Application of geographic population structure (GPS) algorithm for biogeographical analyses of populations with complex ancestries: a case study of South Asians from 1000 genomes project.
Application of geographic population structure (GPS) algorithm for biogeographical analyses of populations with complex ancestries: a case study of South Asians from 1000 genomes project.
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DOI：
10.1186/s12863-017-0579-2
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发表时间：
2017-12-28
期刊：
影响因子：
2.9
通讯作者：
Upadhyai P
中科院分区：
文献类型：
--
作者：
Das R;Upadhyai P
利用生物数据来推断人类的地理起源一直是生物学家和人类学家的长期追求。已经开发了几种生物地理分析工具来利用遗传数据推断人类种群的地理起源。然而，由于遗传信息固有的复杂性，这些方法很容易被误解。地理人口结构 (GPS) 算法是一种基于混合的生物地理分析工具，已用于全球各种人口的地理定位。在这里，我们试图剖析其定位高度混合群体的敏感性和准确性。鉴于印度次大陆人口扩散和基因流动的复杂历史，我们使用人类基因组多样性面板 (HGDP) 中提供的印度次大陆人口和之前描述的参考资料，利用 GPS 工具定位了 1000 个基因组项目中的五个南亚人口：旁遮普语、古吉拉特语、泰米尔语、泰卢固语和孟加拉语，其中一些人是最近移民到美国和英国的。我们的研究结果表明，即使对于在其他地方采样的近期移民人群（即泰米尔语、泰卢固语和古吉拉特语个体）而言，GPS 分配也具有相当高的准确性，其中 96%、87% 和 79% 的个体位于距其家乡 600 公里以内。虽然缺乏适当的参考群体导致旁遮普语和孟加拉语基因组定位的精度处于中低水平。我们的研究结果表明，GPS 方法是有用的，但可能明显依赖于参考人群中混合的相对比例来确定测试个体的生物地理起源。我们的结论是，需要进一步修改以使这种方法更适合高度混合的个体。本文的在线版本（doi：10.1186/s12863-017-0579-2）包含补充材料，可供授权用户使用。
The utilization of biological data to infer the geographic origins of human populations has been a long standing quest for biologists and anthropologists. Several biogeographical analysis tools have been developed to infer the geographical origins of human populations utilizing genetic data. However due to the inherent complexity of genetic information these approaches are prone to misinterpretations. The Geographic Population Structure (GPS) algorithm is an admixture based tool for biogeographical analyses and has been employed for the geo-localization of various populations worldwide. Here we sought to dissect its sensitivity and accuracy for localizing highly admixed groups. Given the complex history of population dispersal and gene flow in the Indian subcontinent, we have employed the GPS tool to localize five South Asian populations, Punjabi, Gujarati, Tamil, Telugu and Bengali from the 1000 Genomes project, some of whom were recent migrants to USA and UK, using populations from the Indian subcontinent available in Human Genome Diversity Panel (HGDP) and those previously described as reference. Our findings demonstrate reasonably high accuracy with regards to GPS assignment even for recent migrant populations sampled elsewhere, namely the Tamil, Telugu and Gujarati individuals, where 96%, 87% and 79% of the individuals, respectively, were positioned within 600 km of their native locations. While the absence of appropriate reference populations resulted in moderate-to-low levels of precision in positioning of Punjabi and Bengali genomes. Our findings reflect that the GPS approach is useful but likely overtly dependent on the relative proportions of admixture in the reference populations for determination of the biogeographical origins of test individuals. We conclude that further modifications are desired to make this approach more suitable for highly admixed individuals. The online version of this article (doi: 10.1186/s12863-017-0579-2) contains supplementary material, which is available to authorized users.
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