Pangenome graphs improve the analysis of structural variants in rare genetic diseases

Cristian Groza, Carl Schwendinger-Schreck, Warren A. Cheung, Emily G. Farrow, Isabelle Thiffault, Juniper Lake, William B. Rizzo, Gilad Evrony, Tom Curran, Guillaume Bourque () and Tomi Pastinen ()
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Cristian Groza: McGill University
Carl Schwendinger-Schreck: Children’s Mercy Hospital and Research Institute
Warren A. Cheung: Children’s Mercy Hospital and Research Institute
Emily G. Farrow: Children’s Mercy Hospital and Research Institute
Isabelle Thiffault: Children’s Mercy Hospital and Research Institute
Juniper Lake: Pacific Biosciences
William B. Rizzo: Nebraska Medical Center
Gilad Evrony: New York University Grossman School of Medicine
Tom Curran: Children’s Mercy Research Institute
Guillaume Bourque: McGill University
Tomi Pastinen: Children’s Mercy Hospital and Research Institute

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: Abstract Rare DNA alterations that cause heritable diseases are only partially resolvable by clinical next-generation sequencing due to the difficulty of detecting structural variation (SV) in all genomic contexts. Long-read, high fidelity genome sequencing (HiFi-GS) detects SVs with increased sensitivity and enables assembling personal and graph genomes. We leverage standard reference genomes, public assemblies (n = 94) and a large collection of HiFi-GS data from a rare disease program (Genomic Answers for Kids, GA4K, n = 574 assemblies) to build a graph genome representing a unified SV callset in GA4K, identify common variation and prioritize SVs that are more likely to cause genetic disease (MAF

Date: 2024
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DOI: 10.1038/s41467-024-44980-2

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