Population substructure within human populations is globally evident and a well-known confounding factor in many genetic studies. In contrast, admixture mapping exploits population stratification to detect genotype-phenotype correlations in admixed populations. Southern Africa has untapped potential for disease mapping of ancestry-specific disease risk alleles due to the distinct genetic diversity in its populations compared to other populations worldwide. This diversity contributes to a number of phenotypes, including ancestry-specific disease risk and response to pathogens. Although the 1000 Genomes Project significantly improved our understanding of genetic variation globally, southern African populations are still severely underrepresented in biomedical and human genetic studies due to insufficient large-scale publicly available data. In addition to a lack of genetic data in public repositories, existing software, algorithms and resources used for imputation and phasing of genotypic data (amongst others) are largely ineffective for populations with a complex genetic architecture such as that seen in southern Africa. This review article, therefore, aims to summarise the current limitations of conducting genetic studies on populations with a complex genetic architecture to identify potential areas for further research and development.

中文翻译：

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南部非洲人口基因组学和疾病图谱的前瞻性途径。

人口中的人口亚结构在全球范围内都是显而易见的，并且是许多遗传研究中众所周知的混杂因素。相比之下，混合作图利用种群分层来检测混合种群中的基因型-表型相关性。由于与世界其他人群相比，南部非洲的人群具有明显的遗传多样性，因此在绘制特定祖先疾病风险等位基因的疾病图谱方面具有未开发的潜力。这种多样性促成了许多表型，包括特定祖先的疾病风险和对病原体的反应。尽管千人基因组计划显着提高了我们对全球遗传变异的理解，但由于大规模公开数据不足，南部非洲人口在生物医学和人类遗传研究中的代表性仍然严重不足。除了公共存储库中缺乏遗传数据外，用于基因型数据（以及其他）的插补和分阶段的现有软件、算法和资源对于具有复杂遗传结构的人群（例如在南部非洲看到的人群）在很大程度上无效。因此，这篇综述文章旨在总结目前对具有复杂遗传结构的人群进行遗传研究的局限性，以确定进一步研究和开发的潜在领域。