PyPop: a mature open-source software pipeline for population genomics

Python for Population Genomics (PyPop) is a software package that processes genotype and allele data and performs large-scale population genetic analyses on highly polymorphic multi-locus genotype data. In particular, PyPop tests data conformity to Hardy-Weinberg equilibrium expectations, performs Ewens-Watterson tests for selection, estimates haplotype frequencies, measures linkage disequilibrium, and tests significance. Standardized means of performing these tests is key for contemporary studies of evolutionary biology and population genetics, and these tests are central to genetic studies of disease association as well. Here, we present PyPop 1.0.0, a new major release of the package, which implements new features using the more robust infrastructure of GitHub, and is distributed via the industry-standard Python Package Index. New features include implementation of the asymmetric linkage disequilibrium measures and, of particular interest to the immunogenetics research communities, support for modern nomenclature, including colon-delimited allele names, and improvements to meta-analysis features for aggregating outputs for multiple populations. Code available at: https://zenodo.org/records/10080668 and https://github.com/alexlancaster/pypop.

Complete HLA genotyping of type 1 diabetes patients and controls from Mali reveals both expected and novel disease associations

HLA genotyping was performed on 99 type 1 diabetes (T1D) patients and 200 controls from Mali. Next-generation sequencing of the classical HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1, and -DPB1 loci revealed strong T1D association for all loci except HLA-C and -DPA1. Class II association is stronger than class I association, with most observed associations predisposing or protective as expected based on previous studies. For example, HLA-DRB1*03:01, HLA-DRB1*09:01, and HLA-DRB1*04:05 predispose for T1D, whereas HLA-DRB1*15:03 is protective. HLA-DPB1*04:02 (OR = 12.73, p = 2.92 × 10-05 ) and HLA-B*27:05 (OR = 21.36, p = 3.72 × 10-05 ) appear highly predisposing, although previous studies involving multiple populations have reported HLA-DPB1*04:02 as T1D-protective and HLA-B*27:05 as neutral. This result may reflect the linkage disequilibrium between alleles on the extended HLA-A*24:02~HLA-B*27:05~HLA-C*02:02~HLA-DRB1*04:05~HLA-DRB4*01:03~HLA-DQB1*02:02~HLA-DQA1*02:01~HLA-DPB1*04:02~HLA-DPA1*01:03 haplotype in this population rather than an effect of either allele itself. Individual amino acid (AA) analyses are consistent with most T1D association attributable to HLA class II rather than class I in this data set. AA-level analyses reveal previously undescribed differences of the HLA-C locus from the HLA-A and HLA-B loci, with more polymorphic positions, spanning a larger portion of the gene. This may reflect additional mechanisms for HLA-C to influence T1D risk, for example, through expression differences or through its role as the dominant ligand for killer cell immunoglobulin-like receptors (KIR). Comparison of these data to those from larger studies and on other populations may facilitate T1D prediction and help elucidate elusive mechanisms of how HLA contributes to T1D risk and autoimmunity.

The genotype list string code syntax for exchanging nomenclature-level genotyping results in clinical and research data management and analysis systems

The nomenclatures used to describe HLA and killer-cell immunoglobulin-like receptor (KIR) alleles distinguish unique nucleotide and peptide sequences, and patterns of expression, but are insufficient for describing genotyping results, as description of ambiguities and relations across loci require terminology beyond allele names. The genotype list (GL) String grammar describes genotyping results for genetic systems with defined nomenclatures, like HLA and KIR, documenting what is known and unknown about a given genotyping result. However, the accuracy of a GL String is dependent on the reference database version under which it was generated. Here, we describe the GL string code (GLSC) system, which associates each GL String with meta-data describing the specific reference context in which the GL String was created, and in which it should be interpreted. GLSC is a defined syntax for exchanging GL Strings in the context of a specific gene-family namespace, allele-name code-system, and pertinent reference database version. GLSC allows HLA and KIR genotyping data to be transmitted, parsed and interpreted in the appropriate context, in an unambiguous manner, on modern data-systems, including Health Level 7 Fast Healthcare Interoperability Resource systems. Technical specification for GLSC can be found at https://glstring.org.

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.

Analysis of the Origin of Emiratis as Inferred from a Family Study Based on HLA-A, -C, -B, -DRB1, and -DQB1 Genes

In this study, we investigated HLA class I and class II allele and haplotype frequencies in Emiratis and compared them to those of Asian, Mediterranean, and Sub-Saharan African populations.

METHODS

Two-hundred unrelated Emirati parents of patients selected for bone marrow transplantation were genotyped for HLA class I (A, B, C) and class II (DRB1, DQB1) genes using reverse sequence specific oligonucleotide bead-based multiplexing. HLA haplotypes were assigned with certainty by segregation (pedigree) analysis, and haplotype frequencies were obtained by direct counting. HLA class I and class II frequencies in Emiratis were compared to data from other populations using standard genetic distances (SGD), Neighbor-Joining (NJ) phylogenetic dendrograms, and correspondence analysis.

RESULTS

The studied HLA loci were in Hardy-Weinberg Equilibrium. We identified 17 HLA-A, 28 HLA-B, 14 HLA-C, 13 HLA-DRB1, and 5 HLA-DQB1 alleles, of which HLA-A*02 (22.2%), -B*51 (19.5%), -C*07 (20.0%), -DRB1*03 (22.2%), and -DQB1*02 (32.8%) were the most frequent allele lineages. DRB1*03~DQB1*02 (21.2%), DRB1*16~DQB1*05 (17.3%), B*35~C*04 (11.7%), B*08~DRB1*03 (9.7%), A*02~B*51 (7.5%), and A*26~C*07~B*08~DRB1*03~DQB1*02 (4.2%) were the most frequent two- and five-locus HLA haplotypes. Correspondence analysis and dendrograms showed that Emiratis were clustered with the Arabian Peninsula populations (Saudis, Omanis and Kuwaitis), West Mediterranean populations (North Africans, Iberians) and Pakistanis, but were distant from East Mediterranean (Turks, Albanians, Greek), Levantine (Syrians, Palestinians, Lebanese), Iranian, Iraqi Kurdish, and Sub-Saharan populations.

