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      Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information

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          Abstract

          The move from OTU-based to sOTU-based analysis, while providing additional resolution, also introduces computational challenges. We demonstrate that one popular method of dealing with sOTUs (building a de novo tree from the short sequences) can provide incorrect results in human gut metagenomic studies and show that phylogenetic placement of the new sequences with SEPP resolves this problem while also yielding other benefits over existing methods.

          ABSTRACT

          Recent algorithmic advances in amplicon-based microbiome studies enable the inference of exact amplicon sequence fragments. These new methods enable the investigation of sub-operational taxonomic units (sOTU) by removing erroneous sequences. However, short (e.g., 150-nucleotide [nt]) DNA sequence fragments do not contain sufficient phylogenetic signal to reproduce a reasonable tree, introducing a barrier in the utilization of critical phylogenetically aware metrics such as Faith’s PD or UniFrac. Although fragment insertion methods do exist, those methods have not been tested for sOTUs from high-throughput amplicon studies in insertions against a broad reference phylogeny. We benchmarked the SATé-enabled phylogenetic placement (SEPP) technique explicitly against 16S V4 sequence fragments and showed that it outperforms the conceptually problematic but often-used practice of reconstructing de novo phylogenies. In addition, we provide a BSD-licensed QIIME2 plugin ( https://github.com/biocore/q2-fragment-insertion) for SEPP and integration into the microbial study management platform QIITA.

          IMPORTANCE The move from OTU-based to sOTU-based analysis, while providing additional resolution, also introduces computational challenges. We demonstrate that one popular method of dealing with sOTUs (building a de novo tree from the short sequences) can provide incorrect results in human gut metagenomic studies and show that phylogenetic placement of the new sequences with SEPP resolves this problem while also yielding other benefits over existing methods.

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          Most cited references29

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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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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              QIIME allows analysis of high-throughput community sequencing data.

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                Author and article information

                Contributors
                Role: Editor
                Journal
                mSystems
                mSystems
                msys
                msys
                mSystems
                mSystems
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2379-5077
                17 April 2018
                May-Jun 2018
                : 3
                : 3
                : e00021-18
                Affiliations
                [a ]Department of Pediatrics, University of California San Diego, La Jolla, California, USA
                [b ]Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA
                [c ]University of Alaska Museum and Department of Biology and Wildlife, Fairbanks, Alaska, USA
                [d ]Departments of Family Medicine & Public Health and Medicine, University of California San Diego, La Jolla, California, USA
                [e ]Department of Medicine, Bone and Mineral Unit, Oregon Health and Sciences University, Portland, Oregon, USA
                [f ]Department of Pediatrics, Washington University, St. Louis, Missouri, USA
                [g ]Center for Microbiome Innovation, University of California San Diego, La Jolla, California, USA
                [h ]Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California, USA
                Mayo Clinic
                Author notes
                Address correspondence to Rob Knight, robknight@ 123456ucsd.edu .

                Citation Janssen S, McDonald D, Gonzalez A, Navas-Molina JA, Jiang L, Xu ZZ, Winker K, Kado DM, Orwoll E, Manary M, Mirarab S, Knight R. 2018. Phylogenetic placement of exact amplicon sequences improves associations with clinical information. mSystems 3:e00021-18. https://doi.org/10.1128/mSystems.00021-18.

                Author information
                https://orcid.org/0000-0003-0955-0589
                Article
                mSystems00021-18
                10.1128/mSystems.00021-18
                5904434
                29719869
                496271b3-8db1-4250-bdb3-a6133bbd1285
                Copyright © 2018 Janssen et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 21 February 2018
                : 20 March 2018
                Page count
                supplementary-material: 2, Figures: 12, Tables: 1, Equations: 0, References: 28, Pages: 14, Words: 7617
                Funding
                Funded by: HHS | National Institutes of Health (NIH), https://doi.org/10.13039/100000002;
                Award ID: P01DK078669
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                Funded by: HHS | National Institutes of Health (NIH), https://doi.org/10.13039/100000002;
                Award ID: RHL134887A
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                Funded by: HHS | National Institutes of Health (NIH), https://doi.org/10.13039/100000002;
                Award ID: U01 AG027810
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                Funded by: HHS | National Institutes of Health (NIH), https://doi.org/10.13039/100000002;
                Award ID: U01 AG042124
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                Funded by: HHS | National Institutes of Health (NIH), https://doi.org/10.13039/100000002;
                Award ID: U01 AG042139
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                Funded by: HHS | National Institutes of Health (NIH), https://doi.org/10.13039/100000002;
                Award ID: U01 AG042140
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                Award ID: U01 AG042143
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                Funded by: HHS | National Institutes of Health (NIH), https://doi.org/10.13039/100000002;
                Award ID: U01 AG042145
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                Funded by: HHS | National Institutes of Health (NIH), https://doi.org/10.13039/100000002;
                Award ID: U01 AG042168
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                Funded by: HHS | National Institutes of Health (NIH), https://doi.org/10.13039/100000002;
                Award ID: U01 AR066160
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                Funded by: HHS | National Institutes of Health (NIH), https://doi.org/10.13039/100000002;
                Award ID: UL1 TR000128
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                Funded by: National Science Foundation (NSF), https://doi.org/10.13039/100000001;
                Award ID: DBI-1565057
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                Funded by: National Science Foundation (NSF), https://doi.org/10.13039/100000001;
                Award ID: ACI-1053575
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                Funded by: National Science Foundation (NSF), https://doi.org/10.13039/100000001;
                Award ID: IIS-1565862
                Award Recipient :
                Funded by: United States Agency for International Development (USAID), https://doi.org/10.13039/100000200;
                Award ID: EDH-A-00-07-00005-00
                Award Recipient :
                Funded by: Alfred P. Sloan Foundation, https://doi.org/10.13039/100000879;
                Award ID: G-2015-13979
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                Funded by: Alfred P. Sloan Foundation, https://doi.org/10.13039/100000879;
                Award ID: G-2015-13933
                Award Recipient :
                Funded by: DOD | United States Navy | Office of Naval Research (ONR), https://doi.org/10.13039/100000006;
                Award ID: N00014-15-1-2809
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                Funded by: Janssen Pharmaceuticals (Janssen Pharmaceuticals, Inc.), https://doi.org/10.13039/100008897;
                Award ID: 20175015
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                Categories
                Research Article
                Ecological and Evolutionary Science
                Custom metadata
                May/June 2018

                sepp,amplicon sequencing,microbial community analysis,phylogenetic placement

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