Efficient and Robust Search of Microbial Genomes via Phylogenetic Compression

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Vast, rapidly growing collections of sequenced genomes are essential for life sciences research.
• Existing search tools struggle to handle the scale of modern genomic datasets, hindering efficient data retrieval.

Purpose of the Study:

• To introduce phylogenetic compression, a novel technique for efficiently searching and compressing large microbial genome collections.
• To develop a practical pipeline for searching phylogeny-compressed genomic data.

Main Methods:

• Phylogenetic compression utilizes evolutionary history to guide data compression and searching.
• The technique is applied to assemblies, de Bruijn graphs, and k-mer indexes.
• A BLAST-like search pipeline was developed for phylogeny-compressed reference data.

Main Results:

• Lossless phylogenetic compression achieves one to two orders of magnitude improvement in compression ratios for large genomic datasets.
• The developed search pipeline can align genes, plasmids, or entire sequencing experiments against millions of bacterial genomes within hours on standard desktop computers.

Conclusions:

• Phylogenetic compression offers a scalable solution for searching massive genomic datasets.
• This technique has broad applications in computational biology and can inform future genomics infrastructure design.