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Multifractal and cross-correlation analysis on mitochondrial genome sequences using chaos game representation
N B Thummadi1, S Charutha2, Mayukha Pal3
1Department of Animal Biology, School of Life Sciences, University of Hyderabad, Gachibowli, Hyderabad 500 046, India.
Mitochondrion
|August 10, 2021
Summary
This study reveals multifractality and power-law cross-correlation in mitochondrial genomes across species using a novel method. This analysis aids in understanding evolutionary relationships and has broad applications in genomics and drug development.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Mitochondrial genomes possess complex structures.
- Understanding genomic correlations is crucial for evolutionary studies.
Purpose of the Study:
- To characterize multifractality and power-law cross-correlation in diverse mitochondrial genomes.
- To develop and apply an integrative approach for phylogenetic analysis.
Main Methods:
- Combined chaos game representation theory with 2D-multifractal detrended cross-correlation analysis.
- Analyzed 32 mitochondrial genomes from various species.
- Performed cluster analysis on scaling exponents to generate a dendrogram.
Main Results:
- All analyzed mitochondrial genomes exhibited multifractal characteristics.
- Evidence of power-law cross-correlation behavior was observed across the datasets.
- Cluster analysis successfully identified class affiliations, visualized through a dendrogram.
Conclusions:
- The integrative approach effectively characterizes mitochondrial genome complexity.
- This method offers a novel tool for understanding phylogeny across kingdoms.
- Potential applications include protein sequence analysis, mRNA studies, next-generation sequencing, and drug development.
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