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

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 < 0.01). Using graphs, we obtain a higher level of reproducibility than the standard reference approach. We observe over 200,000 SV alleles unique to GA4K, including nearly 1000 rare variants that impact coding sequence. With improved specificity for rare SVs, we isolate 30 candidate SVs in phenotypically prioritized genes, including known disease SVs. We isolate a novel diagnostic SV in KMT2E, demonstrating use of personal assemblies coupled with pangenome graphs for rare disease genomics. The community may interrogate our pangenome with additional assemblies to discover new SVs within the allele frequency spectrum relevant to genetic diseases.

Expanded methylome and quantitative trait loci detection by long-read profiling of personal DNA

“…Moreover, computational methods that can compile personalized genomes into pangenome graphs, can capture megabases of non-reference sequences and integrate SVs from a cohort of genomes (Erik Garrison et al 2023; Li, Feng, and Chu 2020; Hickey et al 2023). The publication of the draft human pangenome reference also facilitates the study of SVs and their features at scale in a range of datasets (Liao et al 2023; Groza et al 2024). Indeed, such developments allow mapping epigenomic data directly to SVs and exploring the epigenetic status of regions that were not included in the reference genome (Groza et al 2023; 2020).…”