Founder reconstruction enables scalable and seamless pangenomic analysis

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Standard variant calling workflows rely on single reference sequences, limiting their effectiveness for complex genomic analyses.
• Integrating pangenomic information into variant calling presents scalability and workflow integration challenges.

Purpose of the Study:

• To develop a scalable and accurate variant calling workflow that leverages pangenomic information.
• To address the limitations of single-reference-based variant calling in resequencing projects.

Main Methods:

• Developed PanVC, a workflow based on a multiple alignment of reference sequences using founder sequences.
• Implemented a hybrid indexing scheme with general-purpose read aligners for scalability.
• Integrated with established variant callers like GATK and BCFtools.

Main Results:

• PanVC achieves scalability by consolidating duplicate sequence regions into a founder multiple alignment.
• The workflow demonstrates accuracy in variant calling by utilizing comprehensive pangenomic data.
• Individual components of the workflow, such as vcf2multialign, offer broader applications in pangenome analysis.

Conclusions:

• PanVC provides a robust and scalable solution for variant calling, enhancing genomic analysis.
• The developed tools and methods pave the way for novel pangenome analysis workflows.
• Open access to tools and reproducible experiment instructions are provided.