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HLA-B*27:264 differs from HLA-B*27:05:02:01 in codon 49 in exon 2., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*40:523 differs from HLA-B*40:92 in codon 167 in exon 3., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*31:217 differs from HLA-A*31:01:02:01 in codon 37 in exon 2., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*51:377N differs from HLA-B*51:01:01:01 in codon 13 in exon 2., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*37:107 differs from HLA-B*37:01:01:01 in codon 25 in exon 2., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Major histocompatibility complex class I chain-related genes A and B (MICA and MICB) play a role as ligands in activating the NKG2D receptor expressed in natural killer cells, γδ T-cells and αβ CD8 T-cells and have been defined in human diseases and haematopoietic stem cell transplantation (HSCT). MICA and MICB alleles were genotyped at the three-field level by amplicon-based next-generation sequencing (NGS) using a MiSeqDx system and compared with the results from previous studies in healthy South Korean donors. Exons 2-5 of MICA and exons 2-4 of MICB were amplified using a multiplex polymerase chain reaction (PCR). Sequence reads of ≥ 51 depth counts were consistently obtained for each sample exon, and target exons were determined to match reference sequences contained in the IPD-IMGT/HLA database. MICA and MICB alleles were tested using exon combinations. The program was designed to recognise specific sequences and discriminate between the MICA*008:01:01/*027 alleles. A total of 22 alleles were found in MICA and MICB. We observed 1 HLA-C ~ HLA-B ~ MICA ~ MICB ~ HLA-DRB1 haplotype with significant linkage disequilibrium between alleles at all neighbouring HLA loci. These results are consistent with previous microarray results. Genotyping of MICA and MICB was possible using 11-loci HLA genes. We updated the distribution of MICA and MICB based on three-field allele and haplotype frequencies containing linkage disequilibrium in South Koreans using amplicon-based NGS. These data suggest that high-resolution MICA and MICB typing data obtained using NGS may aid in performing HSCT and disease association studies., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Killer-cell immunoglobulin-like receptors (KIR) control natural killer (NK) cell functions by recognizing HLA molecules and modulating the activity of NK cells. The KIR gene cluster contains polymorphic and highly homologous genes. Diversity of the KIR region is achieved through differences in gene content, allelic polymorphism, and gene copy number, which result in unrelated individuals having different KIR genotypes and individualized immune responses that are relevant to multiple aspects of human health and disease. Therefore, KIR genotyping is increasingly used in epidemiological studies. Here, we developed multiplex polymerase chain reaction with sequence-specific primers (PCR-SSP) to compensate for the shortcomings of the conventional PCR-SSP method, which is most commonly used for KIR analysis. Multiplex PCR-SSP method involves six multiplex reactions that detect 16 KIR genes and distinguish variant types of some KIR genes by adding two reactions. The assay was evaluated in a blind survey using a panel of 40 reference DNA standards from the UCLA KIR Exchange Program. The results are 100% concordant with the genotype determined using Luminex-based reverse sequence-specific oligonucleotide typing systems. Additionally, we investigated the currently known 16 KIR genes and their common variants in 120 unrelated Korean individuals. The results were consistent with the KIR genotype previously reported by Hwang et al. This multiplex PCR-SSP is an efficient method for analyzing KIR genotypes in both small- and large-scale studies with minimal labor, reagents, and DNA. Furthermore, by providing a better definition of KIR polymorphisms it can contribute to developments in immunogenetics., (© 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The range of HLA typing for successful hematopoietic stem cell transplantation (HSCT) is gradually expanding with the next-generation sequencing (NGS)-based improvement in its quality. However, it is influenced by the allocation of finances and laboratory conditions. HLA-A, -B, -C, -DRB1/3/4/5, -DQA1, -DQB1, -DPA1, and -DPB1 alleles were genotyped at the 3-field level by amplicon-based NGS using MiSeqDx system and compared to our previous study employing long-range PCR and NGS using TruSight HLA v2 kit, in healthy donors from South Korea. Exon 2, exons 2/3, exons 2/3/4 or 5 of 11-loci were amplified by multiplex PCR. The sequence reads of over 53 depth counts were consistently obtained in each sample exon, depending on the target