From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package
From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package
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从 DNA 序列到微生物生态学：使用 neonMicrobe R 软件包整理 NEON 土壤微生物数据
DOI：
10.1002/ecs2.3842
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发表时间：
2021
期刊：
影响因子：
2.7
通讯作者：
Pellitier, Peter
中科院分区：
文献类型：
--
作者：
Qin, Clara;Bartelme, Ryan;Chung, Y. Anny;Fairbanks, Dawson;Lin, Yang;Liptzin, Daniel;Muscarella, Chance;Naithani, Kusum;Peay, Kabir;Pellitier, Peter
土壤微生物群落在各种生态系统过程中发挥着关键作用，但由于难以在可用数据集中找到相关样本以及样本收集和处理缺乏标准化，因此大时空尺度的研究一直具有挑战性。国家生态观测站网络 (NEON) 每年多次收集 20 个生态气候领域 47 个陆地地点的土壤微生物群落数据，是迄今为止最广泛的土壤微生物生物多样性标准化采样工作之一。在这里，我们介绍 neonMicrobe R 软件包，这是一套下载、预处理、数据集组装和敏感性分析工具，适用于 NEON 新发布的 16S 和 ITS 扩增子测序数据产品，分别表征土壤细菌和真菌群落。 neonMicrobe 旨在使生态学家更容易获取这些数据，而无需假设以前具有生物信息学流程的经验。我们描述了用于去除质量标记样本的质量控制步骤，报告了用于确定 DADA2 工作流程适当质量过滤参数的敏感性分析，并通过对土壤微生物多样性进行标准分析来证明输出数据的立即可用性。 neonMicrobe 生成的序列丰度表可以与 NEON 的其他数据产品（例如土壤物理和化学特性、植物群落组成）以及 NEON 生物存储库中存档的土壤子样本相关联。我们提供了将 neonMicrobe 纳入可重复的科学工作流程的建议，讨论了大规模扩增子序列分析的技术考虑因素，并概述了 NEON 微生物生态学的未来方向。特别是，我们相信 NEON 标记基因序列数据将使研究人员能够回答有关土壤微生物群落时空动态的突出问题，同时明确考虑尺度依赖性。我们期望 NEON 和 theneonMicrobeR 包产生的数据将作为有价值的生态基线，为未来的实验和建模工作提供信息和背景。
Soil microbial communities play critical roles in various ecosystem processes, but studies at a large spatial and temporal scale have been challenging due to the difficulty in finding the relevant samples in available data sets as well as the lack of standardization in sample collection and processing. The National Ecological Observatory Network (NEON) has been collecting soil microbial community data multiple times per year for 47 terrestrial sites in 20 eco‐climatic domains, producing one of the most extensive standardized sampling efforts for soil microbial biodiversity to date. Here, we introduce the neonMicrobe R package—a suite of downloading, preprocessing, data set assembly, and sensitivity analysis tools for NEON’s newly published 16S and ITS amplicon sequencing data products which characterize soil bacterial and fungal communities, respectively. neonMicrobe is designed to make these data more accessible to ecologists without assuming prior experience with bioinformatic pipelines. We describe quality control steps used to remove quality‐flagged samples, report on sensitivity analyses used to determine appropriate quality filtering parameters for the DADA2 workflow, and demonstrate the immediate usability of the output data by conducting standard analyses of soil microbial diversity. The sequence abundance tables produced byneonMicrobecan be linked to NEON’s other data products (e.g., soil physical and chemical properties, plant community composition) and soil subsamples archived in the NEON Biorepository. We provide recommendations for incorporatingneonMicrobeinto reproducible scientific workflows, discuss technical considerations for large‐scale amplicon sequence analysis, and outline future directions for NEON‐enabled microbial ecology. In particular, we believe that NEON marker gene sequence data will allow researchers to answer outstanding questions about the spatial and temporal dynamics of soil microbial communities while explicitly accounting for scale dependence. We expect that the data produced by NEON and theneonMicrobeR package will act as a valuable ecological baseline to inform and contextualize future experimental and modeling endeavors.