CONCLUSIONS

Emiratis were closely related to Arabian Peninsula populations, West Mediterranean populations and Pakistanis. However, the contribution of East Mediterranean, Levantine Arab, Iranian, and Sub-Saharan populations to the Emiratis' gene pool appears to be minor.

The immunogenetics of viral antigen response is associated with subtype-specific glioma risk and survival

Glioma is a highly fatal cancer with prognostically significant molecular subtypes and few known risk factors. Multiple studies have implicated infections in glioma susceptibility, but evidence remains inconsistent. Genetic variants in the human leukocyte antigen (HLA) region modulate host response to infection and have been linked to glioma risk. In this study, we leveraged genetic predictors of antibody response to 12 viral antigens to investigate the relationship with glioma risk and survival. Genetic reactivity scores (GRSs) for each antigen were derived from genome-wide-significant (p < 5 × 10-8) variants associated with immunoglobulin G antibody response in the UK Biobank cohort. We conducted parallel analyses of glioma risk and survival for each GRS and HLA alleles imputed at two-field resolution by using data from 3,418 glioma-affected individuals subtyped by somatic mutations and 8,156 controls. Genetic reactivity scores to Epstein-Barr virus (EBV) ZEBRA and EBNA antigens and Merkel cell polyomavirus (MCV) VP1 antigen were associated with glioma risk and survival (Bonferroni-corrected p < 0.01). GRSZEBRA and GRSMCV were associated in opposite directions with risk of IDH wild-type gliomas (ORZEBRA = 0.91, p = 0.0099/ORMCV = 1.11, p = 0.0054). GRSEBNA was associated with both increased risk for IDH mutated gliomas (OR = 1.09, p = 0.040) and improved survival (HR = 0.86, p = 0.010). HLA-DQA1∗03:01 was significantly associated with decreased risk of glioma overall (OR = 0.85, p = 3.96 × 10-4) after multiple testing adjustment. This systematic investigation of the role of genetic determinants of viral antigen reactivity in glioma risk and survival provides insight into complex immunogenomic mechanisms of glioma pathogenesis. These results may inform applications of antiviral-based therapies in glioma treatment.

HLA-DRB1 and -DQB1 Alleles, Haplotypes and Genotypes in Emirati Patients with Type 1 Diabetes Underscores the Benefits of Evaluating Understudied Populations

Background: HLA class II (DR and DQ) alleles and antigens have historically shown strong genetic predisposition to type 1 diabetes (T1D). This study evaluated the association of DRB1 and DQB1 alleles, genotypes, and haplotypes with T1D in United Arab Emirates. Materials and Methods: Study subjects comprised 149 patients with T1D, and 147 normoglycemic control subjects. Cases and controls were Emiratis and were HLA-DRB1 and -DQB1 genotyped using sequence-based typing. Statistical analysis was performed using Bridging Immunogenomic Data-Analysis Workflow Gaps R package. Results: In total, 15 DRB1 and 9 DQB1 alleles were identified in the study subjects, of which the association of DRB1*03:01, DRB1*04:02, DRB1*11:01, DRB1*16:02, and DQB1*02:01, DQB1*03:02, DQB1*03:01, and DQB1*06:01 with altered risk of T1D persisted after correcting for multiple comparisons. Two-locus haplotype analysis identified DRB1*03:01∼DQB1*02:01 [0.44 vs. 0.18, OR (95% CI) = 3.44 (2.33-5.1), Pc = 3.48 × 10^-10]; DRB1*04:02∼DQB1*03:02 [0.077 vs. 0.014, OR = 6.06 (2.03-24.37), Pc = 2.3 × 10^-3] and DRB1*04:05∼DQB1*03:02 [0.060 vs. 0.010, OR = 6.24 (1.79-33.34), Pc = 0.011] as positively associated, and DRB1*16:02∼DQB1*05:02 [0.024 vs. 0.075, OR = 0.3 (0.11-0.74), Pc = 0.041] as negatively associated with T1D, after applying Bonferroni correction. Furthermore, the highest T1D risk was observed for DR3/DR4 [0.104 vs. 0.006, OR = 25.03 (8.23-97.2), Pc = 2.6 × 10^-10], followed by DR3/DR3 [0.094 vs. 0.010, OR = 8.72 (3.17-25.32), Pc = 3.18 × 10^-8] diplotypes. Conclusion: While DRB1 and DQB1 alleles and haplotypes associated with T1D in Emiratis showed similarities to Caucasian and non-Caucasian populations, several alleles and haplotypes associated with T1D in European, African, and Asian populations, were not observed. This underscores the contribution of ethnic diversity and possible diverse associations between DRB1 and DQB1 and T1D across different populations.

Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research

The current SARS-CoV-2 pandemic era launched an immediate and broad response of the research community with studies both about the virus and host genetics. Research in genetics investigated HLA association with COVID-19 based on in silico, population, and individual data. However, they were conducted with variable scale and success; convincing results were mostly obtained with broader whole-genome association studies. Here, we propose a technical review of HLA analysis, including basic HLA knowledge as well as available tools and advice. We notably describe recent algorithms to infer and call HLA genotypes from GWAS SNPs and NGS data, respectively, which opens the possibility to investigate HLA from large datasets without a specific initial focus on this region. We thus hope this overview will empower geneticists who were unfamiliar with HLA to run MHC-focused analyses following the footsteps of the Covid-19|HLA & Immunogenetics Consortium.

