Systematic identification of minor histocompatibility antigens predicts outcomes of allogeneic hematopoietic cell transplantation.

T cell alloreactivity against minor histocompatibility antigens (mHAgs)-polymorphic peptides resulting from donor-recipient (D-R) disparity at sites of genetic polymorphisms-is at the core of the therapeutic effect of allogeneic hematopoietic cell transplantation (allo-HCT). Despite the crucial role of mHAgs in graft-versus-leukemia (GvL) and graft-versus-host disease (GvHD) reactions, it remains challenging to consistently link patient-specific mHAg repertoires to clinical outcomes. Here we devise an analytic framework to systematically identify mHAgs, including their detection on HLA class I ligandomes and functional verification of their immunogenicity. The method relies on the integration of polymorphism detection by whole-exome sequencing of germline DNA from D-R pairs with organ-specific transcriptional- and proteome-level expression. Application of this pipeline to 220 HLA-matched allo-HCT D-R pairs demonstrated that total and organ-specific mHAg load could independently predict the occurrence of acute GvHD and chronic pulmonary GvHD, respectively, and defined promising GvL targets, confirmed in a validation cohort of 58 D-R pairs, for the prevention or treatment of post-transplant disease recurrence.

Three novel Er blood group system alleles and insights from protein modeling.

BACKGROUND: The Er blood group system was recently shown to be defined by PIEZO1. The system consists of high prevalence antigens Era, Er3, ERSA, and ERAMA; and low prevalence antigen Erb. Era/Erb are antithetical with Er(a-b+) defined by the ER*B allele [c.7180G>A p.(Gly2394Ser)]. A nonsense variant c.5289C>G p.(Tyr1763*) is associated with a predicted Ernull phenotype, and a missense variant c.7174G>A p.(Glu2392Lys) in close proximity to p.2394 causes loss of both Era and Erb expression. STUDY DESIGN AND METHODS: We investigated PIEZO1 in four Er(a-) individuals who presented with anti-Era. Whole genome sequencing (WGS) and Sanger sequencing were performed. The location and structural differences of predicted protein changes were visualized using the predicted 3-D structure of Piezo1 created using AlphaFold2. RESULTS: One individual was homozygous for the reported ER*B. A second had a novel heterozygous nonsense variant c.3331C>T p.(Gln1111*), but a second allelic variant was not found. In the remaining two individuals, two different heterozygous novel missense variants, c.7184C>T p.(Ala2395Val) or c.7195G>A p.(Gly2399Ser), were in trans to the reported c.7180G>A variant, ER*B. AlphaFold2 protein modeling showed that each of the missense variants is predicted to encode an altered structural conformation near Era and Erb. CONCLUSIONS: Investigation of archived samples resulted in the identification of three novel PIEZO1 alleles including a predicted Ernull and two missense variants. Structural modeling suggests that the missense changes potentially alter Era/Erb epitope expression with p.2399Ser resulting in a small increase in the negative electrostatic potential.

Galectin-4 Antimicrobial Activity Primarily Occurs Through its C-Terminal Domain.

Although immune tolerance evolved to reduce reactivity with self, it creates a gap in the adaptive immune response against microbes that decorate themselves in self-like antigens. This is particularly apparent with carbohydrate-based blood group antigens, wherein microbes can envelope themselves in blood group structures similar to human cells. In this study, we demonstrate that the innate immune lectin, galectin-4 (Gal-4), exhibits strain-specific binding and killing behavior towards microbes that display blood group-like antigens. Examination of binding preferences using a combination of microarrays populated with ABO(H) glycans and a variety of microbial strains, including those that express blood group-like antigens, demonstrated that Gal-4 binds mammalian and microbial antigens that have features of blood group and mammalian-like structures. Although Gal-4 was thought to exist as a monomer that achieves functional bivalency through its two linked carbohydrate recognition domains, our data demonstrate that Gal-4 forms dimers and that differences in the intrinsic ability of each domain to dimerize likely influences binding affinity. While each Gal-4 domain exhibited blood group-binding activity, the C-terminal domain (Gal-4C) exhibited dimeric properties, while the N-terminal domain (Gal-4N) failed to similarly display dimeric activity. Gal-4C not only exhibited the ability to dimerize but also possessed higher affinity toward ABO(H) blood group antigens and microbes expressing glycans with blood group-like features. Furthermore, when compared to Gal-4N, Gal-4C exhibited more potent antimicrobial activity. Even in the context of the full-length protein, where Gal-4N is functionally bivalent by virtue of Gal-4C dimerization, Gal-4C continued to display higher antimicrobial activity. These results demonstrate that Gal-4 exists as a dimer and exhibits its antimicrobial activity primarily through its C-terminal domain. In doing so, these data provide important insight into key features of Gal-4 responsible for its innate immune activity against molecular mimicry.

