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      High-throughput sequencing for community analysis: the promise of DNA barcoding to uncover diversity, relatedness, abundances and interactions in spider communities

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          Abstract

          Large-scale studies on community ecology are highly desirable but often difficult to accomplish due to the considerable investment of time, labor and, money required to characterize richness, abundance, relatedness, and interactions. Nonetheless, such large-scale perspectives are necessary for understanding the composition, dynamics, and resilience of biological communities. Small invertebrates play a central role in ecosystems, occupying critical positions in the food web and performing a broad variety of ecological functions. However, it has been particularly difficult to adequately characterize communities of these animals because of their exceptionally high diversity and abundance. Spiders in particular fulfill key roles as both predator and prey in terrestrial food webs and are hence an important focus of ecological studies. In recent years, large-scale community analyses have benefitted tremendously from advances in DNA barcoding technology. High-throughput sequencing (HTS), particularly DNA metabarcoding, enables community-wide analyses of diversity and interactions at unprecedented scales and at a fraction of the cost that was previously possible. Here, we review the current state of the application of these technologies to the analysis of spider communities. We discuss amplicon-based DNA barcoding and metabarcoding for the analysis of community diversity and molecular gut content analysis for assessing predator-prey relationships. We also highlight applications of the third generation sequencing technology for long read and portable DNA barcoding. We then address the development of theoretical frameworks for community-level studies, and finally highlight critical gaps and future directions for DNA analysis of spider communities.

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          The online version of this article (10.1007/s00427-020-00652-x) contains supplementary material, which is available to authorized users.

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          Environmental DNA for wildlife biology and biodiversity monitoring.

          Extraction and identification of DNA from an environmental sample has proven noteworthy recently in detecting and monitoring not only common species, but also those that are endangered, invasive, or elusive. Particular attributes of so-called environmental DNA (eDNA) analysis render it a potent tool for elucidating mechanistic insights in ecological and evolutionary processes. Foremost among these is an improved ability to explore ecosystem-level processes, the generation of quantitative indices for analyses of species, community diversity, and dynamics, and novel opportunities through the use of time-serial samples and unprecedented sensitivity for detecting rare or difficult-to-sample taxa. Although technical challenges remain, here we examine the current frontiers of eDNA, outline key aspects requiring improvement, and suggest future developments and innovations for research. Copyright © 2014 Elsevier Ltd. All rights reserved.
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            Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding.

            Global biodiversity in freshwater and the oceans is declining at high rates. Reliable tools for assessing and monitoring aquatic biodiversity, especially for rare and secretive species, are important for efficient and timely management. Recent advances in DNA sequencing have provided a new tool for species detection from DNA present in the environment. In this study, we tested whether an environmental DNA (eDNA) metabarcoding approach, using water samples, can be used for addressing significant questions in ecology and conservation. Two key aquatic vertebrate groups were targeted: amphibians and bony fish. The reliability of this method was cautiously validated in silico, in vitro and in situ. When compared with traditional surveys or historical data, eDNA metabarcoding showed a much better detection probability overall. For amphibians, the detection probability with eDNA metabarcoding was 0.97 (CI = 0.90-0.99) vs. 0.58 (CI = 0.50-0.63) for traditional surveys. For fish, in 89% of the studied sites, the number of taxa detected using the eDNA metabarcoding approach was higher or identical to the number detected using traditional methods. We argue that the proposed DNA-based approach has the potential to become the next-generation tool for ecological studies and standardized biodiversity monitoring in a wide range of aquatic ecosystems.
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              The promise of DNA barcoding for taxonomy.

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                Author and article information

                Contributors
                krehenwinkel@uni-trier.de
                Journal
                Dev Genes Evol
                Dev. Genes Evol
                Development Genes and Evolution
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0949-944X
                1432-041X
                10 February 2020
                10 February 2020
                2020
                : 230
                : 2
                : 185-201
                Affiliations
                [1 ]GRID grid.250464.1, ISNI 0000 0000 9805 2626, Biodiversity and Biocomplexity Unit, , Okinawa Institute of Science and Technology, ; Onna, Okinawa, Japan
                [2 ]GRID grid.462628.c, ISNI 0000 0001 2184 5457, LOEWE-Centre for Translational Biodiversity Genomics, , Senckenberg Museum, ; Frankfurt, Germany
                [3 ]GRID grid.452736.1, ISNI 0000 0001 2166 5237, National Zoological Garden, , South African National Biodiversity Institute, ; Pretoria, South Africa
                [4 ]GRID grid.253482.a, ISNI 0000 0001 0170 7903, Graduate Center of the City University New York, ; New York, NY USA
                [5 ]GRID grid.5607.4, ISNI 0000000121105547, Ecole Normale Supérieure, ; Paris, France
                [6 ]GRID grid.209665.e, ISNI 0000 0001 1941 1940, Santa Fe Institute, ; Santa Fe, NM USA
                [7 ]GRID grid.47840.3f, ISNI 0000 0001 2181 7878, Environmental Sciences Policy and Management, , University of California Berkeley, ; Berkeley, CA USA
                [8 ]GRID grid.12391.38, ISNI 0000 0001 2289 1527, Department of Biogeography, , Trier University, ; Trier, Germany
                Author notes

                Communicated by Matthias Pechmann

                Author information
                https://orcid.org/0000-0002-1616-3985
                https://orcid.org/0000-0002-6229-3596
                https://orcid.org/0000-0001-8614-6892
                https://orcid.org/0000-0003-3755-4480
                https://orcid.org/0000-0003-0086-7424
                https://orcid.org/0000-0001-5069-8601
                Article
                652
                10.1007/s00427-020-00652-x
                7127999
                32040713
                f297017e-48af-467b-b34d-599261436221
                © 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 28 November 2019
                : 29 January 2020
                Funding
                Funded by: Deutsche Forschungsgemeinschaft
                Award ID: KR4623
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100008982, National Science Foundation;
                Award ID: DEB 1241253
                Award Recipient :
                Categories
                Original Article
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2020

                Developmental biology
                metabarcoding,portable sequencing,third generation sequencing,gut content analysis,community assembly

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