This research is extremely important, and its significance is multi-layered.
I will go over the insights I draw from some of the points that arise here.

https://twitter.com/angie_rasmussen/status/1786531532301103157

main importance here is from the essence of this paper. a collaboration of a real 🌎all stars of this matter, published less than 2 weeks after USDA released the🧬 an analsys beyond any authority's capabaility by itself.
This is exactly why authorities need to publish data asap.

Several points regarding avian influenza in U.S. cattle.
TL;DR -
It doesn't seem like a fleeting event; the implications are broader than just milk. If we share data on time, we can improve preparedness.

1/9 So - There are two risks to address:
an immediate risk related to consuming milk, and a longer-term risk that has been intensifying over recent years from H5N1.

2/9

Following @EmilyAnne_Smith thread, I am sharing here an advanced analysis I conducted on the genetic variations of the H5N1 viruses that surfaced in the Texas area, with hints of reassortment events and an idea for improvement in the future.

1/9

https://twitter.com/EmilyAnne_Smith/status/1776049248573784275

First lets revisit the phylogenetics. Here is a RAxML build of the🧬for the HA segment.
latest cattle 🧬 from TX (in 🟦).
The latest TX area branch with 🐄 and 🐦‍⬛in 🟪.
The human sample from TX in🟧 (claimed to be linked to 🐄).

2/9

JN.1 update :
One of the strongest indications of a connection between a specific variant and an increase in morbidity is the correlation between its rise and an increase in case number. As even if a variant dominates the overall landscape, it does not necessarily mean it enhances the number of patients (it only indicates its success in competing for patients compared to other variants).

And while it's true that correlation does not imply causation, a lack of correlation here would significantly hinder the conclusion that a variant increases morbidity. To delve deeper into this topic, I utilized case numberfrom Owid and JN.1 proportion from CovSpectrum, focusing on countries with sufficient information in both databases for the recent period.
This led me to 18 countries.

I'm back to viral evolution after a long break. Because JN.1.
To get straight to the point – yes, there's cause for concern. When we will start seeing the variant ratio linked to case numbers, in many countries in parallel, that's when we will know that a another wave is on the rise JN.1, for those unfamiliar, is a subvariant of BA.2.86. Due to Pango's naming system, after three divergences, we transition to the next letter sequence. Therefore, JN.1 is essentially BA.2.86.1.1. It has several mutations beyond its parent (BA.2.86.1), with the one at position 455 in the RBD drawing the most attention. Without delving too deep into biochemistry (others are more hands on than I am on this), it's important to note that concerns about mutations at this specific position were raised even before JN.1 emerged. Hence, after a few sequences with a non-suspicious pattern of JN.1, it started to attract significant attention.

Where BA.2.86 came from?
Contrary to the idea of saltation, variants like BA.2.86 are stepwise evolving, but they are under sequenced in this process. The main source for such 'saltation-like' variants are agreed to be Chronic COVID patients with compromised immunity
1/12 Monitoring prolonged cases is key to predicting variant evolution and potential. Ideally, nations should focus on immunocompromised patients for this tracking and share their complete data on those. Without such targeted data, we'll have to make do with what's available.
2/12

3 Points on BA.2.86.
TL;DR :
Circulation means success, Whether it'll outcompete others is TBD.
Its rise validates the Pi scenario. Huge Saltations can still yield competing strains.
Its presence increases risk, as recombination could yield more potent variants.

1/4 1.
BA.2.86 is successful, without a doubt. 128 smples on @GISAID from 15 countries from all around the world. Whether it will outcompete current variants remains to be seen, but it's circulating and unlikely to disappear. Based on past events—like Alpha vs. WT, Delta vs. Alpha, Gamma vs. Alpha, and BA.2 vs. BA.1—it's clear that it can take a considerable amount of time (up to several months) for one variant to outcompete another. Don't overlook the unique kinetics of BA.1.

And now – convergence.

If you follow my work, you know I'm flagging convergence as a big clue of positive selection since B.1.1.7.
This is key when found in successful circulating variants (in contrast to terminal branched, chronic cases etc.).

In this thread, I'll show data on BA.2.86 convergence. I'll concentrate only on Non Spike as its neglected in the analysis of this virus, although the other 90% of the genome isn't just a filler. and we will see that using convergence clues.
So lets start with the data.
I manage a mutations database that covers 1,106 variants, sub-variants, and key branches. This project began post the emergence of B.1.1.7 in Dec 2020 and is ongoing. While it started as a manual effort, it's now mostly automated, thanks to valuable data of USHER phylogeny from @AngieSHinrichs (without her help – nothing in this analysis would be available and I would not be able to spot on tine BA.2.86. Angie, thank for all your help).
So here is the defining mutations data :

For access to the latest database, reach out if you're a researcher or lab staff. I'll keep you updated.

BA.2.86 may or not become a threat, but what’s for sure is that the π scenario is a real.
In π I refer to a huge saltation successful variant based on past variants such as Δ,Omicrons or something even previous. which may lead to rise in case numbers.

Let's dive in... Two routes in the virus evolution:
Stepwise- small accumulating mutations due to genetic drift from small infecting size.
Saltation- genetic leaps cause most probably in chronic infection in immunocompromised patients, shaped more by selection (from the intra host environment)

As BA.2.86 keeps on poppin, I'll outline key insights on its prevalence, genomic features, potential impacts, diagnostic advancements and highlight for areas requiring immediate focus.

