1. Population-specific reference panel improves imputation quality for genome-wide association studies conducted on the Japanese population.
- Author
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Flanagan J, Liu X, Ortega-Reyes D, Tomizuka K, Matoba N, Akiyama M, Koido M, Ishigaki K, Ashikawa K, Takata S, Shi M, Aoi T, Momozawa Y, Ito K, Murakami Y, Matsuda K, Kamatani Y, Morris AP, Horikoshi M, and Terao C
- Subjects
- Humans, Gene Frequency, Genome, Human, Japan, Polymorphism, Single Nucleotide, Whole Genome Sequencing standards, Whole Genome Sequencing methods, East Asian People genetics, Genome-Wide Association Study methods, Genome-Wide Association Study standards
- Abstract
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., Competing Interests: Competing interests: The authors declare no competing interests. Kaoru Ito is an Editorial Board Member for Communications Biology, but was not involved in the editorial review of, nor the decision to publish this article., (© 2024. The Author(s).)- Published
- 2024
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