Blood Demand Forecasting and Supply Management: An Analytical Assessment of Key Studies Utilizing Novel Computational Techniques.

Use of data-driven methodologies in enhancing blood transfusion practices is rising, leveraging big data, machine learning, and optimization techniques to improve demand forecasting and supply chain management. This review used a narrative approach to identify, evaluate, and synthesize key studies that considered novel computational techniques for blood demand forecasting and inventory management through a search of PubMed and Web of Sciences databases for studies published from January 01, 2016, to March 30, 2023. The studies were analyzed for their utilization of various techniques, and their strengths, limitations, and areas for improvement. Seven key studies were identified. The studies focused on different blood components using various computational methods, such as regression, machine learning, hybrid models, and time series models, across different locations and time periods. Key variables used for demand forecasting were largely derived from electronic health record data, including clinical related predictors such as laboratory test results and hospital census by location. Each study offered unique strengths and valuable insights into the use of data-driven methods in blood bank management. Common limitations were unknown generalizability to other healthcare settings or blood components, need for field-specific performance measures, lack of ABO compatibility consideration, and ethical challenges in resource allocation. While data-driven research in blood demand forecasting and management has progressed, limitations persist and further exploration is needed. Understanding these innovative, interdisciplinary methods and their complexities can help refine inventory strategies and address healthcare challenges more effectively, leading to more robust, accurate models to enhance blood management across diverse healthcare scenarios.

Integrated Immunopeptidomic and Proteomic Analysis of COVID-19 lung biopsies.

Introduction: Severe respiratory illness is the most prominent manifestation of patients infected with SARS-CoV-2, and yet the molecular mechanisms underlying severe lung disease in COVID-19 affected patients still require elucidation. Human leukocyte antigen class I (HLA-I) expression is crucial for antigen presentation and the host's response to SARS-CoV-2. Methods: To gain insights into the immune response and molecular pathways involved in severe lung disease, we performed immunopeptidomic and proteomic analyses of lung tissues recovered at four COVID-19 autopsy and six non-COVID-19 transplants. Results: We found signals of tissue injury and regeneration in lung fibroblast and alveolar type I/II cells, resulting in the production of highly immunogenic self-antigens within the lungs of COVID-19 patients. We also identified immune activation of the M2c macrophage as the primary source of HLA-I presentation and immunogenicity in this context. Additionally, we identified 28 lung signatures that can serve as early plasma markers for predicting infection and severe COVID-19 disease. These protein signatures were predominantly expressed in macrophages and epithelial cells and were associated with complement and coagulation cascades. Discussion: Our findings emphasize the significant role of macrophage-mediated immunity in the development of severe lung disease in COVID-19 patients.

Impact of allele-specific anti-human leukocyte antigen class I antibodies on organ allocation.

Technological advances in the field of histocompatibility have allowed us to define anti-human leukocyte antigen (HLA) antibody specificity at the allelic level. However, how allele-specific antibodies affect organ allocation is poorly studied. We examined allelic specificities of class I HLA antibodies in 6726 consecutive serum samples from 2953 transplant candidates and evaluated their impact on the corresponding crossmatch and organ allocation. Out of 17 class I HLA antigens represented by >1 allele in the LABScreen single antigen bead assay, 12 had potential allele-specific reactivity. Taking advantage of our unbiased cohort of deceased donor-candidate testing (123,135 complement-dependent cytotoxicity crossmatches between 2014 and 2017), we estimated that the presence of allele-specific antibody detected using a single antigen bead assay (median fluorescence intensity, >3000) against only the rare allele was a poor predictor of a positive complement-dependent cytotoxicity crossmatch, with a positive predictive value of 0% to 7%, compared with 52.5% in allele-concordant class I HLA antibodies against A or B locus antigens. Further, we confirmed allele-specific reactivity using flow crossmatch in 3 scenarios: A11:01/A11:02, A68:01/A68:02, and B44:02/B44:03. Our results suggest that allele-specific antibodies may unnecessarily exclude transplant candidates (up to 10%) from organ offers by overcalling unacceptable antigens; incorporation of selective reactivity pattern in allocation may promote precision matching and more equitable allocation.

