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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Multiobjective Formulation of Multiple Sequence Alignment for Phylogeny Inference.

Muhammad Ali Nayeem, Md Shamsuzzoha Bayzid, Atif Hasan Rahman

IEEE Transactions on Cybernetics

|October 12, 2020

Summary

This summary is machine-generated.

Multiobjective (MO) formulation of multiple sequence alignment (MSA) improves phylogenetic tree accuracy. Applying phylogeny-aware metrics to MO-MSA selection enhances evolutionary history inference.

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Area of Science:

Computational Biology
Bioinformatics
Evolutionary Biology

Background:

Multiple sequence alignment (MSA) is crucial for homology inference and phylogenetic tree construction.
Traditional single-objective MSA methods can yield discordant evolutionary histories.
Multiobjective (MO) MSA approaches offer a potential solution by optimizing multiple criteria simultaneously.

Purpose of the Study:

To investigate the practical impact of MO formulation in MSA for phylogeny estimation.
To determine if phylogeny-aware metrics can guide MO-MSA selection for improved phylogenetic accuracy.

Main Methods:

Employed popular evolutionary multiobjective optimization algorithms for MSA.
Compared phylogenetic trees inferred from alignments generated by single-objective and MO-MSA methods.
Conducted an extensive experimental study using phylogeny-aware metrics.

Main Results:

Phylogenetic trees from MO-MSA alignments demonstrated significantly higher quality than those from traditional MSA methods.
Even high-quality alignments, by standard measures, may not guarantee accurate phylogenetic tree generation.
A carefully designed experimental study confirmed that phylogeny-aware metrics can guide MO-MSA selection.

Conclusions:

MO formulation of MSA offers a substantial improvement for accurate phylogeny estimation.
Application-aware metrics are essential for selecting appropriate MO-MSA strategies to ensure reliable evolutionary history inference.