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

Machine learning to optimize automated RH genotyping using whole-exome sequencing data

ABSTRACT

Rh phenotype matching reduces but does not eliminate alloimmunization in patients with sickle cell disease (SCD) due to RH genetic diversity that is not distinguishable by serological typing. RH genotype matching can potentially mitigate Rh alloimmunization but comprehensive and accessible genotyping methods are needed. We developed RHtyper as an automated algorithm to predict RH genotypes using whole-genome sequencing (WGS) data with high accuracy. Here, we adapted RHtyper for whole-exome sequencing (WES) data, which are more affordable but challenged by uneven sequencing coverage and exacerbated sequencing read misalignment, resulting in uncertain predictions for (1) RHD zygosity and hybrid alleles, (2) RHCE∗C vs. RHCE∗c alleles, (3) RHD c.1136C>T zygosity, and (4) RHCE c.48G>C zygosity. We optimized RHtyper to accurately predict RHD and RHCE genotypes using WES data by leveraging machine learning models and improved the concordance of WES with WGS predictions from 90.8% to 97.2% for RHD and 96.3% to 98.2% for RHCE among 396 patients in the Sickle Cell Clinical Research and Intervention Program. In a second validation cohort of 3030 cancer survivors (15.2% Black or African Americans) from the St. Jude Lifetime Cohort Study, the optimized RHtyper reached concordance rates between WES and WGS predications to 96.3% for RHD and 94.6% for RHCE. Machine learning improved the accuracy of RH predication using WES data. RHtyper has the potential, once implemented, to provide a precision medicine-based approach to facilitate RH genotype-matched transfusion and improve transfusion safety for patients with SCD. This study used data from clinical trials registered at ClinicalTrials.gov as #NCT02098863 and NCT00760656.

When and why is red blood cell genotyping applicable in transfusion medicine: a systematic review of the literature

This review aims to provide a better understanding of when and why red blood cell (RBC) genotyping is applicable in transfusion medicine. Articles published within the last 8 years in peer-reviewed journals were reviewed in a systematic manner. RBC genotyping has many applications in transfusion medicine including predicting a patient's antigen profile when serologic methods cannot be used, such as in a recently transfused patient, in the presence of autoantibody, or when serologic reagents are not available. RBC genotyping is used in prenatal care to determine zygosity and guide the administration of Rh immune globulin in pregnant women to prevent hemolytic disease of the fetus and newborn. In donor testing, RBC genotyping is used for resolving ABO/D discrepancies for better donor retention or for identifying donors negative for high-prevalence antigens to increase blood availability and compatibility for patients requiring rare blood. RBC genotyping is helpful to immunohematology reference laboratory staff performing complex antibody workups and is recommended for determining the antigen profiles of patients and prospective donors for accurate matching for C, E, and K in multiply transfused patients. Such testing is also used to determine patients or donors with variant alleles in the Rh blood group system. Information from this testing aides in complex antibody identification as well as sourcing rare allele-matched RBC units. While RBC genotyping is useful in transfusion medicine, there are limitations to its implementation in transfusion services, including test availability, turn-around time, and cost.

Extensive red blood cell matching considering patient alloimmunization risk

BACKGROUND AND OBJECTIVES

Red blood cell (RBC) transfusions pose a risk of alloantibody development in patients. For patients with increased alloimmunization risk, extended preventive matching is advised, encompassing not only the ABO-D blood groups but also the most clinically relevant minor antigens: C, c, E, e, K, Fya, Fyb, Jka, Jkb, S and s. This study incorporates patient-specific data and the clinical consequences of mismatching into the allocation process.

MATERIALS AND METHODS

We have redefined the MINimize Relative Alloimmunization Risks (MINRAR) model to include patient group preferences in selecting RBC units from a finite supply. A linear optimization approach was employed, considering both antigen immunogenicity and the clinical impact of mismatches for specific patient groups. We also explore the advantages of informing the blood bank about scheduled transfusions, allowing for a more strategic blood distribution. The model is evaluated using historical data from two Dutch hospitals, measuring shortages and minor antigen mismatches.

