GeneMiner: A tool for extracting phylogenetic markers from next-generation sequencing data

Area of Science:

• Evolutionary Biology
• Bioinformatics

Background:

• Next-generation sequencing (NGS) has generated vast genomic and transcriptomic data, crucial for evolutionary biology.
• Extracting molecular markers for phylogenetic, evolutionary, and ecological studies from NGS data is vital.
• Challenges exist in accurately and efficiently obtaining these markers, especially for non-model organisms lacking well-annotated reference genomes.

Purpose of the Study:

• To present GeneMiner, an improved tool for extracting phylogenetic molecular markers from NGS data.
• To address limitations in marker extraction for non-model organisms and distant references.
• To provide a user-friendly, efficient, and accurate solution for evolutionary biology research.

Main Methods:

• GeneMiner integrates reference-guided de Bruijn graph assembly with seed self-discovery and greedy extension.
• A parameter-bootstrap method is employed for verification, mitigating issues with distant references.
• The tool processes transcriptomic, genomic, and other NGS data.

Main Results:

• GeneMiner demonstrated accurate acquisition of phylogenetic molecular markers for plants.
• Performance was validated using both experimental and simulation data.
• The tool is user-friendly, fast, memory-efficient, and cross-platform compatible (Linux, Windows, macOS).

Conclusions:

• GeneMiner effectively overcomes challenges in obtaining phylogenetic markers from NGS data, particularly for non-model organisms.
• The tool enhances the study of evolutionary biology by providing accurate and efficient marker extraction.
• Source code is publicly available on GitHub and Gitee for transparency and accessibility.