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利用 GC 分布曲线法识别水平转移基因岛和基因组分割点。

Identification of Horizontally-transferred Genomic Islands and Genome Segmentation Points by Using the GC Profile Method.

机构信息

Center for Molecular Medicine and Genetics, School of Medicine, Wayne State University, Detroit, MI, USA;

State Key Laboratory of Microbial Metabolism and School of Life Sciences & Biotechnology, Shanghai Jiaotong University, Shanghai 200030, China;

出版信息

Curr Genomics. 2014 Apr;15(2):113-21. doi: 10.2174/1389202915999140328163125.

Abstract

The nucleotide composition of genomes undergoes dramatic variations among all three kingdoms of life. GC content, an important characteristic for a genome, is related to many important functions, and therefore GC content and its distribution are routinely reported for sequenced genomes. Traditionally, GC content distribution is assessed by computing GC contents in windows that slide along the genome. Disadvantages of this routinely used window-based method include low resolution and low sensitivity. Additionally, different window sizes result in different GC content distribution patterns within the same genome. We proposed a windowless method, the GC profile, for displaying GC content variations across the genome. Compared to the window-based method, the GC profile has the following advantages: 1) higher sensitivity, because of variation-amplifying procedures; 2) higher resolution, because boundaries between domains can be determined at one single base pair; 3) uniqueness, because the GC profile is unique for a given genome and 4) the capacity to show both global and regional GC content distributions. These characteristics are useful in identifying horizontally-transferred genomic islands and homogenous GC-content domains. Here, we review the applications of the GC profile in identifying genomic islands and genome segmentation points, and in serving as a platform to integrate with other algorithms for genome analysis. A web server generating GC profiles and implementing relevant genome segmentation algorithms is available at: www.zcurve.net.

摘要

基因组的核苷酸组成在所有三个生命领域中都经历了巨大的变化。GC 含量是基因组的一个重要特征,与许多重要功能有关,因此已对测序基因组的 GC 含量及其分布进行了常规报告。传统上,通过在基因组上滑动的窗口来计算 GC 含量来评估 GC 含量分布。这种常用的基于窗口的方法的缺点包括分辨率低和灵敏度低。此外,不同的窗口大小会导致同一基因组内的 GC 含量分布模式不同。我们提出了一种无窗口方法,即 GC 分布曲线,用于显示基因组中 GC 含量的变化。与基于窗口的方法相比,GC 分布曲线具有以下优点:1)更高的灵敏度,因为具有变异放大程序;2)更高的分辨率,因为域之间的边界可以在一个碱基对处确定;3)独特性,因为给定基因组的 GC 分布曲线是唯一的;4)显示全局和局部 GC 含量分布的能力。这些特性可用于识别水平转移的基因组岛和同质性 GC 含量域。在这里,我们综述了 GC 分布曲线在识别基因组岛和基因组分割点中的应用,并作为与用于基因组分析的其他算法集成的平台。可生成 GC 分布曲线并实现相关基因组分割算法的 Web 服务器可在:www.zcurve.net 获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/619d/4009839/67a80ab80f15/CG-15-113_F1.jpg

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