ABO Genotyping finds more A2 to B kidney transplant opportunities than lectin-based subtyping.

ABO compatibility is important for kidney transplantation, with longer waitlist times for blood group B kidney transplant candidates. However, kidneys from non-A1 (eg, A2) subtype donors, which express less A antigen, can be safely transplanted into group B recipients. ABO subtyping is routinely performed using anti-A1 lectin, but DNA-based genotyping is also possible. Here, we compare lectin and genotyping testing. Lectin and genotype subtyping was performed on 554 group A deceased donor samples at 2 transplant laboratories. The findings were supported by 2 additional data sets of 210 group A living kidney donors and 124 samples with unclear lectin testing sent to a reference laboratory. In deceased donors, genotyping found 65% more A2 donors than lectin testing, most with weak lectin reactivity, a finding supported in living donors and samples sent for reference testing. DNA sequencing and flow cytometry showed that the discordances were because of several factors, including transfusion, small variability in A antigen levels, and rare ABO∗A2.06 and ABO∗A2.16 sequences. Although lectin testing is the current standard for transplantation subtyping, genotyping is accurate and could increase A2 kidney transplant opportunities for group B candidates, a difference that should reduce group B wait times and improve transplant equity.

Genome Reporting for Healthy Populations-Pipeline for Genomic Screening from the GENCOV COVID-19 Study.

Genome sequencing holds the promise for great public health benefits. It is currently being used in the context of rare disease diagnosis and novel gene identification, but also has the potential to identify genetic disease risk factors in healthy individuals. Genome sequencing technologies are currently being used to identify genetic factors that may influence variability in symptom severity and immune response among patients infected by SARS-CoV-2. The GENCOV study aims to look at the relationship between genetic, serological, and biochemical factors and variability of SARS-CoV-2 symptom severity, and to evaluate the utility of returning genome screening results to study participants. Study participants select which results they wish to receive with a decision aid. Medically actionable information for diagnosis, disease risk estimation, disease prevention, and patient management are provided in a comprehensive genome report. Using a combination of bioinformatics software and custom tools, this article describes a pipeline for the analysis and reporting of genetic results to individuals with COVID-19, including HLA genotyping, large-scale continental ancestry estimation, and pharmacogenomic analysis to determine metabolizer status and drug response. In addition, this pipeline includes reporting of medically actionable conditions from comprehensive gene panels for Cardiology, Neurology, Metabolism, Hereditary Cancer, and Hereditary Kidney, and carrier screening for reproductive planning. Incorporated into the genome report are polygenic risk scores for six diseases-coronary artery disease; atrial fibrillation; type-2 diabetes; and breast, prostate, and colon cancer-as well as blood group genotyping analysis for ABO and Rh blood types and genotyping for other antigens of clinical relevance. The genome report summarizes the findings of these analyses in a way that extensively communicates clinically relevant results to patients and their physicians. © 2022 Wiley Periodicals LLC. Basic Protocol 1: HLA genotyping and disease association Basic Protocol 2: Large-scale continental ancestry estimation Basic Protocol 3: Dosage recommendations for pharmacogenomic gene variants associated with drug response Support Protocol: System setup.

International Society of Blood Transfusion Working Party on Red Cell Immunogenetics and Blood Group Terminology Report of Basel and three virtual business meetings: Update on blood group systems.

BACKGROUND AND OBJECTIVES: Under the ISBT, the Working Party (WP) for Red Cell Immunogenetics and Blood Group Terminology is charged with ratifying blood group systems, antigens and alleles. This report presents the outcomes from four WP business meetings, one located in Basel in 2019 and three held as virtual meetings during the COVID-19 pandemic in 2020 and 2021. MATERIALS AND METHODS: As in previous meetings, matters pertaining to blood group antigen nomenclature were discussed. New blood group systems and antigens were approved and named according to the serologic, genetic, biochemical and cell biological evidence presented. RESULTS: Seven new blood group systems, KANNO (defined numerically as ISBT 037), SID (038), CTL2 (039), PEL (040), MAM (041), EMM (042) and ABCC1 (043) were ratified. Two (039 and 043) were de novo discoveries, and the remainder comprised reported antigens where the causal genes were previously unknown. A further 15 blood group antigens were added to the existing blood group systems: MNS (002), RH (004), LU (005), DI (010), SC (013), GE (020), KN (022), JMH (026) and RHAG (030). CONCLUSION: The ISBT now recognizes 378 antigens, of which 345 are clustered within 43 blood group systems while 33 still have an unknown genetic basis. The ongoing discovery of new blood group systems and antigens underscores the diverse and complex biology of the red cell membrane. The WP continues to update the blood group antigen tables and the allele nomenclature tables. These can be found on the ISBT website (http://www.isbtweb.org/working-parties/red-cell-immunogenetics-and-blood-group-terminology/).

