High population frequencies of MICA copy number variations originate from independent recombination events.

MICA is a stress-induced ligand of the NKG2D receptor that stimulates NK and T cell responses and was identified as a key determinant of anti-tumor immunity. The MICA gene is located inside the MHC complex and is in strong linkage disequilibrium with HLA-B. While an HLA-B*48-linked MICA deletion-haplotype was previously described in Asian populations, little is known about other MICA copy number variations. Here, we report the genotyping of more than two million individuals revealing high frequencies of MICA duplications (1%) and MICA deletions (0.4%). Their prevalence differs between ethnic groups and can rise to 2.8% (Croatia) and 9.2% (Mexico), respectively. Targeted sequencing of more than 70 samples indicates that these copy number variations originate from independent nonallelic homologous recombination events between segmental duplications upstream of MICA and MICB. Overall, our data warrant further investigation of disease associations and consideration of MICA copy number data in oncological study protocols.

Genotype List String 1.1: Extending the Genotype List String grammar for describing HLA and Killer-cell Immunoglobulin-like Receptor genotypes.

The Genotype List (GL) String grammar for reporting HLA and Killer-cell Immunoglobulin-like Receptor (KIR) genotypes in a text string was described in 2013. Since this initial description, GL Strings have been used to describe HLA and KIR genotypes for more than 40 million subjects, allowing these data to be recorded, stored and transmitted in an easily parsed, text-based format. After a decade of working with HLA and KIR data in GL String format, with advances in HLA and KIR genotyping technologies that have fostered the generation of full-gene sequence data, the need for an extension of the GL String system has become clear. Here, we introduce the new GL String delimiter "?," which addresses the need to describe ambiguity in assigning a gene sequence to gene paralogs. GL Strings that do not include a "?" delimiter continue to be interpreted as originally described. This extension represents version 1.1 of the GL String grammar.

Estimation of German KIR Allele Group Haplotype Frequencies.

The impact of the highly polymorphic Killer-cell immunoglobulin-like receptor (KIR) gene cluster on the outcome of hematopoietic stem cell transplantation (HCST) is subject of current research. To further understand the involvement of this gene family into Natural Killer (NK) cell-mediated graft-versus-leukemia reactions, knowledge of haplotype structures, and allelic linkage is of importance. In this analysis, we estimate population-specific KIR haplotype frequencies at allele group resolution in a cohort of n = 458 German families. We addressed the polymorphism of the KIR gene complex and phasing ambiguities by a combined approach. Haplotype inference within first-degree family relations allowed us to limit the number of possible diplotypes. Structural restriction to a pattern set of 92 previously described KIR copy number haplotypes further reduced ambiguities. KIR haplotype frequency estimation was finally accomplished by means of an expectation-maximization algorithm. Applying a resolution threshold of ½ n, we were able to identify a set of 551 KIR allele group haplotypes, representing 21 KIR copy number haplotypes. The haplotype frequencies allow studying linkage disequilibrium in two-locus as well as in multi-locus analyses. Our study reveals associations between KIR haplotype structures and allele group frequencies, thereby broadening our understanding of the KIR gene complex.

High-Throughput MICA/B Genotyping of Over Two Million Samples: Workflow and Allele Frequencies.

MICA and MICB are ligands of the NKG2D receptor and thereby influence NK and T cell activity. MICA/B gene polymorphisms, expression levels and the amount of soluble MICA/B in the serum have been linked to autoimmune diseases, infections, and cancer. In hematopoietic stem cell transplantation, MICA matching between donor and patient has been correlated with reduced acute and chronic graft-vs.-host disease and improved survival. Hence, we developed an extremely cost-efficient high-throughput workflow for genotyping MICA/B for newly registered potential stem cell donors. Since mid-2017, we have genotyped over two million samples using NGS amplicon sequencing for MICA/B exons 2-5. In donors of German origin, MICA*008 is the most common MICA allele with a frequency of 42.3%. It is followed by MICA*002 (11.7%) and MICA*009 (8.8%). The three most common MICB alleles are MICB*005 (43.9%), MICB*004 (21.7%), and MICB*002 (18.9%). In general, MICB is less diverse than MICA and only 6 alleles, instead of 15, account for a cumulative allele frequency of 99.5%. In 0.5% of the samples we observed at least one allele of MICA or MICB which has so far not been reported to the IPD/IMGT-HLA database. By providing MICA/B typed voluntary donors, clinicians become empowered to include MICA/B into their donor selection process to further improve unrelated hematopoietic stem cell transplantation.

Common, intermediate and well-documented HLA alleles in world populations: CIWD version 3.0.0.

A catalog of common, intermediate and well-documented (CIWD) HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQB1 and -DPB1 alleles has been compiled from over 8 million individuals using data from 20 unrelated hematopoietic stem cell volunteer donor registries. Individuals are divided into seven geographic/ancestral/ethnic groups and data are summarized for each group and for the total population. P (two-field) and G group assignments are divided into one of four frequency categories: common (≥1 in 10 000), intermediate (≥1 in 100 000), well-documented (≥5 occurrences) or not-CIWD. Overall 26% of alleles in IPD-IMGT/HLA version 3.31.0 at P group resolution fall into the three CIWD categories. The two-field catalog includes 18% (n = 545) common, 17% (n = 513) intermediate, and 65% (n = 1997) well-documented alleles. Full-field allele frequency data are provided but are limited in value by the variations in resolution used by the registries. A recommended CIWD list is based on the most frequent category in the total or any of the seven geographic/ancestral/ethnic groups. Data are also provided so users can compile a catalog specific to the population groups that they serve. Comparisons are made to three previous CWD reports representing more limited population groups. This catalog, CIWD version 3.0.0, is a step closer to the collection of global HLA frequencies and to a clearer view of HLA diversity in the human population as a whole.

Allele-Level KIR Genotyping of More Than a Million Samples: Workflow, Algorithm, and Observations.

The killer-cell immunoglobulin-like receptor (KIR) genes regulate natural killer cell activity, influencing predisposition to immune mediated disease, and affecting hematopoietic stem cell transplantation (HSCT) outcome. Owing to the complexity of the KIR locus, with extensive gene copy number variation (CNV) and allelic diversity, high-resolution characterization of KIR has so far been applied only to relatively small cohorts. Here, we present a comprehensive high-throughput KIR genotyping approach based on next generation sequencing. Through PCR amplification of specific exons, our approach delivers both copy numbers of the individual genes and allelic information for every KIR gene. Ten-fold replicate analysis of a set of 190 samples revealed a precision of 99.9%. Genotyping of an independent set of 360 samples resulted in an accuracy of more than 99% taking into account consistent copy number prediction. We applied the workflow to genotype 1.8 million stem cell donor registry samples. We report on the observed KIR allele diversity and relative abundance of alleles based on a subset of more than 300,000 samples. Furthermore, we identified more than 2,000 previously unreported KIR variants repeatedly in independent samples, underscoring the large diversity of the KIR region that awaits discovery. This cost-efficient high-resolution KIR genotyping approach is now applied to samples of volunteers registering as potential donors for HSCT. This will facilitate the utilization of KIR as additional selection criterion to improve unrelated donor stem cell transplantation outcome. In addition, the approach may serve studies requiring high-resolution KIR genotyping, like population genetics and disease association studies.