Current HLA Investigations on SARS-CoV-2 and Perspectives

The rapid, global spread of the SARS-CoV-2 virus during the current pandemic has triggered numerous efforts in clinical and research settings to better understand the host genetics' interactions and the severity of COVID-19. Due to the established major role played by MHC/HLA polymorphism in infectious disease course and susceptibility, immunologists and geneticists have teamed up to investigate its contribution to the SARS-CoV-2 infection and COVID-19 progression. A major goal of the Covid-19|HLA & Immunogenetics Consortium is to support and unify these efforts. Here, we present a review of HLA immunogenomics studies in the SARS-CoV-2 pandemic and reflect on the role of various HLA data, their limitation and future perspectives.

Standard reference sequences for submission of HLA genotyping for the 18th International HLA and Immunogenetics Workshop

The International human leukocyte antigen (HLA) and Immunogenetics Workshops (IHIWs) have fostered international collaborations of researchers and experts in the fields of HLA, histocompatibility and immunology. These IHIW collaborations have comprised many projects focused on achieving a variety of specific goals. The international and collaborative nature of these projects necessitates the collection and analysis of complex data generated in multiple laboratories, often using multiple methods of acquisition. Collection and storage of these data in a consistent way adds value to IHIW projects, which can be extended to future work. DNA‐based genotyping data, especially HLA genotyping data, can be transmitted in the form of a Histoimmunogenetics Markup Language (HML) document. HML facilitates clear communication of a genotype and supporting metadata, such as, sequencing platform, laboratory assays, consensus sequence, and interpretation. Sequence information can be reported relative to known reference sequences, which add meaning and context to genotypes. Selecting the correct reference sequence for a given allele sequence is nuanced, and guidelines have emerged through collaborative community efforts such as Data Standards Hackathons. Here, we describe the guidelines established for the selection of reference sequences to be used in transmission of HLA (and MICA/MICB) genotyping data for the 18th IHIW.

SNP-HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC-centric analyses in genomics

Genome‐wide associations studies have repeatedly identified the major histocompatibility complex genomic region (6p21.3) as key in immune pathologies. Researchers have also aimed to extend the biological interpretation of associations by focusing directly on human leukocyte antigen (HLA) polymorphisms and their combination as haplotypes. To circumvent the effort and high costs of HLA typing, statistical solutions have been developed to infer HLA alleles from single‐nucleotide polymorphism (SNP) genotyping data. Though HLA imputation methods have been developed, no unified effort has yet been undertaken to share large and diverse imputation models, or to improve methods. By training the HIBAG software on SNP + HLA data generated by the Consortium on Asthma among African‐ancestry Populations in the Americas (CAAPA) to create reference panels, we highlighted the importance of (a) the number of individuals in reference panels, with a twofold increase in accuracy (from 10 to 100 individuals) and (b) the number of SNPs, with a 1.5‐fold increase in accuracy (from 500 to 24,504 SNPs). Results showed improved accuracy with CAAPA compared to the African American models available in HIBAG, highlighting the need for precise population‐matching. The SNP‐HLA Reference Consortium is an international endeavor to gather data, enhance HLA imputation and broaden access to highly accurate imputation models for the immunogenomics community.

HLA alleles and haplotypes observed in 263 US families

The 17th International HLA and Immunogenetics Workshop (IHIW) conducted a project entitled "The Study of Haplotypes in Families by NGS HLA". We investigated the HLA haplotypes of 1017 subjects in 263 nuclear families sourced from five US clinical immunogenetics laboratories, primarily as part of the evaluation of related donor candidates for hematopoietic stem cell and solid organ transplantation. The parents in these families belonged to five broad groups - African (72 parents), Asian (115), European (210), Hispanic (118) and "Other" (11). High-resolution HLA genotypes were generated for each subject using next-generation sequencing (NGS) HLA typing systems. We identified the HLA haplotypes in each family using HaplObserve, software that builds haplotypes in families by reviewing HLA allele segregation from parents to children. We calculated haplotype frequencies within each broad group, by treating the parents in each family as unrelated individuals. We also calculated standard measures of global linkage disequilibrium (LD) and conditional asymmetric LD for each ethnic group, and used untruncated and two-field allele names to investigate LD patterns. Finally we demonstrated the utility of consensus DNA sequences in identifying novel variants, confirming them using HLA allele segregation at the DNA sequence level.

Quality control project of NGS HLA genotyping for the 17th International HLA and Immunogenetics Workshop

The 17th International HLA and Immunogenetics Workshop (IHIW) organizers conducted a Pilot Study (PS) in which 13 laboratories (15 groups) participated to assess the performance of the various sequencing library preparation protocols, NGS platforms and software in use prior to the workshop. The organizers sent 50 cell lines to each of the 15 groups, scored the 15 independently generated sets of NGS HLA genotyping data, and generated "consensus" HLA genotypes for each of the 50 cell lines. Proficiency Testing (PT) was subsequently organized using four sets of 24 cell lines, selected from 48 of 50 PS cell lines, to validate the quality of NGS HLA typing data from the 34 participating IHIW laboratories. Completion of the PT program with a minimum score of 95% concordance at the HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 loci satisfied the requirements to submit NGS HLA typing data for the 17th IHIW projects. Together, these PS and PT efforts constituted the 17th IHIW Quality Control project. Overall PT concordance rates for HLA-A, HLA-B, HLA-C, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DRB1, HLA-DRB3, HLA-DRB4 and HLA-DRB5 were 98.1%, 97.0% and 98.1%, 99.0%, 98.6%, 98.8%, 97.6%, 96.0%, 99.1%, 90.0% and 91.7%, respectively. Across all loci, the majority of the discordance was due to allele dropout. The high cost of NGS HLA genotyping per experiment likely prevented the retyping of initially failed HLA loci. Despite the high HLA genotype concordance rates of the software, there remains room for improvement in the assembly of more accurate consensus DNA sequences by NGS HLA genotyping software.

