XG blood group puzzle solved: what’s next?

In this issue of Blood, Möller et al reveal evidence that they have found the genetic variation underlying the last unresolved blood group system, XG. Equipped with an informatics-based study design, the team identified a GATA1 single nucleotide polymorphism (SNP) 3709 bp upstream from the erythroid transcription start site of the XG coding region. Their further molecular genetics and red blood cell (RBC) biology studies provide strong evidence for the relationship between their GATA1 SNP and the Xg(a+) and Xg(a−) phenotypes.¹ 

The XG blood group system includes 2 antigens: Xg^a and CD99 (encoded by the MIC2 gene).^2,3  Although these cell surface sialoglycoproteins are both found on RBCs (Xg^a RBCs only; CD99 distributes to all human cell types tested), their function as RBC proteins is unknown. Unlike blood groups that play a significant role in transfusion compatibility (eg, ABO and Rh⁴ ) or susceptibility to infectious diseases (eg, Fy and vivax malaria,⁵  Kx and severe malaria⁶ ), the XG blood group system has not had a strong relationship with clinically recognized outcomes.²  Instead, as the first blood group mapped to the human X chromosome, the XG blood group experienced its heyday prior to genome mapping and whole-genome sequencing, when it was an important tool used to examine the biology of the human X chromosome as a marker to map sex-linked traits and to help define mechanisms underlying sex chromosome disorders (eg, Turner and Klinefelter syndromes).²  Through these studies, it was determined that XG mapped to the pseudoautosomal region of the X (Xp22.33) and Y (Yp11.2) chromosomes. The X chromosome carries the intact gene comprising 10 exons, whereas the Y chromosome carries only exons 1-3; the XG and MIC2 loci are adjacent to each other, ∼10 000 bp apart.

Möller et al calculated XG gene frequencies in 22 populations compiled from numerous blood group surveys⁴  classified consistently with the African, East Asian, and European superpopulations of the 1000 Genomes Project.⁷  They then compared allele frequencies of 2612 variants in the XG region (defined as 10 kb upstream from the transcription start site to 10 kb downstream of the transcription end site) between these data sources. This analysis identified a SNP (rs311103G/C) that modifies a GATA1 erythroid transcription factor binding site (GATA → CATA) 3709 bp upstream from the erythroid transcription start site of the XG gene. The rs311103C allele subsequently showed compromised GATA1 binding and gene expression, as well as a strong correlation between genotypes and Xg^a protein expression on RBCs in 158 blood donors (74 females, 84 males).

The tangible products of their study (identification of a GATA1 SNP influencing XG expression and a genotyping strategy) are likely to facilitate future association studies that may provide new insights regarding the XG blood group associations with clinical outcomes. Because sialoglycoproteins influence RBC invasion by malaria parasites (keeping in mind large copy-number differences between glycophorin A [800 000 per RBC] and Xg^a [9000 per RBC]),³  genotyping of study populations that are well classified according to defined epidemiological categories (eg, severe anemia, cerebral malaria, and uncomplicated malaria) may be simplified.

Beyond this, the current study by Möller et al appears to have broader implications, by advancing their earlier demonstration in Blood Advances⁸  of how to harness and use the growing abundance of human genome sequence data to investigate the molecular variation underlying blood group phenotypes. Although their earlier informatics work focused on coding region variations across all 36 blood group systems, they followed similar computationally intensive database comparisons to identify and evaluate the regulatory region SNP flanking the XG gene. Increasing surveillance of blood group variation identified bioinformatically will likely uncover new polymorphism. Developing systems to proofread, validate, and evaluate whether new and/or population-specific variation contributes to variation of blood group phenotypes or identifies new antigens points to a new chapter on understanding blood group polymorphism.