Phylogenetic Tree Building in MEGA X

Overview

This lecture covers building phylogenetic trees using MEGA X, including proper sequence alignment, model selection, tree construction methods, and tips for managing data quality.

Steps for Building Phylogenies in MEGA X

• Define your research problem, select taxa and markers, and download relevant sequences.
• Perform multiple sequence alignment to establish homology among sequences.
• Build phylogenetic trees and test tree topology for consistency.
• Interpret trees to extract biological information.

Sequence Alignment and Homology

• Homology means similarity due to common ancestry; similarity alone does not confirm homology.
• Multiple alignment assumes homology and does not test it.
• It is critical to ensure sequences are homologous before alignment.
• Codon-based alignments reduce alignment errors in protein-coding genes.

Alignment Options in MEGA X

• Four alignment options: ClustalW, MUSCLE, and both with codon-based alignment.
• Default alignment parameters are usually sufficient; large changes with parameter tweaks indicate poor homology.
• Check and edit alignments to verify correct translation and identify variable, conserved, and informative sites.

Evolutionary Models for Tree Building

• Poisson (Jukes-Cantor) model: simplest, assumes equal rates and base frequencies.
• More complex models (e.g., Hasegawa, GTR) account for varying rates and base compositions.
• Gamma parameter adjusts for rate variation among sites and can be added to any model.

Model Selection and Data Exploration in MEGA X

• Use the “Explore Active Data” tool to compute distances and inspect model suitability.
• Remove highly divergent or problematic taxa before analysis.
• Assign taxa groups and sequence regions (e.g., exons, introns) for targeted analysis.

Building and Testing Trees

• Construct trees using maximum likelihood or distance-based methods (e.g., neighbor-joining).
• Select evolutionary models and parameters (substitution models, gamma, codon positions).
• Use bootstrapping to test tree robustness, but this may increase computation time.
• Visualize, root, and annotate trees for clearer presentation.

Handling Missing Data and Alignment Quality

• Set site coverage cutoffs (e.g., ≥70% coverage) to manage missing data.
• Use tools like GUIDANCE or Gblocks to assess and improve alignment quality by identifying poorly aligned regions or sequences.

Key Terms & Definitions

• Homology — similarity due to shared ancestry.
• Multiple Sequence Alignment — arrangement of sequences to identify homologous regions.
• Codon-based Alignment — translation of nucleotide sequences into amino acids for alignment, then back-translation.
• Evolutionary Model — mathematical model describing sequence evolution (e.g., Jukes-Cantor, GTR).
• Gamma Parameter — adjusts for rate variation across alignment sites.
• Bootstrapping — resampling method to assess tree reliability.
• Neighbor-Joining — distance-based clustering method for tree construction.

Action Items / Next Steps

• Explore MEGA X’s alignment and tree-building features with your own sequence data.
• Use “Explore Active Data” to review and clean your dataset before analysis.
• Practice selecting appropriate evolutionary models and adjusting for missing data coverage.
• Review GUIDANCE or Gblocks for advanced alignment quality checks.