Informatics of Lyme Disease Biogeography (pilot)

描述(申请人提供)：生物信息学是一种现代信息技术，用于 生物数据的计算机化仓储、可视化和分析。这项技术是为了应对生物信息的爆炸性增长而出现的，这些信息的形式包括全基因组序列、全基因组表达模式和高通量蛋白质结构表征。生物信息的一种形式，即生物系统的多物种相互作用，具有更高的复杂性，自然需要生物信息学解决方案。然而，与基因组学和蛋白质组学计算系统的激增相比，物种相互作用的生物信息学系统的发展还处于初级阶段。莱姆病是美国最流行的病媒传播疾病，是研究病原体(伯氏疏螺旋体)、病媒(硬蜱)和宿主(脊椎动物)之间相互作用的模式系统。在本应用程序中，我们建议开发 莱姆病多物种生物地理变异研究数据库系统 传染系统。该数据库将存储多个疏螺旋体基因组、疏螺旋体和硬蜱的多基因座序列变异，以及与基因组和序列信息相关的生物地理和生态信息。基因组、序列变异和生物地理信息将从公共数据库和已发表的研究中收集。将开发进化分析工具，如系统发生重建和序列变异的中性进化测试，并将其与数据库系统结合。此外，我们还将实施和管理数据库系统的网络接口。拟议的试点项目有两个具体目标。首先，我们将开发一个概念验证的莱姆病生物地理学数据库，包括疏螺旋体基因组信息、疏螺旋体和壁虱多位点遗传变异以及疏螺旋体-壁虱-宿主关联的生态数据。其次，我们将通过检验两个进化假说来验证数据库系统的实用性，一个是关于疏螺旋体和壁虱的共同进化史的，另一个是关于疏螺旋体在地理位置之间的适应性差异的。该项目将为建立生物信息学系统铺平道路 媒介传播感染系统生物地理模式的自动分析和可视化。

DESCRIPTION (provided by applicant): Bioinformatics is a modern information technology for computerized warehousing, visualization and analysis of biological data. The technology emerged in response to the explosive growth of biological information, in forms such as whole-genome sequences, whole-genome expression patterns and high-throughput structure characterization of proteins. One form of biological information, namely the multi-species interactions of a biological system, is of a higher-level complexity that naturally requires bioinformatics solutions. Development of bioinformatics systems of species interactions, however, is in its infancy compared with the proliferation of computing systems for genomics and proteomics. Lyme disease, the most prevalent vector-borne disease in the United States, is a model system for the study of species interactions between a pathogen (Borrelia burgdorferi), its vector (Ixodes ticks) and hosts (vertebrates). In this application, we propose to develop a database system for the study of biogeographic variations of Lyme disease as a multi-species infectious system. The database will host multiple Borrelia genomes, multi-locus sequence variations of Borrelia and Ixodes, as well as biogeographic and ecological information associated with the genome and sequence information. Genomes, sequence variations and biogeographic information will be collected from public databases and published studies. Tools for evolutionary analyses, such as phylogenetic reconstruction and tests of neutral evolution of sequence variations, will be developed and integrated with the database system. In addition, we will implement and curate a web interface to the database system. There are two specific aims for the proposed pilot project. First, we will develop a proof-of-concept database of Lyme disease biogeography, complete with Borrelia genome information, Borrelia and tick multi-locus genetic variations and ecological data on Borrelia-Tick-Host associations. Secondly, we will validate the utility of the database system by testing two evolutionary hypotheses, one on the co-evolutionary history of Borrelia and ticks, and the other on the Borrelia adaptive divergence between geographic localities. The project will pave the way for a bioinformatics system for automated analyses and visualization of biogeographic patterns of vector-borne infectious systems.