exon determined to match the reference sequence contained in the IPD-IMGT/HLA Database. HLA alleles were investigated by combinations of the determined exons. A total of 18 alleles with a frequency over 10% were found at the 11 HLA loci. Three ambiguities of HLA-A, -C, and -DRB1 were resolved. We observed a total of 26 HLA-A ~ C ~ B and 6 HLA-DRB1 ~ DQA1 ~ DQB1 ~ DPA1 ~ DPB1 haplotypes having significant linkage disequilibrium between alleles at all neighboring HLA loci. This result was compatible with the previous one, using TruSight HLA v2 kit. Advantages are simple and short progress time because one plate is used for each PCR step in one PCR machine and 11-loci HLA typing is possible even if only eight samples. These data suggested that expanded 11-loci HLA typing data by amplicon-based NGS might help perform HSCT., (© 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-DRB1*12:97 differs from HLA-DRB1*12:02:01:01 in codon 63 in exon 2., (© 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*07:457 differs from HLA-B*07:02:01:01 in codon 117 in exon 3., (© 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*51:353 differs from HLA-B*51:01:01:01 in codon 95 in exon 3., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-DRB1*09:45 differs from HLA-DRB1*09:01:02:01 in codon 19 in exon 2., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*24:514N differs from HLA-A*24:02:01:01 in codon 167 in exon 3., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*13:144 differs from HLA-B*13:01:01:01 in codon 12 in exon 2., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*11:384 differs from HLA-A*11:01:01:01 in codon 151 in exon 3., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*02:954 differs from HLA-A*02:06:01:01 in codon 82 in exon 2., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA genes play a pivotal role for successful hematopoietic stem cell transplantation (HSCT). There is an increasing need for sophisticated screening of donor HLA genotypes for unrelated HSCT. Next generation sequencing (NGS) has emerged as an alternative for classical Sanger sequence for HLA typing. In this study, HLA-A, -B, and -DRB1 alleles were genotyped at the allelic (6-digit) level using MiSeqDx in 26,202 volunteers from the Korean Network for Organ Sharing. Exon 2 and 3 of HLA-A and -B and exon 2 of HLA-DRB1 were amplified by polymerase chain reaction (PCR) and each allele was determined by matching the targeted exons and the reference sequence consisting of the IPD-IMGT/HLA Database. Seventy alleles of HLA-A, 102 alleles of HLA-B, and 69 alleles of HLA-DRB1 were identified. According to common and well-documented catalogs, 34 alleles in HLA-A, 61 in HLA-B, and 45 in HLA-DRB1 locus were common alleles, and 12, 14, and 11 kinds, were well-documented alleles, respectively. Thirteen novel alleles including 3 alleles in HLA-A, 8 alleles in HLA-B, and 2 alleles in HLA-DRB1 loci were found. Ten haplotypes with a frequency of more than 1.0% accounted for 22.4% of the total haplotype frequencies. Cis/trans ambiguities of HLA-A and -B loci by combination of exons 2 and 3 were analyzed to be 0.17% of 3 and 3.95% of 22 genotypes, respectively. This information on rare and novel alleles found by accurate HLA typing with NGS may be helpful for unrelated HSCT among Koreans., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*35:01:64 differs from HLA-B*35:01:01:01 in codon 58 in exon 2., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Some HLA alleles have been shown to be associated with susceptibility to cytomegalovirus (CMV) disease incidence in vitro. The objective of this study was to identify correlations between donor HLA allotypes and CMV disease incidence in patients with acute myeloid leukemia who had undergone allogeneic hematopoietic stem cell transplantation (HSCT). Methods and materials we retrospectively analyzed the medical records of 613 donors and recipients with acute myeloid leukemia who had received an allogeneic HSCT from matched sibling (n = 260), unrelated (n = 168), or haploidentical (n = 186) donors, from 2012 to 2017. The HLA-A, -B, -C, and -DRB1 allotypes in the donors were determined using sequence-based typing. Overall, CMV disease incidence was significantly associated with three genotype alleles, HLA-A*30:04:01G, -B*51:01:01G, and -DRB1*09:01:02G. In the donor CMV IgG seropositive subgroup, CMV disease incidence was significantly associated with HLA-B*51:01:01G and -DRB1*09:01:02G. In the IgG seropositive donors in the unrelated allo-HSCT subgroup CMV disease incidence was also significantly associated with HLA-B*51:01:01G. In the CMV seropositive donors in the haploidentical allo-HSCT subgroup, the incidence of CMV disease was significantly associated with HLA-A*24:02:01G and -DRB1*09:01:02G. HLA-DRB1*13:02:01G was