Reversal of viral and epigenetic HLA class I repression in Merkel cell carcinoma.

Cancers avoid immune surveillance through an array of mechanisms, including perturbation of HLA class I antigen presentation. Merkel cell carcinoma (MCC) is an aggressive, HLA-I-low, neuroendocrine carcinoma of the skin often caused by the Merkel cell polyomavirus (MCPyV). Through the characterization of 11 newly generated MCC patient-derived cell lines, we identified transcriptional suppression of several class I antigen presentation genes. To systematically identify regulators of HLA-I loss in MCC, we performed parallel, genome-scale, gain- and loss-of-function screens in a patient-derived MCPyV-positive cell line and identified MYCL and the non-canonical Polycomb repressive complex 1.1 (PRC1.1) as HLA-I repressors. We observed physical interaction of MYCL with the MCPyV small T viral antigen, supporting a mechanism of virally mediated HLA-I suppression. We further identify the PRC1.1 component USP7 as a pharmacologic target to restore HLA-I expression in MCC.

Innate immune Galectin-7 specifically targets microbes that decorate themselves in blood group-like antigens.

Adaptive immunity can target a nearly infinite range of antigens, yet it is tempered by tolerogenic mechanisms that limit autoimmunity. Such immunological tolerance, however, creates a gap in adaptive immunity against microbes decorated with self-like antigens as a form of molecular mimicry. Our results demonstrate that the innate immune lectin galectin-7 (Gal-7) binds a variety of distinct microbes, all of which share features of blood group-like antigens. Gal-7 binding to each blood group expressing microbe, including strains of Escherichia coli, Klebsiella pneumoniae, Providencia alcalifaciens, and Streptococcus pneumoniae, results in loss of microbial viability. Although Gal-7 also binds red blood cells (RBCs), this interaction does not alter RBC membrane integrity. These results demonstrate that Gal-7 recognizes a diverse range of microbes, each of which use molecular mimicry while failing to induce host cell injury, and thus may provide an innate form of immunity against molecular mimicry.

Recommendation for validation and quality assurance of non-invasive prenatal testing for foetal blood groups and implications for IVD risk classification according to EU regulations.

BACKGROUND AND OBJECTIVES: Non-invasive assays for predicting foetal blood group status in pregnancy serve as valuable clinical tools in the management of pregnancies at risk of detrimental consequences due to blood group antigen incompatibility. To secure clinical applicability, assays for non-invasive prenatal testing of foetal blood groups need to follow strict rules for validation and quality assurance. Here, we present a multi-national position paper with specific recommendations for validation and quality assurance for such assays and discuss their risk classification according to EU regulations. MATERIALS AND METHODS: We reviewed the literature covering validation for in-vitro diagnostic (IVD) assays in general and for non-invasive foetal RHD genotyping in particular. Recommendations were based on the result of discussions between co-authors. RESULTS: In relation to Annex VIII of the In-Vitro-Diagnostic Medical Device Regulation 2017/746 of the European Parliament and the Council, assays for non-invasive prenatal testing of foetal blood groups are risk class D devices. In our opinion, screening for targeted anti-D prophylaxis for non-immunized RhD negative women should be placed under risk class C. To ensure high quality of non-invasive foetal blood group assays within and beyond the European Union, we present specific recommendations for validation and quality assurance in terms of analytical detection limit, range and linearity, precision, robustness, pre-analytics and use of controls in routine testing. With respect to immunized women, different requirements for validation and IVD risk classification are discussed. CONCLUSION: These recommendations should be followed to ensure appropriate assay performance and applicability for clinical use of both commercial and in-house assays.

PIGG defines the Emm blood group system.

