Equipment for Automated Acquisition of DNA Sequence and DNA Fragment Size Data

NSF提案0140522 -“DNA序列和DNA片段大小数据自动采集设备“摘要已授予大卫E.麦考利在范德比尔特大学，以支持购买自动DNA测序仪，DNA提取系统，并支持计算机硬件。BaseStation从平板凝胶中收集DNA序列数据，并以序列分析软件可以解释的形式存储。该机器还可以收集和处理其他类型的DNA片段大小数据，如微卫星DNA遗传标记。在DNA测序和微卫星分析的情况下，聚合酶链反应（PCR）的产物用荧光染料标记，并在电泳过程中按大小分离。基站的优势在于其96个井的容量和自动加载允许高吞吐量，其配置使其同样适合收集序列和微卫星数据。相关的DNA提取系统将允许从大量样品中快速提取基因组DNA。这些机器收集的数据将被五个私人侦探使用。s（D. McCauley，J. Burke，D.芬克角，澳-地约翰逊和N.O. Pellmyr）在进化和种群生物学的各种研究中，这些研究依赖于大量的DNA序列和/或微卫星数据。将利用设备产生的数据的一些具体研究项目包括以下内容。1)本研究旨在利用DNA序列信息和多态性微卫星标记来研究北美入侵植物--蝇子草的群体遗传学。通过比较北美和欧洲本土的遗传特征，可以确定入侵的机制或途径。2)几种丝兰植物及其传粉蛾类的比较分子系统学研究。这种系统发育研究将有助于记录高度共同进化的植物传粉系统的发展。3)一项利用多态性微卫星位点的研究，这将有助于绘制与向日葵野生亲缘植物驯化相关的基因。4)一个基于DNA序列的研究适应性辐射和寄主植物的变化，在Neochlamisus bebbiumetheet复合体。5)在蓝细菌模型实验室种群中分子标记频率变化后生物钟基因适应意义的研究。所有这些研究将有助于理解基本的生物过程，如范围扩张，共同进化，宿主植物的变化和生物钟的进化。然而，来自这些研究的知识也将有助于解决更多的应用问题，例如如何控制入侵物种，昆虫如何将食物从本地植物物种转移到具有经济价值的植物，如何使驯化物种的遗传操作更有效，或者我们如何克服与生物节律紊乱相关的健康问题。最后，所有研究的结果将有助于新兴的生物信息学领域，因为每项研究都需要P.I.改进收集、存储和分析大量遗传信息的方法。

Abstract for NSF Proposal 0140522 - "Equipment for Automated Acquisition of DNA Sequence and DNA Fragment Size Data"A grant has been awarded to Dr. David E. McCauley at Vanderbilt University to support the purchase of an automated DNA sequencer, a DNA extraction system, and supporting computer hardware. The BaseStation gathers DNA sequence data from slab gels and stores it in a form that can be interpreted by sequence analysis software. The machine can also gather and process other types of DNA fragment size data such as microsatellite DNA genetic markers. In the case of both DNA sequence and microsatellite analysis, products of polymerase chain reaction (PCR) are labeled with a florescent dye and separated by size during electrophoresis. The advantage of the BaseStation is that its 96 well capacity and automated loading allows for high throughput, and its configuration makes it equally suited for gathering sequence and microsatellite data. The associated DNA extraction system will allow for rapid extraction of genomic DNA from a large number of samples. The data gathered by these machines will be used by five P.I.'s (D. McCauley, J. Burke, D. Funk, C. Johnson and N.O. Pellmyr) in a variety of studies in evolutionary and population biology which rely on large quantities of DNA sequence and/or microsatellite data. Some of the specific research projects that will make use of data generated by the equipment include the following. 1) A study designed to use both DNA sequence information and polymorphic microsatellite markers to investigate the population genetics of Silene vulgaris, a plant invasive in North America. Comparison of the genetic characteristics of the plant in North America and in its native Europe should indicate the mechanism or route of invasion. 2) A comparative molecular systematics study of several species of yucca plants and of the moths that pollinate them. This phylogenetic study will help document how highly coevolved plant-pollinator systems develop. 3) A study using polymorphic microsatellite loci that will help to map genes associated with the domestication of sunflowers from their wild relatives. 4) A DNA sequence based study of adaptive radiation and host plant shifts in the Neochlamisus bebbianae beetle complex. 5) A study of the adaptive significance of biological clock genes that follows changes in the frequency of molecular markers in model laboratory populations of cyanobacteria. All of these studies will contribute to understanding basic biological processes such as range expansions, coevolution, host plant shifts and the evolution of the biological clock. However, knowledge coming from these studies will also contribute to the solution of more applied problems such as how invasive species might be controlled, how insects shift feeding from native plant species to plants of economic value, how the genetic manipulation of domesticated species might be made more efficient, or how we might overcome health problems associated with biological rhythm disorders. Finally, the results of all of the studies will contribute to the emerging field of bioinformatics, in that each study will require the P.I. to refine methods of gathering, storing, and analyzing a large volume of genetic information.