scholarly journals Multiple Sequence Alignment and Phylogenetic Tree Construction of Viral Protein 2 of Bluetongue virus

Author(s):  
U. G. Adebo ◽  
J. O. Matthew

Multiple sequence analysis is one of the most widely used model in estimating similarity among genotypes. In a bid to access useful information for the utilization of bush mango genetic resources, nucleotide sequences of eight bush mango (Irvingia gabonensis) cultivars were sourced for and retrieved form NCBI data base, and evaluated for diversity and similarity using computational biology approach. The highest alignment score (26.18), depicting the highest similarity, was between two pairs of sequence combinations; BM07:BM58 and BM12:BM69 respectively, while the least score (19.43) was between BM01: BM13. The phylogenetic tree broadly divided the cultivars into four distinct groups; BM07, BM58 (cluster one), BM01 (cluster 2), BM15, BM13 and BM35 (cluster 3), and BM12, BM69 (cluster 4), while the sequences obtained from the analysis revealed only few fully conserved regions, with the single nucleotides A, and T, which were consistent throughout the evolution. Results obtained from this study indicate that the bush mango cultivars are divergent and can be useful genetic resources for bush mango improvement through breeding.


2020 ◽  
Author(s):  
Rashid Saif ◽  
Sadia Nadeem ◽  
Ali Iftekhar ◽  
Alishba Khaliq ◽  
Saeeda Zia

Abstract Context: Pairwise sequence alignment is one of the ways to arrange two biological sequences to identify regions of resemblance that may suggest the functional, structural, and/or evolutionary relationship (proteins or nucleic acids) between the sequences. There are two strategies in pairwise sequence alignment: Local sequence Alignment (Smith-waterman algorithm) and Global sequence Alignment (Needleman-Wunsch algorithm). In local sequence alignment, two sequences that may or may not be related are aligned to find regions of local similarities in large sequences whereas in global sequence alignment, two sequences same in length are aligned to identify conserved regions. Similarities and divergence between biological sequences identified by sequence alignment also have to be rationalized and visualized in the sense of phylogenetic trees. The phylogenetic tree construction methods are divided into distance-based and character-based methods. Evidence Acquisition: In this article, different algorithms of sequence alignment and phylogenetic tree construction were studied with examples and compared to establish the best among them to look into background of these methods for the better understanding of computational phylogenetics.Conclusions: Pairwise sequence alignment is a very important part of bioinformatics to compare biological sequences to find similarities among them. The alignment data is visualized through phylogenetic tree diagram that shows evolutionary history among organisms. Phylogenetic tree is constructed through various methods some are easier but does not provide accurate evolutionary data whereas others provide accurate evolutionary distance among organism but are computationally exhaustive.


2019 ◽  
Vol 12 (1) ◽  
pp. 30-39
Author(s):  
Siti Amiroch ◽  
M. Syaiful Pradana ◽  
M. Isa Irawan ◽  
Imam Mukhlash

Background:Multiple sequence alignment is a method of getting genomic relationships between 3 sequences or more. In multiple alignments, there are 3 mutation network analyses, namely topological network system, mutation region network and network system of mutation mode. In general, the three analyses show stable and unstable regions that map mutation regions. This area of ​​mutation is described further in a phylogenetic tree which simultaneously illustrates the path of the spread of an epidemic, the Severe Acute Respiratory Syndrome (SARS) epidemic. The process of spreading the SARS viruses, in this case, is described as the process of phylogenetic tree formation, and as a novelty of this research, multiple alignments in the process are analyzed in detail and then optimized with genetic algorithms.Methods:The data used to form the phylogenetic tree for the spread of the SARS epidemic are 14 DNA sequences which are then optimized by using genetic algorithms. The phylogenetic tree is constructed by using the neighbor-joining algorithm with a distance matrix that the intended distance is the genetic distance obtained from sequence alignment by using the Needleman Wunsch Algorithm.Results & Conclusion:The results of the analysis obtained 3649 stable areas and 19 unstable areas. The results of phylogenetic tree from the network system analysis indicated that the spread of the SARS epidemic extended from Guangzhou 16/12/02 to Zhongshan 27/12/02, then spread simultaneously to Guangzhou 18/02/03 and Guangzhou hospital. After that, the virus reached Metropole, Zhongshan, Hongkong, Singapore, Taiwan, Hong kong, and Hanoi which then continued to Guangzhou 01/01/03 and Toronto at once. The results of the mutation region network system demonstrate decomposition of orthogonal mutations in the 1st order arc.


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