Juyal Garima, Mondal Mayukh, Luisi Pierre, Laayouni Hafid, Sood Ajit, Midha Vandana, Heutink Peter, Bertranpetit Jaume, Thelma B K, Casals Ferran
Department of Genetics, University of Delhi South Campus, New Delhi, 110 021, India.
Hum Genet. 2014 Oct;133(10):1273-87. doi: 10.1007/s00439-014-1462-0. Epub 2014 Jul 1.
Indian demographic history includes special features such as founder effects, interpopulation segregation, complex social structure with a caste system and elevated frequency of consanguineous marriages. It also presents a higher frequency for some rare mendelian disorders and in the last two decades increased prevalence of some complex disorders. Despite the fact that India represents about one-sixth of the human population, deep genetic studies from this terrain have been scarce. In this study, we analyzed high-density genotyping and whole-exome sequencing data of a North and a South Indian population. Indian populations show higher differentiation levels than those reported between populations of other continents. In this work, we have analyzed its consequences, by specifically assessing the transferability of genetic markers from or to Indian populations. We show that there is limited genetic marker portability from available genetic resources such as HapMap or the 1,000 Genomes Project to Indian populations, which also present an excess of private rare variants. Conversely, tagSNPs show a high level of portability between the two Indian populations, in contrast to the common belief that North and South Indian populations are genetically very different. By estimating kinship from mates and consanguinity in our data from trios, we also describe different patterns of assortative mating and inbreeding in the two populations, in agreement with distinct mating preferences and social structures. In addition, this analysis has allowed us to describe genomic regions under recent adaptive selection, indicating differential adaptive histories for North and South Indian populations. Our findings highlight the importance of considering demography for design and analysis of genetic studies, as well as the need for extending human genetic variation catalogs to new populations and particularly to those with particular demographic histories.
印度的人口统计学历史具有一些特殊特征,例如奠基者效应、群体间隔离、带有种姓制度的复杂社会结构以及近亲结婚频率较高。它还表现出某些罕见孟德尔疾病的较高发病率,并且在过去二十年中一些复杂疾病的患病率有所上升。尽管印度人口约占世界人口的六分之一,但来自该地区的深入基因研究却很少。在本研究中,我们分析了一组北印度人群和一组南印度人群的高密度基因分型和全外显子测序数据。印度人群之间的分化水平高于其他各大洲人群之间的分化水平。在这项工作中,我们通过专门评估遗传标记从其他人群向印度人群或从印度人群向其他人群的转移性,分析了其后果。我们发现,从诸如国际人类基因组单体型图计划(HapMap)或千人基因组计划等现有遗传资源到印度人群的遗传标记可转移性有限,印度人群还存在过多的私有罕见变异。相反,标签单核苷酸多态性(tagSNPs)在两个印度人群之间显示出高度的可转移性,这与普遍认为的北印度人群和南印度人群在基因上差异很大的观点相反。通过从我们三人组数据中的配偶关系和近亲关系估计亲属关系,我们还描述了两个人群中不同的选型交配和近亲繁殖模式,这与不同的交配偏好和社会结构一致。此外,该分析使我们能够描述近期适应性选择下的基因组区域,表明北印度人群和南印度人群有不同的适应性历史。我们的研究结果强调了在设计和分析基因研究时考虑人口统计学的重要性,以及将人类遗传变异目录扩展到新人群,特别是那些具有特殊人口统计学历史的人群的必要性。