RESULTS

The updated model, emphasizing patient group-specific considerations, achieves a similar number of mismatches as the original, yet shifts mismatches among patient groups and antigens, reducing expected alloimmunization consequences. Simultaneous matching for multiple hospitals at the distribution centre level, considering scheduled demands, led to a 30% decrease in mismatches and a 92% reduction in shortages.

CONCLUSION

The reduction of expected alloimmunization consequences by incorporating patient group preferences demonstrates our strategy's effectiveness for patient health. Substantial reductions in mismatches and shortages with multi-hospital collaboration highlights the importance of sharing information in the blood supply chain.

Next Generation Sequencing of Red Blood Cell Antigens in Transfusion Medicine: Systematic Review and Meta-Analysis

Molecular analysis of blood groups is important in transfusion medicine, allowing the prediction of red blood cell (RBC) antigens. Many blood banks use single nucleotide variant (SNV) based methods for blood group analysis. While this is a well-established approach, it is limited to the polymorphisms included in genotyping panels. Thus, variants that alter antigenic expression may be ignored, resulting in incorrect prediction of phenotypes. The popularization of next-generation sequencing (NGS) has led to its application in transfusion medicine, including for RBC antigens determination. The present review/meta-analysis aimed to evaluate the applicability of the NGS for the prediction of RBC antigens. A systematic review was conducted following a comprehensive literature search in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. Studies were selected based on predefined criteria and evaluated using Strengthening the Reporting of Observational studies in Epidemiology guidelines. The characteristics and results of the studies were extracted and meta-analysis was performed to verify the agreement between results from standard molecular methods and NGS. Kell (rs8176058), Duffy (rs2814778, rs12078), or Kidd (rs1085396) alleles were selected as a model for comparisons. Additionally, results are presented for other blood group systems. Of the 864 eligible studies identified, 10 met the inclusion criteria and were selected for meta-analysis. The pooled concordance proportion for NGS compared to other methods ranged from 0.982 to 0.994. The sequencing depth coverage was identified as crucial parameters for the reliability of the results. Some studies reported difficulty in analyzing more complex systems, such as Rh and MNS, requiring the adoption of specific strategies. NGS is a technology capable of predicting blood group phenotypes and has many strengths such as the possibility of simultaneously analyzing hundred individuals and gene regions, and the ability to provide comprehensive genetic analysis, which is useful in the description of new alleles and a better understanding of the genetic basis of blood groups. The implementation of NGS in the routine of blood banks depends on several factors such as cost reduction, the availability of widely validated panels, the establishment of clear quality parameters and access to bioinformatics analysis tools that are easy to access and operate.

Blood donor genotyping for prediction of blood group antigens: Results from 5 years' experience (2017-2022)

BACKGROUND AND OBJECTIVES

For 5 years, routine genotyping has been performed for selected blood groups of blood donors in the Copenhagen Capital Region, Denmark. The result is summarized in the following.

MATERIALS AND METHODS

Genotyping was carried out by an external service provider using the competitive allele specific PCR (KASP) technology. The genotypes were returned to the blood bank and translated into phenotypes by a proprietary IT application.

RESULTS

In total, 65 alleles from 16 blood group systems (ABO, MNS, Rh, Lutheran, Kell, Duffy, Kidd, Diego, Yt, Dombrock, Colton, Landsteiner-Wiener, Cromer, Knops, Vel, secretor status) and the HPA1, HPA5 and HPA15 antigens were interrogated. After translation, phenotypes were imported into the laboratory information management system of the blood bank. The results from 31,538 genotyped blood donors were used to calculate the allele frequencies for a Danish blood donor population. ABO genotyping was done for sample ID purposes. Determination of the 1061delC single nucleotide polymorphism (SNP) (NM_020469.2), most frequently characteristic of ABO*A2, was validated against a series of 1287 samples with Dolichos biflorus lectin determination of the A1 phenotype.

