Efficient sequence alignment against millions of prokaryotic genomes with LexicMap

Area of Science:

• Bioinformatics
• Genomics
• Computational Biology

Background:

• Microbial sequence databases are rapidly expanding, challenging current alignment tool capabilities.
• Efficiently querying large prokaryotic genome datasets is crucial for biological research.

Purpose of the Study:

• To introduce LexicMap, a novel nucleotide sequence alignment tool.
• To enable efficient querying of moderate-length sequences against massive microbial genome databases.

Main Methods:

• LexicMap utilizes a small set of probe k-mers to efficiently sample and index large databases.
• A hierarchical index stores seed k-mers, enabling fast and low-memory sequence alignment.
• The tool is designed for querying sequences like genes, plasmids, or long reads.

Main Results:

• LexicMap demonstrates comparable accuracy to state-of-the-art alignment methods.
• The tool offers significantly greater speed and lower memory consumption.
• It successfully scales to query millions of bacterial genomes within minutes.

Conclusions:

• LexicMap provides a scalable and efficient solution for microbial sequence alignment.
• The tool's performance is beneficial for diverse biological applications, including epidemiology, ecology, and evolution.
• It addresses the growing challenge of analyzing large-scale genomic data.