Emm is a high incidence red cell antigen with eight previously reported Emm- probands. Anti-Emm appears to be naturally occurring yet responsible for a clinically significant acute hemolytic transfusion reaction. Previous work suggests that Emm is located on a GPI-anchored protein, but the antigenic epitope and genetic basis have been elusive. We investigated samples from a South Asian Indian family with two Emm- brothers by whole genome sequencing (WGS). Additionally, samples from four unrelated Emm- individuals were investigated for variants in the candidate gene. Filtering for homozygous variants found in the Emm- brothers and by gnomAD frequency of < 0.001 resulted in 1818 variants with one of high impact; a 2-bp deletion causing a frameshift and premature stop codon in PIGG [NM_001127178.3:c.2624_2625delTA, p.(Leu875*), rs771819481]. PIGG encodes for a transferase, GPI-ethanolaminephosphate transferase II, which adds ethanolamine phosphate (EtNP) to the second mannose in a GPI-anchor. The four additional unrelated Emm- individuals had various PIGG mutations; deletion of Exons 2-3, deletion of Exons 7-9, insertion/deletion (indel) in Exon 3, and new stop codon in Exon 5. The Emm- phenotype is associated with a rare deficiency of PIGG, potentially defining a new Emm blood group system composed of EtNP bound to mannose, part of the GPI-anchor. The results are consistent with the known PI-linked association of the Emm antigen, and may explain the production of the antibody in the absence of RBC transfusion. Any association with neurologic phenotypes requires further research.

Development and validation of a universal blood donor genotyping platform: a multinational prospective study.

Each year, blood transfusions save millions of lives. However, under current blood-matching practices, sensitization to non-self-antigens is an unavoidable adverse side effect of transfusion. We describe a universal donor typing platform that could be adopted by blood services worldwide to facilitate a universal extended blood-matching policy and reduce sensitization rates. This DNA-based test is capable of simultaneously typing most clinically relevant red blood cell (RBC), human platelet (HPA), and human leukocyte (HLA) antigens. Validation was performed, using samples from 7927 European, 27 South Asian, 21 East Asian, and 9 African blood donors enrolled in 2 national biobanks. We illustrated the usefulness of the platform by analyzing antibody data from patients sensitized with multiple RBC alloantibodies. Genotyping results demonstrated concordance of 99.91%, 99.97%, and 99.03% with RBC, HPA, and HLA clinically validated typing results in 89 371, 3016, and 9289 comparisons, respectively. Genotyping increased the total number of antigen typing results available from 110 980 to >1 200 000. Dense donor typing allowed identification of 2 to 6 times more compatible donors to serve 3146 patients with multiple RBC alloantibodies, providing at least 1 match for 176 individuals for whom previously no blood could be found among the same donors. This genotyping technology is already being used to type thousands of donors taking part in national genotyping studies. Extraction of dense antigen-typing data from these cohorts provides blood supply organizations with the opportunity to implement a policy of genomics-based precision matching of blood.

Overcoming the challenges of interpreting complex and uncommon RH alleles from whole genomes.

BACKGROUND AND OBJECTIVES: Rh is one of the most diverse and complex blood group systems. Recently, next generation sequencing (NGS) has proven to be a viable option for RH genotyping. We have developed automated software (bloodTyper) for determining alleles encoding RBC antigens from NGS-based whole genome sequencing (WGS). The bloodTyper algorithm has not yet been optimized and evaluated for complex and uncommon RH alleles. MATERIALS AND METHODS: Twenty-two samples with previous polymerase chain reaction (PCR) and Sanger sequencing-based RH genotyping underwent WGS. bloodTyper was used to detect RH alleles including those defined by structural variation (SV) using a combination of three independent strategies: sequence read depth of coverage, split reads and paired reads. RESULTS: bloodTyper was programmed to identify D negative and positive phenotypes as well as the presence of alleles encoding weak D, partial D and variant RHCE. Sequence read depth of coverage calculation accurately determined RHD zygosity and detected the presence of RHD/RHCE hybrids. RHCE*C was determined by sequence read depth of coverage and by split read methods. RHD hybrid alleles and RHCE*C were confirmed by using a paired read approach. Small SVs present in RHCE*CeRN and RHCE*ceHAR were detected by a combined read depth of coverage and paired read approach. CONCLUSIONS: The combination of several different interpretive approaches allowed for automated software based-RH genotyping of WGS data including RHD zygosity and complex compound RHD and RHCE heterozygotes. The scalable nature of this automated analysis will enable RH genotyping in large genomic sequencing projects.

