暗物质研究者(Dark mAtteR iNvestigator, dam)工具:了解COI扩增子数据中已知的未知

Haris Zafeiropoulos, L. Gargan, Sanni Hintikka, C. Pavloudi, J. Carlsson
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引用次数: 8

摘要

线粒体细胞色素C氧化酶亚基I基因(COI)常用于环境DNA (eDNA)元条形码研究,特别是用于评估后生物多样性。然而,从这些研究中检索到的大量COI操作分类单位(OTUs)或扩增子序列变体(asv)没有得到参考序列的分类分配。为了评估和调查这些序列,我们开发了暗物质调查员(Dark mAtteR iNvestigator,简称dam)软件工具。为此,从1593个共识序列中构建了一个参考的以coi为导向的系统发育树,涵盖了生命的所有三个领域。在真核生物方面,从Midori reference 2数据库中检索到的183330个序列构建了家族水平的一致序列,占初始参考序列数量的70%。同样,从BOLD和PFam数据库中检索了431个细菌和15个古细菌分类群(分别占初始参考序列数的29%和1%)的科级序列。利用这个系统发育树来研究COI预处理的扩增子样本序列,以提供它们的系统发育分配的表格和图形概述。为了评估adaptive,我们使用不同引物对来自不同水生环境的环境和散装元条形码样本进行了分析。我们证明了大部分非目标原核生物,如细菌和古细菌,也在eDNA样本中被扩增,我们建议将原核生物的COI序列纳入用于分类分配的参考数据库,以便进一步分析暗物质。在GitHub上可以找到源码https://github.com/hariszaf/darn,在https://hub.docker.com/r/hariszaf/darn可以找到Docker镜像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Dark mAtteR iNvestigator (DARN) tool: getting to know the known unknowns in COI amplicon data
The mitochondrial cytochrome C oxidase subunit I gene (COI) is commonly used in environmental DNA (eDNA) metabarcoding studies, especially for assessing metazoan diversity. Yet, a great number of COI operational taxonomic units (OTUs) or/and amplicon sequence variants (ASVs) retrieved from such studies do not get a taxonomic assignment with a reference sequence. To assess and investigate such sequences, we have developed the Dark mAtteR iNvestigator (DARN) software tool. For this purpose, a reference COI-oriented phylogenetic tree was built from 1,593 consensus sequences covering all the three domains of life. With respect to eukaryotes, consensus sequences at the family level were constructed from 183,330 sequences retrieved from the Midori reference 2 database, which represented 70% of the initial number of reference sequences. Similarly, sequences from 431 bacterial and 15 archaeal taxa at the family level (29% and 1% of the initial number of reference sequences respectively) were retrieved from the BOLD and the PFam databases. DARN makes use of this phylogenetic tree to investigate COI pre-processed sequences of amplicon samples to provide both a tabular and a graphical overview of their phylogenetic assignments. To evaluate DARN, both environmental and bulk metabarcoding samples from different aquatic environments using various primer sets were analysed. We demonstrate that a large proportion of non-target prokaryotic organisms, such as bacteria and archaea, are also amplified in eDNA samples and we suggest prokaryotic COI sequences to be included in the reference databases used for the taxonomy assignment to allow for further analyses of dark matter. DARN source code is available on GitHub at https://github.com/hariszaf/darn and as a Docker image at https://hub.docker.com/r/hariszaf/darn.
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来源期刊
Metabarcoding and Metagenomics
Metabarcoding and Metagenomics Agricultural and Biological Sciences-Animal Science and Zoology
CiteScore
5.40
自引率
0.00%
发文量
25
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