1/8 @DarrenM98230782 and I summarize our thoughts on the near-term evolutionary fate of the #Omicron lineage and its individual mutations
(virological.org/t/a-fool-s-err…). As the title implies, prediction of viral evolution has not historically been successful.
2/8 Anyone who claims to *know* where this is going is a fool. The emergence of #Omicron testifies to it. We consider four scenarios for the lineage in the near/midterm. This is also purely from an evolutionary perspective; the ultimate clinical outcomes are a separate story.
3/8
1. Spread with no selective pressure [unlikely]
2. Spread with weak/moderate ongoing selective pressures [most likely]
3. Spread with strong ongoing selective pressures [new data will soon show how likely]
4. Recombination wildcard [not too likely]
4/8 Scenario 2 is consistent with with a general selective sweep, where #Omicron becomes the dominant strain and evolves relatively slowly without significant changes in function/transmissibility/resistance. This would mirror the spread of Alpha and Delta.
5/8 More interestingly, we expect there to be several detectable and interpretable patterns in evolution at specific sites in #Omicron. Our current monitoring and evolutionary analysis capacity can be used to better understand the evolutionary past and future of this lineage.
6/8
1. Population-level maladaptive mutations, if carried over from intra-host evolution, will revert.
2. Adaptive mutations at previously negatively selected sites should be maintained by negative selection.
7/8
3. We expect some of the mutations seen in the 501Y meta-signature to appear in the Omicron lineage (e.g. 5F,18F, 701V etc) and rise in frequency over time
4. It is especially important that the acquisition of mutations that could confer additional immune escape is monitored.
8/8
5. We would expect all the “easily accessible” large effect immune escape and transmission advantage mutations to arise quite rapidly.
6. We should make better use of deep sequencing data to investigate intra-host variability, especially occurring at sub-consensus levels.

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More from @sergeilkp

8 Dec
1/8 Selection analysis update on the S-gene of #Omicron. Caution: preliminary data and analysis; based on ~800 sequences (12/7) from @GISAID classed as B.1.1.529 by #Pangolin. There appears to be signal of positive selection in circulating #Omicron sequences. @DarrenM98230782
2/8 Thanks to all the data contributors, including @Tuliodna and SA colleagues! We find evidence of positive selection at S/346 (K), S/701 (V), S/211 (several states, possibly due to indel alignment issues). Genomes have a lot of noise around S/214, so this could be an artifact.
3/8 Weaker signals are also present at some of the sites that have been selected during the emergence of #Omicron (S/371,S/375, S/505), and sites in the RBD (S/440, S/446,S/452).
Read 8 tweets
5 Dec
1/18 "Selection analysis identifies significant mutational changes in Omicron that are likely to influence both antibody neutralization and Spike function" virological.org/t/selection-an… @DarrenM98230782 @Tuliodna @jbloom_lab @robertson_lab @nekrut @LemeyLab and many others.
2/18 There are 14 mutation in #omicron S-gene that have been under negative selection (or neutral evolution) prior to Nov 2021. This pattern was NOT seen in previous VOC where many of the signatures sites had been detectably selected prior to emergence cell.com/cell/pdf/S0092…
3/18 The 14 #Omicron mutations fall into 3 clusters in Spike
Read 18 tweets
3 Dec
1/4 In a May 2021 preprint on the common evolutionary trajectories of human beta-coronaviruses, we (@EvolveDotZoo, Marina Escalera-Zamudio and others) identified four sites, including S/796 found in #omicron that we hypothesized might be involved in human adaptation Image
2/4 In particular, S/796 has experienced what we termed "stepwise evolution" in SARS-CoV-1 and is near the trimerization surface, which undergoes conformational rearrangements during viral fusion Image
3/4 These types of comparative analyses of beta-coronavirus evolution in humans are effectively studies of evolutionary "replicates" where commonalities commonalities among different viruses can be exploited to develop predictions of what similar viruses may do.
Read 4 tweets
30 Nov
1/11 Can the evolutionary history of sarbecoviruses help predict the effect of mutations in #omicron? Experimental measurment of phenotypic effects is the gold standard (e.g. see the magnificent DMS-based predictions by @jbloom_lab). What about evolutionary predictions?
2/11 Obviously, if a mutation has been observed at appreciable frequencies in SARS-CoV-2 circulation, this provides evidence that it is not particularly deleterious or may be adaptive (at the time it was circulating, anyway).
3/11 How about mutations that have not been seen at "above noise" levels? We can look at evolution in related "species" (viral isolates in this case) to impute the effect of a mutation; this idea has found extensive use in general G2P (e.g. SIFT, PolyPhen, EP).
Read 11 tweets
29 Nov
There's definitely a strong signal of selection on Spike in #Omicron compared to reference clades in our preliminary RASCL analysis of ~60 sequences (thanks @aglucaci, more coming)
1. Spike is under positive selection
2. Spike is under stronger selection than background
There are 9 spike sites where there's stronger selection in #Omicron compared to other clades according to Contrast-FEL (academic.oup.com/mbe/article/38…). Sorted by q-value here (stronger evidence at the top) Image
Full details at observablehq.com/@aglucaci/sc2-… Will post further updates (we will be running daily or so updates as more sequences come in).
Read 4 tweets
22 Oct
#SARSCoV2 selection analyses updates. We switched to running sliding windows analyses (blocks of 3 months) to deal with data volumes and get temporal trends. The current state of analyses is at observablehq.com/@spond/selecti…
This includes an at-a-glance view of selection profiles on the most recent time window
Profiles of selective "forces"
Read 4 tweets

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