SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes.
SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes.
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DOI：
10.1371/journal.pcbi.1008439
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发表时间：
2020-12
影响因子：
4.3
通讯作者：
Salzberg SL
中科院分区：
文献类型：
--
作者：
Lu J;Salzberg SL
GC偏态是在许多细菌基因组中观察到的一种现象，其中同一染色体的两条复制链包含不同比例的鸟嘌呤和胞嘧啶核苷酸。在这里，我们证明了这种在20世纪90年代中期首次发现的现象，今天可以作为NCBI的Refseq文库中15,000多个完整细菌基因组的分析工具。为了分析所有15,000多个基因组，我们引入了一种新方法SkewIT (SkewIT)，它计算一个表示基因组GC倾斜程度的单一度量。利用这一指标，我们证明了GC偏态模式在某些细菌门（如厚壁菌门）中是如何保守的，但在其他系统发育类群（如放线菌门）中却表现出不同的模式。我们还发现SkewIT的异常值突出了潜在的细菌错误组装。使用我们新定义的度量，我们在先前发表的完整细菌基因组中鉴定了多个错误组装的染色体序列。我们提供了一个SkewIT网络应用https://jenniferlu717.shinyapps.io/SkewIT/，可以计算任何用户提供的细菌序列的SkewI。web app还为本文生成的数据提供了一个交互界面，允许用户进一步研究Refseq-97细菌全基因组的SkewI值和阈值。细菌基因组分析的单个脚本在以下存储库中提供：https://github.com/jenniferlu717/SkewIT。尽管在双链DNA分子中，每个鸟嘌呤(G)都与一个胞嘧啶(C)配对，但当我们只关注复制方向上的单链（称为前导链）时，细菌基因组中的G比C多。这种现象被称为GC歪斜，它是如此普遍，以至于它已经被可靠地用于识别数千种细菌的复制起源（DNA开始自我复制过程的位置）。在这里，我们描述了一种新方法，该方法通过找到复制的起点和终点来自动捕获基因组的“偏度”，然后将偏度报告为单个数字。我们计算了超过15,000个基因组的这个值，发现大多数系统发育组都有一个特征的偏度。我们还观察到，偏度值异常低有时表明基因组组装不正确。为了帮助其他人进行这种类型的分析，我们开发了一个图形工具来计算和显示任何感兴趣的基因组的GC-skew。
GC skew is a phenomenon observed in many bacterial genomes, wherein the two replication strands of the same chromosome contain different proportions of guanine and cytosine nucleotides. Here we demonstrate that this phenomenon, which was first discovered in the mid-1990s, can be used today as an analysis tool for the 15,000+ complete bacterial genomes in NCBI’s Refseq library. In order to analyze all 15,000+ genomes, we introduce a new method, SkewIT (Skew Index Test), that calculates a single metric representing the degree of GC skew for a genome. Using this metric, we demonstrate how GC skew patterns are conserved within certain bacterial phyla, e.g. Firmicutes, but show different patterns in other phylogenetic groups such as Actinobacteria. We also discovered that outlier values of SkewIT highlight potential bacterial mis-assemblies. Using our newly defined metric, we identify multiple mis-assembled chromosomal sequences in previously published complete bacterial genomes. We provide a SkewIT web app https://jenniferlu717.shinyapps.io/SkewIT/ that calculates SkewI for any user-provided bacterial sequence. The web app also provides an interactive interface for the data generated in this paper, allowing users to further investigate the SkewI values and thresholds of the Refseq-97 complete bacterial genomes. Individual scripts for analysis of bacterial genomes are provided in the following repository: https://github.com/jenniferlu717/SkewIT. Even though every guanine (G) is paired with a cytosine (C) in double-stranded DNA molecules, bacterial genomes have more G’s than C’s when we focus only on a single strand in the direction of replication, called the leading strand. This phenomenon, called GC skew, is so ubiquitous that it has been used reliably to identify the replication origin (the location from which DNA begins the process of replicating itself) in thousands of bacteria. Here we describe a new method that automatically captures the “skewness” of a genome by finding the origin and terminus of replication, and then reporting skewness as a single number. We calculated this value for over 15,000 genomes, and found that most phylogenetic groups have a characteristic amount of skewness. We also observed that an unusually low value for skewness sometimes indicated that the genome was incorrectly assembled. To assist others in this type of analysis, we developed a graphical tool to compute and display GC-skew for any genome of interest.
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影响因子：
48
作者：
Langmead, Ben;Salzberg, Steven L.
通讯作者：
Salzberg, Steven L.
影响因子：
3.6
作者：
Picardeau, M;Lobry, JR;Hinnebusch, BJ
通讯作者：
Hinnebusch, BJ
DOI：
10.1073/pnas.59.2.598
发表时间：
1968-01-01
影响因子：
11.1
作者：
OKAZAKI, R;OKAZAKI, T;SUGINO, A
通讯作者：
SUGINO, A
影响因子：
3.5
作者：
Frank, AC;Lobry, JR
通讯作者：
Lobry, JR
影响因子：
7
作者：
Breitwieser, Florian P.;Pertea, Mihaela;Salzberg, Steven L.
通讯作者：
Salzberg, Steven L.