ECCsplorer: a pipeline to detect extrachromosomal circular DNA (eccDNA) from next-generation sequencing data.

ECCsplorer: a pipeline to detect extrachromosomal circular DNA (eccDNA) from next-generation sequencing data.
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ECCSPLORER:从下一代测序数据中检测到检测外圆形圆形DNA(ECCDNA)的管道。

DOI:
10.1186/s12859-021-04545-2
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发表时间:
2022-01-14
期刊:
影响因子:
3
通讯作者:
Heitkam T
Heitkam T
中科院分区:
生物学4区
文献类型:
--
作者:
Mann L;Seibt KM;Weber B;Heitkam T

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染色体外环状DNA (eccdna)是一种与染色体物理分离的环状DNA结构,大小在100 bp到几兆对之间。除了携带串联重复的DNA外,eccdna还可能携带额外的基因拷贝或最近激活的转座因子。由于eccdna存在于目前所研究的所有真核生物中,并可能在压力、癌症和衰老中发挥作用,它们已成为最近研究的主要目标,但由于缺乏计算工具,它们的研究受到限制。在这里,我们介绍了ecsplorer,这是一种生物信息学管道,可以使用下一代测序技术检测任何种类的生物体或组织中的eccdna。在illumina对扩增的环状DNA (circSeq)进行测序后,ECCsplorer可以轻松、自动地发现环状DNA候选物。数据分析包括两个主要步骤:首先,对参考基因组的读取映射允许检测信息读取分布,包括高覆盖率,不一致映射和分裂读取。其次,将扩增的eccDNA的读取簇与对照样本数据进行无参考比较,发现特异性富集的DNA环。这两个软件部分可以单独运行,也可以联合运行,这取决于个人目标或数据可用性。为了说明我们方法的广泛适用性,我们分析了来自模式生物Homo sapiens和Arabidopsis thaliana的半人工和已发表的circSeq数据,并从非模式作物植物Beta vulgaris中生成了circSeq reads。我们清楚地从所有数据集中确定了候选的ecdna,无论是否有参考基因组。eccsplover管道可以特异性检测线粒体微环和反转录转座子激活,显示了eccsplover的敏感性和特异性。eccsplover(可在线访问https://github.com/crimBubble/ECCsplorer)是一种生物信息学管道,可使用下一代测序数据检测任何生物或组织中的eccdna。衍生的ecdna靶标对于广泛的下游研究具有价值-从细胞器基因组学的癌症相关eccDNA分析到活性转座元件的鉴定。在线版本包含补充材料,可在10.1186/s12859-021-04545-2获得。
Extrachromosomal circular DNAs (eccDNAs) are ring-like DNA structures physically separated from the chromosomes with 100 bp to several megabasepairs in size. Apart from carrying tandemly repeated DNA, eccDNAs may also harbor extra copies of genes or recently activated transposable elements. As eccDNAs occur in all eukaryotes investigated so far and likely play roles in stress, cancer, and aging, they have been prime targets in recent research—with their investigation limited by the scarcity of computational tools. Here, we present the ECCsplorer, a bioinformatics pipeline to detect eccDNAs in any kind of organism or tissue using next-generation sequencing techniques. Following Illumina-sequencing of amplified circular DNA (circSeq), the ECCsplorer enables an easy and automated discovery of eccDNA candidates. The data analysis encompasses two major procedures: first, read mapping to the reference genome allows the detection of informative read distributions including high coverage, discordant mapping, and split reads. Second, reference-free comparison of read clusters from amplified eccDNA against control sample data reveals specifically enriched DNA circles. Both software parts can be run separately or jointly, depending on the individual aim or data availability. To illustrate the wide applicability of our approach, we analyzed semi-artificial and published circSeq data from the model organisms Homo sapiens and Arabidopsis thaliana, and generated circSeq reads from the non-model crop plant Beta vulgaris. We clearly identified eccDNA candidates from all datasets, with and without reference genomes. The ECCsplorer pipeline specifically detected mitochondrial mini-circles and retrotransposon activation, showcasing the ECCsplorer’s sensitivity and specificity. The ECCsplorer (available online at https://github.com/crimBubble/ECCsplorer) is a bioinformatics pipeline to detect eccDNAs in any kind of organism or tissue using next-generation sequencing data. The derived eccDNA targets are valuable for a wide range of downstream investigations—from analysis of cancer-related eccDNAs over organelle genomics to identification of active transposable elements. The online version contains supplementary material available at 10.1186/s12859-021-04545-2.
DOI: 10.1007/978-1-0716-1134-0_7
发表时间: 2021-01-01
期刊: PLANT TRANSPOSABLE ELEMENTS
影响因子: --
作者:
Lanciano, Sophie;Zhang, Panpan;Mirouze, Marie
通讯作者: Mirouze, Marie
DOI: 10.1038/s41596-020-0301-0
发表时间: 2020-04-03
期刊: NATURE PROTOCOLS
影响因子: 14.8
作者:
Mehta, Devang;Cornet, Luc;Vanderschuren, Herve
通讯作者: Vanderschuren, Herve
DOI: 10.1093/nar/12.11.4747
发表时间: 1984-01-01
影响因子: 14.9
作者:
HANSEN, BM;MARCKER, KA
通讯作者: MARCKER, KA
DOI: 10.1371/journal.pgen.1006630
发表时间: 2017-02
期刊: PLoS genetics
影响因子: 4.5
作者:
Lanciano S;Carpentier MC;Llauro C;Jobet E;Robakowska-Hyzorek D;Lasserre E;Ghesquière A;Panaud O;Mirouze M
通讯作者: Mirouze M
Biopython:用于计算分子生物学和生物信息学的免费 Python 工具。
DOI: 10.1093/bioinformatics/btp163
发表时间: 2009-06-01
期刊: Bioinformatics (Oxford, England)
影响因子: --
作者:
Cock PJ;Antao T;Chang JT;Chapman BA;Cox CJ;Dalke A;Friedberg I;Hamelryck T;Kauff F;Wilczynski B;de Hoon MJ
通讯作者: de Hoon MJ