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Background: The most common large-deletion RHD allele (RHD*01N.01) includes the entire coding sequence, intervening regions and untranslated regions. The rest of large-deletion RHD alleles reported to-date consist of single-exon deletions, such as RHD*01N.67 which includes exon 1., Materials and Methods: Samples from two donors with RhD-negative serology yielded unclear or inconclusive results when subject to confirmatory testing on RHD genotyping arrays. To determine their RHD genotypes, genomic DNA was analyzed with a combination of allele-specific PCR, long-range PCR, Sanger sequencing, and next-generation sequencing assays., Results: Allele-specific PCR failed to detect products for RHD exons 1 to 3 in one sample and RHD exons 1 to 5 in the other. A quantitative next-generation sequencing assay confirmed deletion of exons 1 to 3 and 1 to 5 respectively, and detected the absence of an RHD gene in trans in both samples. Long-range PCR and Sanger sequencing enabled identification of the breakpoints for both alleles. Both deletions start within the 5' Rhesus box (upstream of the identity region for the 1-to-3 deletion, downstream of it for the 1-to-5 deletion), and end within introns., Conclusions: Resolution of unclear or inconclusive results from targeted genotyping arrays often leads to the discovery of new alleles. The 5' Rhesus box may be a hot spot for genetic recombination events, such as the large deletions described in this report., (© 2020 AABB.)

Background: Conventional sequencing uses gene-specific primers to determine the location of RH variants and permits a qualitative assessment of zygosity. Whole-genome and whole-exome sequencing determine the genetic location of variants and enable a quantitative assessment of zygosity. Nonspecific sequencing uses RH-consensus primers to detect variants and sequencing-read ratios to quantify their copy number., Study Design and Methods: Two hundred seventy eight samples with diverse genotypes were analyzed by next-generation sequencing with RH- consensus primers. Custom-developed data analysis software was used to detect individual variants and infer the RH genotype. The method was evaluated for its quantitative nature, its ability to discriminate similar genotypes, its accuracy to detect variants, and its accuracy to assign them to RHD or RHCE., Results: As a measure of balanced amplification of RHD and RHCE sequences, observed ratio medians deviate from expected ratios by 3% or less of the ratio range. As a measure of discriminatory power, contiguous RHCE / [RHD + RHCE] ratio averages are separated by 4 or more standard deviations of the mean. Variants are detected with a sensitivity and specificity greater than 99%, and variants at consensus positions are correctly assigned to RHD vs RHCE with a sensitivity greater than 72% and a specificity greater than 99%. The method is successful in the identification of genotypes with large conversion events and in the detection of copy number variation., Conclusion: Nonspecific sequencing of homologous gene sets combines detection and quantification of genetic variation in a single assay. Evidence is provided for the quantitative nature of the method, its sensitivity and specificity, and its ability to identify complex RH genotypes., (© 2020 AABB.)

Background: The introduction of molecular methods into routine blood typing is prompting the identification of new blood group alleles. Discrepancies between the results of genotyping and serology or chance events uncovered during genotyping prompted additional investigations, which revealed six new RHCE variant alleles., Study Design and Methods: Samples from eight blood donors, two patients (one prenatal), and a patient's relative, all of diverse racial origin, were analyzed by standard serology methods, targeted genotyping arrays, DNA sequencing, and allele-specific polymerase chain reaction., Results: Six new RHCE alleles were identified, namely, RHCE*cE84A, RHCE*ce202G, RHCE*ce307T, RHCE*Ce377G, RHCE*ce697G,712G,733G,744C, and RHCE*Ce733G., Conclusion: While implementation of new assays in commercial genotyping platforms to detect the polymorphisms reported here may not be justified given their apparent rarity, software interpretative algorithms may benefit from the identification of new alleles for a more accurate determination of genotypes and prediction of phenotypes., (© 2015 AABB.)

Correct donor D typing is critical to prevent recipient alloimmunization. No method can detect all variants, and the immunogenicity of many variants is unknown. Routine ABO and D serologic typings are performed in our laboratory by automated microplate testing. Until 2011, routine confirmation of D- status of first-time donors was performed by the manual tube indirect antiglobulin test (IAT); this was replaced by automated solid-phase testing including weak D testing by IAT. Selected donors are investigated by other methods. We describe four weak D type 67 (RHD*01W.67) donors whose samples tested as D- by automated microplate and manual methods but were later determined to be D+ by automated solid-phase and RHD gene analysis. Solid-phase serologic and molecular typing results of all four donors were identical. It was identified that the donors are of English-Irish descent; two are brothers and the others are cousins. Transfusion of blood from one of these donors likely resulted in alloimmunization to D in one of three recipients tested since no other documented exposures were identified. Lookback studies determined that two other D- recipients were not alloimmunized.

Objectives: Fetal RHD screening programs that aim to reduce unnecessary antenatal anti-D prophylaxis are being introduced into clinical practice. Strategies to manage women serologically typed as Rhesus D negative who have maternal RHD variants are needed. This study describes maternal RHD allelic variants detected in nonselected and alloimmunised Rhesus D negative obstetric populations and explores a mathematical approach to identify these variants., Methods: Fetal RHD status was defined by testing cell-free fetal DNA in maternal plasma. Women at risk of an RHD variant were identified by selection for C and E haplotypes or by recognition of low polymerase chain reaction cycle threshold on fetal RHD typing. Maternal RHD alleles were defined by SNP profiling or sequencing., Results: The prevalence of RHD variants in nonselected and alloimmunised groups was 1% (6/603) and 5.5% (6/110), respectively (p < 0.001). An inverse association between RHD cycle threshold values and gestational age was described by a linear model (p < 0.001). Standard residual values with a Z score threshold of -3.00 would have detected all maternal variants with one (1/713) false positive., Conclusions: The prevalence of maternal RHD variants was significantly higher in alloimmunised cases. The causative mechanism for this needs further investigation. Mathematical modeling simplifies the detection of maternal RHD variants., (© 2013 John Wiley & Sons, Ltd.)

Background: Variant alleles that do not produce RhCE antigens are rare. Consequently, they pose a challenge to transfusion when found in alloimmunized patients and make blood units valuable when found in donors., Study Design and Methods: Five index cases and their relatives were studied by both serologic and molecular techniques. Genomic DNA was subjected to microarray genotyping, sequencing, exon scanning, and/or copy number determination assays to identify the RHCE allele(s) responsible for their D+ C- c- E- e- (D- -) phenotype., Results: The five apparent D- - phenotypes were confirmed by molecular methods. Three of them contained unreported RHCE-null alleles, namely, RHCE*Ce-D(3-9)-Ce, RHCE*Ce87&#95;93insT, and RHCE*cE221A., Conclusion: Molecular analysis of D- - phenotypes allows the identification of new RHCE-null variants. Conversely, detection of described RHCE-null variants facilitates confirmation of D- - phenotypes in patients and donors, helping improve transfusion safety., (Published 2013. This article is a U.S. Government work and is in the public domain in the USA.)