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September 23, 202528 citationsOpen Access

A complete diploid human genome benchmark for personalized genomics

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NHNancy F. HansenNDNathan DwarshuisHJHyun Joo Ji

Key Points

  • The benchmark achieves near-perfect accuracy across 99.4% of the diploid HG002 genome, enhancing variant calling.
  • This study adds critical genomic regions not covered by previous benchmarks, including 15.3% of the entire genome.
  • Tools developed for assessing sequencing accuracy yield significant improvements in performance for de novo assembly methods.
  • Adopting genome-based benchmarking may accelerate the development of affordable genome sequencing methods, benefiting genomic medicine.

Abstract

Human genome resequencing typically involves mapping reads to a reference genome to call variants; however, this approach suffers from both technical and reference biases, leaving many duplicated and structurally polymorphic regions of the genome unmapped. Consequently, existing variant benchmarks, generated by the same methods, fail to assess these complex regions. To address this limitation, we present a telomere-to-telomere genome benchmark that achieves near-perfect accuracy (i.e. no detectable errors) across 99.4% of the complete, diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), totaling 15.3% of the genome that was absent from prior benchmarks. We also provide a diploid annotation of genes, transposable elements, segmental duplications, and satellite repeats, including 39,144 protein coding genes across both haplotypes. To facilitate application of the benchmark, we developed tools for measuring the accuracy of sequencing reads, phased variant call sets, and genome assemblies against a diploid reference. Genome-wide analyses show that state-of-the-art de novo assembly methods resolve 2 to 7% more sequence and outperform variant calling accuracy by an order of magnitude, yielding just one error per 100 kb across 99.9% of the benchmark regions. Adoption of genome-based benchmarking is expected to accelerate the development of cost-effective methods for complete genome sequencing, expanding the reach of genomic medicine to the entire genome and enabling a new era of personalized genomics.

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Cite This Study

Hansen et al. (2025) studied this question.

synapsesocial.com/papers/68d4739d31b076d99fa6bbf5https://doi.org/10.1101/2025.09.21.677443
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