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NOVOPlasty: de novo assembly of organelle genomes from whole genome data

机译:NOVOPlasty:从整个基因组数据中重新组装细胞器基因组

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摘要

The evolution in next-generation sequencing (NGS) technology has led to the development of many different assembly algorithms, but few of them focus on assembling the organelle genomes. These genomes are used in phylogenetic studies, food identification and are the most deposited eukaryotic genomes in GenBank. Producing organelle genome assembly from whole genome sequencing (WGS) data would be the most accurate and least laborious approach, but a tool specifically designed for this task is lacking. We developed a seed-and-extend algorithm that assembles organelle genomes from whole genome sequencing (WGS) data, starting from a related or distant single seed sequence. The algorithm has been tested on several new (Gonioctena intermedia and Avicennia marina) and public (Arabidopsis thaliana and Oryza sativa) whole genome Illumina data sets where it outperforms known assemblers in assembly accuracy and coverage. In our benchmark, NOVOPlasty assembled all tested circular genomes in less than 30 min with a maximum memory requirement of 16 GB and an accuracy over 99.99%. In conclusion, NOVOPlasty is the sole de novo assembler that provides a fast and straightforward extraction of the extranuclear genomes from WGS data in one circular high quality contig. The software is open source and can be downloaded at .
机译:下一代测序(NGS)技术的发展已导致开发了许多不同的组装算法,但其中很少有人专注于组装细胞器基因组。这些基因组被用于系统发育研究,食品鉴定中,并且是GenBank中沉积最多的真核生物基因组。从全基因组测序(WGS)数据产生细胞器基因组组装将是最准确,最省力的方法,但是缺少专门为此任务设计的工具。我们开发了一种种子扩展算法,该算法从相关或遥远的单个种子序列开始,根据全基因组测序(WGS)数据组装细胞器基因组。该算法已经在几个新的(Gonioctena intermedia和Avicennia marina)和公共的(Arabidopsis thaliana和Oryza sativa)全基因组Illumina数据集上进行了测试,在组装准确性和覆盖范围方面,该算法均优于已知的汇编程序。在我们的基准测试中,NOVOPlasty在不到30分钟的时间内组装了所有测试的环状基因组,最大内存需求为16 GB,准确度超过99.99%。总之,NOVOPlasty是唯一的从头组装程序,可在一轮高质量重叠群中从WGS数据中快速,直接地提取核外基因组。该软件是开源的,可以从下载。

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