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Anchor-Based Whole Genome Phylogeny (ABWGP): A Tool for Inferring Evolutionary Relationship among Closely Related Microorganims
Authors:Anchal Vishnoi  Rahul Roy  Hanumanthappa K. Prasad  Alok Bhattacharya
Affiliation:1. School of Information Technology, Center for Computational Biology and Bioinformatics, Jawaharlal Nehru University, New Delhi, India.; 2. Indian Statistical Institute, New Delhi, India.; 3. Department of Biotechnology, All India Institute of Medical Sciences (AIIMS), New Delhi, India.; 4. School of Life Sciences, Jawaharlal Nehru University, New Delhi, India.;American Museum of Natural History, United States of America
Abstract:
Phenotypic behavior of a group of organisms can be studied using a range of molecular evolutionary tools that help to determine evolutionary relationships. Traditionally a gene or a set of gene sequences was used for generating phylogenetic trees. Incomplete evolutionary information in few selected genes causes problems in phylogenetic tree construction. Whole genomes are used as remedy. Now, the task is to identify the suitable parameters to extract the hidden information from whole genome sequences that truly represent evolutionary information. In this study we explored a random anchor (a stretch of 100 nucleotides) based approach (ABWGP) for finding distance between any two genomes, and used the distance estimates to compute evolutionary trees. A number of strains and species of Mycobacteria were used for this study. Anchor-derived parameters, such as cumulative normalized score, anchor order and indels were computed in a pair-wise manner, and the scores were used to compute distance/phylogenetic trees. The strength of branching was determined by bootstrap analysis. The terminal branches are clearly discernable using the distance estimates described here. In general, different measures gave similar trees except the trees based on indels. Overall the tree topology reflected the known biology of the organisms. This was also true for different strains of Escherichia coli. A new whole genome-based approach has been described here for studying evolutionary relationships among bacterial strains and species.
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