CONCLUSION

We report allele frequencies and phenotype frequencies for 16 blood groups from a total of 31,538 genotyped blood donors. Blood products were supplied from a total of 64,312 active blood donors, and of these active blood donors 25,396 (39.5%) were genotyped. These donors represent a valuable resource for patient treatment. This genotyping has enabled the provision of rare genotyped donor blood for patients with alloantibodies and rare reagent cells for serology.

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.

Application of Blood Group Genotyping by Next-Generation Sequencing in Various Immunohaematology Cases

BACKGROUND

Next-generation sequencing (NGS) technology has been recently introduced into blood group genotyping; however, there are few studies using NGS-based blood group genotyping in real-world clinical settings. In this study, we applied NGS-based blood group genotyping into various immunohaematology cases encountered in routine clinical practice.

METHODS

This study included 4 immunohaematology cases: ABO subgroup, ABO chimerism, antibody to a high-frequency antigen (HFA), and anti-CD47 interference. We designed a hybridization capture-based NGS panel targeting 39 blood group-related genes and applied it to the 4 cases.

RESULTS

NGS analysis revealed a novel intronic variant (NM_020469.3:c.29-10T>G) in a patient with an Ael phenotype and detected a small fraction of ABO*A1.02 (approximately 3-6%) coexisting with the major genotype ABO*B.01/O.01.02 in dizygotic twins. In addition, NGS analysis found a homozygous stop-gain variant (NM_004827.3:c.376C>T, p.Gln126*; ABCG2*01N.01) in a patient with an antibody to an HFA; consequently, this patient's phenotype was predicted as Jr(a-). Lastly, blood group phenotypes predicted by NGS were concordant with those determined by serology in 2 patients treated with anti-CD47 drugs.

CONCLUSION

NGS-based blood group genotyping can be used for identifying ABO subgroup alleles, low levels of blood group chimerism, and antibodies to HFAs. Furthermore, it can be applied to extended blood group antigen matching for patients treated with anti-CD47 drugs.

Automated Pharmacogenomic Reports for Clinical Genome Sequencing

Clinical laboratories offering genome sequencing have the opportunity to return pharmacogenomic findings to patients, providing the added benefit of preemptive testing that could help inform medication selection or dosing throughout the lifespan. Implementation of pharmacogenomic reporting must address several challenges, including inherent limitations in short-read genome sequencing methods, gene and variant selection, standardization of genotype and phenotype nomenclature, and choice of guidelines and drugs to report. An automated pipeline, lmPGX, was developed as an end-to-end solution that produces two versions of a pharmacogenomic report, presenting either Clinical Pharmacogenetics Implementation Consortium or US Food and Drug Administration guidelines for 12 genes. The pipeline was validated for performance using reference samples and pharmacogenetic data from the Genetic Testing Reference Materials Coordination Program. To determine performance and limitations, lmPGX was compared with three additional publicly available pharmacogenomic pipelines. The lmPGX pipeline offers clinical laboratories an opportunity for seamless integration of pharmacogenomic results with genome reporting.

Prediction of fetal blood group antigens from maternal plasma using Ion AmpliSeq HD technology

BACKGROUND

Fetal blood group (BG) and platelet (HPA) antigens may trigger maternal immunization, causing a fetal disease. Noninvasive prenatal diagnostics (NIPT) predicts fetal genotype, identifying pregnancies with no risk. All current techniques detect fetal antigen alleles with unspecific background and without estimation of fetal fraction, thus new protocols for detection of fetal BG/HPA alleles with ultrahigh sensitivity still need to be tested to improve NIPT.

AIM

To design NIPT of clinically important antigens using Ion AmpliSeq HD technology.

METHODS

Plasma DNA from 36 pregnant women (9-33 week of gestation, 24 immunized with anti-HPA-1a,-3b,-15a, -K, or -D+C+S), with known BG/HPA genotypes of their neonates/partners, was tested on Ion S5 System using the Ion AmpliSeq HD designer custom gene panel. NGS contained 25 rs-targets encoding relevant BG/HPA antigens and 10 markers.

