Premium
Overcoming the challenges of interpreting complex and uncommon RH alleles from whole genomes
Author(s) -
Halls Justin B.L.,
Vege Sunitha,
Simmons Daimon P.,
Aeschlimann Judith,
Bujiriri Baderha,
Mah Helen H.,
Lebo Matthew S.,
Vijay Kumar Prathik K.,
Westhoff Connie M.,
Lane William J.
Publication year - 2020
Publication title -
vox sanguinis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 83
eISSN - 1423-0410
pISSN - 0042-9007
DOI - 10.1111/vox.12963
Subject(s) - genotyping , zygosity , sanger sequencing , genetics , rh blood group system , biology , allele , whole genome sequencing , genome , dna sequencing , computational biology , genotype , gene , antibody
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.