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Decoding the diversity of killer immunoglobulin-like receptors by deep sequencing and a high-resolution imputation method

التفاصيل البيبلوغرافية
العنوان: Decoding the diversity of killer immunoglobulin-like receptors by deep sequencing and a high-resolution imputation method
المؤلفون: 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
المصدر: Cell Genomics, Vol 2, Iss 3, Pp 100101- (2022)
بيانات النشر: Elsevier, 2022.
سنة النشر: 2022
المجموعة: LCC:Genetics
LCC:Internal medicine
مصطلحات موضوعية: killer cell immunoglobulin-like receptor, KIR, target sequencing, next-generation sequencing, imputation, PheWAS, Genetics, QH426-470, Internal medicine, RC31-1245
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2666-979X
Relation: http://www.sciencedirect.com/science/article/pii/S2666979X22000180; https://doaj.org/toc/2666-979X
DOI: 10.1016/j.xgen.2022.100101
URL الوصول: https://doaj.org/article/90501fcf80d34f2380420ddb63a6f8b7
رقم الأكسشن: edsdoj.90501fcf80d34f2380420ddb63a6f8b7
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2666979X
DOI:10.1016/j.xgen.2022.100101