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Update on emerging SARS-CoV-2 variants

We previously investigated the evolutionary Importance of residue positions in the SARS-CoV-2 S protein (Saputri et al. Frontiers in Microbiology 2020). Here, the Importance of a site was defined as the difference in diversity in two groups of viruses

                    Importance = diversity(SARS-CoV-2+outgroup)−diversity(SARS-CoV-2),

Where outgroup included betacoronaviruses infecting bat and pangolin.  We subsequently found that the Importance was a strong indicator of mutations in emerging variants with increased infectivity from England, South Africa and Brazil. We then noticed that  diversity(outgroup) was the major contribution to Importance. Because of the potential use in predicting future variants, we here provide a complete list S protein diversity values.  We list both the original definition of outgroup, as well as a slightly broader definition, in order to increase the amount of data. Regardless of which definition we chose, the correlation between diversity(outgroup) and emerging mutation is significant (Fisher's Exact Test).

sarsdiver_figure.jpg

Table 1. Correlation between diversity in outgroup-original and emerging mutations

    diversity(outgroup-original)   
1
2
3
(p-value)
No. sites
1180
85
9
 
Mutations in variants
15
4
2
(0.00099​​​​​​​)
Mutations in multiple variants
0
3
2
(1.4e-07)

        

 

Table 2. Correlation between diversity in outgroup-broad and emerging mutations
    diversity(outgroup-broad)   
1
2
3
4 5 6 7 (p-value)
No. sites
822 242 126 57 23 2 1  
Mutations in variants
8 3 6 2 2 0 0 (0.0057)
Mutations in multiple variants
0 1 1 1 2 0 0 (0.00046)

 



Announcing Support for 2019-nCoV Sequence Analysis (日本語) (中国語)

The outbreak of a novel coronavirus (2019-nCoV) has prompted many scientists to share their findings through unconventional means such as social media, blogs and impromptu email threads. Recently, a post on Twitter identified more than 300 2019-nCoV-related papers on bioRxiv and requested support from the scientific community in vetting these preprints. Among the questions asked was a direct appeal to our lab to determine whether the MAFFT sequence alignment software was being used appropriately. In addition to attempting to respond to this specific question, we would like to add several general points as follows:

1. MAFFT is frequently used in MSA analyses of 2019-nCoV. For example, in the published literature:

It’s not easy for us to reproduce every MSA by collecting the same input sequences. Therefore, in order to both validate MSA methods and make these analyses more smooth, we propose to accept sequence data from anyone working on 2019-nCoV and, as long as we have time and our computational resources allow, appropriately apply MAFFT to prepare MSAs and/or trees.

2. In addition to carrying out analysis of virus sequences, it may be possible to obtain valuable information pertaining to the immune responses to 2019-nCoV by sequencing the B and T cell receptors of infected individuals. We can also accept such BCR or TCR repertoire data, and use our own in-house tools or third-party tools to identify likely 2019-nCoV-responsive BCRs or TCRs.

If you wish to have your sequence data analyzed in this fashion, please contact us using one of the forms below:

Do not include the data itself (or a link to the data) in this request. After receiving your inquiry we will ask for access to the data and further details.

Highly-Cited Papers in Web of Science (Top 0.1%) 

  • K Katoh, J Rozewicki, and KD Yamada "MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization", Briefings in Bioinformatics, vol. 20 no. 14 (2019)

Kazutaka Katoh & MAFFT in Nikkei Sangyo Shimbun

  • Kazutaka Katoh, author of the MAFFT multiple alignment software, was recently profiled by a journalist from Nikkei Sangyo Shimbun.

Highly-Cited Papers in Web of Science (Top 1%) 

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