6-23-21
"I recover the deleted files from the Google Cloud, and reconstruct partial sequences of 13 early epidemic viruses," Bloom, who is helping with efforts to follow the genetic changes of the coronavirus, wrote in a pre-print paper posted on bioRxiv. It has not yet been peer-reviewed. The NIH confirmed the sequences had been removed in June 2020 at the request of the investigator who originally submitted them in March 2020, and said it was standard practice to allow this. https://www.cnn.com/2021/06/23/health/coronavirus-sequences-database-scientist/index.html
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6-18-21 all reasonable explanations agree that at a deeper level the SARS-CoV-2 genome is derived from bat coronaviruses (Lytras et al. 2021). One would therefore expect the first reported SARS-CoV-2 sequences to be the most similar to these bat coronavirus relatives—but this is not the case.
This conundrum is illustrated in Figure 3, which plots the collection date of SARS-CoV-2 sequences in GISAID versus the relative number of mutational differences from RaTG13 (Zhou et al. 2020b), which is the bat coronavirus with the highest fullgenome sequence identity to SARS-CoV-2. The earliest SARS-CoV-2 sequences were collected in Wuhan in December, but these sequences are more distant from RaTG13 than sequences collected in January from other locations in China or even other countries (Figure 3). The discrepancy is especially pronounced for sequences from patients who had visited the Huanan Seafood Market (WHO 2021). All sequences associated with this market differ from RaTG13 by at least three more mutations than sequences subsequently collected at various other locations (Figure 3)—a fact that is difficult to reconcile with the idea that the market was the original location of spread of a bat coronavirus into humans. Importantly, all these observations also hold true if SARS-CoV-2 is compared to other related bat coronaviruses (Lytras et al. 2021) such as RpYN06 (Zhou et al. 2021) or RmYN02 (Zhou et al. 2020a) rather than RaTG13 (Figure S3).
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Figure 3
The reported collection dates of SARS-CoV-2 sequences in GISAID versus their relative mutational distances from the RaTG13 bat coronavirus outgroup. Mutational distances are relative to the putative progenitor proCoV2 inferred by Kumar et al. (2021). The plot shows sequences in GISAID collected no later than February 28, 2020. Sequences that the joint WHO-China report (WHO 2021) describes as being associated with the Wuhan Seafood Market are plotted with squares. Points are slightly jittered on the y-axis. Go to https://jbloom.github.io/SARS-CoV-2_PRJNA612766/deltadist.html for an interactive version of this plot that enables toggling of the outgroup to RpYN06 and RmYN02, mouseovers to see details for each point including strain name and mutations relative to proCoV2, and adjustment of the y-axis jittering. Static versions of the plot with RpYN06 and RmYN02 outgroups are in Figure S3.
This conundrum can be visualized in a phylogenetic context by rooting a tree of early SARS-CoV-2 sequences so that the progenitor sequence is closest to the bat coronavirus outgroup. If we limit the analysis to sequences with at least two observations among strains collected no later than January 2020, there are three ways to root the tree in this fashion since there are three different sequences equally close to the outgroup (Figure 4, Figure S4). Importantly, none of these rootings place any Huanan Seafood Market viruses (or other Wuhan viruses from December 2019) in the progenitor node—and only one of the rootings has any virus from Wuhan in the progenitor node (in the leftmost tree in Figure 4, the progenitor node contains Wuhan/0126-C13/2020, which was reportedly collected on January 26, 2020). Therefore, inferences about the progenitor of SARS-CoV-2 based on comparison to related bat viruses are inconsistent with other evidence suggesting the progenitor is an early virus from Wuhan (Pipes et al. 2021).
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Figure 4
Phylogenetic trees of SARS-CoV-2 sequences in GISAID with multiple observations among viruses collected before Februrary, 2020. The trees are identical except they are rooted to make the progenitor each of the three sequences with highest identity to the RaTG13 bat coronavirus outgroup. Nodes are shown as pie charts with areas proportional to the number of observations of that sequence, and colored by where the viruses were collected. The mutations on each branch are labeled, with mutations towards the nucleotide identity in the outgroup in purple. The labels at the top of each tree give the first known virus identical to each putative progenitor, as well as mutations in that progenitor relative to proCoV2 (Kumar et al. 2021) and Wuhan-Hu-1. The monophyletic group containing C28144T is collapsed into a node labeled “clade B” in concordance with the naming scheme of Rambaut et al. (2020); this clade contains Wuhan-Hu-1. Figure S4 shows identical results are obtained if the outgroup is RpYN06 or RmYN02.
Several plausible explanations have been proposed for the discordance of phylogenetic rooting with evidence that Wuhan was the origin of the pandemic. Rambaut et al. (2020) suggest that viruses from the clade labeled “B” in Figure 4 may just “happen” to have been sequenced first, but that other SARS-CoV-2 sequences are really more ancestral as implied by phylogenetic rooting. Pipes et al. (2021) discuss the conundrum in detail, and suggest that phylogenetic rooting could be incorrect due to technical reasons such as high divergence of the outgroup or unusual mutational processes not captured in substitution models. Kumar et al. (2021) agree that phylogenetic rooting is problematic, and circumvent this problem by using an alternative algorithm to infer a progenitor for SARS-CoV-2 that they name proCoV2. Notably, proCoV2 turns out to be identical to one of the putative progenitors yielded by my approach in Figure 4 of simply placing the root at the nodes closest to the outgroup. However, neither the sophisticated algorithm of Kumar et al. (2021) nor my more simplistic approach explain why the progenitor should be so different from the earliest sequences reported from Wuhan.
