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.
Another new lineage is AY.98 (green), which is rather numerous (n=11k samples) now comprising between 2%-5% of samples.
π¨βπ»: 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. π€
π§βπ«: 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 π.
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.
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. π³
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.
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. >>
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.
Iβd 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 arenβt really aware of this.
@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
Want to *see* how a tumour has evolved and grown? And also how different clones acquired characteristic transcriptional and histopathological features?
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
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-specβ¦
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). >>
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/s4301β¦
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