Update: Selection analysis on spike glycoproteins of SARS-CoV

In our last article, we mentioned the selection pressure analysis of SARS-CoV-2 spike glycoproteins. Now, we have analyzed spike glycoprotein sequences of SARS-CoV. No single purifying selection site was found in SARS-CoV spike glycoproteins as was revealed from our last analysis of SARS-CoV-2 spike glycoproteins.

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 6 and 2 sites respectively under positive selection. The threshold was set to 0.05 (p-value) for MEME and 0.9 (posterior probability) for FUBAR. Additionally, unlike SARS-CoV-2, BUSTED [3] found evidence of selection on the tested branches of the phylogeny of SARS-CoV spike glycoproteins. It implies that there is at least one site on one branch that has experienced gene-wide episodic positive selection.

Interestingly, negative selection has not been found in both SARS-CoV and SARS-CoV-2 spike glycoproteins. Besides, only a small number of sites have been found to be experienced positive selection. These sites of SARS-CoV spike proteins under selection are being analyzed further.


  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 evolution35(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 evolution32(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 genetics8(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 evolution30(5), 1196-1205.
Tariq is founder of Bioinformatics Review and a professional Software Developer at IQL Technologies. His areas of expertise include algorithm design, phylogenetics, MicroArray, Plant Systematics, and genome data analysis. If you have questions, reach out to him via his homepage.
Muniba is a Bioinformatician based in the South China University of Technology. 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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HOW TO CITE THIS ARTICLE Tariq Abdullah and Muniba Faiza (2020). Update: Selection analysis on spike glycoproteins of SARS-CoV. Bioinformatics Review, 6 (05)
Figure 1. Protein Structure of Corona Virus - Ribbon View
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