从植物基因组副捕获物中评估真菌多样性的蛇形管道。

IF 5.5 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Nicholas W. Bard, T. Jonathan Davies, Quentin C. B. Cronk
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引用次数: 0

摘要

相对而言,人们对植物真菌病原体和内生菌的寄主关联和相容性知之甚少。公开可用的植物基因组DNA可以用于检测偶然的真菌DNA,但由于不同基因组区域和分类群之间的短长度和不同的判别能力,分类分配可能具有挑战性。在这里,我们介绍了一个计算轻量级且易于访问的Snakemake管道,用于快速检测和分类(鉴定和分类等级分配)病原真菌和内生真菌(以及与植物相关的其他真菌),其目标是内部转录间隔区(ITS),这是真菌条形码标准。我们包括最大化查询序列长度的方法,通过扩展到ITS区域的其他片段并提供分类单元特定的局部截止点和置信度分数,为ITS1和ITS2分类分类提供更高的支持。我们通过使用6种不同植物的公开基因组序列数据的案例研究来展示我们的管道,其中包括桦树中的4种,桦树是一种生态和经济上重要的阔叶林树种,灌木和草。我们的管道在几分钟到几小时内对每个寄主个体进行真菌分类,鉴定出204种不同的真菌属,置信度高(≥70%)。我们的管道检测和分类已知与桦木相关的病原和内生属,以及许多其他没有关联记录的属。我们的产品线,利用现有的序列数据,有几个潜在的应用,包括检测隐匿真菌病原体和帮助表征内生真菌微生物组,生物勘探商业上有用的真菌物种,以及确定真菌的植物宿主范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Teknonaturalist: A Snakemake Pipeline for Assessing Fungal Diversity From Plant Genome Bycatch

Teknonaturalist: A Snakemake Pipeline for Assessing Fungal Diversity From Plant Genome Bycatch

Relatively little is known of the host associations and compatibility of fungal plant pathogens and endophytes. Publicly available plant genomic DNA can be mined to detect incidental fungal DNA, but taxonomic assignment can be challenging due to short lengths and variable discriminative power among different genomic regions and taxa. Here, we introduce a computationally lightweight and accessible Snakemake pipeline for rapid detection and classification (identification and assignment to taxonomic rank) of pathogenic and endophytic fungi (and other fungi associated with plants) that targets the internal transcribed spacer (ITS) region, a fungal barcode standard. We include methods for maximising query sequence length, which gives higher support for ITS1 and ITS2 taxonomic classifications by extending to other fragments of the ITS region and providing taxon-specific local cut-off and confidence scores. We demonstrate our pipeline with a case study using public genomic sequence data for six diverse plant species, including four species within Betula, an ecologically and economically important broadleaved forest tree genus, a shrub and a grass. Our pipeline classified fungi within minutes to a few hours per host individual, with 204 different fungal genera identified at high confidence (≥ 70%). Our pipeline detected and classified pathogenic and endophytic genera known to associate with Betula, and many others with no prior record of association. Our pipeline, leveraging existing sequence data, has several potential applications, including detecting cryptic fungal pathogens and helping characterise the endophytic fungal microbiome, bioprospecting commercially useful fungal species, and determining the plant host range of fungi.

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来源期刊
Molecular Ecology Resources
Molecular Ecology Resources 生物-进化生物学
CiteScore
15.60
自引率
5.20%
发文量
170
审稿时长
3 months
期刊介绍: Molecular Ecology Resources promotes the creation of comprehensive resources for the scientific community, encompassing computer programs, statistical and molecular advancements, and a diverse array of molecular tools. Serving as a conduit for disseminating these resources, the journal targets a broad audience of researchers in the fields of evolution, ecology, and conservation. Articles in Molecular Ecology Resources are crafted to support investigations tackling significant questions within these disciplines. In addition to original resource articles, Molecular Ecology Resources features Reviews, Opinions, and Comments relevant to the field. The journal also periodically releases Special Issues focusing on resource development within specific areas.
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