Damn this is the first comment contrarian to the article that acually addresses the main argument : Silent vs non-silent mutations ratio. The article pretty much convinced me and I am not sure I am really unconvinced yet but I have to thank you.

It's also much more complicated to define "silent" in the context of a virus. In a larger-genomed organism there is a relatively clear (though still not completely clear) function of a coding region, where the change of a nucleic acid will have no effect on the protein made - but still might (subtly) effect regulation in some way.

In a virus, most nucleic acids have multiple, layered, and unknown functions - it's much much harder to assign any given nucleic acid as "silent", and be confident that that is the case from an evolutionary perspective.

As another posted, it's a good hypothesis that's straightforward to test statistically against all of the other variants. But on its own, it's not necessarily convincing here that the S/NS ratio is particularly concerning (and as above, doesn't speak to how directed evolution works either).

The S:NS ratio cited in the blog post also appears to be simply incorrect: https://twitter.com/eigenrobot/status/1471336024827568130?s=...

So, you take on faith that the s/ns ratio as described by "Eigenrobot" who is quoting "Brett" (who are they?) is correct, and the s/ns ratio described by many microbiologists and genome experts, identifiable on their Twitter accounts, is wrong?

I mean, we can find anyone on Twitter saying anything. I could create an account right now that says I'm an expert on time travel and tweet about it.

And of course now that omicron is circulating widely in humans, its pattern and ratio of mutations is occurring as one would expect. I wonder why something we know is a natural occurrence (mutation as it infects humans worldwide) looks natural. It makes me wonder why the original omicron looked so weird.

To me this is not a conversation about whether a lab leak occurred. It's a conversation about why the experts are not ruling out hypotheses that explain the information so they can (if necessary) move on to other hypotheses. Just dismissing hypotheses that explain the existing information is not very scientific, unless the hypotheses are untestable or are truly off the wall. This hypothesis is not truly off the wall.

Honest question : as a GoF researcher, wouldn’t I generate thousands (millions) of mutations from my 1st virus pool, which would each have a low number of mutation (s or n) compared to the original strain, then “select” the most resistant ones from that 1st pool of mutants, and use those to repeat the process ? I’d expect the result to be much richer in n mutation than in silent ones, just because I forced their selection. Am I missing something?

This may be the standard approach, but the question is how else it could have happened other than some GoF procedure. Any idea what the odds are of this ratio happening by chance?

> how else it could have happened other than some GoF procedure

There are at least 2 other possibilities:

* The virus could have stayed alive in an immunocompromised person for months and accumulated mutations there.

* The virus could have jumped to animals (e.g. mouses), accumulate mutations, and jump back to humans.

Neither one of those hypotheses accounts for the four weirdnesses described in the article. So they don't seem like very good hypotheses.

Similarly "it came from an animal" that we've never found two years later is not a hypothesis that accounts for the information we have about the first COVID-19 outbreak either.

To me that sounds very much like OJ vowing to find the real killer, but somehow he never did.