PG4AD: Scaling up pangenome graph for genotyping complex structural variations for Alzheimer's disease genetics

/ABSTRACT The Human Pangenome Reference Consortium (HPRC) has built a tremendously valuable resource of high- quality human pangenome reference assemblies of individuals and their corresponding pangenome graph that greatly reduced reference biases. However, uptake and utilization of the HPRC pangenome resources by the human genetics community for the analysis of complex structural variations (SV) remains limited. Most existing SV methods are based on existing catalogs of known SVs represented in linear reference-based VCF files, and thus still suffer from reference biases. Lack of methods and tools for better leveraging the reference pangenome graph is a critical gap that hinders the realization of the full potential of pangenome-enabled genetic studies, including those for Alzheimer’s disease (AD) and other complex traits. We will address these challenges by developing path-based algorithms for genotyping complex SVs and extending the pangenome reference using AD genetics data. We will translate our expertise and experience in developing positional Burrows-Wheeler transform (PBWT) algorithms to its pangenome counterpart, the GBWT (Graph Burrows- Wheeler transform), a proven data structure already in use in the HPRC consortium. First, we will develop GBWT-block-based methods for identifying frequent and long SV haplotype in pangenome graphs for genotyping and panel smoothing. Second, we will develop SV genotype imputation methods based on pangenome GBWT. Third, we will apply the developed methods to the Alzheimer’s disease sequencing project (ADSP) data to empower AD genetics research. We will build PG4ADSP, an expanded approximate reference pangenome panel and its PBWT from ADSP data. We will identify frequent and long SV haplotypes in ADSP and conduct SV-GWAS to identify SV loci associated with AD risks. Finally, we will rigorously evaluate our methods and build software for broad use. Successful completion of this project will broaden the adoption of HPRC resources by the human genetics and AD genetics community. Project Number: 1U01AG098387-01 | Fiscal Year: 2026 | NIH Institute/Center: National Institute on Aging (NIA) | Principal Investigator: Degui Zhi (+1 co-PI) | Institution: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON, HOUSTON, TX | Award Amount: $556,359 | Activity Code: U01 | Study Section: Special Emphasis Panel[ZRG1 MGG-W (50)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11295134