Sampling bias and incorrect rooting make phylogenetic network tracing of SARS-COV-2 infections unreliable.

There is obvious interest in gaining insights into the epidemiology and evolution of the virus that has recently emerged in humans as the cause of the coronavirus disease 2019 (COVID-19) pandemic. The recent paper by Forster et al. (1), analyzed 160 SARS-CoV-2 full genomes available (https://www.gisaid.org/) in early March 2020. The central claim is the identification of three main SARS-CoV-2 types, named A, B, and C, circulating in different proportions among Europeans and Americans (types A and C) and East Asian (type B). According to a median-joining network analysis, variant A is proposed to be the ancestral type because it links to the sequence of a coronavirus from bats, used as an outgroup to trace the ancestral origin of the human strains. The authors further suggest that the “ancestral Wuhan B-type virus is immunologically or environmentally adapted to a large section of the East Asian population, and may need to mutate to overcome resistance outside East Asia”. There are several serious flaws with their findings and interpretation. First, and most obviously, the sequence identity between SARS-CoV-2 and the bat virus is only 96.2%, implying that these viral genomes (which are nearly 30,000 nucleotides long) differ by more than 1,000 mutations. Such a distant outgroup is unlikely to provide a reliable root for the network. Yet, strangely, the branch to the bat virus, in Figure 1 of the paper, is only 16 or 17 mutations in length. Indeed, the network seems to be mis-rooted because (see Supplementary Figure 4) a virus from Wuhan from week 0 (24th December 2019) is portrayed as a descendant of a clade of viruses collected in weeks 1-9 (presumably from many places outside China), which makes no evolutionary (2), nor epidemiological sense (3).N

Alpha diversity statistics of microbial 16S rRNA gene sequence data in <i>S. purpurea</i> samples, with (+CS) and without <i>C. steinii</i> (−CS).

<p>Alpha diversity statistics of microbial 16S rRNA gene sequence data in <i>S. purpurea</i> samples, with (+CS) and without <i>C. steinii</i> (−CS).</p

Non-metric multidimensional scaling (NMDS) ordination of normalized 16S rRNA iTag sequence data.

<p>(A) NMDS ordination of the first and third axes showing sample grouping based on the presence or absence of the protozoan predator. (B) NMDS ordination with those OTUs that were statistically significantly correlated with an axis and had a p-value < 0.03 shown by vectors.</p

Rarefaction curve of the number of observed OTUs from 16S rRNA iTag sequence data.

<p>Rarefaction curve of the number of observed OTUs from 16S rRNA iTag sequence data.</p

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Time-scaled Bayesian phylogenetic maximum clade credibility (MCC) trees of arbovirus strains.

<p>MCC trees for (A) CHIKV, (B) ZIKV, (C) DENV-2 and (D) MAYV were inferred from full genome sequences using BEAST v1.8.4. Gray arrows indicate strains from CHIKV and ZIKV co-infected patients, orange from CHIKV and DENV-2, black from CHIKV and MAYV (sequence for CHIKV strain from the co-infected patient was not determined). Letters next to arrows indicate ID of co-infected patients. Tips are colored by sampling location as indicated in the legends to the left of each tree; diamonds at each node indicate strong statistical support along branches defined as posterior probability > 0.9. For MAYV (D), insert box shows relationship of recent Haitian and Brazilian strains.</p