A Complete Diploid Human Genome Benchmark for Personalized Genomics

Authors

• Nancy F. Hansen, National Human Genome Research Institute, National Institutes of Health
• Nathan Dwarshuis, National Institute of Standards and Technology
• Hyun Joo Ji, Johns Hopkins University
• Arang Rhie, National Human Genome Research Institute, National Institutes of Health
• Hailey Loucks, University of California
• Glennis A. Logsdon, Perelman School of Medicine
• Mitchell R. Vallger, University of Washington School of Medicine
• Jessica M. Storer, University of Connecticut, Storrs
• Juhyun Kim, National Institutes of Health
• Eleni Adam, Old Dominion UniversityFollow
• Nicolas Alternose, Stanford University
• Dmitry Antipov, National Human Genome Research Institute, National Institutes of Health
• Mobin Asri, University of California, Santa Cruz
• Sofia Barreira, National Human Genome Research Institute, National Institutes of Health
• Stephanie C. Bohaczuk, University of Washington School of Medicine
• Andrey V. Bzikadze, University of California
• Sara A. Carioscia, Johns Hopkins University
• Andrew Carroll, Google LLC, Mountain View, CA
• Kuan-Hao Chao, Johns Hopkins University
• Yanan Chu, Chinese Academy of Sciences
• Arun Das, Johns Hopkins University
• Peter Ebert, Heinrich-Heine-Universität Düsseldorf
• Adam English, Baylor College of Medicine
• Mark Fleharty, Broad Clinical Labs
• Laura E. Fleming, Broad Clinical Labs
• Giulio Formenti, The Rockefeller University
• Andrea Guarracino, Bioinnovation and Genome Sciences, the Translational Genomics Research Institute (TGen), Phoenix, Az
• Gabrielle A. Hartley, University of Connecticut
• Katharine Jenike, Johns Hopkins University
• Jenna Kalleberg, University of Missouri – Columbia
• Yu Kang, Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing
• Robert King, Oxford Nanopore Technologies
• Josipa Lipovac, University of Zagreb
• Mira Mastoras, University of California, Santa Cruz
• Matthew W. Mitchell, Coriell Institute for Medical Research
• Shloka Negi, University of California, Santa Cruz
• Nathan D. Olson, National Institute of Standards and Technology
• Keisuke K. Oshima, University of Pennsylvania
• Luis F. Paulin, Baylor College of Medicine
• Brandon D. Pickett, National Human Genome Research Institute, National Institutes of Health
• David Porubsky, University of Washington School of Medicine
• Jane Ranchalis, University of Washington School of Medicine
• Desh Ranjan, Old Dominion UniversityFollow
• Mikko Rautiainen, University of Helsinki
• Harold Riethman, Old Dominion UniversityFollow
• Robert D. Schnabel, University of Missouri – Columbia
• Fritz J. Sedlazeck, Baylor College of Medicine
• Kishwar Shafin, Google LLC
• Mile Sikic, University of Zagreb
• Steven J. Solar, National Human Genome Research Institute, National Institutes of Health
• Alexander P. Sweeten, Johns Hopkins University
• Winston Timp, Johns Hopkins University
• Justin Wagner, National Institute of Standards and Technology
• DongAhn Yoo, University of Washington School of Medicine
• Ying Zhou, Dana-Farber Cancer Institute
• Erik Garrison, University of Tennessee Health Science Center
• Evan E. Eichler, University of Washington School of Medicine
• Michaeel C. Schatz, Johns Hopkins University
• Andrew B. Stergachis, University of Washington School of Medicine
• Rachel J. O'Neill, University of Connecticut - Storrs
• Karen H. Miga, University of California, Santa Cruz
• Steven L. Salzberg, Johns Hopkins University
• Sergey Koren, National Human Genome Research Institute, National Institutes of Health
• Justin M. Zook, National Institute of Standards and Technology, Gaithersburrg, MD
• Adam M. Phillippy, Johns Hopkins University

