A T2T Benchmark Reveals How Reference Choice Shapes Human Genome Interpretation

Huang, Z.; Chu, Y.; Tian, Y.; Shao, C.; Wang, J.; Zhang, X.; Chen, J.; Jia, Z.; Li, L.; Li, J.; Lin, G.; Zhang, K.; Antonarakis, S. E.; Kang, Y.; Huang, J.

doi:10.64898/2026.09.07.749735

bioRxiv · 10.64898/2026.09.07.749735

A T2T Benchmark Reveals How Reference Choice Shapes Human Genome Interpretation

Huang, Z.·Chu, Y.·Tian, Y.·Shao, C.·Wang, J.·Zhang, X.·Chen, J.·Jia, Z.·Li, L.·Li, J.·Lin, G.·Zhang, K.·Antonarakis, S. E.·Kang, Y.·Huang, J.

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Abstract

The completion of telomere-to-telomere (T2T) human genomes has expanded the accessible landscape of human genetic variation, yet benchmark resources remain limited to conventional high-confidence regions defined by existing reference frameworks. Here, we generated a near-perfect diploid T2T genome (T2T-LIN) from a Chinese individual and established assembly-based truth sets by comparison with T2T-YAO, an ancestry-matched near-perfect T2T reference genome. The benchmark showed a heterozygous/homozygous SNV ratio of ~2, consistent with expectations under Hardy-Weinberg equilibrium, and enabled genome-wide evaluation of reference-dependent biases. We found that reference choice substantially influences genome interpretation: ancestry-matched linear T2T references provided the most faithful representation of individual genomic variation and enabled more accurate genome reconstruction than unmatched linear, diploid and graph-based references. Benchmarking previously inaccessible repetitive and structurally complex regions revealed substantial limitations of current variant callers that were masked by conventional metrics. The T2T-LIN and YAO-LIN benchmarks establish a T2T-era framework for evaluating reference-dependent genome interpretation and variant discovery across nearly the complete human genome.

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Huang, Z., Chu, Y., Tian, Y., Shao, C., Wang, J., Zhang, X., Chen, J., Jia, Z., Li, L., Li, J., Lin, G., Zhang, K., Antonarakis, S. E., Kang, Y., Huang, J.. 2026-09-10. A T2T Benchmark Reveals How Reference Choice Shapes Human Genome Interpretation. https://doi.org/10.64898/2026.09.07.749735

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