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Updated: Aug 10, 2025

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing
Published on: March 15, 2019
Decoding the diversity of killer immunoglobulin-like receptors by deep sequencing and a high-resolution imputation
Saori Sakaue1,2,3,4,5, Kazuyoshi Hosomichi6, Jun Hirata1
1Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan.
Abstract:
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.
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