POPULATION MIXTURES EFFECTS ON GENETIC VARIATION

点击翻译按钮获取中文摘要

During the past four years our research has demonstrated that mixtures of subpopulations. the main constituent of most genetic surveys of human populations. differentially affect various measures of genetic variation. Recognizing the presence of mixtures and identifying the mixture components. therefore. are important for understanding the maintenance of genetic variation and for reconstructing evolutionary history. We demonstrated that the effects of population mixture are more efficiently detected through the use of the class of polymorphic loci known as variable number of tandem repeat (VNTR) loci. Since new variation at these loci is generated differently from new variation in classical markers (blood groups and proteins). new analytical tools are needed to study the evolutionary dynamics and statistical properties of summary measures of genetic variation at these hypervariable loci. VNTR loci (microsatellites. short tandem repeats. and minisatellites) appear to be maintained by different mutational mechanisms. which will be the focus of our proposed studies. Using both types of population mixtures (amalgamation and gene flow), we propose to develop methods for studying intrapopulation and interpopulation variation and so to investigate evolutionary relatedness between individuals and between populations. Multilocus measures will also be developed that can be used for evolutionary studies using DNA fingerprint data. Models of different molecular mechanisms of mutations (involving intrastrand and interstrand processes) will be used. The effects of incomplete identification of alleles and of convergent changes (independent mutations producing the same copy-number of repeat units at a VNTR locus) will be examined. The techniques used will be analytical tools of stochastic processes (incorporating drift and mutations) and computer simulations. Data on human populations with different histories of mixtures. as well as data from other species. will be used to validate the theory. New experimental data will be used to design the simulation procedures and parameters. Such studies will also help us to understand the etiology of complex diseases in populations with different mixture histories. and to develop survey strategies for mapping such disease genes using hypervariable loci.