A 515,579-Genome Reference Panel Improves Rare-Variant Imputation Across Multiple Underrepresented Populations
- 1Children's National Hosptial
Abstract
Genotype imputation remains essential for large-scale human genetics studies, but its performance is limited by the size and ancestral diversity of available reference panels, reducing accuracy for rare variants and underrepresented populations. Here, we present a cloud-based imputation service built on a multi-ancestry reference panel derived from 515,579 jointly phased genomes from the All of Us (N=414,830) and National Human Genome Research Institutes Analysis, Visualization, and Informatics Lab-space (AnVIL, N=100,749) datasets. The All of Us + AnVIL reference panel is highly diverse and includes 261,163 participants most genetically similar to non-European reference populations, spanning 665,398,839 high-quality autosomal sites, representing a nearly 50% increase over TOPMed, the previous largest imputation service. Across multiple ancestry groups, the panel enables accurate imputation (empirical R{superscript 2} > 0.8) for variants with allele frequencies as low as 0.2%, extending reliable imputation into the rare-variant frequency spectrum, including allele frequencies down to 0.002% and 0.006% for samples with European ancestry and African ancestry in the United States, respectively. Compared with TOPMed, the panel improves imputation accuracy across all ancestry groups except Africans, and recovers additional trait-associated variants not represented in existing reference panels. To facilitate broad community access while preserving participant privacy, we deploy the panel through a secure cloud-based imputation platform using privacy-preserving recombined haplotypes. This resource establishes a new foundation for genome-wide association studies (GWAS) and fine-mapping, especially in previously underrepresented populations.
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BibTeX
@misc{ivankovic2026515579genome,
title = {{A 515,579-Genome Reference Panel Improves Rare-Variant Imputation Across Multiple Underrepresented Populations}},
author = {F. Ivankovic and A. Ko and M. M. Aster and M. K. Balaconis and E. Banks and M. Bemis and K. R. Cibulskis and K. Degatano and L. D. Gauthier and G. Grant and A. Hatcher and C. Kachulis and K. J. Karczewski and S. M. Labrecque and J. Lawson and C. Liao and R. Magner and R. Munshi and M. C. Schatz and P. M. Schultz and S. P. Shah and E. A. Sheets and K. Tibbetts and K. A. Vernest and R. Ye and S. Gabriel and N. J. Lennon and B. M. Neale and B. L. Browning and L. T. Lichtenstein},
howpublished = {medRxiv},
year = {2026},
month = aug,
doi = {10.64898/2026.08.25.26361247},
url = {https://www.medrxiv.org/content/10.64898/2026.08.25.26361247v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - A 515,579-Genome Reference Panel Improves Rare-Variant Imputation Across Multiple Underrepresented Populations
AU - F. Ivankovic
AU - A. Ko
AU - M. M. Aster
AU - M. K. Balaconis
AU - E. Banks
AU - M. Bemis
AU - K. R. Cibulskis
AU - K. Degatano
AU - L. D. Gauthier
AU - G. Grant
AU - A. Hatcher
AU - C. Kachulis
AU - K. J. Karczewski
AU - S. M. Labrecque
AU - J. Lawson
AU - C. Liao
AU - R. Magner
AU - R. Munshi
AU - M. C. Schatz
AU - P. M. Schultz
AU - S. P. Shah
AU - E. A. Sheets
AU - K. Tibbetts
AU - K. A. Vernest
AU - R. Ye
AU - S. Gabriel
AU - N. J. Lennon
AU - B. M. Neale
AU - B. L. Browning
AU - L. T. Lichtenstein
PY - 2026
DA - 2026/08/25
PB - medRxiv
DO - 10.64898/2026.08.25.26361247
UR - https://www.medrxiv.org/content/10.64898/2026.08.25.26361247v1
AB - Genotype imputation remains essential for large-scale human genetics studies, but its performance is limited by the size and ancestral diversity of available reference panels, reducing accuracy for rare variants and underrepresented populations. Here, we present a cloud-based imputation service built on a multi-ancestry reference panel derived from 515,579 jointly phased genomes from the All of Us (N=414,830) and National Human Genome Research Institutes Analysis, Visualization, and Informatics Lab-space (AnVIL, N=100,749) datasets. The All of Us + AnVIL reference panel is highly diverse and includes 261,163 participants most genetically similar to non-European reference populations, spanning 665,398,839 high-quality autosomal sites, representing a nearly 50% increase over TOPMed, the previous largest imputation service. Across multiple ancestry groups, the panel enables accurate imputation (empirical R{superscript 2} > 0.8) for variants with allele frequencies as low as 0.2%, extending reliable imputation into the rare-variant frequency spectrum, including allele frequencies down to 0.002% and 0.006% for samples with European ancestry and African ancestry in the United States, respectively. Compared with TOPMed, the panel improves imputation accuracy across all ancestry groups except Africans, and recovers additional trait-associated variants not represented in existing reference panels. To facilitate broad community access while preserving participant privacy, we deploy the panel through a secure cloud-based imputation platform using privacy-preserving recombined haplotypes. This resource establishes a new foundation for genome-wide association studies (GWAS) and fine-mapping, especially in previously underrepresented populations.
ER -