Before moving to the next section, I will also briefly address two less plausible explanations for the discordance between phylogenetic rooting and epidemiological data that have gained traction in discussion of SARS-CoV-2’s origins. The first explanation, which has circulated on social media, suggests that the RaTG13 sequence might be faked in a way that confounds phylogenetic inference of SARS-CoV-2’s progenitor. But although there are unusual aspects of RaTG13’s primary sequencing data (Singla et al. 2020; Rahalkar and Bahulikar 2020), the conundrum about inferring the progenitor holds for other outgroups such as RpYN06, RmYN02, and more distant bat coronaviruses reported before emergence of SARS-CoV-2 such as ZC45 (Tang et al. 2020). The second explanation, which was proposed in a blog post by Garry (2021) and amplified by a popular podcast (Racaniello et al. 2021), is that there were multiple zoonoses from distinct markets, with the Huanan Seafood Market being the source of viruses in clade B, and some other market being the source of viruses that lack the T8782C and C28144T mutations. However, inspection of Figure 4 shows that clade B is connected to viruses lacking T8782C and C28144T by single mutational steps via other human isolates, so this explanation requires not only positing two markets with two progenitors differing by just two mutations, but also the exceedingly improbable evolution of one of these progenitors towards the other after it had jumped to humans.
Sequences recovered from the deleted project and better annotation of Wuhan-derived viruses help reconcile inferences about SARS-CoV-2’s progenitor
To examine if the sequences recovered from the deleted data set help resolve the conundrum described in the previous section, I repeated the analyses including those sequences. In the process I noted another salient fact: four GISAID sequences collected in Guangdong that fall in a putative progenitor node are from two different clusters of patients who traveled to Wuhan in late December of 2019 and developed symptoms before or on the day that they returned to Guangdong, where their viruses were ultimately sequenced (Chan et al. 2020; Kang et al. 2020b). Since these patients were clearly infected in Wuhan even though they were sequenced in Guangdong, I annotated them separately from both the other Wuhan and other China sequences.
Repeating the analysis of the previous section with these changes shows that several sequences from the deleted project and all sequences from patients infected in Wuhan but sequenced in Guangdong are more similar to the bat coronavirus outgroup than sequences from the Huanan Seafood Market (Figure 5). This fact suggests that the market sequences, which are the primary focus of the genomic epidemiology in the joint WHO-China report (WHO 2021), are not representative of the viruses that were circulating in Wuhan in late December of 2019 and early January of 2020.
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Figure 5
Relative mutational distance from RaTG13 bat coronavirus outgroup calculated only over the region of the SARS-CoV-2 genome covered by sequences from the deleted data set (21,570–29,550). The plot shows sequences in GISAID collected before February of 2020, as well as the 13 early Wuhan epidemic sequences in Table 1. Mutational distance is calculated relative to proCoV2, and points are jittered on the y-axis. Go to https://jbloom.github.io/SARS-CoV-2_PRJNA612766/deltadist_jitter.html for an interactive version of this plot that enables toggling the outgroup to RpYN06 or RmYN02, mouseovers to see details for each point, and adjustment of jittering.
Furthermore, it is immediately apparent that the discrepancy between outgroup rooting and the evidence that Wuhan was the origin of SARS-CoV-2 is alleviated by adding the deleted sequences and annotating Wuhan infections sequenced in Guangdong. The rooting of the middle tree in Figure 6 is now highly plausible, as half its progenitor node is derived from early Wuhan infections, which is more than any other equivalently large node. The first known sequence identical to this putative progenitor (Guangdong/HKU-SZ-002/2020) is from a patient who developed symptoms on January 4 while visiting Wuhan (Chan et al. 2020). This putative progenitor has three mutations towards the bat coronavirus outgroup relative to Wuhan-Hu-1 (C8782T, T28144C, and C29095T), and two mutations relative to proCoV2 (T18060C away from the outgroup and C29095T towards the outgroup). The leftmost tree in Figure 6, which has a progenitor identical to proCoV2 (Kumar et al. 2021) also looks plausible, with some weight from Wuhan sequences. However, analysis of this rooting is limited by the fact that the defining C18060T mutation is in a region not covered in the deleted sequences. The rightmost tree in Figure 6 looks less plausible, as it has almost no weight from Wuhan and the first sequence identical to its progenitor was not collected until January 24.
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Figure 6
Phylogenetic trees like those in Figure 4 with the addition of the early Wuhan epidemic sequences from the deleted data set, and Guangdong patients infected in Wuhan prior to January 5 annotated separately. Because the deleted sequences are partial, they cannot all be placed unambiguously on the tree. Therefore, they are added to each compatible node proportional to the number of sequences already in that node. The deleted sequences with C28144T (clade B) or C29095T (putative progenitor in middle tree) can be placed relatively unambiguously as defining mutations occur in the sequenced region, but those that lack either of these mutations are compatible with a large number of nodes including the proCoV2 putative progenitor. Figure S4 demonstrates that the results are identical if RpYN06 or RmYN02 is instead used as the outgroup.
We can also qualitatively examine the three progenitor placements in Figure 6 using the principle employed by Worobey et al. (2020) to help evaluate scenarios for emergence of SARS-CoV-2 in Europe and North America: namely that during a growing outbreak, a progenitor is likely to give rise to multiple branching lineages. This principle is especially likely to hold for the scenarios in Figure 6, since there are multiple individuals infected with each putative progenitor sequence, implying multiple opportunities to transmit descendants with new mutations. Using this qualitative principle, the middle scenario in Figure 6 seems most plausible, the leftmost (proCoV2) scenario also seems plausible, and the rightmost scenario seems less plausible. I acknowledge these arguments are purely qualitative and lack the formal statistical analysis of Worobey et al. (2020)—but as discussed below, there may be wisdom in qualitative reasoning when there are valid concerns about the nature of the underlying data. https://www.biorxiv.org/content/10.1101/2021.06.18.449051v1.full
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