Korea4K: whole genome sequences of 4,157 Koreans with 107 phenotypes derived from extensive health check-ups

IF 11.8 2区 生物学 Q1 MULTIDISCIPLINARY SCIENCES
Sungwon Jeon, Hansol Choi, Yeonsu Jeon, Whan-Hyuk Choi, Hyunjoo Choi, Kyungwhan An, Hyojung Ryu, Jihun Bhak, Hyeonjae Lee, Yoonsung Kwon, Sukyeon Ha, Yeo Jin Kim, Asta Blazyte, Changjae Kim, Yeonkyung Kim, Younghui Kang, Yeong Ju Woo, Chanyoung Lee, Jeongwoo Seo, Changhan Yoon, Dan Bolser, Orsolya Biro, Eun-Seok Shin, Byung Chul Kim, Seon-Young Kim, Ji-Hwan Park, Jongbum Jeon, Dooyoung Jung, Semin Lee, Jong Bhak
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引用次数: 0

Abstract

Background Phenome-wide association studies (PheWASs) have been conducted on Asian populations, including Koreans, but many were based on chip or exome genotyping data. Such studies have limitations regarding whole genome–wide association analysis, making it crucial to have genome-to-phenome association information with the largest possible whole genome and matched phenome data to conduct further population-genome studies and develop health care services based on population genomics. Results Here, we present 4,157 whole genome sequences (Korea4K) coupled with 107 health check-up parameters as the largest genomic resource of the Korean Genome Project. It encompasses most of the variants with allele frequency >0.001 in Koreans, indicating that it sufficiently covered most of the common and rare genetic variants with commonly measured phenotypes for Koreans. Korea4K provides 45,537,252 variants, and half of them were not present in Korea1K (1,094 samples). We also identified 1,356 new genotype–phenotype associations that were not found by the Korea1K dataset. Phenomics analyses further revealed 24 significant genetic correlations, 14 pleiotropic associations, and 127 causal relationships based on Mendelian randomization among 37 traits. In addition, the Korea4K imputation reference panel, the largest Korean variants reference to date, showed a superior imputation performance to Korea1K across all allele frequency categories. Conclusions Collectively, Korea4K provides not only the largest Korean genome data but also corresponding health check-up parameters and novel genome–phenome associations. The large-scale pathological whole genome–wide omics data will become a powerful set for genome–phenome level association studies to discover causal markers for the prediction and diagnosis of health conditions in future studies.
Korea4K:4 157 名韩国人的全基因组序列,其中 107 种表型来自广泛的健康检查
背景 对包括韩国人在内的亚洲人群进行了全表型关联研究(Phenome-wide Association Studies,PheWASs),但许多研究是基于芯片或外显子组基因分型数据进行的。这些研究在全基因组关联分析方面存在局限性,因此,拥有尽可能多的全基因组和匹配表型组数据的基因组到表型组关联信息对于开展进一步的人群基因组研究和开发基于人群基因组学的医疗保健服务至关重要。结果 在这里,我们展示了 4,157 个全基因组序列(Korea4K)和 107 个健康检查参数,这是韩国基因组计划最大的基因组资源。它涵盖了韩国人等位基因频率>0.001的大多数变异,表明它充分涵盖了韩国人大多数常见和罕见的基因变异,以及常见的测量表型。Korea4K 提供了 45,537,252 个变体,其中一半在 Korea1K 中不存在(1,094 个样本)。我们还发现了 1,356 个新的基因型-表型关联,这些关联是 Korea1K 数据集所没有的。表型组学分析进一步揭示了 37 个性状中的 24 个显著遗传相关性、14 个多效性关联和 127 个基于孟德尔随机化的因果关系。此外,Korea4K 归因参考面板是迄今为止最大的韩国变异参考面板,在所有等位基因频率类别中都显示出优于 Korea1K 的归因性能。结论 总的来说,Korea4K 不仅提供了最大的韩国基因组数据,还提供了相应的健康检查参数和新的基因组-表型组关联。大规模病理全基因组 omics 数据将成为基因组-表型组水平关联研究的强大数据集,在未来的研究中为预测和诊断健康状况发现因果标记。
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来源期刊
GigaScience
GigaScience MULTIDISCIPLINARY SCIENCES-
CiteScore
15.50
自引率
1.10%
发文量
119
审稿时长
1 weeks
期刊介绍: GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.
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