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      18S rRNA V9 metabarcoding for diet characterization: a critical evaluation with two sympatric zooplanktivorous fish species

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          Abstract

          The potential of the 18S rRNA V9 metabarcoding approach for diet assessment was explored using MiSeq paired‐end (PE; 2 × 150 bp) technology. To critically evaluate the method′s performance with degraded/digested DNA, the diets of two zooplanktivorous fish species from the Bay of Biscay, European sardine ( Sardina pilchardus) and European sprat ( Sprattus sprattus), were analysed. The taxonomic resolution and quantitative potential of the 18S V9 metabarcoding was first assessed both in silico and with mock and field plankton samples. Our method was capable of discriminating species within the reference database in a reliable way providing there was at least one variable position in the 18S V9 region. Furthermore, it successfully discriminated diet between both fish species, including habitat and diel differences among sardines, overcoming some of the limitations of traditional visual‐based diet analysis methods. The high sensitivity and semi‐quantitative nature of the 18S V9 metabarcoding approach was supported by both visual microscopy and qPCR‐based results. This molecular approach provides an alternative cost and time effective tool for food‐web analysis.

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          Universal and rapid salt-extraction of high quality genomic DNA for PCR-based techniques.

          A very simple, fast, universally applicable and reproducible method to extract high quality megabase genomic DNA from different organisms is described. We applied the same method to extract high quality complex genomic DNA from different tissues (wheat, barley, potato, beans, pear and almond leaves as well as fungi, insects and shrimps' fresh tissue) without any modification. The method does not require expensive and environmentally hazardous reagents and equipment. It can be performed even in low technology laboratories. The amount of tissue required by this method is approximately 50-100 mg. The quantity and the quality of the DNA extracted by this method is high enough to perform hundreds of PCR-based reactions and also to be used in other DNA manipulation techniques such as restriction digestion, Southern blot and cloning.
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            A Method for Studying Protistan Diversity Using Massively Parallel Sequencing of V9 Hypervariable Regions of Small-Subunit Ribosomal RNA Genes

            Background Massively parallel pyrosequencing of amplicons from the V6 hypervariable regions of small-subunit (SSU) ribosomal RNA (rRNA) genes is commonly used to assess diversity and richness in bacterial and archaeal populations. Recent advances in pyrosequencing technology provide read lengths of up to 240 nucleotides. Amplicon pyrosequencing can now be applied to longer variable regions of the SSU rRNA gene including the V9 region in eukaryotes. Methodology/Principal Findings We present a protocol for the amplicon pyrosequencing of V9 regions for eukaryotic environmental samples for biodiversity inventories and species richness estimation. The International Census of Marine Microbes (ICoMM) and the Microbial Inventory Research Across Diverse Aquatic Long Term Ecological Research Sites (MIRADA-LTERs) projects are already employing this protocol for tag sequencing of eukaryotic samples in a wide diversity of both marine and freshwater environments. Conclusions/Significance Massively parallel pyrosequencing of eukaryotic V9 hypervariable regions of SSU rRNA genes provides a means of estimating species richness from deeply-sampled populations and for discovering novel species from the environment.
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              Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences

              We present a performance-optimized algorithm, subsampled open-reference OTU picking, for assigning marker gene (e.g., 16S rRNA) sequences generated on next-generation sequencing platforms to operational taxonomic units (OTUs) for microbial community analysis. This algorithm provides benefits over de novo OTU picking (clustering can be performed largely in parallel, reducing runtime) and closed-reference OTU picking (all reads are clustered, not only those that match a reference database sequence with high similarity). Because more of our algorithm can be run in parallel relative to “classic” open-reference OTU picking, it makes open-reference OTU picking tractable on massive amplicon sequence data sets (though on smaller data sets, “classic” open-reference OTU clustering is often faster). We illustrate that here by applying it to the first 15,000 samples sequenced for the Earth Microbiome Project (1.3 billion V4 16S rRNA amplicons). To the best of our knowledge, this is the largest OTU picking run ever performed, and we estimate that our new algorithm runs in less than 1/5 the time than would be required of “classic” open reference OTU picking. We show that subsampled open-reference OTU picking yields results that are highly correlated with those generated by “classic” open-reference OTU picking through comparisons on three well-studied datasets. An implementation of this algorithm is provided in the popular QIIME software package, which uses uclust for read clustering. All analyses were performed using QIIME’s uclust wrappers, though we provide details (aided by the open-source code in our GitHub repository) that will allow implementation of subsampled open-reference OTU picking independently of QIIME (e.g., in a compiled programming language, where runtimes should be further reduced). Our analyses should generalize to other implementations of these OTU picking algorithms. Finally, we present a comparison of parameter settings in QIIME’s OTU picking workflows and make recommendations on settings for these free parameters to optimize runtime without reducing the quality of the results. These optimized parameters can vastly decrease the runtime of uclust-based OTU picking in QIIME.
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                Author and article information

                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                19 February 2016
                March 2016
                : 6
                : 6 ( doiID: 10.1002/ece3.2016.6.issue-6 )
                : 1809-1824
                Affiliations
                [ 1 ] Laboratory of Genetics Department of Genetics, Physical Anthropology & Animal PhysiologyUniversity of the Basque Country (UPV/EHU) Leioa 48940Spain
                [ 2 ] Marine Research DivisionAZTI Tecnalia Herrera Kaia Portualdea z/g P.O. Box 20110 Pasaia GipuzkoaSpain
                Author notes
                [*] [* ] Correspondence

                Aitor Albaina, Laboratory of Genetics, University of the Basque Country (UPV/EHU), Leioa 48940, Spain.

                Tel: (+34) 946015503;

                Fax: +34‐946013145;

                E‐mail: aitoralbaina@ 123456hotmail.com / aitor.albaina@ 123456ehu.es .

                Article
                ECE31986
                10.1002/ece3.1986
                4801955
                27087935
                161e49a2-6865-4859-97fc-7dc973a25c3d
                © 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 December 2015
                : 23 December 2015
                : 03 January 2016
                Page count
                Pages: 16
                Funding
                Funded by: ECOGENBAY
                Award ID: MICINN CTM2009‐13570‐C02‐02
                Funded by: Government of Spain
                Funded by: Basque Government
                Award ID: IT558‐10
                Funded by: European Commission within the frame of the National Sampling Programme
                Award ID: 665/2008
                Funded by: Euskampus Foundation
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                ece31986
                March 2016
                Converter:WILEY_ML3GV2_TO_NLMPMC version:4.8.5 mode:remove_FC converted:21.03.2016

                Evolutionary Biology
                18s rrna v9,diet analysis,metabarcoding,miseq paired‐end technology,plankton,sardina pilchardus,sprattus sprattus

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