Bioinformatics matters: The accuracy of plant and soil fungal community data is highly dependent on the metabarcoding pipeline
Bioinformatics matters: The accuracy of plant and soil fungal community data is highly dependent on the metabarcoding pipeline
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DOI：
10.1016/j.funeco.2019.03.005
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发表时间：
2019-10-01
期刊：
影响因子：
2.9
通讯作者：
Vacher, Corinne
中科院分区：
文献类型：
--
作者：
Pauvert, Charlie;Buee, Marc;Vacher, Corinne
与植物和土壤相关的真菌群落会影响植物的适应性和生态系统的功能。它们经常被以核糖体内转录间隔区(ITS)为靶标的元编码方法进行研究，但对于分析这些数据的最合适的生物信息学方法还没有达成共识。为了比较360软件和参数组合的性能，我们对一个由189个菌株组成的人工真菌群落进行了测序，覆盖了子囊菌门和担子菌门的广泛范围。最敏感的方法，基于USEARCH和VSearch聚类算法，检测到几乎所有的真菌菌株，但大大高估了菌株的总数。相比之下，使用DADA2检测扩增子序列变异的方法在恢复真菌群落的丰富度和组成方面是最有效的。我们的结果表明，分析含有DADA2的单正向(R1)序列，除了去除低质量和嵌合序列外，不使用任何过滤器，是描述真菌群落特征的一个很好的选择。(C)2019年爱思唯尔有限公司和英国真菌学会。版权所有。
Fungal communities associated with plants and soil influence plant fitness and ecosystem functioning. They are frequently studied by metabarcoding approaches targeting the ribosomal internal transcribed spacer (ITS), but there is no consensus concerning the most appropriate bioinformatic approach for the analysis of these data. We sequenced an artificial fungal community composed of 189 strains covering a wide range of Ascomycota and Basidiomycota, to compare the performance of 360 software and parameter combinations. The most sensitive approaches, based on the USEARCH and VSEARCH clustering algorithms, detected almost all fungal strains but greatly overestimated the total number of strains. By contrast, approaches using DADA2 to detect amplicon sequence variants were the most effective for recovering the richness and composition of the fungal community. Our results suggest that analyzing single forward (R1) sequences with DADA2 and no filter other than the removal of low-quality and chimeric sequences is a good option for fungal community characterization. (C) 2019 Elsevier Ltd and British Mycological Society. All rights reserved.