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Phylogenetic Analysis

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Abstract

In this chapter, the authors attempt to understand the underlying phylogeny principle and how researchers implement diverse methods to discover the appropriate phylogeny. Results obtained revealed that phylogenetic trees reflect evolutionary past as a canonical framework. Phylogenetic tree building step essentially comprises of five steps: (a) selecting molecular markers; (b) multiple sequence alignment; (c) determining the best evolutionary model; (d) determination of tree building method; and (e) assessment of tree reliability. Phylogenetic trees have various functional uses in different biological fields, such as conservation biology, epidemiology, forensics, cancer evolution, HIV transmission, gene expression prediction, protein structure prediction, and drug design. However, researchers face different challenges for generating a more accurate tree, like memory efficiency and implementation and optimization of the likelihood function. The authors believe, in the near future, the development of exciting new algorithms, which dramatically reduce the necessary amount of likeliness assessment, combined with enhanced knowledge of previously described high-performance machine problems in the group, is likely to detect more accurate phylogenetic tree that include 10,000–20,000 sequences. Additionally, it will also permit the tree inferences on medium-sized PC.

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Abbreviations

BI:

Bayesian inference

cpDNA:

Chloroplast DNA

dN:

Non-synonymous

dS:

Synonymous

GBS:

Genotyping-by-sequencing

HTU:

Hypothetical taxonomic units

ITS:

Internal transcribed spacer

JC:

Jukes and Cantor

LCA:

Last common ancestor

LUCA:

Last universal common ancestor

ML:

Maximum-like

MSA:

Multiple sequence alignment

OTUS:

Operational taxonomic units

PCR:

Polymerase chain reaction

UCES:

Ultra-conserved elements

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Figure 9.1b has been used under the terms of the Creative Commons Attribution License [20].

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Authors and Affiliations

  1. Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, Odisha, India

    Manoj Kumar Gupta, Gayatri Gouda, S. Sabarinathan, Ravindra Donde & Lambodar Behera

  2. Department of Seed Science and Technology, College of Agriculture, Odisha University of Agriculture and Technology, Bhubaneswar, Odisha, India

    S. Sabarinathan

  3. Department of Biotechnology and Bioinformatics, Yogi Vemana University, Kadapa, Andhra Pradesh, India

    N. Rajesh & Ramakrishna Vadde

  4. District Headquarter Hospital, Ganjam, Odisha, India

    Pallabi Pati

  5. Department of Zoology, Khallikote Autonomous College, Ganjam, Odisha, India

    Sushil Kumar Rathore

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    Manoj Kumar Gupta

  2. Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, Odisha, India

    Lambodar Behera

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Gupta, M.K. et al. (2021). Phylogenetic Analysis. In: Gupta, M.K., Behera, L. (eds) Bioinformatics in Rice Research. Springer, Singapore. https://doi.org/10.1007/978-981-16-3993-7_9

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