Robust expansion of phylogeny for fast-growing genome sequence data

Area of Science:

• Phylogenetics
• Bioinformatics
• Genomics

Background:

• Massive sequencing of pathogens like SARS-CoV-2 necessitates efficient phylogenetic tree updating.
• De novo phylogenetic inference is computationally intensive for large datasets.

Purpose of the Study:

• To develop and evaluate TIPars, a novel method for efficiently inserting new samples into existing phylogenies.
• To assess TIPars' accuracy and performance compared to other phylogenetic placement methods.

Main Methods:

• TIPars integrates parsimony analysis with pre-computed ancestral sequences.
• The method was benchmarked on four diverse datasets, including SARS-CoV-2 genomes.

Main Results:

• TIPars inserted 100 SARS-CoV-2 genomes into a 100k-taxa tree in 21 seconds.
• Achieved high accuracy for moderately similar sequences; second best for highly similar and divergent sequences.

Conclusions:

• TIPars provides an efficient and accurate approach for expanding phylogenies.
• The method has broad biological applications beyond SARS-CoV-2 genomics.