the primary mechanism at all - or at least not fully understood.

P.S. This opinion piece does not claim that viruses do not exist, nor does it endorse such views. It simply questions the validity of the current methods used in genome assembly and pathogen identification, and calls for greater transparency, validation, and scientific rigor. Personally, I am still actively researching and seeking to understand this complex topic. Many questions remain unresolved for me, and I do not claim to have all the answers.

Let me know your thoughts in the comments!