TreeProfiler: large-scale metadata profiling along gene and species trees

Area of Science:

• Comparative genomics
• Bioinformatics
• Evolutionary biology

Background:

• Phylogenetic profiling is crucial for inferring gene function, ancestral states, and ecological associations.
• Existing tools lack scalability and robust methods for summarizing traits at internal tree nodes.

Purpose of the Study:

• Introduce TreeProfiler, a novel tool for automated annotation and exploration of biological traits on large phylogenetic trees.
• Address limitations of existing profiling tools regarding scalability and trait summarization.

Main Methods:

• TreeProfiler supports profiling of custom continuous and discrete traits.
• Incorporates ancestral character reconstruction and phylogenetic signal tests.
• Integrates genomic features like sequence alignments, protein domains, and functional annotations.

Main Results:

• Demonstrated efficient handling of massive datasets, including over 400,000 sequences for the methyl-accepting chemotaxis protein family.
• Successfully profiled the relative abundance of nearly 125,000 species across 51 biomes.
• Showcased TreeProfiler's utility beyond traditional phylogenetic profiling.

Conclusions:

• TreeProfiler provides a scalable and versatile solution for analyzing biological traits on phylogenetic trees.
• Facilitates automated annotation and interactive exploration of complex genomic and ecological data.
• Offers advanced features for comparative genomics and evolutionary research.