Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

Phylogenetics Overview Phylogenetic analysis reconstructs the evolutionary history of biological sequences (genes, proteins, genomes) by inferring the branching pattern of descent. This skill covers the standard pipeline: 1. MAFFT — Multiple sequence alignment 2. IQ TREE 2 — Maximum likelihood tree inference with model selection 3. FastTree — Fast approximate maximum likelihood (for large datasets) 4. ETE3 — Python library for tree manipulation and visualization Installation: When to Use This Skill Use phylogenetics when: Evolutionary relationships : Which organism/gene is most closely related to my sequence? Viral phylodynamics : Trace outbreak spread and estimate transmission dates Protein family analysis : Infer evolutionary relationships within a gene family Horizontal gene transfer detection : Identify genes with discordant species/gene trees Ancestral sequence reconstruction : Infer ancestral protein sequences Molecular clock analysis : Estimate divergence dates using temporal sampling GWAS companion : Place variants in evolutionary context (e.g., SARS CoV 2 variants) Microbiology : Species phylogeny from 16S rRNA or core genome phylogeny Standard Workflow 1. Multiple Sequence Alignment with MAFFT 2. Trim Alignment (Optional but Recommended) 3. IQ TREE 2 — Maximum Likelihood Tree 4. FastTree — Fast Approximate ML For large datasets ( 1000 sequences) where IQ TREE is too slow: 5. Tree Analysis and Visualization with ETE3 6. Complete Analysis Script IQ TREE Model Guide DNA Models Model Description Use case GTR+G4 General Time Reversible + Gamma Most flexible DNA model HKY+G4 Hasegawa Kishino Yano + Gamma Two rate model (common) TrN+G4 Tamura Nei Unequal transitions JC Jukes Cantor Simplest; all rates equal Protein Models Model Description Use case LG+G4 Le Gascuel + Gamma Best average protein model WAG+G4 Whelan Goldman Widely used JTT+G4 Jones Taylor Thornton Classical model Q.pfam+G4 pfam trained For Pfam like protein families Q.bird+G4 Bird specific Vertebrate proteins Tip: Use m TEST to let IQ TREE automatically select the best model. Best Practices Alignment quality first : Poor alignment → unreliable trees; check alignment manually Use linsi for small (<200 seq), fftns or auto for large alignments Model selection : Always use m TEST for IQ TREE unless you have a specific reason Bootstrap : Use ≥1000 ultrafast bootstraps ( B 1000 ) for branch support Root the tree : Unrooted trees can be misleading; use outgroup or midpoint rooting FastTree for 5000 sequences : IQ TREE becomes slow; FastTree is 10–100× faster Trim long alignments : TrimAl removes unreliable columns; improves tree accuracy Check for recombination in viral/bacterial sequences before building trees ( RDP4 , GARD ) Additional Resources MAFFT : https://mafft.cbrc.jp/alignment/software/ IQ TREE 2 : http://www.iqtree.org/ Tutorial: https://www.iqtree.org/workshop/molevol2022 FastTree : http://www.microbesonline.org/fasttree/ ETE3 : http://etetoolkit.org/ FigTree (GUI visualization): https://tree.bio.ed.ac.uk/software/figtree/ iTOL (web visualization): https://itol.embl.de/ MUSCLE (alternative aligner): https://www.drive5.com/muscle/ TrimAl (alignment trimming): https://vicfero.github.io/trimal/