Cell Genomics (Mar 2022)
Decoding the diversity of killer immunoglobulin-like receptors by deep sequencing and a high-resolution imputation method
- Saori Sakaue,
- Kazuyoshi Hosomichi,
- Jun Hirata,
- Hirofumi Nakaoka,
- Keiko Yamazaki,
- Makoto Yawata,
- Nobuyo Yawata,
- Tatsuhiko Naito,
- Junji Umeno,
- Takaaki Kawaguchi,
- Toshiyuki Matsui,
- Satoshi Motoya,
- Yasuo Suzuki,
- Hidetoshi Inoko,
- Atsushi Tajima,
- Takayuki Morisaki,
- Koichi Matsuda,
- Yoichiro Kamatani,
- Kazuhiko Yamamoto,
- Ituro Inoue,
- Yukinori Okada
Affiliations
- Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan; Center for Data Sciences, Harvard Medical School, Boston, MA 02115, USA; Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Corresponding author
- Kazuyoshi Hosomichi
- Department of Bioinformatics and Genomics, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University, Ishikawa 920-8640, Japan
- Jun Hirata
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan
- Hirofumi Nakaoka
- Human Genetics Laboratory, National Institute of Genetics, Shizuoka 411-8540, Japan
- Keiko Yamazaki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Department of Public Health, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
- Makoto Yawata
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, and National University Health System, Singapore 119228, Singapore; NUSMed Immunology Translational Research Programme, and Immunology Programme, Life Sciences Institute, National University of Singapore, Singapore 117456, Singapore; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore 117609, Singapore; International Research Center for Medical Sciences, Kumamoto University, Kumamoto 860-0811, Japan
- Nobuyo Yawata
- Department of Ocular Pathology and Imaging Science, Kyushu University, 812-8582, Japan; Singapore Eye Research Institute, Singapore 169856, Singapore; Duke-NUS Medical School, Singapore 169857, Singapore
- Tatsuhiko Naito
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan; Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
- Junji Umeno
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka 812-8582, Japan
- Takaaki Kawaguchi
- Division of Gastroenterology, Department of Medicine, Tokyo Yamate Medical Center, Tokyo 169-0073, Japan
- Toshiyuki Matsui
- Department of Gastroenterology, Fukuoka University Chikushi Hospital, Fukuoka 818-0067, Japan
- Satoshi Motoya
- Department of Gastroenterology, Sapporo-Kosei General Hospital, Sapporo 060-0033, Japan
- Yasuo Suzuki
- Department of Internal Medicine, Faculty of Medicine, Toho University, Chiba 274-8510, Japan
- Hidetoshi Inoko
- GenoDive Pharma Inc., Atsugi 243-0018, Japan
- Atsushi Tajima
- Department of Bioinformatics and Genomics, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University, Ishikawa 920-8640, Japan
- Takayuki Morisaki
- Division of Molecular Pathology, The Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan
- Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan
- Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan
- Kazuhiko Yamamoto
- Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
- Ituro Inoue
- Human Genetics Laboratory, National Institute of Genetics, Shizuoka 411-8540, Japan
- Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan; Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita 565-0871, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan; Center for Infectious Disease Education and Research (CiDER), Osaka University, Suita 565-0871, Japan; Corresponding author
- Journal volume & issue
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Vol. 2,
no. 3
p. 100101
Abstract
Summary: The killer cell immunoglobulin-like receptor (KIR) recognizes human leukocyte antigen (HLA) class I molecules and modulates the function of natural killer cells. Despite its role in immunity, the complex genomic structure has limited a deep understanding of the KIR genomic landscape. Here we conduct deep sequencing of 16 KIR genes in 1,173 individuals. We devise a bioinformatics pipeline incorporating copy number estimation and insertion or deletion (indel) calling for high-resolution KIR genotyping. We define 118 alleles in 13 genes and demonstrate a linkage disequilibrium structure within and across KIR centromeric and telomeric regions. We construct a KIR imputation reference panel (nreference = 689, imputation accuracy = 99.7%), apply it to biobank genotype (ntotal = 169,907), and perform phenome-wide association studies of 85 traits. We observe a dearth of genome-wide significant associations, even in immune traits implicated previously to be associated with KIR (the smallest p = 1.5 × 10−4). Our pipeline presents a broadly applicable framework to evaluate innate immunity in large-scale datasets.
