A gender- and sex-agnostic interpretation algorithm for Xga blood typing by enrichment next-generation sequencing

Self-declared gender and sex assigned at birth can be inaccurate proxies for sex-chromosome ploidy. To uphold gender inclusivity while providing a precise XG blood group antigen phenotype prediction from enrichment NGS data, we present a quantification tool calibrated with 18 samples with diverse sex chromosome ploidies. The model was validated with 96 test samples with known X and Y chromosome ploidies by real-time PCR, yielding 0.93 correlation for X-specific regions by continuous scale and accurately detecting an aneuploid sample. Finally, the algorithm was applied for Xg a and CD99 red blood cell phenotype prediction from enrichment NGS data in 14 well-characterized panel cell samples with known serologic Xg a phenotype. Ambiguous Xg a typing results in two samples were accurately resolved through a strategy combining TELL-Seq with long-read sequencing of long PCR amplicons spanning the pseudoautosomal (PA) boundary. NGS-predicted Xg a phenotype was discrepant with the documented phenotype in one panel cell sample with multiple homozygous variants in the CD99 and XG genes. CD99 phenotype predictions were verified by flow-cytometry.