KSGP 3.1:使用LotuS2、基因组分类数据库和RNAseq数据对古菌群落进行改进的分类标注。

IF 5.1 Q1 ECOLOGY
ISME communications Pub Date : 2025-06-03 eCollection Date: 2025-01-01 DOI:10.1093/ismeco/ycaf094
Alastair Grant, Abdullah Aleidan, Charli S Davies, Solomon C Udochi, Joachim Fritscher, Mohammad Bahram, Falk Hildebrand
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引用次数: 0

摘要

分类标注是古细菌元条形码研究的一个重大挑战。可用的参考序列数量有限;系统发育多样性的很大一部分没有得到充分的描述;广泛使用的数据库不能反映当前的古细菌分类,并且包含错误标记的序列。我们以基因组分类数据库(GTDB)为基础,结合真核生物PR2和MIDORI线粒体数据库,采用系统和易于处理的方法来解决这些差距。在去除不一致、嵌合和重复的SSU序列后,与SILVA相比,该组合(GTDB+)在一组河口古细菌操作分类单元(OTUs)的注释上有了微小的改进。我们在SILVA中添加了近全长rRNA序列和原核生物SSU序列,创建了一个新的参考数据库KSGP (K arst, S ilva, G TDB和PR2)。使用三种不同的方法对附加序列进行(重新)注释。最保守的方法,使用最低的共同祖先,提供了进一步的小改进。使用SINTAX的注释比SILVA增加了2.7倍和4.2倍的Class和Order赋值,尽管这可能包括一些未命名和命名分支的“集中”。基于相似性的聚类可以进一步将数据库序列划分为所有分类水平的推定分类群,分别将60%和41%的古生菌OTUs划分为推定科和属水平的分类群。未经清洗的GTDB和GreenGenes2都表现不佳,不推荐用于古细菌。我们在KSGP .earlham.ac.uk提供GTDB+和KSGP数据库;将它们集成到元条形码管道LotuS2中,并概述它们用于注释古细菌otu和元转录组数据的用途。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
KSGP 3.1: improved taxonomic annotation of Archaea communities using LotuS2, the genome taxonomy database and RNAseq data.

Taxonomic annotation is a substantial challenge for Archaea metabarcoding. A limited number of reference sequences are available; a substantial fraction of phylogenetic diversity is not fully characterized; widely used databases do not reflect current archaeal taxonomy and contain mislabelled sequences. We address these gaps with a systematic and tractable approach based around the Genome Taxonomy Database (GTDB) combined with the eukaryote PR2 and MIDORI mitochondrial databases. After removing incongruent, chimeric and duplicate SSU sequences, this combination (GTDB+) provides a small improvement in annotation of a set of estuarine Archaea Operational Taxonomic Units (OTUs) compared to SILVA. We add to this a collection of near full length rRNA sequences and the prokaryote SSU sequences in SILVA, creating a new reference database, KSGP ( K arst, S ilva, G TDB, and PR2). The additional sequences are (re-)annotated using three different approaches. The most conservative, using lowest common ancestor, gives a further small improvement. Annotation using SINTAX increases Class and Order assignments by 2.7 and 4.2 times over SILVA, although this may include some "lumping" of un-named and named clades. Still further improvement can be made using similarity based clustering to group database sequences into putative taxa at all taxonomic levels, assigning 60% and 41% of Archaea OTUs to putative family and genus level taxa respectively. GTDB without cleaning and GreenGenes2 both perform poorly and cannot be recommended for use with Archaea. We make the GTDB+ and KSGP databases available at ksgp.earlham.ac.uk; integrate them into a metabarcoding pipeline, LotuS2 and outline their use to annotate Archaea OTUs and metatranscriptomic data.

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