Microarrays for high-throughput genotyping of MICA alleles using allele-specific primer extension

Distributions of MICA and MICB Alleles Typed by Amplicon-Based Next-Generation Sequencing in South Koreans

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.

Distributions of 11-loci HLA alleles typed by amplicon-based next-generation sequencing in South Koreans

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.

Establishment of HLA class I and MICA/B null HEK-293T panel expressing single MICA alleles to detect anti-MICA antibodies

Pre- and post-transplantation anti-MICA antibody detection development are associated with an increased rejection risk and low graft survival. We previously generated HLA class I null HEK-293T using CRISPR/Cas9, while MICA and MICB genes were removed in this study. A panel of 11 cell lines expressing single MICA alleles was established. Anti-MICA antibody in the sera of kidney transplant patients was determined using flow cytometric method (FCM) and the Luminex method. In the 44 positive sera, the maximum FCM value was 2879 MFI compared to 28,135 MFI of Luminex method. Eleven sera (25%) were determined as positive by FCM and 32 sera (72%) were positive by the Luminex method. The sum of total MICA antigens, MICA*002, *004, *009, *019, and *027 correlation showed a statistically significant between the two methods (P = 0.0412, P = 0.0476, P = 0.0019, P = 0.0098, P = 0.0467, and P = 0.0049). These results demonstrated that HEK-293T-based engineered cell lines expressing single MICA alleles were suitable for measuring specific antibodies against MICA antigens in the sera of transplant patients. Studies of antibodies to MICA antigens may help to understand responses in vivo and increase clinical relevance at the cellular level such as complement-dependent cytotoxicity.

MICB Allele Genotyping on Microarrays by Improving the Specificity of Extension Primers

Major histocompatibility complex (MHC) class I chain-related gene B (MICB) encodes a ligand for activating NKG2D that expressed in natural killer cells, γδ T cells, and αβ CD8⁺ T cells, which is associated with autoimmune diseases, cancer, and infectious diseases. Here, we have established a system for genotyping MICB alleles using allele-specific primer extension (ASPE) on microarrays. Thirty-six high quality, allele-specific extension primers were evaluated using strict and reliable cut-off values using mean fluorescence intensity (MFI), whereby an MFI >30,000 represented a positive signal and an MFI <10,000 represented a negative signal. Eight allele-specific extension primers were found to be false positives, five of which were improved by adjusting their length, and three of which were optimized by refractory modification. The MICB alleles (*002:01, *003, *005:02/*010, *005:03, *008, *009N, *018, and *024) present in the quality control panel could be exactly defined by 22 allele-specific extension primers. MICB genotypes that were identified by ASPE on microarrays were in full concordance with those identified by PCR-sequence-based typing. In conclusion, we have developed a method for genotyping MICB alleles using ASPE on microarrays; which can be applicable for large-scale single nucleotide polymorphism typing studies of population and disease associations.

Computational and experimental approaches to reveal the effects of single nucleotide polymorphisms with respect to disease diagnostics

DNA mutations are the cause of many human diseases and they are the reason for natural differences among individuals by affecting the structure, function, interactions, and other properties of DNA and expressed proteins. The ability to predict whether a given mutation is disease-causing or harmless is of great importance for the early detection of patients with a high risk of developing a particular disease and would pave the way for personalized medicine and diagnostics. Here we review existing methods and techniques to study and predict the effects of DNA mutations from three different perspectives: in silico, in vitro and in vivo. It is emphasized that the problem is complicated and successful detection of a pathogenic mutation frequently requires a combination of several methods and a knowledge of the biological phenomena associated with the corresponding macromolecules.