a protective marker among IgG seropositive donors in the unrelated allo-HSCT recipient category. Discussion and conclusions The incidence of CMV disease among HSCT recipients varies according to donor HLA alleles and the donor CMV IgG serostatus. Certain donor HLA alleles can be considered to be risk or protective markers. Donors' HLA types and CMV IgG serostatus should be considered in donor selection., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*33:03:42 differs from HLA-A*33:03:01:01 in codon 90 in exon 2., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*24:480 differs from HLA-A*24:02:01:01 in codon 178 in exon 3., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-DRB1*04:05:21 differs from HLA-DRB1*04:05:01:01 in codon 83 in exon 2., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*15:529 differs from HLA-B*15:01:01:01 in codon 138 in exon 3., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*51:284 differs from HLA-B*51:01:01:01 in codon 44 in exon 2., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*02:842 differs from HLA-A*02:149 in codon 99 in exon 3., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*54:41 differs from HLA-B*54:01:01:01 in codon 121 in exon 3., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*07:367 differs from HLA-B*07:02:01:01 in codon 181 in exon 3., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*31:154 differs from HLA-A*31:01:02:01 in codon 115 in exon 3., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*02:877 differs from HLA-A*02:06:01:01 in codon 183 in exon 3., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*46:01:26 differs from HLA-B*46:01:01:01 in codon 66 in exon 2., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-DRB1*04:277 differs from HLA-DRB1*04:06:01:01 in codon 62 in exon 2., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*44:454 differs from HLA-B*44:03:02:01 in codon 81 in exon 2., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-C*06:66 differs from HLA-C*06:02:01:01 in codon 151 in exon 3., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-C*01:32:02 differs from HLA-C*01:02:01:01 in codons 131 and 135 in exon 3., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-C*03:272 differs from HLA-C*03:03:01:01 in exon 3, codon 163., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*46:67 differs from HLA-B*46:01:01 in codons 94, 95, and 103 in exon 3., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-DQB1*04:02:03 differs from HLA-DQB1*04:02:01:01 in a codon 62 in exon 2., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-DRB1*09:29 differs from HLA-DRB1*09:01:02:01 in a codon 75 in exon 2., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*40:330 differs from HLA-B*40:06:01:01 in codons 113 and 116 in exon 3., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-C*07:478 differs from HLA-C*07:02:01:01 in codon 81 in exon 2., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*33:110 differs from HLA-A*33:03:01:01 in a codon 149 in exon 3., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*54:35 and -B*54:38 differ from HLA-B*54:01:01 in codons in exons 2 and 3., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*15:400N differs from HLA-B*15:01:01:01 by nucleotide deletions from position 328 to 331 in exon 3., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-B*58:01:20 differs from HLA-B*58:01:01:01 by a single synonymous nucleotide exchange at position 297 in exon 3., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*26:132 differs from HLA-A*26:01:01:01 at nucleotides 269 and 346 in exons 2 and 3., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The role of major histocompatibility complex (MHC) class I chain-related gene A (MICA), a ligand of NKG2D, has been defined in human diseases by its allele associations with various autoimmune diseases, hematopoietic stem cell transplantation (HSCT) and cancer. This study describes a practical system to develop MICA genotyping by allele-specific primer extension (ASPE) on microarrays. From the results of 20 control primers, strict and reliable cut-off values of more than 30,000 mean fluorescence intensity (MFI) as positive and less than 3000 MFI as negative, were applied to select high-quality specific extension primers. Among 55 allele-specific primers, 44 primers could be initially selected as optimal primer. Through adjusting the length, six primers were improved. The other failed five primers were corrected by refractory modification. MICA genotypes by ASPE on microarrays showed the same results as those by nucleotide sequencing. On the basis of these results, ASPE on microarrays may provide high-throughput genotyping for MICA alleles for population studies, disease-gene associations and HSCT., (© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)