RH genotyping by nonspecific quantitative next‐generation sequencing

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.

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.

DETERMINATION OF RH TYPE AND GENDER USING CIRCULATING CELL-FREE FETAL DNA IN EARLY PREGNANCY OF RH NEGATIVE WOMEN IN TURKEY

INTRODUCTION

Choosing the right clinical approach for early and reliable diagnosis/screening is becoming more important day by day. The aim of the study was to determine the early RhD type with cff-DNA obtained from maternal plasma, especially in the light of recent developments. In this way, it is aimed to apply Rh Ig only to mothers who are determined to have RhD (+) fetuses and to prevent unnecessary further tests that may possess a risk for RhD (-) fetuses.

METHODS

Prediction of fetal gender and RH genotype was performed by using RT-qPCR method. With simultaneous amplification of sequences of SRY, DYS14 and RH genes (exon 7 and exon 10). Fetal gender and RhD were determined in 30 RHD (-) pregnant women with cfDNA.

RESULTS

As a result of genotyping, the gender of 67% (20/30) fetuses was determined as male; the gender of 33% (10/30) fetuses was determined as female in a sample group of 30 pregnancies. It was determined that the DYS14 100% (20/20) gene was more sensitive than the SRY 97% (18/20) gene in gender determination after examining prenatal and postnatal results. As a result of the analysis, the presence of 17% (5/30) RhD (-) fetuses and 83% (25/30) RhD (+) fetuses were determined which is 100% compatible with postnatal results.

DISCUSSION

Detecting fetal RhD gene in maternal plasma made an important contribution to its use in non-invasive prenatal screening. This study shows that unnecessary intervention and cost can be avoided with successful genotyping analysis performed with RT-qPCR.

Frequency and characterization of RHD and RHCE variants in the Noir Marron population from French Guiana

BACKGROUND

The RH system is one of the most polymorphic blood group systems due to the proximity and opposite orientation of RHD and RHCE genes. Numerous alleles are described and can affect Rh protein expression. This complexity is especially evident in populations of African origin. We performed RHD and RHCE genotyping of the Noir Marron population in French Guiana. This population belongs to the Maroon community who are direct descendants of African slaves, who escaped from Dutch plantations, in the current day Suriname, during the 17th century. They represent an original ethnic group with highly blended culture.

METHODS AND MATERIALS

A total of 89 DNA samples were collected from four different ethnic groups of the Noir Marron population of French Guiana. RHD and RHCE genotyping was performed using DNA microarray and/or sequencing.

RESULTS AND DISCUSSION

Significant allelic diversity was shown, with 45% of individuals presenting an RHD gene variant (most common: RHD*DAU, RHD*DIVa, and RHD*DIIIa allele) and 9.4% with a partial D phenotype. Likewise, 85% presenting an RHCE gene variant and 9% a partial RH2 antigen. One original allele was identified in two D+ Noir Marron individuals: a hybrid RHD*DIIIa-CE(9)-D allele, encoding probably a partial D antigen and associated with an RHCE*ce(48C,733G,1006T) allele. The African diversity of RHD and RHCE genes is found in this population with preserved genetic but mixed cultural backgrounds. These data allow us to describe the characteristics of the RH system antigen and highlights a significant number of partial antigens with a risk of alloimmunization.

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.

New ABO intron 1 variant alleles

Unusual and discrepant ABO phenotypes are often due to genetic variants that lead to altered levels or activity of ABO transferases and consequently to altered expression of ABO antigens. This report describes eight genetic alterations found in 15 cases with reduced or undetectable expression of ABO antigens. Forward and reverse ABO grouping was performed by standard gel or tube methods. Adsorption-heat elution and saliva testing for H and A substances followed the AABB technical manual procedures. Genomic DNA extracted from whole blood was PCR-amplified to cover the entire ABO coding sequence, splice junctions, proximal promoter, and intron 1 enhancer. Amplification products were sequenced by next-generation or Sanger dideoxy methods, either directly or after cloning into a bacterial plasmid vector. Eight unreported alleles were found in the 15 cases analyzed. Alleles ABO*A(28+1C) and ABO*A(29-5G) harbor variants that alter the consensus sequence at the intron 1 donor and acceptor splice sites, respectively. The other alleles harbor variants that alter the consensus sequence at transcription factor-binding sites in the intron 1 enhancer: specifically, ABO*A(28+5792T), ABO*A(28+5859A), and ABO*A(28+5860G) at GATA-1 sites; ABO*B(28+5877T) and ABO*B(28+5878G) at a RUNX1 site; and ABO*A(28+5843A) at or near a C/EBP site. Molecular and serologic characterization of ABO alleles can help in their future identification and in the resolution of discrepancies.

