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      Spatiotemporal Patterns in Diversity and Assembly Process of Marine Protist Communities of the Changjiang (Yangtze River) Plume and Its Adjacent Waters

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          Abstract

          Marine protists are highly heterogeneous and play key roles in the structure and functioning of marine ecosystems. However, little is known on the underlying biogeographic processes and seasonal diversity patterns that shape their community assembly in a regional scale in marginal sea. In this study, we conducted high-throughput sequencing of 18S rRNA gene to survey the protist community compositions (PCCs) of the Changjiang (Yangtze River) plume, an intensely human-affected coastal area, to the adjacent continental shelf waters over three seasons. Furthermore, the different impacts of environmental and spatial factors on marine PCCs were examined. The results revealed significant dissimilarities of PCC’s diversity among seasons and habitats, with more obvious seasonal variations in the Changjiang plume. Procrustes analysis showed better consistency of the community-environment relationship in shelf area, further supported by stronger correlation coefficients computed in the Mantel tests. This might be explained by seasonal dynamics of Changjiang Diluted Waters (i.e., the mixing of the Changjiang runoff with inshore water of the East China Sea) that changed the environmental conditions of coastal area dramatically, resulting in lower importance of spatial factors (dispersal limitation) on PCCs compared with environmental filters, including physicochemical properties (e.g., water temperature, salinity, dissolved oxygen, and nutrients), as well as biotic factors (e.g., Chl a and food abundance). This was further explained by higher immigration rate and fitness to neutral model, which suggested a predominant role of neutral process in shaping the PCCs in coastal area. Different richness, diversity, and taxonomic compositions but comparable biogeographic patterns were observed among abundant and rare sub-communities. In general, the abundant sub-communities exhibited higher dispersal ability which tend to respond to environmental selection during dispersal, whereas the rare sub-communities appeared to be present only in few samples due to dispersal limitation. Co-occurrence network further indicated the importance of biotic interactions in community assembly and potential roles of rare taxa in maintaining the community structure. Overall, this study suggests the dynamic in the biogeographic patterns of PCCs of the Changjiang plume to the adjacent waters in the ECS responding with the changing environmental conditions and geographical factors.

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          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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            WGCNA: an R package for weighted correlation network analysis

            Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at .
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              Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.

              mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                06 October 2020
                2020
                : 11
                : 579290
                Affiliations
                Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystems, College of the Environment and Ecology, Xiamen University , Xiamen, China
                Author notes

                Edited by: Hongbin Liu, Hong Kong University of Science and Technology, Hong Kong

                Reviewed by: George B. Mcmanus, University of Connecticut Groton, United States; Jean-François Mangot, Consejo Superior de Investigaciones Científicas (CSIC), Spain

                *Correspondence: Lingfeng Huang, huanglf@ 123456xmu.edu.cn

                This article was submitted to Aquatic Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2020.579290
                7573215
                33123109
                bdc33b3c-6ffa-4444-b4c4-53c794bf1ced
                Copyright © 2020 Guo, Wu and Huang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 02 July 2020
                : 16 September 2020
                Page count
                Figures: 8, Tables: 3, Equations: 0, References: 104, Pages: 21, Words: 15483
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 41676131
                Award ID: 41876155
                Funded by: National Basic Research Program of China 10.13039/501100012166
                Award ID: 2011CB409804
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                protist,diversity,biogeography,community assembly,changjiang (yangtze river) plume

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