Tools for building, analyzing and evaluating HLA haplotypes from families

The highly polymorphic classical human leukocyte antigen (HLA) genes display strong linkage disequilibrium (LD) that results in conserved multi-locus haplotypes. For unrelated individuals in defined populations, HLA haplotype frequencies can be estimated using the expectation-maximization (EM) method. Haplotypes can also be constructed using HLA allele segregation from nuclear families. It is straightforward to identify many HLA genotyping inconsistencies by visually reviewing HLA allele segregation in family members. It is also possible to identify potential crossover events when two or more children are available in a nuclear family. This process of visual inspection can be unwieldy, and we developed the "HaplObserve" program to standardize the process and automatically build haplotypes using family-based HLA allele segregation. HaplObserve facilitates systematically building haplotypes, and reporting potential crossover events. HLA Haplotype Validator (HLAHapV) is a program originally developed to impute chromosomal phase from genotype data using reference haplotype data. We updated and adapted HLAHapV to systematically compare observed and estimated haplotypes. We also used HLAHapV to identify haplotypes when uninformative HLA genotypes are present in families. Finally, we developed "pould", an R package that calculates haplotype frequencies, and estimates standard measures of global (locus-level) LD from both observed and estimated haplotypes.

Sequence-based HLA-A, B, C, DP, DQ, and DR typing of 496 adults from San Diego, California, USA

DNA sequence-based typing at the HLA-A, -B, -C, -DPB1, -DQA1, -DQB1, and -DRB1 loci was performed on 496 healthy adult donors from San Diego, California, to characterize allele frequencies in support of studies of T cell responses to common allergens. Deviations from Hardy Weinberg proportions were detected at each locus except A and C. Several alleles were found in more than 15% of individuals, including the class II alleles DPB1∗02:01, DPB1∗04:01, DQA1∗01:02, DQA1∗05:01, DQB1∗03:01, and the class I allele A∗02:01. Genotype data will be available in the Allele Frequencies Net Database (AFND 3562).

Collection and storage of HLA NGS genotyping data for the 17th International HLA and Immunogenetics Workshop

For over 50 years, the International HLA and Immunogenetics Workshops (IHIW) have advanced the fields of histocompatibility and immunogenetics (H&I) via community sharing of technology, experience and reagents, and the establishment of ongoing collaborative projects. Held in the fall of 2017, the 17th IHIW focused on the application of next generation sequencing (NGS) technologies for clinical and research goals in the H&I fields. NGS technologies have the potential to allow dramatic insights and advances in these fields, but the scope and sheer quantity of data associated with NGS raise challenges for their analysis, collection, exchange and storage. The 17th IHIW adopted a centralized approach to these issues, and we developed the tools, services and systems to create an effective system for capturing and managing these NGS data. We worked with NGS platform and software developers to define a set of distinct but equivalent NGS typing reports that record NGS data in a uniform fashion. The 17th IHIW database applied our standards, tools and services to collect, validate and store those structured, multi-platform data in an automated fashion. We have created community resources to enable exploration of the vast store of curated sequence and allele-name data in the IPD-IMGT/HLA Database, with the goal of creating a long-term community resource that integrates these curated data with new NGS sequence and polymorphism data, for advanced analyses and applications.

High resolution HLA analysis reveals independent class I haplotypes and amino-acid motifs protective for multiple sclerosis

We investigated association between HLA class I and class II alleles and haplotypes, and KIR loci and their HLA class I ligands, with multiple sclerosis (MS) in 412 European-American MS patients and 419 ethnically-matched controls, using next generation sequencing. The DRB1*15:01~DQB1*06:02 haplotype was highly predisposing (odds ratio (OR) = 3.98; 95% confidence interval (CI) = 3−5.31; p-value (p) = 2.22E−16), as was DRB1*03:01~DQB1*02:01 (OR = 1.63; CI = 1.19–2.24; p = 1.41E−03). Hardy-Weinberg (HW) analysis in MS patients revealed a significant DRB1*03:01~DQB1*02:01 homozyote excess (15 observed, 8.6 expected; p = 0.016). The OR for this genotype (5.27; CI = 1.47–28.52; p = 0.0036) suggests a recessive MS risk model. Controls displayed no HW deviations. The C*03:04~B*40:01 haplotype (OR = 0.27; CI = 0.14–0.51; p = 6.76E−06) was highly protective for MS, especially in haplotypes with A*02:01 (OR = 0.15; CI = 0.04–0.45; p = 6.51E−05). By itself, A*02:01 is moderately protective, (OR = 0.69; CI = 0.54–0.87; p = 1.46E−03), and haplotypes of A*02:01 with the HLA-B Thr80 Bw4 variant (Bw4T) more so (OR = 0.53; CI = 0.35–0.78; p = 7.55E−04). Protective associations with the Bw4 KIR ligand resulted from linkage disequilibrium (LD) with DRB1*15:01, but the Bw4T variant was protective (OR = 0.64; CI = 0.49–0.82; p = 3.37E−04) independent of LD with DRB1*15:01. The Bw4I variant was not associated with MS. Overall, we find specific class I HLA polymorphisms to be protective for MS, independent of the strong predisposition conferred by DRB1*15:01.

Sequence-based HLA-A, B, C, DP, DQ, and DR typing of 714 adults from Colombo, Sri Lanka

DNA sequence-based typing at the HLA-A, -B, -C, -DPB1, -DQA1, -DQB1, and -DRB1 loci was performed on 714 healthy adult blood bank donors from Colombo, Sri Lanka, to characterize allele frequencies in support of studies on T cell immunity against pathogens, including Dengue virus. Deviations from Hardy Weinberg proportions were not detected at any locus. Several alleles were found in >30% of individuals, including the class II alleles DPB1 * 04:01, DPB1 * 02:01, DQB1 * 06:01 and DRB1 * 07:01, and the class I alleles A * 33:03 and A * 24:02. Genotype data will be available in the Allele Frequencies Net Database.