RESULTS

Using the NGS protocol, 76 out of 85 differences in fetal/maternal BG/HPA genotypes were determined in concentration above 2% fetal paternally inherited allele chimerism. The level of unspecific reads for BG/HPA alleles was below 0.87%. In 24 immunized women NGS revealed feto-maternal incompatibility in 11 cases (from 2.44% to 7.41%) and excluded in 10 (<0.05%), three cases had inconclusive results (1.79%, 0.19%, 0.11%). The presence of fetal DNA was confirmed in each case by detecting markers with at least 2% chimerism.

CONCLUSION

The use of Ion AmpliSeq HD technology improves the prediction of feto-maternal incompatibility, increasing the sensitivity of BG/HPA NIPT and serving confirmation of the fetal DNA at the same workflow.

BGvar: A comprehensive resource for blood group immunogenetics

BACKGROUND

Blood groups form the basis of effective and safe blood transfusion. There are about 43 well-recognised human blood group systems presently known. Blood groups are molecularly determined by the presence of specific antigens on the red blood cells and are genetically determined and inherited following Mendelian principles. The lack of a comprehensive, relevant, manually compiled and genome-ready dataset of red cell antigens limited the widespread application of genomic technologies to characterise and interpret the blood group complement of an individual from genomic datasets.

MATERIALS AND METHODS

A range of public datasets was used to systematically annotate the variation compendium for its functionality and allele frequencies across global populations. Details on phenotype or relevant clinical importance were collated from reported literature evidence.

RESULTS

We have compiled the Blood Group Associated Genomic Variant Resource (BGvar), a manually curated online resource comprising all known human blood group related allelic variants including a total of 1700 International Society of Blood Transfusion approved alleles and 1706 alleles predicted and curated from literature reports. This repository includes 1682 single nucleotide variations (SNVs), 310 Insertions, Deletions (InDels) and Duplications (Copy Number Variations) and about 1360 combination mutations corresponding to 43 human blood group systems and 2 transcription factors. This compendium also encompasses gene fusion and rearrangement events occurring in human blood group genes.

CONCLUSION

To the best of our knowledge, BGvar is a comprehensive and a user-friendly resource with most relevant collation of blood group alleles in humans. BGvar is accessible online at URL: http://clingen.igib.res.in/bgvar/.

Preventing alloimmunization using a new model for matching extensively typed red blood cells

BACKGROUND AND OBJECTIVES

Alloimmunization is a well-known adverse event associated with red blood cell (RBC) transfusions, caused by phenotype incompatibilities between donor and patient RBCs that may lead to haemolytic transfusion reactions on subsequent transfusions. Alloimmunization can be prevented by transfusing fully matched RBC units. Advances in RBC genotyping render the extensive typing of both donors and patients affordable in the foreseeable future. However, the exponential increase in the variety of extensively typed RBCs asks for a software-driven selection to determine the 'best product for a given patient'.

MATERIALS AND METHODS

We propose the MINimize Relative Alloimmunization Risks (MINRAR) model for matching extensively typed RBC units to extensively typed patients to minimize the risk of alloimmunization. The key idea behind this model is to use antigen immunogenicity to represent the clinical implication of a mismatch. Using simulations of non-elective transfusions in Caucasian donor and patient populations, the effect on the alloimmunization rate of the MINRAR model is compared with that of a baseline model that matches antigens A, B and RhD only.

RESULTS

Our simulations show that with the MINRAR model, even for small inventories, the expected number of alloimmunizations can be reduced by 78.3% compared with a policy of only matching on antigens A, B and RhD. Furthermore, a reduction of 93.7% can be achieved when blood is issued from larger inventories.

CONCLUSION

Despite an exponential increase in phenotype variety, matching of extensively typed RBCs can be effectively implemented using our MINRAR model, effectuating a substantial reduction in alloimmunization risk without introducing additional outdating or shortages.

