Identifying genes within pathways in unannotated genomes with PaGeSearch

Area of Science:

• Genomics
• Bioinformatics
• Comparative Genomics

Background:

• Accurate gene identification and comparison across species are crucial for biological research.
• Genome annotation is resource-intensive, and sequence similarity searches can produce false positives.

Purpose of the Study:

• To introduce Pathway Gene Search (PaGeSearch), a novel tool for identifying genes from predefined lists within genomes.
• To improve the accuracy and efficiency of gene ortholog identification, particularly for genes within specific biological pathways.

Main Methods:

• PaGeSearch employs an initial sequence similarity search to locate relevant genomic regions.
• It then utilizes targeted gene prediction and neural network-based filtering to refine results.
• The tool is designed for application across mammals, fish, birds, eudicotyledons, and Liliopsida.

Main Results:

• PaGeSearch demonstrates superior sensitivity and positive/negative predictive values compared to GeMoMa and miniprot.
• It achieves higher exon coverage for predicted gene models than existing tools.
• The tool shows resilience to variations in genome assembly quality (chromosome, scaffold, contig).

Conclusions:

• PaGeSearch offers a more accurate and sensitive method for identifying pathway-specific genes and their orthologs across diverse species.
• Its robustness across different assembly levels and higher exon coverage make it a valuable tool for genomic research.