Sequence-based HLA-A, B, C, DP, DQ, and DR typing of 339 adults from Managua, Nicaragua

DNA sequence-based typing at the HLA-A, -B, -C, -DPB1, -DQA1, -DQB1, and -DRB1 loci was performed on anonymized samples provided by 339 healthy adult blood bank donors in Managua, Nicaragua. The purpose of the study was to characterize allele frequencies in the local population to support studies of T cell immunity against pathogens, including Dengue virus. Deviations from Hardy Weinberg proportions were detected for all class II loci (HLA-DPB1, -DQA1, -DQB1 and -DRB1), and at the class I C locus, but not at the class I A and B loci. The genotype data will be available in the Allele Frequencies Net Database.

Sequence-based HLA-A, B, C, DP, DQ, and DR typing of 100 Luo infants from the Boro area of Nyanza Province, Kenya

One hundred healthy infants enrolled as controls in a tuberculosis vaccine study in Nyanza Province, Kenya provided anonymized samples for DNA sequence-based typing at the HLA-A, -B, -C, -DPB1, -DQA1, -DQB1, -DRB1, and -DRB3/4/5 loci. The purpose of the study was to characterize allele frequencies in the local population, to support studies of T cell immunity against pathogens, including Mycobacterium tuberculosis. There are no detectable deviations from Hardy Weinberg proportions for the HLA-B, -C, -DRB1, -DPB1, -DQA1 and -DQB1 loci. A minor deviation was detected at the HLA-A locus due to an excess of HLA-A*02:02, 29:02, 30:02, and 68:02 homozygotes. The genotype data are available in the Allele Frequencies Net Database under identifier 3393.

A gene feature enumeration approach for describing HLA allele polymorphism

HLA genotyping via next generation sequencing (NGS) poses challenges for the use of HLA allele names to analyze and discuss sequence polymorphism. NGS will identify many new synonymous and non-coding HLA sequence variants. Allele names identify the types of nucleotide polymorphism that define an allele (non-synonymous, synonymous and non-coding changes), but do not describe how polymorphism is distributed among the individual features (the flanking untranslated regions, exons and introns) of a gene. Further, HLA alleles cannot be named in the absence of antigen-recognition domain (ARD) encoding exons. Here, a system for describing HLA polymorphism in terms of HLA gene features (GFs) is proposed. This system enumerates the unique nucleotide sequences for each GF in an HLA gene, and records these in a GF enumeration notation that allows both more granular dissection of allele-level HLA polymorphism and the discussion and analysis of GFs in the absence of ARD-encoding exon sequences.

The GL service: Web service to exchange GL string encoded HLA & KIR genotypes with complete and accurate allele and genotype ambiguity

Genotype list (GL) Strings use a set of hierarchical character delimiters to represent allele and genotype ambiguity in HLA and KIR genotypes in a complete and accurate fashion. A RESTful web service called genotype list service was created to allow users to register a GL string and receive a unique identifier for that string in the form of a URI. By exchanging URIs and dereferencing them through the GL service, users can easily transmit HLA genotypes in a variety of useful formats. The GL service was developed to be secure, scalable, and persistent. An instance of the GL service is configured with a nomenclature and can be run in strict or non-strict modes. Strict mode requires alleles used in the GL string to be present in the allele database using the fully qualified nomenclature. Non-strict mode allows any GL string to be registered as long as it is syntactically correct. The GL service source code is free and open source software, distributed under the GNU Lesser General Public License (LGPL) version 3 or later.

HLA Haplotype Validator for quality assessments of HLA typing

HLA alleles are observed in specific haplotypes, due to Linkage Disequilibrium (LD) between particular alleles. Haplotype frequencies for alleles in strong LD have been established for specific ethnic groups and racial categories. Application of high-resolution HLA typing using Next Generation Sequencing (NGS) is becoming a common practice in research and clinical laboratory settings. HLA typing errors using NGS occasionally occur due to allelic sequence imbalance or misalignment. Manual inspection of HLA genotypes is labor intensive and requires an in-depth knowledge of HLA alleles and haplotypes. We developed the "HLA Haplotype Validator (HLAHapV)" software, which inspects an HLA genotype for both the presence of common and well-documented alleles and observed haplotypes. The software also reports warnings when rare alleles, or alleles that do not belong to recognized haplotypes, are found. The software validates observable haplotypes in genotype data, providing increased confidence regarding the accuracy of the HLA typing, and thus reducing the effort involved in correcting potential HLA typing errors. The HLAHapV software is a powerful tool for quality control of HLA genotypes prior to the application of downstream analyses. We demonstrate the use of the HLAHapV software for identifying unusual haplotypes, which can lead to finding potential HLA typing errors.

Minimum information for reporting next generation sequence genotyping (MIRING): Guidelines for reporting HLA and KIR genotyping via next generation sequencing

The development of next-generation sequencing (NGS) technologies for HLA and KIR genotyping is rapidly advancing knowledge of genetic variation of these highly polymorphic loci. NGS genotyping is poised to replace older methods for clinical use, but standard methods for reporting and exchanging these new, high quality genotype data are needed. The Immunogenomic NGS Consortium, a broad collaboration of histocompatibility and immunogenetics clinicians, researchers, instrument manufacturers and software developers, has developed the Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) reporting guidelines. MIRING is a checklist that specifies the content of NGS genotyping results as well as a set of messaging guidelines for reporting the results. A MIRING message includes five categories of structured information - message annotation, reference context, full genotype, consensus sequence and novel polymorphism - and references to three categories of accessory information - NGS platform documentation, read processing documentation and primary data. These eight categories of information ensure the long-term portability and broad application of this NGS data for all current histocompatibility and immunogenetics use cases. In addition, MIRING can be extended to allow the reporting of genotype data generated using pre-NGS technologies. Because genotyping results reported using MIRING are easily updated in accordance with reference and nomenclature databases, MIRING represents a bold departure from previous methods of reporting HLA and KIR genotyping results, which have provided static and less-portable data. More information about MIRING can be found online at miring.immunogenomics.org.

