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      Relative Abundances of Species or Sequence Variants Can Be Misleading: Soil Fungal Communities as an Example

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          Abstract

          Plant production systems that are more sustainable than conventional monoculture croplands are the vision of future agriculture. With numerous environmental benefits, agroforestry is among the most promising alternatives. Although soil fungi are key drivers of plant productivity and ecosystem processes, investigations of these microorganisms in temperate agroforestry systems are scarce, leaving our understanding of agricultural systems under agroforestry practice incomplete. Here, we assessed the composition and diversity of the soil fungal community as well as the frequency (relative abundance) of fungal groups in three paired temperate poplar-based alley cropping (agroforestry) and monoculture cropland systems by amplicon sequencing. Analysis of microbiomes using relative abundances of species or sequence variants obtained from amplicon sequencing ignores microbial population size, which results in several problems. For example, species stimulated by environmental parameters may appear unaffected or suppressed in amplicon counts. Therefore, we determined absolute abundances of selected fungal groups as well as total fungal population size by real-time polymerase chain reaction (PCR). Tree rows strongly affected the community composition and increased the population size and species richness of soil fungi. Furthermore, ectomycorrhiza were strongly promoted by the tree rows. We speculate that mycorrhiza improved the nutrient acquisition in unfertilized tree rows, thereby contributing to the total productivity of the system. Comparison of relative and absolute abundances revealed dramatic discrepancies, highlighting that amplicon sequencing alone cannot adequately assess population size and dynamics. The results of our study highlight the necessity of combining frequency data based on amplicon sequencing with absolute quantification.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            NIH Image to ImageJ: 25 years of image analysis

            For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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              DADA2: High resolution sample inference from Illumina amplicon data

              We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Microorganisms
                Microorganisms
                microorganisms
                Microorganisms
                MDPI
                2076-2607
                13 March 2021
                March 2021
                : 9
                : 3
                : 589
                Affiliations
                Molecular Phytopathology and Mycotoxin Research, University of Goettingen, 37077 Goettingen, Germany; markus.arndt@ 123456stud.uni-goettingen.de (M.A.); pkarlov@ 123456gwdg.de (P.K.)
                Author notes
                Author information
                https://orcid.org/0000-0003-1107-7540
                https://orcid.org/0000-0002-6532-5856
                Article
                microorganisms-09-00589
                10.3390/microorganisms9030589
                7999432
                33805593
                7c479698-f191-4252-85c5-31e923e942b7
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 14 February 2021
                : 12 March 2021
                Categories
                Article

                temperate agroforestry,tree-based intercropping,alley cropping,soil fungal community,amplicon sequencing,real-time pcr,soil microbiome

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