The genetics of East African populations: a Nilo-Saharan component in the African genetic landscape
The genetics of East African populations: a Nilo-Saharan component in the African genetic landscape
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DOI：
10.1038/srep09996
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发表时间：
2015-05-28
影响因子：
4.6
通讯作者：
Bertranpetit, Jaume
中科院分区：
文献类型：
--
作者：
Dobon, Begona;Hassan, Hisham Y.;Bertranpetit, Jaume
东非是研究人类遗传多样性的战略区域，因为存在着种族、语言和地理上多样化的人口。在这里，我们通过分析属于三个非洲语系（尼日尔-科尔多法尼语、尼罗-撒哈拉语和亚非语系）的9个族群，为生活在东非苏丹地区的人群的遗传历史提供了新的见解。共有500人对20万个单核苷酸多态性进行了基因分型。采用主成分分析、admix聚类分析、FST统计和三种群检验对不同民族语言群体的遗传结构和祖先进行了研究。我们的分析揭示了苏丹尼罗-撒哈拉语系人群（达尔富尔人和部分努巴人）与南苏丹尼罗人相关的遗传成分，但与其他苏丹人群或其他撒哈拉以南人群无关。居住在该地区北部的人口与北非表现出密切的遗传亲缘关系，其中有一部分可能是阿拉伯人从阿拉伯迁移之前北非人的残余。此外，我们发现种群之间抗疟疾和抗细菌宿主防御重要基因的遗传距离非常低，这表明这些基因存在类似的选择压力，并强调考虑功能途径以理解种群进化史的重要性。
East Africa is a strategic region to study human genetic diversity due to the presence of ethnically, linguistically, and geographically diverse populations. Here, we provide new insight into the genetic history of populations living in the Sudanese region of East Africa by analysing nine ethnic groups belonging to three African linguistic families: Niger-Kordofanian, Nilo-Saharan and Afro-Asiatic. A total of 500 individuals were genotyped for 200,000 single-nucleotide polymorphisms. Principal component analysis, clustering analysis using ADMIXTURE, FST statistics, and the three-population test were used to investigate the underlying genetic structure and ancestry of the different ethnolinguistic groups. Our analyses revealed a genetic component for Sudanese Nilo-Saharan speaking groups (Darfurians and part of Nuba populations) related to Nilotes of South Sudan, but not to other Sudanese populations or other sub-Saharan populations. Populations inhabiting the North of the region showed close genetic affinities with North Africa, with a component that could be remnant of North Africans before the migrations of Arabs from Arabia. In addition, we found very low genetic distances between populations in genes important for anti-malarial and anti-bacterial host defence, suggesting similar selective pressures on these genes and stressing the importance of considering functional pathways to understand the evolutionary history of populations.