Genome-wide association study and admixture mapping reveal new loci associated with total IgE levels in Latinos

BACKGROUND

IgE is a key mediator of allergic inflammation, and its levels are frequently increased in patients with allergic disorders.

OBJECTIVE

We sought to identify genetic variants associated with IgE levels in Latinos.

METHODS

We performed a genome-wide association study and admixture mapping of total IgE levels in 3334 Latinos from the Genes-environments & Admixture in Latino Americans (GALA II) study. Replication was evaluated in 454 Latinos, 1564 European Americans, and 3187 African Americans from independent studies.

RESULTS

We confirmed associations of 6 genes identified by means of previous genome-wide association studies and identified a novel genome-wide significant association of a polymorphism in the zinc finger protein 365 gene (ZNF365) with total IgE levels (rs200076616, P = 2.3 × 10(-8)). We next identified 4 admixture mapping peaks (6p21.32-p22.1, 13p22-31, 14q23.2, and 22q13.1) at which local African, European, and/or Native American ancestry was significantly associated with IgE levels. The most significant peak was 6p21.32-p22.1, where Native American ancestry was associated with lower IgE levels (P = 4.95 × 10(-8)). All but 22q13.1 were replicated in an independent sample of Latinos, and 2 of the peaks were replicated in African Americans (6p21.32-p22.1 and 14q23.2). Fine mapping of 6p21.32-p22.1 identified 6 genome-wide significant single nucleotide polymorphisms in Latinos, 2 of which replicated in European Americans. Another single nucleotide polymorphism was peak-wide significant within 14q23.2 in African Americans (rs1741099, P = 3.7 × 10(-6)) and replicated in non-African American samples (P = .011).

CONCLUSION

We confirmed genetic associations at 6 genes and identified novel associations within ZNF365, HLA-DQA1, and 14q23.2. Our results highlight the importance of studying diverse multiethnic populations to uncover novel loci associated with total IgE levels.

Common and well-documented HLA alleles: 2012 update to the CWD catalogue

We have updated the catalogue of common and well-documented (CWD) human leukocyte antigen (HLA) alleles to reflect current understanding of the prevalence of specific allele sequences. The original CWD catalogue designated 721 alleles at the HLA-A, -B, -C, -DRB1, -DRB3/4/5, -DQA1, -DQB1, and -DPB1 loci in IMGT (IMmunoGeneTics)/HLA Database release 2.15.0 as being CWD. The updated CWD catalogue designates 1122 alleles at the HLA-A, -B, -C, -DRB1, -DRB3/4/5, -DQA1, -DQB1, -DPA1 and -DPB1 loci as being CWD, and represents 14.3% of the HLA alleles in IMGT/HLA Database release 3.9.0. In particular, we identified 415 of these alleles as being 'common' (having known frequencies) and 707 as being 'well-documented' on the basis of ~140,000 sequence-based typing observations and available HLA haplotype data. Using these allele prevalence data, we have also assigned CWD status to specific G and P designations. We identified 147/151 G groups and 290/415 P groups as being CWD. The CWD catalogue will be updated on a regular basis moving forward, and will incorporate changes to the IMGT/HLA Database as well as empirical data from the histocompatibility and immunogenetics community. This version 2.0.0 of the CWD catalogue is available online at cwd.immunogenomics.org, and will be integrated into the Allele Frequencies Net Database, the IMGT/HLA Database and National Marrow Donor Program's bioinformatics web pages.

Genotype List String: a grammar for describing HLA and KIR genotyping results in a text string

Knowledge of an individual's human leukocyte antigen (HLA) genotype is essential for modern medical genetics, and is crucial for hematopoietic stem cell and solid-organ transplantation. However, the high levels of polymorphism known for the HLA genes make it difficult to generate an HLA genotype that unambiguously identifies the alleles that are present at a given HLA locus in an individual. For the last 20 years, the histocompatibility and immunogenetics community has recorded this HLA genotyping ambiguity using allele codes developed by the National Marrow Donor Program (NMDP). While these allele codes may have been effective for recording an HLA genotyping result when initially developed, their use today results in increased ambiguity in an HLA genotype, and they are no longer suitable in the era of rapid allele discovery and ultra-high allele polymorphism. Here, we present a text string format capable of fully representing HLA genotyping results. This Genotype List (GL) String format is an extension of a proposed standard for reporting killer-cell immunoglobulin-like receptor (KIR) genotype data that can be applied to any genetic data that use a standard nomenclature for identifying variants. The GL String format uses a hierarchical set of operators to describe the relationships between alleles, lists of possible alleles, phased alleles, genotypes, lists of possible genotypes, and multilocus unphased genotypes, without losing typing information or increasing typing ambiguity. When used in concert with appropriate tools to create, exchange, and parse these strings, we anticipate that GL Strings will replace NMDP allele codes for reporting HLA genotypes.

16(th) IHIW: immunogenomic data-management methods. report from the immunogenomic data analysis working group (IDAWG)

SUMMARY

The goal of the immunogenomic data analysis working group (IDAWG) is to facilitate the consistent analysis of HLA and KIR data, and the sharing of those data among the immunogenomic and larger genomic communities. However, the data management approaches currently applied by immunogenomic researchers are not widely discussed or reported in the literature, and the effect of different approaches on data analyses is not known. With ASHI's support, the IDAWG developed a 45 question survey on HLA and KIR data generation, data management and data analysis practices. Survey questions detailed the loci genotyped, typing systems used, nomenclature versions reported, computer operating systems and software used to manage and transmit data, the approaches applied to resolve HLA ambiguity and the methods used for basic population-level analyses. Respondents were invited to demonstrate their HLA ambiguity resolution approaches in simulated data sets. By May 2012, 156 respondents from 35 nations had completed the survey. These survey respondents represent a broad sampling of the Immunogenomic community; 52% were European, 30% North American, 10% Asian, 4% South American and 4% from the Pacific. The project will continue in conjunction with the 17th Workshop, with the aim of developing community data sharing standards, ambiguity resolution documentation formats, single-task data Management tools and novel data analysis methods and applications. While additional project details and plans for the 17th IHIW will be forthcoming, we welcome the input and participation in these projects from the histocompatibility and immunogenetics community.

