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Updated: May 23, 2025

Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
JoGo-LILR caller: Unveiling and navigating the complex diversity of LILRB3-LILRA6 copy number haplotype structures
Masao Nagasaki1, Kouyuki Hirayasu2, Seik-Soon Khor3
1Division of Biomedical Information Analysis, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan; Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Abstract:
Leukocyte immunoglobulin-like receptors (LILRs), encoded on human chromosome 19q13.4, comprise a set of 11 immunoglobulin superfamily receptors known for their genetic heterogeneity. Notably, LILRB3 and LILRA6 within this cluster exhibit pronounced sequence homology in immunoglobulin-like domains involved in ligand binding and variable copy number (CN) states. However, understanding their precise role remains challenging. To address this difficulty, we developed an algorithm and tool named JoGo-LILR Caller, which jointly calls CNs of LILRB3 and LILRA6 from a population-scale whole-genome short-read sequencing dataset. This tool was applied to 2,504 international HapMap samples and yielded a global CN profile. The 100 % concordance rate corroborated this profile with the CN data obtained from 40 samples of pangenome reference assemblies provided by the Human Pangenome Reference Consortium (HPRC). The frequencies of LILRB3-LILRA6 CN haplotype structures were also estimated for five continental groups with a global CN profile. The established allele frequency profile allowed our tool to estimate LILRB3-LILRA6 CN haplotype combinations. JoGo-LILR-trio enhanced the prediction reliability for haplotype pairs within trio datasets, with trio analysis on 40 child samples demonstrating a 100 % concordance between the predicted pair of haploid CN types and the diploid reference assemblies. Its utility will extend to facilitating software advancements for imputing LILRB3-LILRA6 CN types from SNP array genotyping data, enabling subsequent association analyses that link these CN types to diverse phenotypic traits and diseases, e.g., inflammatory bowel diseases and Takayasu arteritis.
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