From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package

Abstract 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...

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Autores principales:	Clara Qin, Ryan Bartelme, Y. Anny Chung, Dawson Fairbanks, Yang Lin, Daniel Liptzin, Chance Muscarella, Kusum Naithani, Kabir Peay, Peter Pellitier, Ayanna St. Rose, Lee Stanish, Zoey Werbin, Kai Zhu
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	biogeography bioinformatics DADA2 macroecology marker gene sequences neonMicrobe Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/170650990cef473d9c6e4b6da22cf76f
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spelling	oai:doaj.org-article:170650990cef473d9c6e4b6da22cf76f2021-11-29T07:06:43ZFrom DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package2150-892510.1002/ecs2.3842https://doaj.org/article/170650990cef473d9c6e4b6da22cf76f2021-11-01T00:00:00Zhttps://doi.org/10.1002/ecs2.3842https://doaj.org/toc/2150-8925Abstract 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 by neonMicrobe can 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 incorporating neonMicrobe into 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 the neonMicrobe R package will act as a valuable ecological baseline to inform and contextualize future experimental and modeling endeavors.Clara QinRyan BartelmeY. Anny ChungDawson FairbanksYang LinDaniel LiptzinChance MuscarellaKusum NaithaniKabir PeayPeter PellitierAyanna St. RoseLee StanishZoey WerbinKai ZhuWileyarticlebiogeographybioinformaticsDADA2macroecologymarker gene sequencesneonMicrobeEcologyQH540-549.5ENEcosphere, Vol 12, Iss 11, Pp n/a-n/a (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	biogeography bioinformatics DADA2 macroecology marker gene sequences neonMicrobe Ecology QH540-549.5
spellingShingle	biogeography bioinformatics DADA2 macroecology marker gene sequences neonMicrobe Ecology QH540-549.5 Clara Qin Ryan Bartelme Y. Anny Chung Dawson Fairbanks Yang Lin Daniel Liptzin Chance Muscarella Kusum Naithani Kabir Peay Peter Pellitier Ayanna St. Rose Lee Stanish Zoey Werbin Kai Zhu From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package
description	Abstract 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 by neonMicrobe can 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 incorporating neonMicrobe into 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 the neonMicrobe R package will act as a valuable ecological baseline to inform and contextualize future experimental and modeling endeavors.
format	article
author	Clara Qin Ryan Bartelme Y. Anny Chung Dawson Fairbanks Yang Lin Daniel Liptzin Chance Muscarella Kusum Naithani Kabir Peay Peter Pellitier Ayanna St. Rose Lee Stanish Zoey Werbin Kai Zhu
author_facet	Clara Qin Ryan Bartelme Y. Anny Chung Dawson Fairbanks Yang Lin Daniel Liptzin Chance Muscarella Kusum Naithani Kabir Peay Peter Pellitier Ayanna St. Rose Lee Stanish Zoey Werbin Kai Zhu
author_sort	Clara Qin
title	From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package
title_short	From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package
title_full	From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package
title_fullStr	From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package
title_full_unstemmed	From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package
title_sort	from dna sequences to microbial ecology: wrangling neon soil microbe data with the neonmicrobe r package
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/170650990cef473d9c6e4b6da22cf76f
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From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package

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