Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Box 7026, SE-750 07, Uppsala, Sweden.
Department of Biological and Environmental Sciences, University of Gothenburg, Box 461, SE-405 30, Gothenburg, Sweden.
New Phytol. 2013 Jul;199(1):288-299. doi: 10.1111/nph.12243. Epub 2013 Mar 28.
Novel high-throughput sequencing methods outperform earlier approaches in terms of resolution and magnitude. They enable identification and relative quantification of community members and offer new insights into fungal community ecology. These methods are currently taking over as the primary tool to assess fungal communities of plant-associated endophytes, pathogens, and mycorrhizal symbionts, as well as free-living saprotrophs. Taking advantage of the collective experience of six research groups, we here review the different stages involved in fungal community analysis, from field sampling via laboratory procedures to bioinformatics and data interpretation. We discuss potential pitfalls, alternatives, and solutions. Highlighted topics are challenges involved in: obtaining representative DNA/RNA samples and replicates that encompass the targeted variation in community composition, selection of marker regions and primers, options for amplification and multiplexing, handling of sequencing errors, and taxonomic identification. Without awareness of methodological biases, limitations of markers, and bioinformatics challenges, large-scale sequencing projects risk yielding artificial results and misleading conclusions.
新型高通量测序方法在分辨率和幅度上优于早期方法。它们能够识别和相对定量群落成员，并为真菌群落生态学提供新的见解。这些方法目前正在取代主要工具，用于评估与植物相关的内生真菌、病原体和菌根共生体以及自由生活的腐生生物的真菌群落。我们利用六个研究小组的集体经验，在这里回顾了真菌群落分析涉及的不同阶段，从田间采样到实验室程序，再到生物信息学和数据解释。我们讨论了潜在的陷阱、替代方案和解决方案。重点讨论了以下方面的挑战：获得具有代表性的 DNA/RNA 样本和重复样本，这些样本涵盖了群落组成的目标变化；选择标记区域和引物；扩增和多重扩增的选择；测序错误的处理；以及分类鉴定。如果不了解方法学偏见、标记物的局限性和生物信息学挑战，大规模测序项目可能会产生人为的结果和误导性的结论。
