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      Symbioses are restructured by repeated mass coral bleaching

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          Abstract

          Survival of symbiotic reef-building corals under global warming requires rapid acclimation or adaptation. The impact of accumulated heat stress was compared across 1643 symbiont communities before and after the 2016 mass bleaching in three coral species and free-living in the environment across ~900 kilometers of the Great Barrier Reef. Resilient reefs (less aerial bleaching than predicted from high satellite sea temperatures) showed low variation in symbioses. Before 2016, heat-tolerant environmental symbionts were common in ~98% of samples and moderately abundant (9 to 40% in samples). In corals, heat-tolerant symbionts were at low abundances (0 to 7.3%) but only in a minority (13 to 27%) of colonies. Following bleaching, environmental diversity doubled (including heat-tolerant symbionts) and increased in one coral species. Communities were dynamic ( Acropora millepora) and conserved ( Acropora hyacinthus and Acropora tenuis), including symbiont community turnover and redistribution. Symbiotic restructuring after bleaching occurs but is a taxon-specific ecological opportunity.

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          Climate change-driven mass coral bleaching restructures algal symbiont communities in some corals and in the environment.

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          DADA2: High resolution sample inference from Illumina amplicon data

          We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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            phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

            Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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              lmerTest Package: Tests in Linear Mixed Effects Models

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing
                Role: Formal analysisRole: SoftwareRole: VisualizationRole: Writing - original draft
                Role: Data curationRole: Formal analysisRole: InvestigationRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing - review & editing
                Role: Data curationRole: InvestigationRole: Project administrationRole: ResourcesRole: Validation
                Role: Data curationRole: InvestigationRole: ResourcesRole: Validation
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing - review & editing
                Journal
                Sci Adv
                Sci Adv
                sciadv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                December 2022
                07 December 2022
                : 8
                : 49
                : eabq8349
                Affiliations
                [ 1 ]Australian Institute of Marine Science, Townsville, QLD, Australia.
                [ 2 ]Minderoo Foundation, Perth, WA, Australia.
                [ 3 ]Oceans Institute, University of Western Australia, Perth, WA, Australia.
                [ 4 ]James Cook University, Townsville, QLD, Australia.
                Author notes
                [* ]Corresponding author. Email: katemarie.quigley@ 123456my.jcu.edu.au
                Author information
                https://orcid.org/0000-0001-5558-1904
                https://orcid.org/0000-0001-9961-945X
                https://orcid.org/0000-0002-6754-1691
                https://orcid.org/0000-0001-9913-302X
                https://orcid.org/0000-0002-9760-2977
                Article
                abq8349
                10.1126/sciadv.abq8349
                9728966
                36475796
                8bcbb4b6-bcb9-4d93-b524-a7d607ad9b22
                Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

                History
                : 04 May 2022
                : 02 November 2022
                Funding
                Funded by: National Environmental Science Program;
                Categories
                Research Article
                Earth, Environmental, Ecological, and Space Sciences
                SciAdv r-articles
                Oceanography
                Custom metadata
                Lou Notario

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