THEORETICAL INVESTIGATIONS OF GENETIC IDENTITY AND DISEQUILIBRIA

包括理论分析、计算机模拟和 已经进行了分子数据的分析以确定 从某些类型的数据中获取遗传信息的可行性。 我们已经展示了如何从DNA估计平均杂合性 指纹数据，例如我们自己的实验室获得的数据。 我们 也采取了一种新的方法对人类遗传连锁研究， 关注人口水平的连锁不平衡，而不是更多 传统的家庭研究。 连锁不平衡的关键方面 研究的重点是，我们正在关注最近 (i.e.,大约几百年）种族混合的历史。 众所周知，种族混合会造成配子不平衡 对于许多基因来说，可以通过与测量 连锁不平衡 这种不平衡在很大程度上是虚假的， 这是真正的物理联系的观点，但预计它会以 速率取决于重组速率。 所以，几代之后， 任何剩余的不平衡预计是由于真正的物理 联动 我们正在调查相关参数，希望 优化基因图谱的工作， 战略 初步结果表明，这一战略可能是一个强大的 作为更传统的基因定位策略的补充， 家系分离。 我们也有兴趣对此进行评估 战略作为一种方法，对定位基因，其中家庭数据是 缺乏或意义不大的基因，如与病毒、寄生虫或 环境暴露是关键的其他机会性感染 因子

Investigations involving theoretical analyses, computer simulations, and analyses of molecular data have been conducted to determine the feasibility of obtaining genetic information from certain types of data. We have shown how to estimate average heterozygosity from DNA fingerprinting data such as that obtained by our own laboratory. We are also taking a novel approach toward human genetic linkage studies, focussing on population-level linkage disequilibrium rather than on more traditional family studies. The key aspect of the linkage disequilibrium study is that we are focussing on human populations that have a recent (i.e., on the order of a few hundred years) history of racial admixture. It is well known that racial admixture will create gametic disequilibrium for many genes, measurable by exactly the same statistics used to measure linkage disequilibrium. Much of this disequilibrium will be spurious from the standpoint of true physical linkage, but it is expected to decay at a rate dictated by the recombination rate. Hence, after a few generations, any remaining disequilibrium is expected to be due to true physical linkage. We are investigating the relevant parameters in hope of optimizing gene mapping efforts that could make use of this particular strategy. Initial results indicate that this strategy could be a powerful adjunct to the more traditional strategy of mapping genes by their segregation in pedigrees. We are also interested in evaluating this strategy as an approach toward mapping genes in which family data is scarce or less meaningful, such as genes relevant to virus, parasite, or other opportunistic infections in which environmental exposure is a key factor.