Cataloguing experimentally confirmed 80.7 kb-long ACKR1 haplotypes from the 1000 Genomes Project database

Background

Clinically effective and safe genotyping relies on correct reference sequences, often represented by haplotypes. The 1000 Genomes Project recorded individual genotypes across 26 different populations and, using computerized genotype phasing, reported haplotype data. In contrast, we identified long reference sequences by analyzing the homozygous genomic regions in this online database, a concept that has rarely been reported since next generation sequencing data became available.

Study design and methods

Phased genotype data for a 80.6 kb region of chromosome 1 was downloaded for all 2,504 unrelated individuals of the 1000 Genome Project Phase 3 cohort. The data was centered on the ACKR1 gene and bordered by the CADM3 and FCER1A genes. Individuals with heterozygosity at a single site or with complete homozygosity allowed unambiguous assignment of an ACKR1 haplotype. A computer algorithm was developed for extracting these haplotypes from the 1000 Genome Project in an automated fashion. A manual analysis validated the data extracted by the algorithm.

Results

We confirmed 902 ACKR1 haplotypes of varying lengths, the longest at 80,584 nucleotides and shortest at 1,901 nucleotides. The combined length of haplotype sequences comprised 19,895,388 nucleotides with a median of 16,014 nucleotides. Based on our approach, all haplotypes can be considered experimentally confirmed and not affected by the known errors of computerized genotype phasing.

Conclusions

Tracts of homozygosity can provide definitive reference sequences for any gene. They are particularly useful when observed in unrelated individuals of large scale sequence databases. As a proof of principle, we explored the 1000 Genomes Project database for ACKR1 gene data and mined long haplotypes. These haplotypes are useful for high throughput analysis with next generation sequencing. Our approach is scalable, using automated bioinformatics tools, and can be applied to any gene.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04169-6.

A novel algorithm comprehensively characterizes human RH genes using whole-genome sequencing data

RHD and RHCE genes encode Rh blood group antigens and exhibit extensive single-nucleotide polymorphisms and chromosome structural changes in patients with sickle cell disease (SCD). RH variation can drive loss of antigen epitopes or expression of new epitopes, predisposing patients with SCD to Rh alloimmunization. Serologic antigen typing is limited to common Rh antigens, necessitating a genetic approach to detect variant antigen expression. We developed a novel algorithm termed RHtyper for RH genotyping from existing whole-genome sequencing (WGS) data. RHtyper determined RH genotypes in an average of 3.4 and 3.3 minutes per sample for RHD and RHCE, respectively. In a validation cohort consisting of 57 patients with SCD, RHtyper achieved 100% accuracy for RHD and 98.2% accuracy for RHCE, when compared with genotypes obtained by RH BeadChip and targeted molecular assays and after verification by Sanger sequencing and independent next-generation sequencing assays. RHtyper was next applied to WGS data from an additional 827 patients with SCD. In the total cohort of 884 patients, RHtyper identified 38 RHD and 28 RHCE distinct alleles, including a novel RHD DAU allele, RHD* 602G, 733C, 744T 1136T. RHtyper provides comprehensive and high-throughput RH genotyping from WGS data, facilitating deconvolution of the extensive RH genetic variation among patients with SCD. We have implemented RHtyper as a cloud-based public access application in DNAnexus (https://platform.dnanexus.com/app/RHtyper), enabling clinicians and researchers to perform RH genotyping with next-generation sequencing data.

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.

An open-source python library for detection of known and novel Kell, Duffy and Kidd variants from exome sequencing

BACKGROUND AND OBJECTIVES

Next generation sequencing (NGS) has promising applications in transfusion medicine. Exome sequencing (ES) is increasingly used in the clinical setting, and blood group interpretation is an additional value that could be extracted from existing data sets. We provide the first release of an open-source software tailored for this purpose and describe its validation with three blood group systems.

MATERIALS AND METHODS

The DTM-Tools algorithm was designed and used to analyse 1018 ES NGS files from the ClinSeq® cohort. Predictions were correlated with serology for 5 antigens in a subset of 108 blood samples. Discrepancies were investigated with alternative phenotyping and genotyping methods, including a long-read NGS platform.

