Read2Tree: scalable and accurate phylogenetic trees from raw reads

Area of Science:

• Evolutionary Biology
• Genomics
• Bioinformatics

Background:

• Phylogenetic tree inference is crucial but computationally intensive, requiring high-quality sequencing data and complex pipelines.
• Current phylogenomic methods face challenges with computational cost, labor, and data quality constraints.

Approach:

• Read2Tree is an assembly-free tool that processes raw sequencing reads directly to identify corresponding genes.
• This novel approach bypasses traditional assembly and annotation steps, streamlining phylogenetic analysis.

Key Points:

• Read2Tree demonstrated 10-100x speed improvement over conventional methods across diverse datasets.
• Accuracy was comparable or superior, especially with lower sequencing coverage or closely related species.
• Successfully reconstructed a yeast tree of life and classified diverse Coronaviridae samples, including SARS-CoV-2.

Conclusions:

• Read2Tree offers a fast, accurate, and versatile solution for phylogenetic inference.
• The tool enables large-scale comparative genomics by overcoming existing computational and data quality barriers.