A population-specific genomic reference panel for Taiwan: NHRI-RP-1.

Authors

Kuang-Huan Cheng, Yi-Rong Chen, Ren-Hua Chung, Ming-Wei Lin, Hui-Ying Weng, Yuh-Ru Lin, Yung-Feng Lin, Jacob Shujui Hsu, Ralph Kirby, Shao-Yuan Chuang, Yu-Li Liu, Shiu-Feng Kathy Huang, Wei J Chen, Chih-Cheng Hsu, Wayne Huey-Herng Sheu, Shih-Feng Tsai

Published in

Journal of biomedical science. Volume 33. Issue 1. Aug 11, 2026. Epub Aug 11, 2026.

Abstract

To enhance the efficiency of identifying rare variants within the Taiwanese population and to support genome-wide association studies (GWAS) and imputation studies for genetic risk prediction in the Han population, we have developed the National Health Research Institutes (NHRI) reference panel (NHRI-RP-1).
NHRI-RP-1 is based on 2,561 whole genome sequences taken from the in-house NHRI datasets. Our objective was to optimize conditions of sample sizes (0.5K, 1K, 1.5K, 2K, 2.5K), minor allele frequency (MAF) thresholds (MAF ≥ 0.05, 0.01, 0.001, 2 × 10^-4), and imputation quality (r² ≥ 0, 0.3, 0.5) to build an aggregated genome reference panel for genetic medicine by comparing with worldwide references. Clinical applications and GWAS were then evaluated to demonstrate the capability of the reference panel.
Among different combinations of relevant parameters, the NHRI-RP-1 (with a 2,500-sample size, MAF ≥ 2 × 10^-4, r² ≥ 0) demonstrated a superior F1 score on local match, genotype concordance and r-squared, as compared to those using worldwide reference genomes, particularly for rare MAFs. Furthermore, NHRI-RP-1 achieved over 95% accuracy for nine pathogenic variants present in the Taiwan Biobank and 93.49% and 92.9% accuracy for imputing two DRD1 variants.
The use of different reference panels can influence the outcomes of GWAS. Our case studies demonstrate the utility of the NHRI-RP-1 for genetic medicine. Incorporating a population-specific panel such as NHRI-RP-1 can facilitate the development of prediction models using polygenic risk scores for diseases that are common in the Han population.

PMID:
42576224
Bibliographic data and abstract were imported from PubMed on 11 Aug 2026.

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