RESULTS

Of 116 genomic variants queried, those corresponding to 18 known KEL, FY and JK alleles were identified in this cohort. 596 additional exonic variants were identified KEL, ACKR1 and SLC14A1, including 58 predicted frameshifts. Software predictions were validated by serology in 108 participants; one case in the FY blood group and three cases in the JK blood group were discrepant. Investigation revealed that these discrepancies resulted from (1) clerical error, (2) serologic failure to detect weak antigenic expression and (3) a frameshift variant absent in blood group databases.

CONCLUSION

DTM-Tools can be employed for rapid Kell, Duffy and Kidd blood group antigen prediction from existing ES data sets; for discrepancies detected in the validation data set, software predictions proved accurate. DTM-Tools is open-source and in continuous development.

Diversity of variant alleles encoding Kidd, Duffy, and Kell antigens in individuals with sickle cell disease using whole genome sequencing data from the NHLBI TOPMed Program

BACKGROUND

Genetic variants in the SLC14A1, ACKR1, and KEL genes, which encode Kidd, Duffy, and Kell red blood cell antigens, respectively, may result in weakened expression of antigens or a null phenotype. These variants are of particular interest to individuals with sickle cell disease (SCD), who frequently undergo chronic transfusion therapy with antigen-matched units. The goal was to describe the diversity and the frequency of variants in SLC14A1, ACKR1, and KEL genes among individuals with SCD using whole genome sequencing (WGS) data.

STUDY DESIGN AND METHODS

Two large SCD cohorts were studied: the Recipient Epidemiology and Donor Evaluation Study III (REDS-III) (n = 2634) and the Outcome Modifying Gene in SCD (OMG) (n = 640). Most of the studied individuals were of mixed origin. WGS was performed as part of the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program.

RESULTS

In SLC14A1, variants included four encoding a weak Jka phenotype and five null alleles (JKnull ). JKA*01N.09 was the most common JKnull . One possible JKnull mutation was novel: c.812G>T. In ACKR1, identified variants included two that predicted Fyx (FY*X) and one corresponding to the c.-67T>C GATA mutation. The c.-67T>C mutation was associated with FY*A (FY*01N.01) in four participants. FY*X was identified in 49 individuals. In KEL, identified variants included three null alleles (KEL*02N.17, KEL*02N.26, and KEL*02N.04) and one allele predicting Kmod phenotype, all in heterozygosity.

CONCLUSIONS

We described the diversity and distribution of SLC14A1, ACKR1, and KEL variants in two large SCD cohorts, comprising mostly individuals of mixed ancestry. This information may be useful for planning the transfusion support of patients with SCD.

DNA sequence analysis and Jk blood group genotype-phenotype assessment

Background

The Kidd (JK) blood group is critical for clinical blood transfusion. Various methods for Jk typing have been commonly used, including urea hemolysis, serological test, and genotyping. However, the application of molecular methods has so far been restricted to selected samples and not been applied to the population-scale analysis.

Methods

One hundred eighty-three blood samples, containing 174 samples collected from voluntary blood donors of Chinese Han individuals, together with 3 Jk (aw+b-) and 6 Jk (a-b-) samples, were investigated by standard serology urea hemolysis test and Sanger-sequencing. Complete coverage of exons 4-11 and intron-exon borders have been sequenced.

Results

We report the frequencies of three SNPs in exon 4, 7, and intron 9. Besides, sequence analysis revealed the simultaneous DNA variants of intron 7 (-68) and exon 9 (838) found in all samples, suggesting the co-inheritance of these SNPs-taking the observed SNPs frequencies into account. Further, we discuss the potential of the sequencing technique for high-resolution genotyping.

Conclusions

The described sequencing method for Jk exons delivers a genotyping technique for Jk molecular characterization. According to the co-inheritance of these DNA variants in intron 7 (-68) and exon 9 (838), and their regularity linkage with Jk phenotypes, these two sites offer a potential sequencing target for rapid and far more simplified Jk typing that can supplement routine serology and urea hemolysis tests.

