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 forRHgenotyping. 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-basedRHgenotyping 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 variantRHCE. Sequence read depth of coverage calculation accurately determinedRHDzygosity and detected the presence ofRHD/RHCEhybrids.RHCE*Cwas determined by sequence read depth of coverage and by split read methods.RHDhybrid alleles andRHCE*Cwere confirmed by using a paired read approach. Small SVs present inRHCE*CeRNandRHCE*ceHARwere 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-RHgenotyping of WGS data includingRHDzygosity and complex compoundRHDandRHCEheterozygotes. The scalable nature of this automated analysis will enableRHgenotyping in large genomic sequencing projects.