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转座子:一种从未组装序列读取中注释转座元件家族的工具包。

Transposome: a toolkit for annotation of transposable element families from unassembled sequence reads.

机构信息

Department of Genetics and Department of Plant Biology, University of Georgia, Athens, GA 30602, USA.

出版信息

Bioinformatics. 2015 Jun 1;31(11):1827-9. doi: 10.1093/bioinformatics/btv059. Epub 2015 Feb 1.

Abstract

MOTIVATION

Transposable elements (TEs) can be found in virtually all eukaryotic genomes and have the potential to produce evolutionary novelty. Despite the broad taxonomic distribution of TEs, the evolutionary history of these sequences is largely unknown for many taxa due to a lack of genomic resources and identification methods. Given that most TE annotation methods are designed to work on genome assemblies, we sought to develop a method to provide a fine-grained classification of TEs from DNA sequence reads. Here, we present a toolkit for the efficient annotation of TE families from low-coverage whole-genome shotgun (WGS) data, enabling the rapid identification of TEs in a large number of taxa. We compared our software, Transposome, with other approaches for annotating repeats from WGS data, and we show that it offers significant improvements in run time and produces more precise estimates of genomic repeat abundance. Transposome may also be used as a general toolkit for working with Next Generation Sequencing (NGS) data, and for constructing custom genome analysis pipelines.

AVAILABILITY AND IMPLEMENTATION

The source code for Transposome is freely available (http://sestaton.github.io/Transposome), implemented in Perl and is supported on Linux.

摘要

动机

转座元件 (TEs) 几乎存在于所有真核生物基因组中,具有产生进化新颖性的潜力。尽管 TEs 在广泛的分类群中分布,但由于缺乏基因组资源和鉴定方法,这些序列的进化历史在许多分类群中还很大程度上未知。鉴于大多数 TE 注释方法都是针对基因组组装设计的,我们试图开发一种从 DNA 序列读取中提供 TE 家族精细分类的方法。在这里,我们提出了一个工具包,用于从低覆盖率全基因组鸟枪法 (WGS) 数据中高效注释 TE 家族,使能够快速识别大量分类群中的 TE。我们将我们的软件 Transposome 与其他用于注释 WGS 数据中重复序列的方法进行了比较,结果表明它在运行时间方面有显著的改进,并能更准确地估计基因组重复序列的丰度。Transposome 也可用于处理下一代测序 (NGS) 数据的通用工具包,以及构建自定义基因组分析管道。

可用性和实现

Transposome 的源代码是免费提供的 (http://sestaton.github.io/Transposome),用 Perl 实现,支持 Linux。

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