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Evolution

Update: Selection analysis on spike glycoprotein of SARS-CoV-2

Dr. Muniba Faiza
Last updated: May 31, 2020 12:17 am
Dr. Muniba Faiza
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Figure 1. Protein Structure of Corona Virus - Ribbon View
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We have recently conducted a selection pressure analysis on SARS-CoV-2 spike glycoprotein sequences. The analysis revealed not even a single site showing evidence of purifying selection but episodic diversifying selection on three sites. Out of these three sites, two sites are potentially relevant (Fig. 3).

Fig. 3 Structure of Spike Glycoprotein (PDB ID: 6VXX) of SARS-CoV-2. The detected residues under positive selection are shown in red color.

The analysis was performed using Hyphy [1] on the Datamonkey server [2]. BUSTED [3], MEME [4], and FUBAR [5] methods were used. MEME [4] and FUBAR [5] found 3 and 5 sites respectively under positive selection. However, BUSTED [3] did not found any evidence of selection on the tested branches of the phylogeny.

These spike glycoproteins are being analyzed further. Additionally, we are analyzing spike glycoproteins of SARS-CoV for comparison between SARS-CoV and SARS-CoV-2 spike glycoproteins.

References

  1. Pond, S. L. K., & Muse, S. V. (2005). HyPhy: hypothesis testing using phylogenies. In Statistical methods in molecular evolution (pp. 125-181). Springer, New York, NY.
  2. Weaver, S., Shank, S. D., Spielman, S. J., Li, M., Muse, S. V., & Kosakovsky Pond, S. L. (2018). Datamonkey 2.0: a modern web application for characterizing selective and other evolutionary processes. Molecular biology and evolution, 35(3), 773-777.
  3. Murrell, B., Weaver, S., Smith, M. D., Wertheim, J. O., Murrell, S., Aylward, A., … & Scheffler, K. (2015). Gene-wide identification of episodic selection. Molecular biology and evolution, 32(5), 1365-1371.
  4. Murrell, B., Wertheim, J. O., Moola, S., Weighill, T., Scheffler, K., & Pond, S. L. K. (2012). Detecting individual sites subject to episodic diversifying selection. PLoS genetics, 8(7).
  5. Murrell, B., Moola, S., Mabona, A., Weighill, T., Sheward, D., Kosakovsky Pond, S. L., & Scheffler, K. (2013). FUBAR: a fast, unconstrained bayesian approximation for inferring selection. Molecular biology and evolution, 30(5), 1196-1205.
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ByDr. Muniba Faiza
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Dr. Muniba is a Bioinformatician based in New Delhi, India. She has completed her PhD in Bioinformatics from South China University of Technology, Guangzhou, China. She has cutting edge knowledge of bioinformatics tools, algorithms, and drug designing. When she is not reading she is found enjoying with the family. Know more about Muniba
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