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      Spatiotemporal dynamics of the archaeal community in coastal sediments: assembly process and co-occurrence relationship

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          Abstract

          Studies of marine benthic archaeal communities are updating our view of their taxonomic composition and metabolic versatility. However, large knowledge gaps remain with regard to community assembly processes and inter taxa associations. Here, using 16S rRNA gene amplicon sequencing and qPCR, we investigated the spatiotemporal dynamics, assembly processes, and co-occurrence relationships of the archaeal community in 58 surface sediment samples collected in both summer and winter from across ~1500 km of the eastern Chinese marginal seas. Clear patterns in spatiotemporal dynamics in the archaeal community structure were observed, with a more pronounced spatial rather than seasonal variation. Accompanying the geographic variation was a significant distance-decay pattern with varying contributions from different archaeal clades, determined by their relative abundance. In both seasons, dispersal limitation was the most important process, explaining ~40% of the community variation, followed by homogeneous selection and ecological drift, that made an approximately equal contribution (~30%). This meant that stochasticity rather than determinism had a greater impact on the archaeal community assembly. Furthermore, we observed seasonality in archaeal co-occurrence patterns: closer inter-taxa connections in winter than in summer, and unmatched geographic patterns between community composition and co-occurrence relationship. These results demonstrate that the benthic archaeal community was assembled under a seasonal-consistent mechanism but the co-occurrence relationships changed over the seasons, indicating complex archaeal dynamic patterns in coastal sediments of the eastern Chinese marginal seas.

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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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            QIIME allows analysis of high-throughput community sequencing data.

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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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                Author and article information

                Contributors
                xhzhang@ouc.edu.cn
                Journal
                ISME J
                ISME J
                The ISME Journal
                Nature Publishing Group UK (London )
                1751-7362
                1751-7370
                4 March 2020
                June 2020
                : 14
                : 6
                : 1463-1478
                Affiliations
                [1 ]ISNI 0000 0001 2152 3263, GRID grid.4422.0, MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, , Ocean University of China, ; Qingdao, 266003 China
                [2 ]ISNI 0000 0004 5998 3072, GRID grid.484590.4, Laboratory for Marine Ecology and Environmental Science, , Qingdao National Laboratory for Marine Science and Technology, ; Qingdao, 266071 China
                [3 ]ISNI 0000 0001 2152 3263, GRID grid.4422.0, Institute of Evolution & Marine Biodiversity, , Ocean University of China, ; Qingdao, 266003 China
                [4 ]ISNI 0000 0001 2152 3263, GRID grid.4422.0, Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education/Institute for Advanced Ocean Studies, , Ocean University of China, ; Qingdao, 266100 China
                [5 ]ISNI 0000 0001 2152 3263, GRID grid.4422.0, College of Chemistry and Chemical Engineering, , Ocean University of China, ; Qingdao, 266100 China
                Author information
                http://orcid.org/0000-0002-8906-4929
                Article
                621
                10.1038/s41396-020-0621-7
                7242467
                32132664
                1f10ec9e-cfc7-4714-bd5c-f303b7f006d2
                © The Author(s) 2020

                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 September 2019
                : 15 February 2020
                : 18 February 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 41506154
                Award ID: 41976101
                Award Recipient :
                Categories
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                © International Society for Microbial Ecology 2020

                Microbiology & Virology
                microbial ecology
                Microbiology & Virology
                microbial ecology

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