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      Vertical diversity and association pattern of total, abundant and rare microbial communities in deep‐sea sediments

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          Abstract

          Microbial abundance and community composition in marine sediments have been widely explored. However, high‐resolution vertical changes of benthic microbial diversity and co‐occurrence patterns are poorly described. The ecological contributions of abundant and rare species in sediments also remain largely unknown. Here, by analysing microbial populations at 14 depth layers of 10 subseafloor sediment cores (water depth 1,250–3,530 m) obtained in the South China Sea, we provided the vertical profiles of microbial β‐diversity and co‐occurrence influenced by subcommunities of different abundance. These 134 sediment samples were clustered into four groups according to sediment depth (1–2, 6–10, 30–90 and 190–790 cm) with obvious shifts in microbial community compositions. The vertical succession of microorganisms was consistent with redox zonation and influenced by terrestrial inputs. Partitioning of vertical β‐diversity showed extremely high species replacement between deep layers and the surface layer, indicating selection‐induced loss of rare species and dispersal of dormant cells and spores. By contrast, for horizontal β‐diversity, richness of rare species became increasingly significant in deep sediments. Accompanying this β‐diversity profile were clear changes in the association pattern, with microorganisms being less connected in deeper sediment layers, probably reflecting reduced syntrophic interactions. Rare species accounted for an indispensable proportion in the co‐occurrence network, and tended to form complex “small worlds.” The rare subcommunity also responded differently to various environmental factors compared with the abundant subcommunity. Our findings expand current knowledge on vertical changes of marine benthic microbial diversity and their association patterns, emphasizing the potential roles of rare species.

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          Most cited references110

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            UPARSE: highly accurate OTU sequences from microbial amplicon reads.

            Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.
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              Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

              The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.

                Author and article information

                Contributors
                liujiwen@ouc.edu.cn
                Journal
                Mol Ecol
                Mol Ecol
                10.1111/(ISSN)1365-294X
                MEC
                Molecular Ecology
                John Wiley and Sons Inc. (Hoboken )
                0962-1083
                1365-294X
                16 May 2021
                June 2021
                : 30
                : 12 ( doiID: 10.1111/mec.v30.12 )
                : 2800-2816
                Affiliations
                [ 1 ] College of Marine Life Sciences Frontiers Science Center for Deep Ocean Multispheres and Earth System Ocean University of China Qingdao China
                [ 2 ] Laboratory for Marine Ecology and Environmental Science Qingdao National Laboratory for Marine Science and Technology Qingdao China
                [ 3 ] Institute of Evolution & Marine Biodiversity Ocean University of China Qingdao China
                [ 4 ] Key Laboratory of Marine Chemistry Theory and Technology Ministry of Education Ocean University of China Qingdao China
                [ 5 ] Key Laboratory of Submarine Geosciences and Prospecting Techniques Ministry of Education/College of Marine Geosciences Ocean University of China Qingdao China
                [ 6 ] Laboratory for Marine Geology Qingdao National Laboratory for Marine Science and Technology Qingdao China
                Author notes
                [*] [* ] Correspondence

                Jiwen Liu, College of Marine Life Sciences, and Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China, Qingdao, China.

                Email: liujiwen@ 123456ouc.edu.cn

                Author information
                https://orcid.org/0000-0002-7428-7775
                https://orcid.org/0000-0001-9453-2670
                Article
                MEC15937
                10.1111/mec.15937
                8251536
                33960545
                ccaf5fdd-9c67-48f3-b72b-12b807c6d860
                © 2021 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 21 April 2021
                : 29 October 2020
                : 22 April 2021
                Page count
                Figures: 5, Tables: 0, Pages: 17, Words: 12814
                Funding
                Funded by: Fundamental Research Funds for the Central Universities
                Award ID: 202172002
                Award ID: 202072003
                Funded by: Programs of China Geological Survey
                Award ID: DD20160221
                Funded by: National Natural Science Foundation of China
                Award ID: 91751202
                Award ID: 41730530
                Award ID: 41906099
                Award ID: 92051115
                Award ID: 41976101
                Funded by: China Postdoctoral Science Foundation
                Award ID: 2019M652469
                Categories
                Original Article
                ORIGINAL ARTICLES
                Ecological Genomics
                Custom metadata
                2.0
                June 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.4 mode:remove_FC converted:02.07.2021

                Ecology
                co‐occurrence network,deep‐sea sediment,microbial community,rare biosphere,β‐diversity

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