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
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.