Conserved associations between G-quadruplex-forming DNA motifs and virulence gene families in malaria parasites.

backgroundThe Plasmodium genus of malaria parasites encodes several families of antigen-encoding genes. These genes tend to be hyper-variable, highly recombinogenic and variantly expressed. The best-characterized family is the var genes, exclusively found in the Laveranian subgenus of malaria parasites infecting humans and great apes. Var genes encode major virulence factors involved in immune evasion and the maintenance of chronic infections. In the human parasite P. falciparum, var gene recombination and diversification appear to be promoted by G-quadruplex (G4) DNA motifs, which are strongly associated with var genes in P. falciparum. Here, we investigated how this association might have evolved across Plasmodium species - both Laverania and also more distantly related species which lack vars but encode other, more ancient variant gene families.

resultsThe association between var genes and G4-forming motifs was conserved across Laverania, spanning ~ 1 million years of evolutionary time, with suggestive evidence for evolution of the association occurring within this subgenus. In rodent malaria species, G4-forming motifs were somewhat associated with pir genes, but this was not conserved in the Laverania, nor did we find a strong association of these motifs with any gene family in a second outgroup of avian malaria parasites. Secondly, we compared two different G4 prediction algorithms in their performance on extremely A/T-rich Plasmodium genomes, and also compared these predictions with experimental data from G4-seq, a DNA sequencing method for identifying G4-forming motifs. We found a surprising lack of concordance between the two algorithms and also between the algorithms and G4-seq data.

conclusionsG4-forming motifs are uniquely strongly associated with Plasmodium var genes, suggesting a particular role for G4s in recombination and diversification of these genes. Secondly, in the A/T-rich genomes of Plasmodium species, the choice of prediction algorithm may be particularly influential when studying G4s in these important protozoan pathogens.