Connect with us

Phylogenetics

Phylogenetics analysis of SARS-CoV-2 spike glycoproteins

Published

on

Phylogenetic Tree of Covid Corona Virus with other Species

A novel coronavirus (CoV), named Severe Acute Respiratory Syndrome-CoV-2 (SARS-CoV-2) or nCoV-2019, has emerged since December 2019 from Wuhan city of Hubei province in China [1]. This virus belongs to the coronavirus family from which previous outbreaks have emerged (SARS and MERS). They have been a great threat to public health causing many deaths including  SARS-CoV-2. There is no proper treatment available to cure this coronavirus disease (covid19). Scientists and researchers are trying really hard to develop a drug or a vaccine or a proper way to cure covid19.

In this essence, Bioinformatics Review has built up a team of worldwide researchers to work on covid19. We will be updating all findings we get during this project. The first study we conducted on SARS-CoV-2 is explained as follows.

Phylogenetics analysis of SARS-CoV-2

The phylogenetic tree is shown below. This tree was created using the IQTREE tool [2] and the best model was found using ModelFinder [3].

Fig. 1 Phylogenetic tree of SARS-CoV-2 spike sequences with SARS-CoV spike sequences as an outgroup. The red color denotes SARS-CoV-2 spike sequences and green color denotes SARS-CoV spike sequences. The best model was VT+F4 as selected by the ModelFinder and the tree was constructed with 1000 replications.

The branch lengths of spike sequences suggest the divergence of SARS-CoV from SARS-CoV-2. The multiple sequence alignment (MSA) (Fig. 2) of these sequences shows several conserved regions across the entire alignment (File 1).

Further, experiments are being performed for a complete phylogeny and evolutionary study of these sequences. For all updates regarding Covid19 work being done by our research group, visit this page.

 

References

  1. Zhu, N., Zhang, D., & Wang, W. China Novel Coronavirus Investigating and Research Team. A novel coronavirus from patients with pneumonia in China, 2019 [published January 24, 2020]. N Engl J Med.
  2. Nguyen, L. T., Schmidt, H. A., Von Haeseler, A., & Minh, B. Q. (2015). IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Molecular biology and evolution32(1), 268-274.
  3. Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K., von Haeseler, A., & Jermiin, L. S. (2017). ModelFinder: fast model selection for accurate phylogenetic estimates. Nature methods14(6), 587.

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

Phylogenetics

How to find a best fit model using IQ-TREE?

Published

on

How to find a best fit model using IQ-TREE?

Previously, we have provided an installation tutorial for IQ-TREE on Ubuntu. In this article, we are going to perform model selection for a dataset using the standalone tool of IQ-TREE. (more…)

Continue Reading

Phylogenetics

Installing TREE-PUZZLE on Ubuntu

Published

on

Installing tree-puzzle on Ubuntu

TREE-PUZZLE is a software to reconstruct phylogenetic trees using the maximum likelihood method [1,2]. It requires sequence data as input and implements a fast search algorithm and quartet puzzling. It can process large datasets easily. In this article, we will install TREE-PUZZLE on Ubuntu. (more…)

Continue Reading

Phylogenetics

Tutorial: Constructing phylogenetic tree using MEGA7

Published

on

mega7

MEGAX is a bioinformatics software/tool used for phylogenetic tree construction. In this article, we will construct a maximum likelihood (ML) tree for a number of protein sequences using MEGA7 [1]. (more…)

Continue Reading

LATEST ISSUE

ADVERT