Unusual and discrepant ABO phenotypes are often due to genetic variants that lead to altered levels or activity of ABO transferases and consequently to altered expression of ABO antigens. This report describes eight genetic alterations found in 15 cases with reduced or undetectable expression of ABO antigens. Forward and reverse ABO grouping was performed by standard gel or tube methods. Adsorption-heat elution and saliva testing for H and A substances followed the AABB technical manual procedures. Genomic DNA extracted from whole blood was PCR-amplified to cover the entire ABO coding sequence, splice junctions, proximal promoter, and intron 1 enhancer. Amplification products were sequenced by next-generation or Sanger dideoxy methods, either directly or after cloning into a bacterial plasmid vector. Eight unreported alleles were found in the 15 cases analyzed. Alleles ABO*A(28+1C) and ABO*A(29–5G) harbor variants that alter the consensus sequence at the intron 1 donor and acceptor splice sites, respectively. The other alleles harbor variants that alter the consensus sequence at transcription factor–binding sites in the intron 1 enhancer: specifically, ABO*A(28+5792T), ABO*A(28+5859A), and ABO*A(28+5860G) at GATA-1 sites; ABO*B(28+5877T) and ABO*B(28+5878G) at a RUNX1 site; and ABO*A(28+5843A) at or near a C/EBP site. Molecular and serologic characterization of ABO alleles can help in their future identification and in the resolution of discrepancies.

How to avoid the problem of erythrocyte alloimmunization in sickle cell disease

Erythrocyte alloimmunization is a major barrier to transfusion in sickle cell disease (SCD) because it can lead to transfusion deadlock and the development of life-threatening hemolytic transfusion reactions (HTRs). Several risk factors have been identified, such as blood group polymorphism in these patients of African ancestry frequently exposed to antigens they do not carry and an inflammatory clinical state of the disease. The most important preventive measure is prophylactic red blood cell antigen matching, and there is a consensus that matching for Rh (D, C, E, c, e) and K antigens should be performed for all SCD patients. However, some patients are high responders and more at risk of developing antibodies and HTRs. For these patients, the extension of matching to other blood groups, including variant antigens of the RH blood group, the use of genotyping rather than serology to characterize significant blood groups, and the prophylactic administration of immunosuppressive treatments remain a matter of debate due to low levels of certainty concerning their effects and the difficulty of determining which patients, other than those already immunized, are at high risk. These issues were recently addressed by a panel of experts established by the American Society of Hematology. Here, we review and stratify the various interventions for preventing alloimmunization, based on the literature and our experience and taking into account the obstacles to their implementation and any future developments required.

The Significance of RHD Genotyping and Characteristic Analysis in Chinese RhD Variant Individuals

Background

RhD is the most important and complex blood group system because of its highly polymorphic and immunogenic nature. RhD variants can induce immune response by allogeneic transfusion, organ transplantation, and fetal immunity. The transfusion strategies are different for RhD variants formed by various alleles. Therefore, extensive investigation of the molecular mechanism underlying RhD variants is critical for preventing immune-related blood transfusion reactions and fetal immunity.

Methods

RhD variants were collected from donors and patients in Zhejiang Province, China. The phenotypes were classified using the serologic method. The full coding regions of RHD gene were analyzed using the PCR-SBT method. The multiplex ligation-dependent probe amplification (MLPA) assay was used to analyze the genotype and gene copy number. SWISS-MODLE and PyMOL software were used to analyze 3D structures of RhD caused by the variant alleles. The effect of non-synonymous substitutions was predicted using Polymorphism Phenotyping algorithm (PolyPhen-2), Sorting Intolerant From Tolerant (SIFT), and Protein Variation Effect Analyzer (PROVEAN) software.

Results

In the collected RhD variants, 28 distinct RHD variant alleles were identified, including three novel variant alleles. RH-MLPA assay is advantageous for determining the copy number of RHD gene. 3D homology modeling predicted that protein conformation was disrupted and may explain RhD epitope differential expression. A total of 14 non-synonymous mutations were determined to be detrimental to the protein structure.

Discussion

We revealed the diversity of RHD alleles present in eastern Chinese RhD variants. The bioinformatics of these variant alleles extended our knowledge of RhD variants, which was crucial for evaluating their impact to guide transfusion support and avoid immune-related blood transfusion reactions.

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.