Targeted exome sequencing designed for blood group, platelet, and neutrophil antigen investigations: Proof-of-principle study for a customized single-test system

BACKGROUND

Immunohematology reference laboratories provide red blood cell (RBC), platelet (PLT), and neutrophil typing to resolve complex cases, using serology and commercial DNA tests that define clinically important antigens. Broad-range exome sequencing panels that include blood group targets provide accurate blood group antigen predictions beyond those defined by serology and commercial typing systems and identify rare and novel variants. The aim of this study was to design and assess a panel for targeted exome sequencing of RBC, PLT, and neutrophil antigen-associated genes to provide a comprehensive profile in a single test, excluding unrelated gene targets.

STUDY DESIGN AND METHODS

An overlapping probe panel was designed for the coding regions of 64 genes and loci involved in gene expression. Sequencing was performed on 34 RBC and 17 PLT/neutrophil reference samples. Variant call outputs were analyzed using software to predict star allele diplotypes. Results were compared with serology and previous sequence genotyping data.

RESULTS

Average coverage exceeded 250×, with more than 94% of targets at Q30 quality or greater. Increased coverage revealed a variant in the Scianna system that was previously undetected. The software correctly predicted allele diplotypes for 99.5% of RBC blood groups tested and 100% of PLT and HNA antigens excepting HNA-2. Optimal throughput was 12 to 14 samples per run.

CONCLUSION

This single-test system demonstrates high coverage and quality, allowing for the detection of previously overlooked variants and increased sample throughput. This system has the potential to integrate genomic testing across laboratories within hematologic reference settings.

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.

Next Generation Sequencing-Based Fetal ABO Blood Group Prediction by Analysis of Cell-Free DNA from Maternal Plasma

Introduction

ABO blood group incompatibility between a pregnant woman and her fetus as a cause of morbidity or mortality of the fetus or newborn remains an important, albeit rare, risk. When a pregnant woman has a high level of anti-A or anti-B IgG antibodies, the child may be at risk for hemolytic disease of the fetus and newborn (HDFN). Performing a direct prenatal determination of the fetal ABO blood group can provide valuable clinical information.

Objective

Here, we report a next generation sequencing (NGS)-based assay for predicting the prenatal ABO blood group.

Materials and Methods

A total of 26 plasma samples from 26 pregnant women were tested from gestational weeks 12 to 35. Of these samples, 20 were clinical samples and 6 were test samples. Extracted cell-free DNA was PCR-amplified using 2 primer sets followed by NGS. NGS data were analyzed by 2 different methods, FASTQ analysis and a grep search, to ensure robust results. The fetal ABO prediction was compared with the known serological infant ABO type, which was available for 19 samples.

Results

There was concordance for 19 of 19 predictable samples where the phenotype information was available and when the analysis was done by the 2 methods. For immunized pregnant women (n = 20), the risk of HDFN was predicted for 12 fetuses, and no risk was predicted for 7 fetuses; one result of the clinical samples was indeterminable. Cloning and sequencing revealed a novel variant harboring the same single nucleotide variations as ABO*O.01.24 with an additional c.220C>T substitution. An additional indeterminable result was found among the 6 test samples and was caused by maternal heterozygosity. The 2 indeterminable samples demonstrated limitations to the assay due to hybrid ABO genes or maternal heterozygosity.

Conclusions

We pioneered an NGS-based fetal ABO prediction assay based on a cell-free DNA analysis from maternal plasma and demonstrated its application in a small number of samples. Based on the calculations of variant frequencies and ABO*O.01/ABO*O.02 heterozygote frequency, we estimate that we can assign a reliable fetal ABO type in approximately 95% of the forthcoming clinical samples of type O pregnant women. Despite the vast genetic variations underlying the ABO blood groups, many variants are rare, and prenatal ABO prediction is possible and adds valuable early information for the prevention of ABO HDFN.