Multiple GYPB gene deletions associated with the U- phenotype in those of African ancestry.

BACKGROUND: The MNS blood group system is defined by three homologous genes: GYPA, GYPB, and GYPE. GYPB encodes for glycophorin B (GPB) carrying S/s and the "universal" antigen U. RBCs of approximately 1% of individuals of African ancestry are U- due to absence of GPB. The U- phenotype has long been attributed to a deletion encompassing GYPB exons 2 to 5 and GYPE exon 1 (GYPB*01N). STUDY DESIGN AND METHODS: Samples from two U-individuals underwent Illumina short read whole genome sequencing (WGS) and Nanopore long read WGS. In addition, two existing WGS datasets, MedSeq (n = 110) and 1000 Genomes (1000G, n = 2535), were analyzed for GYPB deletions. Deletions were confirmed by Sanger sequencing. Twenty known U- donor samples were tested by a PCR assay to determine the specific deletion alleles present in African Americans. RESULTS: Two large GYPB deletions in U- samples of African ancestry were identified: a 110 kb deletion extending left of GYPB (DEL_B_LEFT) and a 103 kb deletion extending right (DEL_B_RIGHT). DEL_B_LEFT and DEL_B_RIGHT were the most common GYPB deletions in the 1000 Genomes Project 669 African genomes (allele frequencies 0.04 and 0.02). Seven additional deletions involving GYPB were seen in African, Admixed American, and South Asian samples. No samples analyzed had GYPB*01N. CONCLUSIONS: The U- phenotype in those of African ancestry is primarily associated with two different complete deletions of GYPB (with intact GYPE). Seven additional less common GYPB deletion backgrounds were found. GYPB*01N, long assumed to be the allele commonly encoding U- phenotypes, appears to be rare.

A large peptidome dataset improves HLA class I epitope prediction across most of the human population.

Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides across a large fraction of the human population, we used mass spectrometry to profile >185,000 peptides eluted from 95 HLA-A, -B, -C and -G mono-allelic cell lines. We identified canonical peptide motifs per HLA allele, unique and shared binding submotifs across alleles and distinct motifs associated with different peptide lengths. By integrating these data with transcript abundance and peptide processing, we developed HLAthena, providing allele-and-length-specific and pan-allele-pan-length prediction models for endogenous peptide presentation. These models predicted endogenous HLA class I-associated ligands with 1.5-fold improvement in positive predictive value compared with existing tools and correctly identified >75% of HLA-bound peptides that were observed experimentally in 11 patient-derived tumor cell lines.

Automated typing of red blood cell and platelet antigens from whole exome sequences.

BACKGROUND: Genotyping has expanded the number red blood cell (RBC) and platelet (PLT) antigens that can readily be typed, but often represents an additional testing cost. The analysis of existing genomic data offers a cost-effective approach. We recently developed automated software (bloodTyper) for determination of RBC and PLT antigens from whole genome sequencing. Here we extend the algorithm to whole exome sequencing (WES). STUDY DESIGN AND METHODS: Whole exome sequencing was performed on samples from 75 individuals. WES-based bloodTyper RBC and PLT typing was compared to conventional polymerase chain reaction (PCR) RHD zygosity testing and serologic and single-nucleotide polymorphism (SNP) typing for 38 RBC antigens in 12 systems (17 serologic and 35 SNPs) and 22 PLT antigens (22 SNPs). Samples from the first 20 individuals were used to modify bloodTyper to interpret WES followed by blinded typing of 55 samples. RESULTS: Over the first 20 samples, discordances were noted for C, M, and N antigens, which were due to WES-specific biases. After modification, bloodTyper was 100% accurate on blinded evaluation of the last 55 samples and outperformed both serologic (99.67% accurate) and SNP typing (99.97% accurate) reflected by two Fyb and one N serologic typing errors and one undetected SNP encoding a Jknull phenotype. RHD zygosity testing by bloodTyper was 100% concordant with a combination of hybrid Rhesus box PCR and PCR-restriction fragment length polymorphism for all samples. CONCLUSION: The automated bloodTyper software was modified for WES biases to allow for accurate RBC and PLT antigen typing. Such analysis could become a routing part of future WES efforts.