For ongoing updates, please follow my page.

Let’s go: Most important note :
Only 5 BA.2.86 cases verified so far by sequencing. that's not much.
We must analyze with caution to prevent overinterpretation. With such limited data, We can easily make more noise than data. Nevertheless, these few cases could signal an emerging concern, requiring continued vigilance and alertness.

How wild can it gets?
One of our labs in Israel just uploaded a sample to @GISAID (EPI_ISL_18096761) from a patient which is not chronic nor infected by one (mans able to transmit inter host).
It's so wild I had to consult with some colleagues(*) to analyze if it's not BA.6... https://t.co/IXXjAnjwrktwitter.com/i/web/status/1…
@GISAID If were taking it as a BA.2 2nd gen, it means it got :
18 RBD mutations (incld 3 reversions and a deletion)
69-70,144&211 dels, 4 AA insertion and plenty of mutations in the NTD
681 turn to R

This thing went far from BA.2 more than it went from the WT. https://t.co/jCNQ6ta3ivtwitter.com/i/web/status/1…

So where SARS-CoV-2 is going?
I'm sharing an analysis I've undertaken, looking at RBD SNPs in variants as a marker for antigenic drift, and synonymous SNPs as an index for time since the pandemic's onset. I took the definitions of 526 Omicrons sub-variants (from a DB i maintain and will share in the end here). This entailed assessing the count of synonymous SNPs against RBD SNPs in each varaiant. Averaging # RBD SNP's for each # of synonymous SNP's.

Here is a variant definition DB I'm maintaining.
its includes an upgraded type of VCF with Aliases dict, mutations added relative to previous branches, mediator branchpoint (when such are not defined) and more for main @pango variants (842 so far).

docs.google.com/spreadsheets/d…

1/6 Every entry goes through an analysis includes statistical examination of mutations, verification against USHER's Mutational path, study of parent's defining mutations, and analysis of mutation positions, including Ambiguous nucleotide and discontinuous regions.

2/6

In 2021, I analyzed mutation rates in various variants, considering only samples with defining mutations. I then grouped these in consecutive time frames.

https://twitter.com/shay_fleishon/status/1466131725650640903

1/13 Prof. @richardneher later published a similar analysis yielding significant insights.

biorxiv.org/content/10.110…

2/13

Are there more variants now?
Geneticwise, mutations are constantly added to the genome as the virus passes between hosts. Until May-June 2022, it was thought that these stepwise additions of mutations were not a result of selection-based evolution, but rather genetic drift.
1/10 In the last half a year, the trend has changed. Now there are stepwise (and saltation) variants accumulating convergent S1 mutations, which seems to give them an advantage. So there is not necessarily an increase in diversity, but rather that this diversity is beneficial.
2/10

I think we now have a visualization problem for SARS-CoV-2 evolution.
So many advantageous variants are rising in main parallel branches worldwide.
This is no Δ21J vs. BA.1. It’s stepwise and on all branches.
I have an idea to make it easier to analyze. But I need help. Now let’s not get to the reasons for the new evolutionary trend, but it’s here, and it’s getting more complicated.

Take CV.1 or CC.1; if you hear they rise somewhere, will you know that the first is a BA.2.75 sub-lineage and the second is BA.5?

https://twitter.com/shay_fleishon/status/1576649691554455553

I started to write a thread several times this month. Each time it gets more complex, I lose the point somewhere. So I’ll say it straight. Maybe later will upload all the analysis behind this :

1/10 Something is happening with SARS-CoV-2🧬. Something big. We don’t know what it’ll cause. Maybe it's nothing, or maybe the next thing is on its way to cause waves; perhaps it means that the virus gave all it got, and with all of this, it is still "losing" the battle?

2/10

BA.2.75.2 may be “a” concern, but it’s not “the” concern.
What is worrying is the trend that happened in the last few months in Omicron, and more robust in the polytomy of BA.2.75 - The RBD region, which was highly conserved in the past, shows increasing plasticity.
1/4 For instance, BA.2.75.2 indeed has already gained R346T and F486S. But! BM.1.1.1 (=BA.2.75.3.1.1.1) accumulated both extra mutations in the RBD as BA.2.75.2 and also F490S.
It is a more recent evolving variant, so the data is still not as clear as with BA.2.75.2.
2/4

Let's look in depth in 4 countries for the advancement of BA.4 and BA.5 :

https://twitter.com/shay_fleishon/status/1559645171305807873

I hear many claims that BA.5 advantage is mostly Immune evasion related. And I wonder, how could we be sure of that when BA.4 has an identical S gene as BA.5?

I dive in using data from @GISAID (the motor of all SARS-CoV-2 genomic research).
1/5 Distinguishing between the 2 is hard, but Talya Shechter made excellent @GenSpectrum queries for that (link below).
When Looking roughly at their part of global sequences, it is evident that BA.5 has the advantage.
github.com/cov-lineages/p…
2/5

Another BA.2 2nd gen popped on GISAID. Spotted by a variant spotter called Silcn, @alchemytoday & @LongDesertTrain (+ data from @PeacockFlu).
11 seq, not that much, but from 5 different states within India.
11 novel mutations. 4 in the RBD, 2 NTD dels.
github.com/cov-lineages/p… If you follow me, you know that it was expected. And this is a trend that is expected to continue.

https://twitter.com/shay_fleishon/status/1542578727766425603