EFFECTS OF POPULATION MIXTURES ON GENETIC VARIATION

在人类群体中进行的基因调查通常涉及到 亚群。混合物存在的识别和识别 对于理解混合物组件的维护是必不可少的 基因变异，以及重建进化史。这 该项目的目的是定量评估外加剂对 自然种群中的遗传变异。将有两种类型的混合物 所研究的：(A)由于亚群的融合而产生的混合；和(B) 由于源种群之间的基因流动而产生的混合。在这两种情况下，我们 将开发统计方法来确定混合物的来源，以及 估计混合成分。由于混合物的存在会影响 观察等位基因频率分布，调整影响因素 混合物成分将提供对特定基因座的可靠估计 多基因座的变异率(v‘s)和有效种群大小(e’s) 等位基因频率数据。混合种群在遗传研究中的应用 复杂疾病的流行病学研究将由 基因座间的等位基因关联动态及其与遗传多样性的关系 外加剂的历史。 最大似然原理将被用于发展分析方法。 对于这样的分析，将提供数值算法来涵盖 数据丢失和来源人口未知的可能性。这一理论 将应用于美洲印第安人的等位酶数据，以及三个主要的 种族群体，以测试其有效性，并提供经验观察 关于混合物对遗传变异的影响。遗传证据表明 混合剂将在印度的悉迪和斯里兰卡的僧伽罗语中进行研究。 斯里兰卡，其父母人口并不确切知道。广泛性 亚洲猕猴已发表数据的计算机模拟和重新分析 果蝇将被用来检验这些理论并研究 估计量的统计性质。 对特定基因座突变率的估计将有助于 理解不同基因座或DNA上的可变性变异 人类基因组不同部分的片段。同时估计 V‘s和Ne’s将允许有效地比较自发频率 不同生物体中的突变。外加剂之间的关系 等位基因的水平和多位点关联将有助于(A) 了解复杂疾病的遗传病因，以及(B) 开发有效的调查策略来定位与此相关的基因 疾病。

Genetic surveys in human populations often involve a mixture of subpopulations. Recognition of the presence of mixtures and identification of mixture components is essential in understanding the maintenance of genetic variation, and for reconstructing evolutionary history. This project aims at a quantitative assessment of the effect of admixture on genetic variation in natural populations. Two types of mixtures will be studied: (a) mixture due to amalgamation of subpopulations; and (b) admixture due to gene flow among source populations. In both instances, we will develop statistical methods to identify the source of mixtures, and estimate the mixing components. Since the presence of mixture affects the observed allele frequency distribution, adjustment for the effects of mixture components will provide reliable estimates of locus-specific mutation rates (v's) and effective population size (e's) from multi-locus allele frequency data. The utility of admixed populations for genetic- epidemiological studies of complex diseases will be examined by the dynamics of allelic association among loci and its relationship with the history of admixture. The maximum likelihood principle will be used to develop analytical methods for such analyses, and numerical algorithms will be provided to encompass the possibility of missing data and unknown source populations. The theory will be applied to allozyme data from the Amerindians, and the three major ethnic groups, to test its validity, and to provide empirical observations on the effect of mixtures on genetic variation. Genetic evidence of admixture will be studied in the Siddis of India, and the Sinhalese of Sri Lanka, whose parental populations are not precisely known. Extensive computer simulations and re-analysis of published data from Asian Macaques and Drosophila will be used to test the theories and to study the statistical properties of the estimators. The estimation of locus-specific mutation rates will contribute to an understanding of the variation of mutability at different loci, or at DNA segments in different parts of the human genome. Simultaneous estimates of v's and Ne's will allow effective comparisons of the rate of spontaneous mutations in different organisms. The relationship between admixture levels and the multi-locus association of alleles will aid (a) in understanding the genetic etiology of complex diseases, and (b) in developing efficient survey strategies for mapping genes underlying such diseases.