16(th) IHIW: extending the number of resources and bioinformatics analysis for the investigation of HLA rare alleles

Continuing a project presented at the 15th International HLA and Immunogenetics Workshop (IHIWS) on the rarity of HLA alleles, we sought to expand the number of data sources and bioinformatics tools available in the Allele Frequencies Net Database website (AFND, www.allelefrequencies.net). In this 16th IHIWS Rare Alleles project, HLA alleles described in the latest IMGT/HLA Database (release 3.8.0) were queried against different sources including data from registries (stem cell) and from 74 different laboratories around the world. We demonstrated that approximately 40% of the alleles officially named in the IMGT/HLA Database have been reported only once across all different sources. To facilitate the large-scale analysis of rare alleles, we have produced an online tool called the Rare Allele Detector that simplifies the detection of alleles that are considered to be 'very rare', 'rare' or 'frequent'. Tools and associated data can be accessed via the www.allelefrequencies.net website.

A sequence-based approach demonstrates that balancing selection in classical human leukocyte antigen (HLA) loci is asymmetric

Balancing selection has maintained human leukocyte antigen (HLA) allele diversity, but it is unclear whether this selection is symmetric (all heterozygotes are comparable and all homozygotes are comparable in terms of fitness) or asymmetric (distinct heterozygote genotypes display greater fitness than others). We tested the hypothesis that HLA is under asymmetric balancing selection in populations by estimating allelic branch lengths from genetic sequence data encoding peptide-binding domains. Significant deviations indicated changes in the ratio of terminal to internal branch lengths. Such deviations could arise even if no individual alleles present a strikingly altered branch length (e.g. if there is an overall distortion, with all or many terminal branches being longer than expected). DQ and DP loci were also analyzed as haplotypes. Using allele frequencies for 419 distinct populations in 10 geographical regions, we examined population differentiation in alleles within and between regions, and the relationship between allelic branch length and frequency. The strongest evidence for asymmetrical balancing selection was observed for HLA-DRB1, HLA-B and HLA-DPA1, with significant deviation (P ≤ 1.1 × 10(-4)) in about half of the populations. There were significant results at all loci except HLA-DQB1/DQA1. We observed moderate genetic variation within and between geographic regions, similar to the rest of the genome. Branch length was not correlated with allele frequency. In conclusion, sequence data suggest that balancing selection in HLA is asymmetric (some heterozygotes enjoy greater fitness than others). Because HLA polymorphism is crucial for pathogen resistance, this may manifest as a frequency-dependent selection with fluctuation in the fitness of specific heterozygotes over time.

A community standard for immunogenomic data reporting and analysis: proposal for a STrengthening the REporting of Immunogenomic Studies statement

Modern high-throughput HLA and KIR typing technologies are generating a wealth of immunogenomic data with the potential to revolutionize the fields of histocompatibility and immune-related disease association and population genetic research, much as SNP-based approaches have revolutionized association research. The STrengthening the REporting of Genetic Association studies (STREGA) statement provides community-based data reporting and analysis standards for genomic disease-association studies, identifying specific areas in which adoption of reporting guidelines can improve the consistent interpretation of genetic studies. While aspects of STREGA can be applied to immunogenomic studies, HLA and KIR research requires additional consideration, as the high levels of polymorphism associated with immunogenomic data pose unique methodological and computational challenges to the synthesis of information across datasets. Here, we outline the principle challenges to consistency in immunogenomic studies, and propose that an immunogenomic-specific analog to the STREGA statement, a STrengthening the REporting of Immunogenomic Studies (STREIS) statement, be developed as part of the 16th International HLA and Immunogenetics Workshop. We propose that STREIS extends at least four of the 22 elements of the STREGA statement to specifically address issues pertinent to immunogenomic data: HLA and KIR nomenclature, data-validation, ambiguity resolution, and the analysis of highly polymorphic genetic systems. As with the STREGA guidelines, the intent behind STREIS is not to dictate the design of immunogenomic studies, but to ensure consistent and transparent reporting of research, facilitating the synthesis of HLA and KIR data across studies.

Analytical methods for immunogenetic population data

In this chapter, we describe analyses commonly applied to immunogenetic population data, along with software tools that are currently available to perform those analyses. Where possible, we focus on tools that have been developed specifically for the analysis of highly polymorphic immunogenetic data. These analytical methods serve both as a means to examine the appropriateness of a dataset for testing a specific hypothesis, as well as a means of testing hypotheses. Rather than treat this chapter as a protocol for analyzing any population dataset, each researcher and analyst should first consider their data, the possible analyses, and any available tools in light of the hypothesis being tested. The extent to which the data and analyses are appropriate to each other should be determined before any analyses are performed.

