Blom Jochen, Albaum Stefan P, Doppmeier Daniel, Pühler Alfred, Vorhölter Frank-Jörg, Zakrzewski Martha, Goesmann Alexander
Computational Genomics, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany.
BMC Bioinformatics. 2009 May 20;10:154. doi: 10.1186/1471-2105-10-154.
The introduction of next generation sequencing approaches has caused a rapid increase in the number of completely sequenced genomes. As one result of this development, it is now feasible to analyze large groups of related genomes in a comparative approach. A main task in comparative genomics is the identification of orthologous genes in different genomes and the classification of genes as core genes or singletons.
To support these studies EDGAR - "Efficient Database framework for comparative Genome Analyses using BLAST score Ratios" - was developed. EDGAR is designed to automatically perform genome comparisons in a high throughput approach. Comparative analyses for 582 genomes across 75 genus groups taken from the NCBI genomes database were conducted with the software and the results were integrated into an underlying database. To demonstrate a specific application case, we analyzed ten genomes of the bacterial genus Xanthomonas, for which phylogenetic studies were awkward due to divergent taxonomic systems. The resultant phylogeny EDGAR provided was consistent with outcomes from traditional approaches performed recently and moreover, it was possible to root each strain with unprecedented accuracy.
EDGAR provides novel analysis features and significantly simplifies the comparative analysis of related genomes. The software supports a quick survey of evolutionary relationships and simplifies the process of obtaining new biological insights into the differential gene content of kindred genomes. Visualization features, like synteny plots or Venn diagrams, are offered to the scientific community through a web-based and therefore platform independent user interface http://edgar.cebitec.uni-bielefeld.de, where the precomputed data sets can be browsed.
新一代测序方法的引入使得完全测序基因组的数量迅速增加。这一发展的结果之一是，现在以比较的方法分析大量相关基因组变得可行。比较基因组学的一项主要任务是在不同基因组中识别直系同源基因，并将基因分类为核心基因或单拷贝基因。
为支持这些研究，开发了EDGAR（“使用BLAST评分比率进行比较基因组分析的高效数据库框架”）。EDGAR旨在以高通量方式自动进行基因组比较。使用该软件对来自NCBI基因组数据库的75个属组中的582个基因组进行了比较分析，并将结果整合到一个基础数据库中。为了展示一个具体的应用案例，我们分析了黄单胞菌属的十个基因组，由于分类系统不同，对其进行系统发育研究比较困难。EDGAR提供的系统发育结果与最近采用传统方法得到的结果一致，而且能够以前所未有的准确性确定每个菌株的根。
EDGAR提供了新颖的分析功能，并显著简化了相关基因组的比较分析。该软件支持快速审视进化关系，并简化了获取关于亲属基因组差异基因含量的新生物学见解的过程。通过基于网络且因此与平台无关的用户界面http://edgar.cebitec.uni-bielefeld.de向科学界提供了诸如共线性图或维恩图等可视化功能，在该界面可以浏览预先计算的数据集。
