EFFECTS OF POPULATION MIXTURES ON GENETIC VARIATION

人类群体的遗传调查通常涉及以下几个方面的混合 亚群 混合物存在的识别和鉴别 混合物成分的分析对于理解 遗传变异和重建进化史。 这 该项目旨在定量评估外加剂对 自然种群的遗传变异。 将有两种类型的混合物 研究：（a）由于亚群合并而产生的混合物;以及（B） 由于源种群之间的基因流动而产生的混合物。 在这两种情况下，我们 将开发统计方法，以确定混合物的来源， 估计混合分量。 由于混合物的存在会影响 观察到的等位基因频率分布，调整的影响 混合成分将提供可靠的估计位点特异性 多位点突变率（v's）和有效群体大小（e's） 等位基因频率数据。 混合种群在遗传学上的效用- 复杂疾病的流行病学研究将由 基因座间等位基因关联的动态及其与基因型的关系 混合物的历史 最大似然原理将被用于开发分析方法 对于这种分析，将提供数值算法，以涵盖 缺失数据和来源不明人群的可能性。 理论 将被应用于等位酶数据从美洲印第安人，和三个主要的 种族群体，以测试其有效性，并提供实证观察 混合物对遗传变异的影响。 的基因证据 混合物将在印度的Siddis和斯里兰卡的僧伽罗人中进行研究。 Lanka，其亲本种群并不确切。 广泛 亚洲猕猴已发表数据的计算机模拟和重新分析 而果蝇将被用来检验这些理论， 估计量的统计特性。 基因座特异性突变率的估计将有助于 理解不同基因座或DNA上的突变性变异 人类基因组的不同部分。 同时估计 v和Ne将允许有效地比较自发性的速率。 不同生物体的突变。 掺合料之间的关系 水平和等位基因的多位点关联将有助于（a） 理解复杂疾病的遗传病因，和（B）在 制定有效的调查策略， 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.