Next Generation Sequencing for Blood Group Antigen Profiling

There are over 300 serologically defined red blood cell (RBC) antigens and 33 serologically defined platelet antigens, most of which have known genetic changes in 45 RBC or 6 platelet genes that correlate with antigen expression. Exposure to non-self RBC antigens during transfusion or pregnancy can lead to the development of alloantibodies, which on re-exposure can lead to clinically significant and even fatal complications. Therefore, it is vital to know which antigens are present on RBCs. However, traditional serologic phenotyping methods are labor intensive, costly, sometimes unreliable, and reagents are not always available. As such, routine antigen typing is only done for ABO and D antigens.

A large percentage of blood is given for hematologic malignancies that will soon get routine whole genome sequencing (WGS). For a minor added cost this data could be used for RBC antigen prediction. However, there are no published reports of using WGS data to predict RBC antigens. This is likely for several reasons: (1) none of the existing WGS data sets have paired serologic RBC phenotypes, (2) there are no fully annotated and complete databases of genotypes to phenotypes, (3) all of the known alleles are defined using cDNAs numbered relative to the start codon without human genome coordinates, and (4) lack of software capable of automated RBC antigen prediction.

We have created a fully interactive web site of all known blood group genotype to phenotype correlations, fully annotated with relevant information, and mapped to and visually overlaid to their corresponding human reference genome gene sequences, with algorithms to predict antigen phenotypes from inputted sequences. These predictions are part of the General Genome Reports for the 100 patients getting WGS as part of The MedSeq Project. In addition, each patient is undergoing an extensive antigen phenotypic workup using traditional blood bank serology and currently available SNP PCR based assays, which are being used to validate and improve our prediction strategies.

As clinical WGS becomes pervasive we hope that comprehensive blood group prediction will be done on everyone, allowing for easy identification of rare donors and the prevention of alloantibody formation using extended upfront matching of antigens from sequenced recipients and donor.