Jukes-Cantor Correction for Phylogenetic Tree Reconstruction

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Abstract

Phylogenetic tree reconstruction relies on accurate estimation of evolutionary distances between sequences. However, the observed Hamming distance between sequences can be misleading due to saturation, where multiple substitutions at the same site obscure the true evolutionary history. The Jukes-Cantor correction method addresses this by accounting for multiple substitutions, providing a more accurate representation of evolutionary distance. This study investigates the application of the Jukes-Cantor correction to the Hamming distance of genetic sequences in a case study, highlighting its impact on phylogenetic tree reconstruction. Our results demonstrate that the Jukes-Cantor correction significantly improves the accuracy of phylogenetic inference, particularly for sequences with substantial evolutionary divergence. However, the model’s reliance on simplifying assumptions, such as equal substitution rates and lack of base composition bias, limits its applicability to sequences with moderate levels of divergence. This study stands as a bedrock for further research into more complex models that can account for model violations and provide more accurate estimations of evolutionary distances for highly divergent sequences.
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Abstract Phylogenetic tree reconstruction relies on accurate estimation of evolutionary distances between sequences. However, the observed Hamming distance between sequences can be misleading due to saturation, where multiple substitutions at the same site obscure the true evolutionary history. The Jukes-Cantor correction method addresses this by accounting for multiple substitutions, providing a more accurate representation of evolutionary distance. This study investigates the application of the Jukes-Cantor correction to the Hamming distance of genetic sequences in a case study, highlighting its impact on phylogenetic tree reconstruction. Our results demonstrate that the Jukes-Cantor correction significantly improves the accuracy of phylogenetic inference, particularly for sequences with substantial evolutionary divergence. However, the model’s reliance on simplifying assumptions, such as equal substitution rates and lack of base composition bias, limits its applicability to sequences with moderate levels of divergence. This study stands as a bedrock for further research into more complex models that can account for model violations and provide more accurate estimations of evolutionary distances for highly divergent sequences. Competing Interest Statement The authors have declared no competing interest. Footnotes Email(s):ugbene.ifeanyi{at}fupre.edu.ng

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