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The Paternal Landscape along the Bight of Benin - Testing Regional Representativeness of West-African Population Samples Using Y-Chromosomal Markers.

Larmuseau MH, Vessi A, Jobling MA, Van Geystelen A, Primativo G, Biondi G, Martínez-Labarga C, Ottoni C, Decorte R, Rickards O - PLoS ONE (2015)

Bottom Line: Geographic proximity turned out to be the best predictor of genetic affinity between populations along the Bight of Benin.Furthermore, the analysis of the HapMap sample YRI of a Yoruban population from South-western Nigeria based on Y-SNPs and Y-STR data showed for the first time its regional representativeness, a result which is important for standard population and forensic genetic applications using the YRI sample.Therefore, the uniquely and powerful geographical information carried by the Y-chromosome makes it an important locus to test the representativeness of a certain sample even in the genomic era, especially in poorly investigated areas like Africa.

View Article: PubMed Central - PubMed

Affiliation: KU Leuven, Forensic Biomedical Sciences, Department of Imaging & Pathology, Leuven, Belgium.

ABSTRACT
Patterns of genetic variation in human populations across the African continent are still not well studied in comparison with Eurasia and America, despite the high genetic and cultural diversity among African populations. In population and forensic genetic studies a single sample is often used to represent a complete African region. In such a scenario, inappropriate sampling strategies and/or the use of local, isolated populations may bias interpretations and pose questions of representativeness at a macrogeographic-scale. The non-recombining region of the Y-chromosome (NRY) has great potential to reveal the regional representation of a sample due to its powerful phylogeographic information content. An area poorly characterized for Y-chromosomal data is the West-African region along the Bight of Benin, despite its important history in the trans-Atlantic slave trade and its large number of ethnic groups, languages and lifestyles. In this study, Y-chromosomal haplotypes from four Beninese populations were determined and a global meta-analysis with available Y-SNP and Y-STR data from populations along the Bight of Benin and surrounding areas was performed. A thorough methodology was developed allowing comparison of population samples using Y-chromosomal lineage data based on different Y-SNP panels and phylogenies. Geographic proximity turned out to be the best predictor of genetic affinity between populations along the Bight of Benin. Nevertheless, based on Y-chromosomal data from the literature two population samples differed strongly from others from the same or neighbouring areas and are not regionally representative within large-scale studies. Furthermore, the analysis of the HapMap sample YRI of a Yoruban population from South-western Nigeria based on Y-SNPs and Y-STR data showed for the first time its regional representativeness, a result which is important for standard population and forensic genetic applications using the YRI sample. Therefore, the uniquely and powerful geographical information carried by the Y-chromosome makes it an important locus to test the representativeness of a certain sample even in the genomic era, especially in poorly investigated areas like Africa.

No MeSH data available.


Principal component analysis (PCA), together with a biplot, of 14 West-African population samples, (a) inclusively and (b) exclusively the Ghanaian C1 population sample, based on the Y-SNP frequencies using the phylogeny given in S3 Fig.The cumulative proportion of plot (a) is 0.92 for the first two principal components (PC1: 0.83; PC2: 0.09), and of plot (b) is 0.81 for the first two principal components (PC1: 0.45; PC2: 0.36). The nomenclature and the references of the population samples are available in S1 Table.
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pone.0141510.g002: Principal component analysis (PCA), together with a biplot, of 14 West-African population samples, (a) inclusively and (b) exclusively the Ghanaian C1 population sample, based on the Y-SNP frequencies using the phylogeny given in S3 Fig.The cumulative proportion of plot (a) is 0.92 for the first two principal components (PC1: 0.83; PC2: 0.09), and of plot (b) is 0.81 for the first two principal components (PC1: 0.45; PC2: 0.36). The nomenclature and the references of the population samples are available in S1 Table.

Mentions: Second, Y-SNP data of 741 individuals from 14 population samples within Ivory Coast, Ghana, Benin, Nigeria and Cameroon were compared according to the phylogeny presented in S3 Fig (see S4 Table for haplogroup frequencies). The population sample from Ghana (C1) and the Benin population sample from Brucato et al. [27] (D1) were the most differentiated based on the subhaplogroup frequencies (S4 Table), the FST-values (S8A Table) and the PCA plot (Fig 2). In the CA-plot (S7 Fig) population samples D3 and B2 were also differentiated, next to samples C1 and D1. The Nigerian populations (E1-E3) always clustered together, as did the Cameroonian populations (F1-F3).