Document Type

Article

Publication Date

2026

DOI

10.1016/j.cell.2026.06.016

Publication Title

Cell

Volume

189

Issue

16

Pages

4857-4875.e31

Abstract

Human genome sequencing typically relies on mapping reads to a reference genome to call variants, but this approach introduces technical biases, excluding duplicated and structurally polymorphic regions of the genome. To overcome this, we present a telomere-to-telomere genome benchmark with near-perfect accuracy across 99.4% of the diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), which were absent from prior benchmarks. We annotated genes and repeats on both haplotypes, including 19,956 protein-coding genes on the maternal haplotype and 19,190 on the paternal haplotype, and developed new methods to measure the accuracy of reads, phased variant call sets, and assemblies against a diploid reference. Genome-wide analyses show that de novo assembly resolves 2%-7% more sequence and outperforms variant calling accuracy by an order of magnitude, expanding the reach of genomic medicine to the entire genome and enabling a new era of personalized genomics.

Rights

© 2026 The Authors.

This is an open access article under the Creative Commons Attribution 4.0 International (CC-BY 4.0) License.

ORCID

0000-0002-7548-4375 (Adam), 0000-0003-4626-4733 (Riethman)

Original Publication Citation

Hansen, N. F., Dwarshuis, N., Ji, H. J., Rhie, A., Loucks, H., Logsdon, G. A., Vollger, M. R., Storer, J. M., Kim, J., Adam, E., Altemose, N., Antipov, D., Asri, M., Barreira, S., Bohaczuk, S. C., Bzikadze, A. V., Carioscia, S. A., Carroll, A., Chao, K. H.,…Phillippy, A. M. (2026). A complete diploid human genome benchmark for personalized genomics. Cell, 189(16), 4857-4875.e4831. https://doi.org/10.1016/j.cell.2026.06.016 

Repository Citation

Hansen, Nancy F.; Dwarshuis, Nathan; Ji, Hyun Joo; Rhie, Arang; Loucks, Hailey; Logsdon, Glennis A.; Vallger, Mitchell R.; Storer, Jessica M.; Kim, Juhyun; Adam, Eleni; Alternose, Nicolas; Antipov, Dmitry; Asri, Mobin; Barreira, Sofia; Bohaczuk, Stephanie C.; Bzikadze, Andrey V.; Carioscia, Sara A.; Carroll, Andrew; Chao, Kuan-Hao; Chu, Yanan; Das, Arun; Ebert, Peter; English, Adam; Fleharty, Mark; Fleming, Laura E.; Formenti, Giulio; Guarracino, Andrea; Hartley, Gabrielle A.; Jenike, Katharine; Kalleberg, Jenna; Kang, Yu; King, Robert; Lipovac, Josipa; Mastoras, Mira; Mitchell, Matthew W.; Negi, Shloka; Olson, Nathan D.; Oshima, Keisuke K.; Paulin, Luis F.; Pickett, Brandon D.; Porubsky, David; Ranchalis, Jane; Ranjan, Desh; Rautiainen, Mikko; Riethman, Harold; Schnabel, Robert D.; Sedlazeck, Fritz J.; Shafin, Kishwar; Sikic, Mile; Solar, Steven J.; Sweeten, Alexander P.; Timp, Winston; Wagner, Justin; Yoo, DongAhn; Zhou, Ying; Garrison, Erik; Eichler, Evan E.; Schatz, Michaeel C.; Stergachis, Andrew B.; O'Neill, Rachel J.; Miga, Karen H.; Salzberg, Steven L.; Koren, Sergey; Zook, Justin M.; and Phillippy, Adam M., "A Complete Diploid Human Genome Benchmark for Personalized Genomics" (2026). School of Medical Diagnostics & Translational Sciences Publications. 51.
https://digitalcommons.odu.edu/medicaldiagnostics_fac_pubs/51