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本文引用的文献

1
Effects of natural selection and gene conversion on the evolution of human glycophorins coding for MNS blood polymorphisms in malaria-endemic African populations.自然选择和基因转换对人类糖蛋白编码的 MNS 血型多态性在疟疾流行的非洲人群中的进化影响。
Am J Hum Genet. 2011 Jun 10;88(6):741-754. doi: 10.1016/j.ajhg.2011.05.005.
2
Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.混合人群 GWAS 的增强统计检验:使用来自 CARe 和乳腺癌联盟的非裔美国人进行评估。
PLoS Genet. 2011 Apr;7(4):e1001371. doi: 10.1371/journal.pgen.1001371. Epub 2011 Apr 21.
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Population genetics of malaria resistance in humans.人类疟疾抗性的群体遗传学。
Heredity (Edinb). 2011 Oct;107(4):283-304. doi: 10.1038/hdy.2011.16. Epub 2011 Mar 23.
4
Population-genetic properties of differentiated human copy-number polymorphisms.人类分化拷贝数多态性的群体遗传特性。
Am J Hum Genet. 2011 Mar 11;88(3):317-32. doi: 10.1016/j.ajhg.2011.02.004.
5
Genome-wide association study of coronary heart disease and its risk factors in 8,090 African Americans: the NHLBI CARe Project.全基因组关联研究冠心病及其风险因素在 8090 名非裔美国人:美国国立卫生研究院 CARe 项目。
PLoS Genet. 2011 Feb 10;7(2):e1001300. doi: 10.1371/journal.pgen.1001300.
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Classic selective sweeps were rare in recent human evolution.经典的选择清除在人类近期进化中较为罕见。
Science. 2011 Feb 18;331(6019):920-4. doi: 10.1126/science.1198878.
7
MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes.MaCH:利用序列和基因型数据来估计单倍型和未观测基因型。
Genet Epidemiol. 2010 Dec;34(8):816-34. doi: 10.1002/gepi.20533.
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Identifying signatures of natural selection in Tibetan and Andean populations using dense genome scan data.利用密集基因组扫描数据鉴定藏人和安第斯人自然选择的特征。
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Integrating common and rare genetic variation in diverse human populations.整合不同人类群体中的常见和罕见遗传变异。
Nature. 2010 Sep 2;467(7311):52-8. doi: 10.1038/nature09298.
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Genome-wide association analyses identifies a susceptibility locus for tuberculosis on chromosome 18q11.2.全基因组关联分析鉴定出染色体 18q11.2 上的结核病易感性位点。
Nat Genet. 2010 Sep;42(9):739-741. doi: 10.1038/ng.639. Epub 2010 Aug 8.

对来自 CARe 和其他队列的非洲裔人群进行全基因组比较,揭示了自然选择的信号。

Genome-wide comparison of African-ancestry populations from CARe and other cohorts reveals signals of natural selection.

机构信息

Harvard- Massachusetts Institute of Technology (MIT) Division of Health, Science and Technology, Cambridge, USA.

出版信息

Am J Hum Genet. 2011 Sep 9;89(3):368-81. doi: 10.1016/j.ajhg.2011.07.025.

DOI:10.1016/j.ajhg.2011.07.025
PMID:21907010
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3169818/
Abstract

The study of recent natural selection in human populations has important applications to human history and medicine. Positive natural selection drives the increase in beneficial alleles and plays a role in explaining diversity across human populations. By discovering traits subject to positive selection, we can better understand the population level response to environmental pressures including infectious disease. Our study examines unusual population differentiation between three large data sets to detect natural selection. The populations examined, African Americans, Nigerians, and Gambians, are genetically close to one another (F(ST) < 0.01 for all pairs), allowing us to detect selection even with moderate changes in allele frequency. We also develop a tree-based method to pinpoint the population in which selection occurred, incorporating information across populations. Our genome-wide significant results corroborate loci previously reported to be under selection in Africans including HBB and CD36. At the HLA locus on chromosome 6, results suggest the existence of multiple, independent targets of population-specific selective pressure. In addition, we report a genome-wide significant (p = 1.36 × 10(-11)) signal of selection in the prostate stem cell antigen (PSCA) gene. The most significantly differentiated marker in our analysis, rs2920283, is highly differentiated in both Africa and East Asia and has prior genome-wide significant associations to bladder and gastric cancers.

摘要

对人类群体中近期自然选择的研究对人类历史和医学具有重要的应用价值。正性自然选择驱动有益等位基因的增加,并在解释人类群体之间的多样性方面发挥作用。通过发现受正性选择影响的特征,我们可以更好地理解包括传染病在内的环境压力对人群的影响。我们的研究通过三个大型数据集之间的异常群体分化来检测自然选择。所研究的群体,非裔美国人、尼日利亚人和冈比亚人,彼此之间遗传上非常接近(所有对之间的 F(ST) < 0.01),这使我们即使在等位基因频率发生适度变化的情况下也能检测到选择。我们还开发了一种基于树的方法,通过整合跨群体的信息,确定发生选择的群体。我们在全基因组范围内显著的结果证实了先前在非洲人中报告的受选择影响的位点,包括 HBB 和 CD36。在 6 号染色体上的 HLA 基因座,结果表明存在多个针对特定人群的选择压力的独立靶点。此外,我们报告了前列腺干细胞抗原(PSCA)基因中存在全基因组范围内显著选择信号(p = 1.36×10(-11))。在我们的分析中,最显著分化的标记 rs2920283 在非洲和东亚都高度分化,并且先前与膀胱癌和胃癌的全基因组显著关联。