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A complete diploid human genome benchmark for personalized genomics
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A complete diploid human genome benchmark for personalized genomics

Nancy F. Hansen, Nathan Dwarshuis, Hyun Joo Ji +62 more
September 2025
 ·
bioRxiv
 ·
DOI 
10.1101/2025.09.21.677443
94
%
Reproducible
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Why this is interesting

Overturning the assumption that read mapping defines genomic accuracy, this first complete diploid human benchmark proves de novo assembly outperforms variant calling by an order of magnitude and unlocks 15% of the genome for evaluation.

QED claims analysis

Summary

A telomere-to-telomere diploid genome benchmark for HG002 achieves near-perfect accuracy across 99.4% of the complete 6 Gbp genome, adding 15.3% previously unmapped sequence, and reveals that de novo assembly methods now outperform variant calling by an order of magnitude while exposing that over half of genomic errors are missed by traditional variant-based benchmarking due to reference bias and incomplete coverage.

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Main Claim 1 –

T2T-HG002v1.1 benchmarks 99.4% diploid genome, adds 15.3%

Supporting evidence

  • Diploid HG002 annotation finds 39,144 protein-coding genes, 26 haplotype-unique
Main Claim 2 –

De novo assemblies resolve 2–7% more sequence, improving over time

Supporting evidence

  • Long reads have 100× higher indels yet better difficult-region coverage
Main Claim 3 –

De novo assembly surpasses variant calling accuracy by tenfold

Main Claim 4 –

Variant benchmarks miss over half of genome-detectable errors

Supporting evidence

  • Genome benchmarking reduces reference bias via diploid sequence comparisons

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 2–7% 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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