Toward a standardized framework for pangenome graph evaluation: assessing crop plant pangenome variation graph...

Area of Science:

• Genomics
• Bioinformatics

Background:

• Pangenomes are essential for exploring species-wide genetic diversity and identifying core and variable genes.
• Understanding pangenome graph assembly is critical for comprehensive genomic analysis.

Purpose of the Study:

• To compare the performance of three key pangenome graph assembly pipelines: Minigraph, PGGB, and Minigraph-Cactus.
• To introduce and validate novel metrics for evaluating pangenome graph quality, including completeness, duplication levels, and structural variant fidelity.

Main Methods:

• Utilized publicly available Sorghum datasets for comparative analysis.
• Developed and applied tailored metrics to assess pangenome graph completeness, duplication, and structural variant accuracy.
• Extended metric application to pangenome graphs of soybean, barley, and oilseed rape.

Main Results:

• Evaluated the efficacy of Minigraph, PGGB, and Minigraph-Cactus in handling diverse genomic features within Sorghum.
• Provided detailed insights into the strengths and limitations of each pangenome assembly tool.
• Demonstrated the utility of the developed metrics for objective and robust pangenome graph comparisons across multiple crop species.

Conclusions:

• This benchmarking study enhances the understanding of pangenome assembly tools.
• Established a foundation for standardized evaluation metrics in pangenome graph analysis.
• Future work will focus on optimizing tool selection for downstream applications like genome-wide association studies to improve analytical accuracy.