Metagenomic next⁃generation sequencing (mNGS) data reveals the phyllosphere microbiome of wheat plants infected by the fungal pathogen Zymoseptoria tritici

IF 3.3 3区 生物学 Q2 MICROBIOLOGY Phytobiomes Journal Pub Date : 2022-05-26 DOI:10.1094/pbiomes-02-22-0008-fi
Didac Barroso-Bergadà, M. Massot, Noémie Vignolles, Julie Faivre d’Arcier, É. Chancerel, E. Guichoux, A. Walker, C. Vacher, D. Bohan, V. Laval, F. Suffert
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引用次数: 2

Abstract

The fungal pathogen Zymoseptoria tritici is the causal agent of Septoria tritici blotch (STB), a major wheat disease in Western Europe. Microorganisms inhabiting wheat leaves might act as beneficial, biocontrol or facilitating agents that could limit or stimulate the development of Z. tritici. Improving our understanding of microbial communities in the wheat phyllosphere would lead to new insights into STB management. This resource announcement provides fungal and bacterial metabarcoding datasets obtained by sampling wheat leaves with and without symptoms caused by Z. tritici. Tissues were sampled from three commercial wheat varieties on three sampling dates during a cropping season. Weeds around wheat fields were sampled as well. In total, more than 450 leaf samples were collected. The pathogen Z. tritici was quantified using qPCR. We provide the raw metabarcoding datasets, the Amplicon Sequence Variant (ASV) tables obtained after bioinformatic processing, the metadata associated to each sample (sampling date, wheat variety and tissue health condition), a preliminary descriptive analysis of the data, and the code used for bioinformatic and descriptive statistical analysis.
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metagenomics next generation sequencing (mNGS)数据揭示了小麦侵染真菌酵母菌(Zymoseptoria tritici)的根层微生物组
真菌病原体小麦Zymoseptoria tritici是引起西欧小麦主要病害小麦赤霉病(STB)的病原体。小麦叶片中的微生物可能是限制或刺激小麦生长发育的有益、生物控制或促进剂。提高我们对小麦叶层微生物群落的了解将为STB管理带来新的见解。本资源公告提供了真菌和细菌代谢条形码数据集,这些数据集是通过对小麦叶片进行采样获得的,这些叶片有或没有由小麦引起的症状。在一个种植季节的三个采样日期,对三个商品小麦品种的组织进行了采样。麦田周围的杂草也进行了采样。总共收集了450多个叶片样本。用qPCR方法对小麦病原菌Z.tritici进行定量。我们提供了原始代谢编码数据集、生物信息学处理后获得的扩增子序列变异株(ASV)表、与每个样本相关的元数据(采样日期、小麦品种和组织健康状况)、数据的初步描述性分析,以及用于生物信息学和描述性统计分析的代码。
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CiteScore
7.40
自引率
6.80%
发文量
42
审稿时长
4 weeks
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