Admixture mapping comes of age.

Admixture mapping comes of age.
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DOI:
10.1146/annurev-genom-082509-141523
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发表时间:
2010
影响因子:
8.7
通讯作者:
Smith MW
Smith MW
中科院分区:
生物学2区
文献类型:
--
作者:
Winkler CA;Nelson GW;Smith MW

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混合作图是基于这样的假设,即人群之间疾病率的差异部分是由于致病遗传变异的频率差异。在混合群体中,这些遗传变异更经常发生在从具有较高疾病变异频率的祖先群体遗传的染色体片段上。对疾病关联的基因组扫描只需要足够的标记来识别祖先染色体片段;对于最近混合的人群,如非洲裔美国人,1,500 - 2,500个祖先信息标记(AIM)就足够了。该方法是在50多年前提出的,但所需的AIM面板和统计方法直到最近才可用。自2005年第一次混合物扫描以来,已经通过混合物作图确定了一系列疾病/性状的遗传基础。在这里,我们提供了一个历史的角度来看,审查AIM面板和软件包,并讨论最近的成功和意想不到的见解人类疾病,表现出不同的利率在人群中。
Admixture mapping is based on the hypothesis that differences in disease rates between populations are due in part to frequency differences in disease-causing genetic variants. In admixed populations, these genetic variants occur more often on chromosome segments inherited from the ancestral population with the higher disease variant frequency. A genome scan for disease association requires only enough markers to identify the ancestral chromosome segments; for recently admixed populations, such as African Americans, 1,500–2,500 ancestry-informative markers (AIMs) are sufficient. The method was proposed over 50 years ago, but the AIM panels and statistical methods required have only recently become available. Since the first admixture scan in 2005, the genetic bases for a range of diseases/traits have been identified by admixture mapping. Here, we provide a historical perspective, review AIM panels and software packages, and discuss recent successes and unexpected insights into human diseases that exhibit disparate rates across human populations.
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