Socioeconomic and cultural factors are thought to have an important role in influencing human population genetic structure. To explain such population structure differences, most studies analyse genetic differences among widely dispersed human populations. In contrast, we have studied the genetic structure of an ethnic group occupying a single village in north-eastern Ghana. We found a markedly skewed male population substructure because of an almost complete lack of male gene flow among Bimoba clans in this village. We also observed a deep male substructure within one of the clans in this village. Among all males, we observed only three Y-single-nucleotide polymorphism (SNP) haplogroups: E1b1a*-M2, E1b1a7a*-U174 and E1b1a8a*-U209, P277, P278. In contrast to the marked Y-chromosomal substructure, mitochondrial DNA HVS-1 sequence variation and autosomal short-tandem repeats variation patterns indicate high genetic diversities and a virtually random female-mediated gene flow among clans. On the extreme micro-geographical scale of this single Bimoba village, correspondence between the Y-chromosome lineages and clan membership could be due to the combined effects of the strict patrilocal and patrilineal structure. If translated to larger geographic scales, our results would imply that the extent of variation in uniparentally inherited genetic markers, which are typically associated with historical migration on a continental scale, could equally likely be the result of many small and different cumulative effects of social factors such as clan membership that act at a local scale. Such local scale effects should therefore be considered in genetic studies, especially those that use uniparental markers, before making inferences about human history at large.
Oral history and oral genealogies are mechanisms of collective memory and a main cultural heritage of many populations without a writing system. In the effort to analytically address the correspondence between genetic data and historical genealogies, anthropologists hypothesised that genealogies evolve through time, ultimately containing three parts: literal – where the most recent ancestry is truthfully represented; intended – where ancestry is inferred and reflects political relations among groups; and mythical – that does not represent current social reality. While numerous studies discuss oral genealogies, to our knowledge no genetic studies have been able to investigate to what extent genetic relatedness corresponds to the literal and intended parts of oral genealogies. We report on the correspondence between genetic data and oral genealogies among Bimoba males in a single village in North-Eastern Ghana. We compared the pairwise mismatch distribution of Y chromosome short tandem repeat (Y-STR) haplotypes among all lineages present in this village to the self-reported (oral) relatedness. We found that Bimoba are able to correctly identify unrelated individuals in 92% of the cases. In contrast, they are able to correctly identify related individuals only in 38% of the cases, which can be explained by three processes: (1) the compression of genealogies, leading to increasing inaccuracy with increasing genealogical distance, (2) inclusions into the lineage from intended relations such as clan co-option or adoptions, and (3) false paternities, which in this study were found to have a minor effect on the correspondence between genetic data and oral genealogies. In addition, we observed that 70% of unrelated pairs have from six to eight Y-STR differences, a diversification peak which we attribute to an ancient West African expansion dating around 9454 years ago. We conclude that, despite all caveats, oral genealogies are reflecting ancient lineages more accurately than previously thought.
Human survival probability and fertility decline strongly with age. These life history traits have been shaped by evolution. However, research has failed to uncover a consistent genetic determination of variation in survival and fertility. As an explanation, such genetic determinants have been selected in adverse environments, in which humans have lived during most of their history, but are almost exclusively studied in populations in modern affluent environments. Here, we present a large-scale candidate gene association study in a rural African population living in an adverse environment. In 4387 individuals, we studied 4052 SNPs in 148 genes that have previously been identified as possible determinants of survival or fertility in animals or humans. We studied their associations with survival comparing newborns, middle-age adults, and old individuals. In women, we assessed their associations with reported and observed numbers of children. We found no statistically significant associations of these SNPs with survival between the three age groups nor with women's reported and observed fertility. Population stratification was unlikely to explain these results. Apart from a lack of power, we hypothesise that genetic heterogeneity of complex phenotypes and gene-environment interactions prevent the identification of genetic variants explaining variation in survival and fertility in humans.
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