Models of Complex Genetic Systems

新的DNA测序方法产生了大量的DNA 人类和许多其他物种的序列，包括现已灭绝的物种。这个 拟议的研究将有助于分析和解释DNA序列数据 既用于理解基本的遗传过程，如自然选择和 重组和理解人类的历史和遗传基础 遗传性疾病。拟进行的研究有四个方面：(一)DNA分析 尼安德特人骨骼的序列数据，目的是了解 尼安德特人与现代人的关系以及理解 现代人从尼安德特人分离以来的近代史，(Ii) 对经历了最近一次基因突变的人群中基因频率模式的预测 射程扩展，特别强调过去现代的射程扩展 欧洲、亚洲和美洲的人类人口，(Iii)DNA分析 从极端环境样本中获得的细菌物种序列，用于 量化基因重组和分化程度的目的 不同菌株，(Iv)模拟复杂遗传性疾病的遗传基础，如 精神分裂症，许多癌症，以及1型和2型糖尿病，用于量化目的 产生高风险的基因之间的相互作用和设计新的方法 识别与高风险相关的基因。虽然这四个领域的目标是 每一种方法都略有不同，但数学和统计方法相似。 种群遗传力模型，包括自然选择、重组、遗传 将开发漂移和迁移，并根据现有数据进行测试。电脑 将使用对这些模型的模拟来生成用于测试的假设数据集 提出了统计方法。

New methods of DNA sequencing have produced a great abundance of DNA sequences from humans and many other species, including species now extinct. The proposed research will be intended to help analyze and interpret DNA sequence data both for understanding basic genetic processes such as natural selection and recombination and for understanding the history of humans and the genetic basis of inherited diseases. The proposed research is in four areas: (i) the analysis of DNA sequence data from Neanderthal bones for the purpose of understanding the relationship between Neanderthals and modern humans and for understanding the recent history of modern humans since their separation from Neanderthals, (ii) the prediction of patterns in gene frequencies in populations that have undergone a recent range expansion, with particular emphasis on past range expansions of modern humans populations in Europe, Asia, and the Americas, (iii) the analysis of DNA sequences of bacterial species obtained in samples from extreme environments, for the purpose of quantifying the extent of genetic recombination and differentiation between different strains, (iv) modeling the genetic basis of complex inherited diseases such as schizophrenia, many cancers, and type 1 and 2 diabetes, for the purpose of quantifying the interactions among genes that create higher risk and for devising new methods for identifying genes associated with higher risk. Although the goals of the four areas are somewhat different, similar mathematical and statistical methods will be used in each. Models of population genetic forces, including natural selection, recombination, genetic drift and migration will be developed and tested against available data. Computer simulations of those models will be used to generate hypothetical data sets for testing proposed statistical methods.