The Paternal Landscape along the Bight of Benin - Testing Regional Representativeness of West-African Population Samples Using Y-Chromosomal Markers.

Larmuseau MH, Vessi A, Jobling MA, Van Geystelen A, Primativo G, Biondi G, Martínez-Labarga C, Ottoni C, Decorte R, Rickards O - PLoS ONE (2015)

Principal component analysis (PCA), together with a biplot, of 14 West-African population samples, (a) inclusively and (b) exclusively the Ghanaian C1 population sample, based on the Y-SNP frequencies using the phylogeny given in S3 Fig.The cumulative proportion of plot (a) is 0.92 for the first two principal components (PC1: 0.83; PC2: 0.09), and of plot (b) is 0.81 for the first two principal components (PC1: 0.45; PC2: 0.36). The nomenclature and the references of the population samples are available in S1 Table.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4636292&req=5

pone.0141510.g002: Principal component analysis (PCA), together with a biplot, of 14 West-African population samples, (a) inclusively and (b) exclusively the Ghanaian C1 population sample, based on the Y-SNP frequencies using the phylogeny given in S3 Fig.The cumulative proportion of plot (a) is 0.92 for the first two principal components (PC1: 0.83; PC2: 0.09), and of plot (b) is 0.81 for the first two principal components (PC1: 0.45; PC2: 0.36). The nomenclature and the references of the population samples are available in S1 Table.
Mentions: Second, Y-SNP data of 741 individuals from 14 population samples within Ivory Coast, Ghana, Benin, Nigeria and Cameroon were compared according to the phylogeny presented in S3 Fig (see S4 Table for haplogroup frequencies). The population sample from Ghana (C1) and the Benin population sample from Brucato et al. [27] (D1) were the most differentiated based on the subhaplogroup frequencies (S4 Table), the FST-values (S8A Table) and the PCA plot (Fig 2). In the CA-plot (S7 Fig) population samples D3 and B2 were also differentiated, next to samples C1 and D1. The Nigerian populations (E1-E3) always clustered together, as did the Cameroonian populations (F1-F3).

Bottom Line: Geographic proximity turned out to be the best predictor of genetic affinity between populations along the Bight of Benin.Furthermore, the analysis of the HapMap sample YRI of a Yoruban population from South-western Nigeria based on Y-SNPs and Y-STR data showed for the first time its regional representativeness, a result which is important for standard population and forensic genetic applications using the YRI sample.Therefore, the uniquely and powerful geographical information carried by the Y-chromosome makes it an important locus to test the representativeness of a certain sample even in the genomic era, especially in poorly investigated areas like Africa.

View Article: PubMed Central - PubMed

Affiliation: KU Leuven, Forensic Biomedical Sciences, Department of Imaging & Pathology, Leuven, Belgium.

ABSTRACT
Patterns of genetic variation in human populations across the African continent are still not well studied in comparison with Eurasia and America, despite the high genetic and cultural diversity among African populations. In population and forensic genetic studies a single sample is often used to represent a complete African region. In such a scenario, inappropriate sampling strategies and/or the use of local, isolated populations may bias interpretations and pose questions of representativeness at a macrogeographic-scale. The non-recombining region of the Y-chromosome (NRY) has great potential to reveal the regional representation of a sample due to its powerful phylogeographic information content. An area poorly characterized for Y-chromosomal data is the West-African region along the Bight of Benin, despite its important history in the trans-Atlantic slave trade and its large number of ethnic groups, languages and lifestyles. In this study, Y-chromosomal haplotypes from four Beninese populations were determined and a global meta-analysis with available Y-SNP and Y-STR data from populations along the Bight of Benin and surrounding areas was performed. A thorough methodology was developed allowing comparison of population samples using Y-chromosomal lineage data based on different Y-SNP panels and phylogenies. Geographic proximity turned out to be the best predictor of genetic affinity between populations along the Bight of Benin. Nevertheless, based on Y-chromosomal data from the literature two population samples differed strongly from others from the same or neighbouring areas and are not regionally representative within large-scale studies. Furthermore, the analysis of the HapMap sample YRI of a Yoruban population from South-western Nigeria based on Y-SNPs and Y-STR data showed for the first time its regional representativeness, a result which is important for standard population and forensic genetic applications using the YRI sample. Therefore, the uniquely and powerful geographical information carried by the Y-chromosome makes it an important locus to test the representativeness of a certain sample even in the genomic era, especially in poorly investigated areas like Africa.

No MeSH data available.