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      Inter-domain microbial diversity within the coral holobiont Siderastrea siderea from two depth habitats

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          Abstract

          Corals host diverse microbial communities that are involved in acclimatization, pathogen defense, and nutrient cycling. Surveys of coral-associated microbes have been particularly directed toward Symbiodinium and bacteria. However, a holistic understanding of the total microbiome has been hindered by a lack of analyses bridging taxonomically disparate groups. Using high-throughput amplicon sequencing, we simultaneously characterized the Symbiodinium, bacterial, and fungal communities associated with the Caribbean coral Siderastrea siderea collected from two depths (17 and 27 m) on Conch reef in the Florida Keys. S. siderea hosted an exceptionally diverse Symbiodinium community, structured differently between sampled depth habitats. While dominated at 27 m by a Symbiodinium belonging to clade C, at 17 m S. siderea primarily hosted a mixture of clade B types. Most fungal operational taxonomic units were distantly related to available reference sequences, indicating the presence of a high degree of fungal novelty within the S. siderea holobiont and a lack of knowledge on the diversity of fungi on coral reefs. Network analysis showed that co-occurrence patterns in the S. siderea holobiont were prevalent among bacteria, however, also detected between fungi and bacteria. Overall, our data show a drastic shift in the associated Symbiodinium community between depths on Conch Reef, which might indicate that alteration in this community is an important mechanism facilitating local physiological adaptation of the S. siderea holobiont. In contrast, bacterial and fungal communities were not structured differently between depth habitats.

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

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            Modularity and community structure in networks

            M. Newman (2006)
            Many networks of interest in the sciences, including a variety of social and biological networks, are found to divide naturally into communities or modules. The problem of detecting and characterizing this community structure has attracted considerable recent attention. One of the most sensitive detection methods is optimization of the quality function known as "modularity" over the possible divisions of a network, but direct application of this method using, for instance, simulated annealing is computationally costly. Here we show that the modularity can be reformulated in terms of the eigenvectors of a new characteristic matrix for the network, which we call the modularity matrix, and that this reformulation leads to a spectral algorithm for community detection that returns results of better quality than competing methods in noticeably shorter running times. We demonstrate the algorithm with applications to several network data sets.
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              Fast unfolding of communities in large networks

              We propose a simple method to extract the community structure of large networks. Our method is a heuristic method that is based on modularity optimization. It is shown to outperform all other known community detection method in terms of computation time. Moreover, the quality of the communities detected is very good, as measured by the so-called modularity. This is shown first by identifying language communities in a Belgian mobile phone network of 2.6 million customers and by analyzing a web graph of 118 million nodes and more than one billion links. The accuracy of our algorithm is also verified on ad-hoc modular networks. .
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                9 February 2018
                2018
                : 6
                : e4323
                Affiliations
                [1 ]Department of Biological Sciences, Florida International University , Miami, FL, USA
                [2 ]Aquatic Microbiology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam , Amsterdam, The Netherlands
                [3 ]NASA Johnson Space Center , Houston, TX, USA
                Author information
                http://orcid.org/0000-0002-9823-6761
                http://orcid.org/0000-0002-2811-3002
                http://orcid.org/0000-0002-6951-5390
                http://orcid.org/0000-0002-0811-8500
                Article
                4323
                10.7717/peerj.4323
                5808317
                29441234
                e8acb71a-8de0-4136-8331-e8ed6a93c6c3
                © 2018 Bonthond et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 16 August 2017
                : 13 January 2018
                Funding
                Funded by: NEEMO mission
                Funded by: Florida International University
                This work was funded by the NEEMO mission and by a Florida International University start-up grant awarded to Mauricio Rodriguez-Lanetty. There was no additional external funding received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Marine Biology
                Microbiology

                symbiosis,coral,fungi,microbial community,coral-associated microbiome,symbiodinium

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