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Population-specific reference panel improves imputation quality for genome-wide association studies conducted on the Japanese population

  • Jack Flanagan,
  • Xiaoxi Liu,
  • David Ortega-Reyes,
  • Kohei Tomizuka,
  • Nana Matoba,
  • Masato Akiyama,
  • Masaru Koido,
  • Kazuyoshi Ishigaki,
  • Kyota Ashikawa,
  • Sadaaki Takata,
  • MingYang Shi,
  • Tomomi Aoi,
  • Yukihide Momozawa,
  • Kaoru Ito,
  • Yoshinori Murakami,
  • Koichi Matsuda,
  • Koichi Matsuda,
  • Yuji Yamanashi,
  • Yoichi Furukawa,
  • Takayuki Morisaki,
  • Yoshinori Murakami,
  • Yoichiro Kamatani,
  • Kaori Muto,
  • Akiko Nagai,
  • Wataru Obara,
  • Ken Yamaji,
  • Kazuhisa Takahashi,
  • Satoshi Asai,
  • Yasuo Takahashi,
  • Takao Suzuki,
  • Nobuaki Sinozaki,
  • Hiroki Yamaguchi,
  • Shiro Minami,
  • Shigeo Murayama,
  • Kozo Yoshimori,
  • Satoshi Nagayama,
  • Daisuke Obata,
  • Masahiko Higashiyama,
  • Akihide Masumoto,
  • Yukihiro Koretsune,
  • Yoichiro Kamatani,
  • Andrew P. Morris,
  • Momoko Horikoshi,
  • Chikashi Terao

摘要

To improve imputation quality for genome-wide association studies (GWAS) conducted on the Japanese population, we developed and evaluated four Japanese population-specific reference panels. These panels were constructed through the augmentation of the 1000 Genomes Project (1KG) panel using Japanese whole genome sequencing (WGS) data, with sample sizes ranging from 1 K to 7 K individuals enrolled through the Biobank Japan (BBJ) project, and sequencing depths ranging from 3× to 30×. Among these panels, an augmented reference panel comprising 7472 WGS samples of mixed depth (1KG+7K) exhibit the greatest improvement in imputation quality relative to the Trans-Omics for Precision Medicine (TOPMed) reference panel. Notably, we observe these improvements primarily for rare variants with a minor allele frequency (MAF) <5%. To demonstrate the benefits of improved imputation quality in association analyses of complex traits, we conducted GWAS for serum uric acid and total cholesterol levels following imputation up to the 1KG+7K panel. The analysis reveals several loci reaching genome-wide significance (P < 5 × 10–8) in the 1KG+7K imputation output yet remaining undetected when the same sample set is imputed up to the TOPMed reference panel. In summary, the 1KG+7K panel demonstrates significant advantages in the discovery of trait-associated loci, particularly those influenced by low-frequency association signals.