The influence of habitats on female mobility in Central and Western Africa inferred from human mitochondrial variation

Abstract

BackgroundWhen studying the genetic structure of human populations, the role of cultural factors may be difficult to ascertain due to a lack of formal models. Linguistic diversity is a typical example of such a situation. Patrilocality, on the other hand, can be integrated into a biological framework, allowing the formulation of explicit working hypotheses. The present study is based on the assumption that patrilocal traditions make the hypervariable region I of the mtDNA a valuable tool for the exploration of migratory dynamics, offering the opportunity to explore the relationships between genetic and linguistic diversity. We studied 85 Niger-Congo-speaking patrilocal populations that cover regions from Senegal to Central African Republic. A total of 4175 individuals were included in the study.ResultsBy combining a multivariate analysis aimed at investigating the population genetic structure, with a Bayesian approach used to test models and extent of migration, we were able to detect a stepping-stone migration model as the best descriptor of gene flow across the region, with the main discontinuities corresponding to forested areas.ConclusionsOur analyses highlight an aspect of the influence of habitat variation on human genetic diversity that has yet to be understood. Rather than depending simply on geographic linear distances, patterns of female genetic variation vary substantially between savannah and rainforest environments. Our findings may be explained by the effects of recent gene flow constrained by environmental factors, which superimposes on a background shaped by pre-agricultural peopling.

Tracing the genetic legacy in the French Caribbean islands: A study of mitochondrial and Y‐chromosome lineages in the Guadeloupe archipelago

“…When considering only African haplotypes, the highest percentage of shared haplotypes could be found with Western Africa and West‐Central Africa (32 and 24.7%, respectively) but also Caribbean region (29.6%; Figure S2). Guadeloupe archipelago specifically shared numerous maternal haplotypes with the West‐African populations of Benin (47.3% of shared haplotypes; Brucato et al, ), Nigeria (44.1%; Montano et al, ), Sierra Leone (40.3%; Jackson et al, ), Mali (38%; A. M. González et al, ), and Senegal (37%; Stefflova et al, ). Essential percentages of shared haplotypes were also measured with countries from West‐Central Africa such as Angola (33%; Beleza, Gusmão, Amorim, Carracedo, & Salas, ) and Congo (29.7%; Montano et al, ).…”

“…Guadeloupe archipelago specifically shared numerous maternal haplotypes with the West‐African populations of Benin (47.3% of shared haplotypes; Brucato et al, ), Nigeria (44.1%; Montano et al, ), Sierra Leone (40.3%; Jackson et al, ), Mali (38%; A. M. González et al, ), and Senegal (37%; Stefflova et al, ). Essential percentages of shared haplotypes were also measured with countries from West‐Central Africa such as Angola (33%; Beleza, Gusmão, Amorim, Carracedo, & Salas, ) and Congo (29.7%; Montano et al, ). Concerning the American region, Guadeloupe shared 55% of haplotypes with the Garifunas from Honduras (Salas et al, ), 42.8% with Jamaica (Deason et al, ), 29.9% with English‐Carib islands (Benn Torres et al, ), 26.8% with Haiti (Wilson, Saint‐Louis, Auguste, & Jackson, ), and more than 30% with African American (Diegoli et al, ) or African‐Brazilian (Gonçalves, Carvalho, Bortolini, Bydlowski, & Pena, ) groups.…”

Neogene paleoceanography of the eastern equatorial Pacific based on the radiolarian record of IODP drill sites off Costa Rica

“…It partitions the samples analyzed into discrete groups based on their specific contents synthesizing the overall variability in a few variables (the discriminant functions). This analysis is closely related to an analysis of variance (ANOVA), but it maximizes the ratio of the variance among groups and minimizes the variance within groups [ Montano et al ., ]. The Bayesian Information Criterion (BIC) is first used to establish the best number of groups comparing the decrease of the residual variance among different numbers of groups, with the best number corresponding to the lowest BIC value [ Jombart et al ., ].…”

Genetic population study of Y-chromosome markers in Benin and Ivory Coast ethnic groups

“…Over the past decades, Population Genetics studies have investigated paternal and maternal genetic diversity in numerous West African populations, such as those in Senegal [3], Guinea-Bissau [4][5][6], Ghana [7,8], Burkina Faso [9], and Nigeria [10]. These studies revealed the high genetic diversity in these populations, due to diverse human migration episodes and admixture processes [2,[11][12][13]. There is still a great need for Population Genetics studies to genotype additional human groups in order to gain an accurate picture of West African genetic diversity.…”