bioRxivGenomicsPreprint
Telomere-to-Telomere Accurate and Gapless Korean Standard Reference Genome
Jihun BhakiD, Yoonsung KwoniD, Dong-Hyun ShiniD, Kyungwhan AniD, H. Alex ChoiiD, Sang Soo ParkiD, Changhan YooniD, Yookyung Christy ChoiiD, Hyomin Lee, Daeui ParkiD, Yeonsu JeoniD, Jongbum JeoniD, Soobok JoeiD, Jin Ok YangiD, Jong-Hwan KimiD, Yun Sung ChoiD, Jungeun KimiD, Kyun Shik ChaeiD, Chang-Geun KimiD, Delger Bayarsaikhan, Bong‐Hee Lee, Semin LeeiD, Haeyoung JeongiD, Jong BhakiD
Abstract
We present KOREF1-G-TTAGGA, the first Telomere-to-Telomere Accurate and Gapless Genome Assembly, standing as the Korean standard reference genome. The paternal and maternal haplotypes spanned 2.91 and 3.03 Gb. Genome-wide, at least 99.15% of assembled sequences were reliably haplotype-resolved, and over 95% remained accurate even in the most error-prone loci, including centromeric satellite arrays and segmental duplications. Rare-k-mer copy-number concordance within satellite arrays held up 98.9% and 98.8% per haplotype. Bionano optical maps fully spanned all canonical rDNA arrays on the five acrocentric chromosomes. The assembly quality index (AQI) of 99.77 and 99.69 exceeded the reference-quality threshold of 90, and more than 99.99% of gene and cCRE sequence was free of structural error. Both haplotypes further showed high base-level accuracy, with consensus quality value (QV) of 81.19 and 79.03, corresponding to one error per 131 and 80 Mb. KOREF1-G-TTAGGA is among the highest-quality East Asian telomere-to-telomere assemblies. It moreover anchors a decade-spanning multi-ome reference dataset for defining individual molecular states. Together, these resources define the personal referenceome as a foundation for individual biology and precision medicine, with the assemblies, annotations, and all multi-omic data openly available at https://koreanreference.org.
- organism: human
- assay: whole-genome sequencing
- research focus: database / resource
- research focus: genome assembly
- research focus: variant calling
- research focus: gene regulatory network inference
- approach: experimental assay
- Citations
- 1
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