Distance, Consensus, and Query Algorithms for Recombinant Genealogies

由于DNA的重组，遗传给后代的基因将是来自两个祖父母的DNA的独特组合。因为一个有机体？当DNA或基因组被组织成染色体时，重组的结果是染色体的不同部分可以有不同的历史。一些计算机程序声称能够重建DNA组织的这些错综复杂的历史，但这些说法并没有得到很好的验证。这个项目将开发一种数学方法来衡量染色体历史重建之间的相似性，这样研究人员就可以测试现有的重建算法是否真的有效。它还将开发软件来评估和显示多次重建中一致或不一致的领域。这些软件工具将被整合到基于计算机的实验室练习中，以提高本科和研究生生物学学生对基因组结构的理解。这项工作旨在改进用于基因定位的计算工具，这对于理解生物体编码的特征很重要。包括疾病遗传，以及改善农业动植物品种。这些工具将有助于推断密切相关的生物体之间的关系和进化模式，包括作物物种、病原体和害虫。最后，这项研究将有助于识别随着时间的推移而增加或减少的遗传性状，例如与驯化或抗病有关的性状。教育材料将帮助学生准备在进化生物学，人口遗传学和保护科学的工作。

Due to recombination of DNA, the genes passed to an offspring will be a unique combination of DNA from the two grandparents. Because an organism?s DNA, or genome, is organized into chromosomes, a result of recombination is that different parts of a chromosome can have different histories going back in time. Several computer programs claim to be able to reconstruct these tangled histories of the organization of DNA, but these claims are not well validated. This project will develop a mathematical measure of similarity between reconstructions of a chromosome's history, so that researchers can test whether existing reconstruction algorithms actually work. It will also develop software to assess and display areas of agreement or disagreement among multiple reconstructions. These software tools will be incorporated into computer-based lab exercises to improve understanding of genome structure among undergraduate and graduate college biology students.This work aims to improve computational tools used in gene mapping, important in understanding traits encoded in an organism?s DNA including disease inheritance, and improving agricultural breeds of plants and animals. The tools will contribute to inferring relationships and patterns of evolution among closely related organisms, including crop species, pathogens and pests. Finally, this research will contribute to identification of genetic traits that have increased or decreased over time, such as traits involved in domestication or disease resistance. The educational materials will help prepare students to work in evolutionary biology, population genetics, and conservation science.