Pangenome graphs improve the analysis of rare genetic diseases

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 against reference genomes with increased sensitivity and also enables the assembly of personal and graph genomes. We leveraged standard reference genomes, publicly available human haploid assemblies (n=94), together with a large collection of HiFi-GS data from a rare disease program (Genomic Answers for Kids, GA4K, n=574 assemblies). These data allowed us to build a deep population graph genome distinguishing very rare SVs from recurrent polymorphisms. Using graphs to discover SVs, we obtained a higher level of reproducibility than that obtained by the standard reference approach. We observed over 200,000 SV alleles unique to the rare disease GA4K cohort, including nearly 1,000 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 novel diagnostic SV in KMT2E in a patient demonstrating use of personal assemblies coupled with pangenome graphs as a new handle for rare disease genomics. ### Competing Interest Statement Juniper Lake is a current or past employee of Pacific Biosciences. ### Funding Statement This work was made possible by the generous gifts to Children's Mercy Research Institute and Genomic Answers for Kids program at Children's Mercy Kansas City. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Institutional Review Board (IRB) of Children's Mercy Kansas City gave ethical approval for this work (Study#11120514). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data are accessible through DbGaP controlled access.