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      Host habitat rather than evolutionary history explains gut microbiome diversity in sympatric stickleback species

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          Abstract

          Host-associated microbiota can influence host phenotypic variation, fitness and potential to adapt to local environmental conditions. In turn, both host evolutionary history and the abiotic and biotic environment can influence the diversity and composition of microbiota. Yet, to what extent environmental and host-specific factors drive microbial diversity remains largely unknown, limiting our understanding of host-microbiome interactions in natural populations. Here, we compared the intestinal microbiota between two phylogenetically related fishes, the three-spined stickleback ( Gasterosteus aculeatus) and the nine-spined stickleback ( Pungitius pungitius) in a common landscape. Using amplicon sequencing of the V3-V4 region of the bacterial 16S rRNA gene, we characterised the α and β diversity of the microbial communities in these two fish species from both brackish water and freshwater habitats. Across eight locations, α diversity was higher in the nine-spined stickleback, suggesting a broader niche use in this host species. Habitat was a strong determinant of β diversity in both host species, while host species only explained a small fraction of the variation in gut microbial composition. Strong habitat-specific effects overruled effects of geographic distance and historical freshwater colonisation, suggesting that the gut microbiome correlates primarily with local environmental conditions. Interestingly, the effect of habitat divergence on gut microbial communities was stronger in three-spined stickleback than in nine-spined stickleback, possibly mirroring the stronger level of adaptive divergence in this host species. Overall, our results show that microbial communities reflect habitat divergence rather than colonisation history or dispersal limitation of host species.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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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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              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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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                12 October 2023
                2023
                : 14
                : 1232358
                Affiliations
                [1] 1Faculty of Biosciences and Aquaculture, Nord University , Bodø, Norway
                [2] 2School of Biological and Behavioural Sciences, Queen Mary University of London , London, United Kingdom
                Author notes

                Edited by: Zhiyong Li, Shanghai Jiao Tong University, China

                Reviewed by: Jianping Jiang, Chinese Academy of Sciences (CAS), China; Libby Wilson, Kansas State University, United States

                *Correspondence: Aruna M. Shankregowda, arungowda9738@ 123456gmail.com
                Article
                10.3389/fmicb.2023.1232358
                10601471
                37901806
                a3513e2c-3c0c-44ab-8a60-c87ccc5e1bdf
                Copyright © 2023 Shankregowda, Siriyappagouder, Kuizenga, Bal, Abdelhafiz, Eizaguirre, Fernandes, Kiron and Raeymaekers.

                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
                : 31 May 2023
                : 18 September 2023
                Page count
                Figures: 8, Tables: 3, Equations: 0, References: 78, Pages: 12, Words: 8895
                Categories
                Microbiology
                Original Research
                Custom metadata
                Microbial Symbioses

                Microbiology & Virology
                host microbiota,sticklebacks,evolutionary history,host habitat,adaptation,symbiotic microbiota,adaptive divergence

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