RH genotyping by nonspecific quantitative next‐generation sequencing

Abstract

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 RHconsensus 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. Conventional sequencing of homologous blood group genes such as RHD and RHCE makes use of gene-specific primers, with data analysis limited to a qualitative determination of homozygosity for the common sequence,

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

“…We chose 27 rs positions encoding BG/HPA antigens and markers for creating the Ion AmpliSeq HD designer custom ordered gene panel. Twenty‐five ROIs were applied; however, primers for the rs676785 and rs7682260 used by Wienzek‐Lischka et al, for RhC/c and M/N antigens, respectively, were reported not to be included due to high homology to other regions 18,19 . The Ion AmpliSeq HD panel improved the efficiency of the HPA‐5 sequencing, while the reactions for the GYPB gene had a lower yield compared with other ROIs (Table S1).…”

“…Twenty-five ROIs were applied; however, primers for the rs676785 and rs7682260 used by Wienzek-Lischka et al, for RhC/c and M/N antigens, respectively, were reported not to be included due to high homology to other regions. 18,19 The Ion AmpliSeq HD panel improved the efficiency of the HPA-5 sequencing, while the reactions for the GYPB gene had a lower yield compared with other ROIs (Table S1). Considering the detection of RHD gene, it is known that the real-time PCR technique is a gold standard for fetal RHD typing for immunized RhDnegative women and targeted antenatal immunoprophylaxis in non-immunized mothers, so there is no need to convert a test into other expensive technique.…”

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

“…Current research on the distribution of variant RHD alleles has been mostly focused on European donor and patient cohorts (10)(11)(12)(13)(14). Additionally, there are some corresponding reports on the diversity of RHD alleles in African and Asian populations (15).…”

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

“…We propose that blood antigen interpretation is a universal clinical benefit that could increase the cost‐efficiency of genomic sequencing performed in the clinical setting [14]. To this end, important challenges involve design and validation of bioinformatic pipelines tailored to evaluate blood antigen expression and compatibility, and automation suitable for application to a large number of donor and recipient genomes [13,15–21].…”