An update on 🦠 SARS-CoV-2 variants in England.

Today: AY.4.2.1, AY.98 and other introductions.

TLDR: It seems to be ok.
Background: The list of Delta sublineages has gotten longer – more than 121 AY.x lineages + sublineages.

This is thanks to the virus hunters @PangoNetwork spotting epidemiologically relevant variants across the 🌍.

These appear as colored branches at cov2tree.org
In England, @CovidGenomicsUK operates a very systematic sequencing programme, which allows to detect & characterise the spread of new lineages early.

Every Monday @jcbarret and his team release data from around 25,000 samples (~10% of cases) on covid19.sanger.ac.uk
In order to shorten the 2-3 weeks between lineage spotting and annotation, @theosanderson has developed a tool that rapidly assigns genomes to the very latest lineages.

(I mention this because the data is slightly ahead of Monday's release using official annotation.)
This latest, provisional data includes a number of new lineages down to AY.120.2.1.

We have been using the model by @harald_voeh to track the fate of 278 lineages. nature.com/articles/s4158…
The first lineage to mention is AY.4.2.1, the purple emerging clade within the green AY.4.2 branch, spotted by @CorneliusRoemer.

It comprises ~3400 samples by now and is found in all English regions, comprising between 1% and 4% of samples in the week ending 6 Nov.
AY.4.2.1's growth was, on average, ~1% faster per day compared to AY.4.2. In some regions it was about the same as AY.4.2.

πŸ‘©β€πŸ”¬: AY.4.2.1 has spike mutation V36F, which could be a hint of a mechanism. But r=1% is within the typical range of fluctuations, so it's inconclusive.
Another new lineage is AY.98 (green), which is rather numerous (n=11k samples) now comprising between 2%-5% of samples.

πŸ‘¨β€πŸ’»: AY.98 is in fact a rather old branch of Delta and has been added mostly to complete the taxonomy.
It has been increasing slowly in all regions except the North East, where it's stagnant at higher levels. πŸ€”

πŸ§‘β€πŸ«: AY.98 was among the first founders of the Delta wave in N/E, reaching high numbers by chance. It now slowly diffuses to other regions until the frequencies are equal.
Lastly, there are also many currently uncharacterised variants across the 🌍.

As the pandemic accelerates in regions such as Eastern Europe, variants from such places also appear in the UK in increasing numbers.
One example is the pink branch below, defined by Orf3a:202L. It doesn't have a pango lineage name yet.

The branch is prevalent in Eastern Europe (πŸ‡©πŸ‡ͺ: 6-10%, πŸ‡΅πŸ‡±: ~10%, πŸ‡ΉπŸ‡· 20-30%). But the relative proportions there are fairly stable, arguing against a large growth advantage.
In England Orf3a:202L is mostly found in London, where it rose noticeably to around 80 cases (2%) per day. These numbers are comparable to AY.4.2.1; the growth was even faster. 😳

πŸ‘©β€πŸ’»: The increase mostly reflects the rising cases elsewhere rather than an inherent advantage.
So overall, the situation in England seems to be in a fluent state, as expected.

The spread of most lineages reflects the stochastic and complex domestic and international dynamics of the pandemic.

AY.4.2.1 may have a very small growth advantage, but I wouldn't bet on it yet.

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More from @MoritzGerstung

14 Oct
Just out - the rise and fall of SARS-CoV-2 lineages in England.

In the last 1.5yrs the UK has been a bell weather for SARS-CoV-2 evolution and genomic epidemiology thanks to the data sequenced by @CovidGenomicsUK and @sangerinstitute.

Let's recap. >>
nature.com/articles/s4158…
As any virus, SARS-CoV-2 accumulates mutations and undergoes an evolutionary journey where fitter variants succeed. Most mutations are neutral and enable us to define lineages, which derive from a single ancestor and share all its mutations. By now there are >1000 lineages. >>
As new variants emerge all the time it is important to characterise their behaviour as soon as possible and an essential question is whether one variant has a growth advantage over others, as this may change the future course of the epidemic. >>
Read 27 tweets
26 Sep
It’s election day in Germany.

A long 🧡 about what’s happening and some anecdotes for my friends abroad.

TLDR: It’s almost spooky how little has changed in the 9 years when I was away. Time for a fresh start, see leader below.

economist.com/leaders/2021/0…
The areas where I feel Germany has to catch up compared to other countries where I lived and worked in the last 13 years are: climate, digitisation and bureaucracy.

I’d also think that it needs to take more responsibility in Europe and sort out its domestic demographic problems.
Among the most pressing things would be a pragmatic approach to reach net zero asap.

Yet Germany emits more greenhouse gas per capita than many other European nations.

The problem is that Germans aren’t really aware of this.
Read 26 tweets
26 May
What have we learned from analysing 200,000 SARS-CoV-2 genomes from genomic surveillance in England in the last 9 months?

These data provide important context for the current situation related to B.1.617.2.

Here’s a summary of the preprint. medrxiv.org/content/10.110…
@harald_voeh has developed a model that tracks 62 different lineages across 315 local authorities in England. His model estimates total and lineage-specific incidence and growth rates.
The model also calculates lineage-specific relative growth rates and provides a fairly accurate reconstruction of the epidemic and its many subepidemics across the nation between Sep '20 and Apr' 21. We also included a provisional analysis until 15 May '21 to track B.1.617.2
Read 14 tweets
17 Apr
Want to *see* how a tumour has evolved and grown? And also how different clones acquired characteristic transcriptional and histopathological features?

Hold on, that's magic.

No, it's our new preprint by @LucyYat47076319 and @MatsNilssonLab 1/9

biorxiv.org/content/10.110…
Jessica Svedlund developed a base-specific extension of the in situ sequencing protocol (BaSISS) to detect somatic mutations on a microscopy slide with fluorescently tagged padlock probes. 2/9
These signals are denoised and assembled into microscopic maps of subclonal growth using @LomakinAI's rigorous machine learning model. 3/9
Read 9 tweets
30 Dec 20
Did the new SARS-CoV-2 B.1.1.7 lineage spread during the English national lockdown? Rising numbers and estimated higher R value suggest so. Together with our colleagues from COG-UK we took a closer look. >> virological.org/t/lineage-spec…
Fitting lineage-agnostic daily PCR test and viral genome data from COG-UK to 382 local authorities we find evidence that B.1.1.7 has spread in a staggering 200/246 of affected LTLAs during the November lockdown (R>1) while at the same time other lineages contracted (R<1). >>
The evidence is therefore overwhelming that B.1.1.7 was repeatedly capable to proliferate under lockdown measures sufficient to suppress other SARS-CoV-2 lineages. B.1.1.7 spread was not an isolated event of general failure of viral containment (both R>1). >>
Read 10 tweets
27 Jul 20
Can you see mutations in cancer cells? Kind of.

We trained a neural network on 17k tumour slides with known genomics transcriptomics to assess how histopathology, molecular tumour characteristics and survival correspond. 1/8 nature.com/articles/s4301…
This analysis discovered histopathological patterns of 167 different mutations ranging from whole genome duplications to point mutations in cancer driver genes - about 1/4 mutations tested. 2/8
Further, around 40% of the transcriptome is correlated with histopathology reflecting tumour grade and composition. This is probably best illustrated at the example of infiltrating lymphocytes TILs, which can be identified and localised through their expression signature. 3/8
Read 9 tweets

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