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      Unravelling the interplay of ecological processes structuring the bacterial rare biosphere

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          Abstract

          Most ecological communities harbor many rare species (i.e., the rare biosphere), however, relatively little is known about how distinct ecological processes structure their existence. Here, we used spatiotemporal data on soil bacterial communities along a natural ecosystem gradient to model the relative influences of assembly processes structuring the rare and common biospheres. We found a greater influence of homogeneous selection (i.e., imposed by spatiotemporally constant variables) mediating the assembly of the rare biosphere, whereas the common biosphere was mostly governed by variable selection (i.e., imposed by spatial and/or temporal fluctuating variables). By partitioning the different types of rarity, we found homogeneous selection to explain the prevalence of permanently rare taxa, thus suggesting their persistence at low abundances to be restrained by physiological traits. Conversely, the dynamics of conditionally rare taxa were mostly structured by variable selection, which aligns with the ability of these taxa to switch between rarity and commonness as responses to environmental spatiotemporal variations. Taken together, our study contributes to the establishment of a link between conceptual and empirical developments in the ecology of the soil microbial rare biosphere. Besides, this study provides a framework to better understand, model, and predict the existence and dynamics of microbial rare biospheres across divergent systems and scales.

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          Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample.

          The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.
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            Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms

            DNA sequencing continues to decrease in cost with the Illumina HiSeq2000 generating up to 600 Gb of paired-end 100 base reads in a ten-day run. Here we present a protocol for community amplicon sequencing on the HiSeq2000 and MiSeq Illumina platforms, and apply that protocol to sequence 24 microbial communities from host-associated and free-living environments. A critical question as more sequencing platforms become available is whether biological conclusions derived on one platform are consistent with what would be derived on a different platform. We show that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons.
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              APE: Analyses of Phylogenetics and Evolution in R language.

              Analysis of Phylogenetics and Evolution (APE) is a package written in the R language for use in molecular evolution and phylogenetics. APE provides both utility functions for reading and writing data and manipulating phylogenetic trees, as well as several advanced methods for phylogenetic and evolutionary analysis (e.g. comparative and population genetic methods). APE takes advantage of the many R functions for statistics and graphics, and also provides a flexible framework for developing and implementing further statistical methods for the analysis of evolutionary processes. The program is free and available from the official R package archive at http://cran.r-project.org/src/contrib/PACKAGES.html#ape. APE is licensed under the GNU General Public License.
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                Author and article information

                Contributors
                xibeihenai@gmail.com
                j.falcao.salles@rug.nl
                Journal
                ISME Commun
                ISME Commun
                ISME Communications
                Nature Publishing Group UK (London )
                2730-6151
                2730-6151
                3 October 2022
                3 October 2022
                2022
                : 2
                : 96
                Affiliations
                [1 ]GRID grid.4830.f, ISNI 0000 0004 0407 1981, Microbial Ecology Cluster, Genomics Research in Ecology and Evolution in Nature (GREEN), Groningen Institute for Evolutionary Life Sciences (GELIFES), , University of Groningen, ; Groningen, 9747AG The Netherlands
                [2 ]GRID grid.29857.31, ISNI 0000 0001 2097 4281, Department of Plant Science, , The Pennsylvania State University, Pennsylvania, ; University Park, PA 16801 USA
                [3 ]GRID grid.29857.31, ISNI 0000 0001 2097 4281, Huck Institutes of the Life Sciences, , The Pennsylvania State University, ; University Park, PA 16801 USA
                Author information
                https://orcid.org/http://orcid.org/0000-0003-1129-1942
                https://orcid.org/http://orcid.org/0000-0002-6654-0769
                https://orcid.org/http://orcid.org/0000-0003-4317-7263
                Article
                177
                10.1038/s43705-022-00177-6
                9723687
                c49bf886-536f-4c11-a684-743f5c1bd8da
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 April 2022
                : 13 September 2022
                : 13 September 2022
                Categories
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                © The Author(s) 2022

                microbial ecology,community ecology
                microbial ecology, community ecology

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