Suppr超能文献

自混合以来墨西哥人MHC区域的强选择作用

Strong Selection at MHC in Mexicans since Admixture.

作者信息

Zhou Quan, Zhao Liang, Guan Yongtao

机构信息

USDA/ARS Children's Nutrition Research Center, Houston, Texas, United States of America.

Department of Pediatrics, Baylor College of Medicine, Houston, Texas, United States of America.

出版信息

PLoS Genet. 2016 Feb 10;12(2):e1005847. doi: 10.1371/journal.pgen.1005847. eCollection 2016 Feb.

Abstract

Mexicans are a recent admixture of Amerindians, Europeans, and Africans. We performed local ancestry analysis of Mexican samples from two genome-wide association studies obtained from dbGaP, and discovered that at the MHC region Mexicans have excessive African ancestral alleles compared to the rest of the genome, which is the hallmark of recent selection for admixed samples. The estimated selection coefficients are 0.05 and 0.07 for two datasets, which put our finding among the strongest known selections observed in humans, namely, lactase selection in northern Europeans and sickle-cell trait in Africans. Using inaccurate Amerindian training samples was a major concern for the credibility of previously reported selection signals in Latinos. Taking advantage of the flexibility of our statistical model, we devised a model fitting technique that can learn Amerindian ancestral haplotype from the admixed samples, which allows us to infer local ancestries for Mexicans using only European and African training samples. The strong selection signal at the MHC remains without Amerindian training samples. Finally, we note that medical history studies suggest such a strong selection at MHC is plausible in Mexicans.

摘要

墨西哥人是美洲印第安人、欧洲人和非洲人的近期混合群体。我们对从dbGaP获取的两项全基因组关联研究中的墨西哥样本进行了局部祖先分析,发现与基因组的其他部分相比,墨西哥人在MHC区域有过多的非洲祖先等位基因,这是近期对混合样本选择的标志。两个数据集的估计选择系数分别为0.05和0.07,这使我们的发现跻身于人类中已知的最强选择之列,即北欧人的乳糖酶选择和非洲人的镰状细胞性状。使用不准确的美洲印第安人训练样本是先前报道的拉丁裔选择信号可信度的一个主要问题。利用我们统计模型的灵活性,我们设计了一种模型拟合技术,该技术可以从混合样本中学习美洲印第安人祖先单倍型,这使我们能够仅使用欧洲和非洲训练样本推断墨西哥人的局部祖先。在没有美洲印第安人训练样本的情况下,MHC区域的强选择信号依然存在。最后,我们注意到病史研究表明,在墨西哥人中,MHC区域如此强烈的选择是合理的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8e1/4749250/bb83ee70cdd3/pgen.1005847.g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验