Immunogenetics as a tool in anthropological studies

The genes coding for the main molecules involved in the human immune system--immunoglobulins, human leucocyte antigen (HLA) molecules and killer-cell immunoglobulin-like receptors (KIR)--exhibit a very high level of polymorphism that reveals remarkable frequency variation in human populations. 'Genetic marker' (GM) allotypes located in the constant domains of IgG antibodies have been studied for over 40 years through serological typing, leading to the identification of a variety of GM haplotypes whose frequencies vary sharply from one geographic region to another. An impressive diversity of HLA alleles, which results in amino acid substitutions located in the antigen-binding region of HLA molecules, also varies greatly among populations. The KIR differ between individuals according to both gene content and allelic variation, and also display considerable population diversity. Whereas the molecular evolution of these polymorphisms has most likely been subject to natural selection, principally driven by host-pathogen interactions, their patterns of genetic variation worldwide show significant signals of human geographic expansion, demographic history and cultural diversification. As current developments in population genetic analysis and computer simulation improve our ability to discriminate among different--either stochastic or deterministic--forces acting on the genetic evolution of human populations, the study of these systems shows great promise for investigating both the peopling history of modern humans in the time since their common origin and human adaptation to past environmental (e.g. pathogenic) changes. Therefore, in addition to mitochondrial DNA, Y-chromosome, microsatellites, single nucleotide polymorphisms and other markers, immunogenetic polymorphisms represent essential and complementary tools for anthropological studies.

Human leukocyte antigen-A, -B, -C, -DRB1 allele and haplotype frequencies in Americans originating from southern Europe: contrasting patterns of population differentiation between Italian and Spanish Americans

High-resolution DNA sequencing was used to identify the human leukocyte antigen (HLA) -A, -B, -C, and -DRB1 alleles found in 552 individuals from the United States indicating Southern European (Italian or Spanish) heritage. A total of 46 HLA-A, 80 HLA-B, 32 HLA-C, and 50 DRB1 alleles were identified. Frequent alleles included A*02:01:01G (allele frequency = 0.26 in Italian Americans and 0.22 in Spanish Americans); B*07:02:01G (Italian Americans allele frequency = 0.11); B*44:03 (Spanish Americans allele frequency = 0.07); C*04:01:01G and C*07:01:01G (allele frequency = 0.13 and 0.16, respectively, in Italian Americans; 0.15 and 0.12, respectively, in Spanish Americans); and DRB1*07:01:01 (allele frequency = 0.12 in each population). The action of balancing selection was inferred at the HLA-B and -C loci in both populations. The A*01:01:01G-C*07:01:01G-B*08:01:01G-DRB1*03:01:01 haplotype was the most frequent A-C-B-DRB1 haplotype in Italian Americans (haplotype frequency = 0.049), and was the second most frequent haplotype in Spanish Americans (haplotype frequency = 0.021). A*29:02:01-C*16:01:01-B*44:03-DRB1*07:01:01 was the most frequent A-C-B-DRB1 in Spanish Americans (haplotype frequency = 0.023), and was observed at a frequency of 0.015 in Italian Americans. Pairwise F'(st) values measuring the degree of differentiation between these Southern European American populations as well as European and European American populations suggest that Spanish Americans constitute a distinct subset of the European American population, most similar to Mexican Americans, whereas Italian Americans cannot be distinguished from the larger European American population.

Allele Name Translation Tool and Update NomenCLature: software tools for the automated translation of HLA allele names between successive nomenclatures

In this brief communication, we describe the Allele Name Translation Tool (antt) and Update NomenCLature (uncl), free programs developed to facilitate the translation of human leukocyte antigen (HLA) allele names recorded using the December 2002 version of the HLA allele nomenclature (e.g. A*01010101) to those recorded using the colon-delimited version of the HLA allele nomenclature (e.g. A*01:01:01:01) that was adopted in April 2010. In addition, the antt and uncl translate specific HLA allele-name changes (e.g. DPB1*0502 is translated to DPB1*104:01), as well as changes to the locus prefix for HLA-C (i.e. Cw* is translated to C*). The antt and uncl will also translate allele names that have been truncated to two, four, or six digits, as well as ambiguous allele strings. The antt is a locally installed and run application, while uncl is a web-based tool that requires only an Internet connection and a modern browser. The antt accepts a variety of HLA data-presentation and allele-name formats. In addition, the antt can translate using user-defined conversion settings (e.g. the names of alleles that encode identical peptide binding domains can be translated to a common 'P-code'), and can serve as a preliminary data-sanity tool. The antt is available for download, and uncl for use, at www.igdawg.org/software.

Association analysis of SNPs in the IL4R locus with type I diabetes

The Type I Diabetes Genetics Consortium (T1DGC) has collected thousands of multiplex and simplex families with type I diabetes (T1D) with the goal of identifying genes involved in T1D susceptibility. These families have all been genotyped for the HLA class I and class II loci and a subset of samples has been typed for an major histocompatibility complex (MHC) single-nucleotide polymorphism (SNP) panel. In addition, the T1DGC has genotyped SNPs in candidate genes to evaluate earlier reported T1D associations. Individual SNPs and SNP haplotypes in IL4R, which encodes the alpha-chain of the IL4 and IL13 receptors, have been associated with T1D in some reports, but not in others. In this study, 38 SNPs in IL4R were genotyped using the Sequenom iPLEX Gold MassARRAY technology in 2042 multiplex families from nine cohorts. Association analyses (transmission-disequilibrium test and parental-disequilibrium test) were performed on individual SNPs and on three-SNP haplotypes. Analyses were also stratified on the high-risk HLA DR3/DR4-DQB1*0302 genotype. A modest T1D association in HBDI families (n=282) was confirmed in this larger collection of HBDI families (n=424). The variant alleles at the non-synonymous SNPs (rs1805011 (E400A), rs1805012 (C431R), and rs1801275 (Q576R)), which are in strong linkage disequilibrium, were negatively associated with T1D risk. These SNPs were more associated with T1D among non-DR3/DR4-DQB1*0302 genotypes than DR3/DR4-DQB1*0302 genotypes. This association was stronger, both in terms of odds ratio and P-values, than the initial report of the smaller collection of HBDI families. However, the IL4R SNPs and the three-SNP haplotype containing the variant alleles were not associated with T1D in the total data. Thus, in the overall families, these results do not show evidence for an association of SNPs in IL4R with T1D.