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      Oral microbiota and dental caries data from monozygotic and dizygotic twin children

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          Abstract

          There are recent studies which aimed to detect the inheritance on the etiology of dental caries exploring oral composition. We present data on the oral microbiota and its relation with dental caries and other factors in monozygotic (MZ) and dizygotic (DZ) twin children. Following clinical investigation, DNA samples were collected and isolated from saliva of 198 patients (49 MZ and 50 DZ twins) with an average age of 9.7 ± 2.7 years. Salivary bacterial microbiota analysis was performed using high throughput amplicon sequencing method targeting V3-V4 region of the 16S rRNA gene. A total of 8,297,859 raw reads corresponding to 41,908 reads per sample were obtained on average. The QIIME2-deblur workflow was used for 16S rRNA amplicon analysis. Microbiome similarity analyses between twins (based on Bray-Curtis dissimilarity, weighted and unweighted Unifrac distances) showed that monozygotic twins share more bacterial microbial content compared to dizygotic twins. This is a large microbial community dataset of MZ and DZ twins with or without dental findings which can be further used for children oral microbiome profile explorations.

          Abstract

          Measurement(s) Oral Microbiome • DNA • dental health
          Technology Type(s) twin design • amplicon sequencing • Examination
          Factor Type(s) zygosity status • age • sex
          Sample Characteristic - Organism Microbiota • Homo sapiens
          Sample Characteristic - Environment saliva

          Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12987797

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          Most cited references32

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          Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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            Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea.

            Salinity is a major factor controlling the distribution of biota in aquatic systems, and most aquatic multicellular organisms are either adapted to life in saltwater or freshwater conditions. Consequently, the saltwater-freshwater mixing zones in coastal or estuarine areas are characterized by limited faunal and floral diversity. Although changes in diversity and decline in species richness in brackish waters is well documented in aquatic ecology, it is unknown to what extent this applies to bacterial communities. Here, we report a first detailed bacterial inventory from vertical profiles of 60 sampling stations distributed along the salinity gradient of the Baltic Sea, one of world's largest brackish water environments, generated using 454 pyrosequencing of partial (400 bp) 16S rRNA genes. Within the salinity gradient, bacterial community composition altered at broad and finer-scale phylogenetic levels. Analogous to faunal communities within brackish conditions, we identified a bacterial brackish water community comprising a diverse combination of freshwater and marine groups, along with populations unique to this environment. As water residence times in the Baltic Sea exceed 3 years, the observed bacterial community cannot be the result of mixing of fresh water and saltwater, but our study represents the first detailed description of an autochthonous brackish microbiome. In contrast to the decline in the diversity of multicellular organisms, reduced bacterial diversity at brackish conditions could not be established. It is possible that the rapid adaptation rate of bacteria has enabled a variety of lineages to fill what for higher organisms remains a challenging and relatively unoccupied ecological niche.
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              Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns

              Deblur provides a rapid and sensitive means to assess ecological patterns driven by differentiation of closely related taxa. This algorithm provides a solution to the problem of identifying real ecological differences between taxa whose amplicons differ by a single base pair, is applicable in an automated fashion to large-scale sequencing data sets, and can integrate sequencing runs collected over time.
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                Author and article information

                Contributors
                yelda.kasimoglu@istanbul.edu.tr
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                13 October 2020
                13 October 2020
                2020
                : 7
                : 348
                Affiliations
                [1 ]GRID grid.9601.e, ISNI 0000 0001 2166 6619, Department of Pedodontics, Faculty of Dentistry, , Istanbul University, ; Istanbul, Turkey
                [2 ]GRID grid.506076.2, ISNI 0000 0004 1797 5496, Department of Pedodontics, Faculty of Dentistry, , Istanbul University Cerrahpasa, ; Istanbul, Turkey
                [3 ]GRID grid.411776.2, ISNI 0000 0004 0454 921X, Department of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences, , Istanbul Medeniyet University, ; Istanbul, Turkey
                [4 ]GRID grid.9601.e, ISNI 0000 0001 2166 6619, Department of Microbiology, Faculty of Dentistry, , Istanbul University, ; Istanbul, Turkey
                Author information
                http://orcid.org/0000-0003-1022-2486
                http://orcid.org/0000-0002-2077-5095
                http://orcid.org/0000-0002-3990-7270
                http://orcid.org/0000-0003-3100-0866
                http://orcid.org/0000-0002-5041-1129
                http://orcid.org/0000-0001-6450-6869
                http://orcid.org/0000-0002-9628-0099
                http://orcid.org/0000-0001-7010-2035
                Article
                691
                10.1038/s41597-020-00691-z
                7555494
                33051450
                6bd5bb00-2190-44da-8297-607460ec4b87
                © 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/.

                The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.

                History
                : 24 April 2020
                : 4 September 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100004410, Türkiye Bilimsel ve Teknolojik Araştirma Kurumu (Scientific and Technological Research Council of Turkey);
                Award ID: 214S284
                Award ID: 214S284
                Award ID: 214S284
                Award ID: 214S284
                Award ID: 214S284
                Award ID: 214S284
                Award ID: 214S284
                Award ID: 214S284
                Award Recipient :
                Categories
                Data Descriptor
                Custom metadata
                © The Author(s) 2020

                paediatric dentistry,oral microbiology
                paediatric dentistry, oral microbiology

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