Gm, Am and Km allotypes were investigated in two Tunisian populations (236 samples from Mahdia and 142 samples from Sfax). These populations descend from immigrants and, therefore, the results were compared with those obtained in other populations living in the Near East and in North Africa. The subclass heavy chain allotypes G1m, G2m, G3m and A2m are inherited in fixed combinations. There were five main and four minor Gm-Am haplotypes that could be deduced from the phenotypes. This led to the conclusion that the populations studied are Caucasoids with some African admixture (about 10%) and a very low oriental contribution. Furthermore, there were 11 samples which showed 8 uncommon Gm-Am phenotypes. These could be explained by the assumption of five different uncommon Gm-Am haplotypes. Four of these may have arisen by equal crossing over of prevalent haplotypes. The fifth may be the result of unequal crossing over of prevalent haplotypes. The fifth may be the result of unequal crossing over, since it was proven, by family study, that more markers are transmitted together than are present in the prevalent haplotypes.
Allotypes of IgG1, IgG2, IgG3, and IgA2 subclasses were investigated in seven Lebanese communities (three Moslem and four Christian). The Gm-Am haplotypes found were mainly those prevalent in Caucasians with a low frequency of haplotypes usually observed in Africans and Orientals. The difference between highlanders and lowlanders as expressed by G2m(23) was highly significant and suggested a possible adaptation to selective pressure related to the gamma2 genes, possibly due to endemic malaria in the past. Exceptional Gm-Am haplotypes were unambiguously determined by family studies. Some were characterized either by a deletion or a repression or, in contrast, by a partial or total duplication of gamma genes. Two others had uncommon combinations of allotypes: Gm17;23;5,10,11,13,14 A2m1, where G1m (17) was present without G1m (1); and Gm3;23;5,14 A2m1, where the CH3 allotypes G3m (10,11,13) were lacking.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.