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      Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4

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          Abstract

          Metagenomic assembly enables new organism discovery from microbial communities, but it can only capture few abundant organisms from most metagenomes. Here we present MetaPhlAn 4, which integrates information from metagenome assemblies and microbial isolate genomes for more comprehensive metagenomic taxonomic profiling. From a curated collection of 1.01 M prokaryotic reference and metagenome-assembled genomes, we define unique marker genes for 26,970 species-level genome bins, 4,992 of them taxonomically unidentified at the species level. MetaPhlAn 4 explains ~20% more reads in most international human gut microbiomes and >40% in less-characterized environments such as the rumen microbiome and proves more accurate than available alternatives on synthetic evaluations while also reliably quantifying organisms with no cultured isolates. Application of the method to >24,500 metagenomes highlights previously undetected species to be strong biomarkers for host conditions and lifestyles in human and mouse microbiomes and shows that even previously uncharacterized species can be genetically profiled at the resolution of single microbial strains.

          Abstract

          Integration of metagenomic assemblies and microbial isolate genomes improves profiling of uncharacterized species.

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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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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                Author and article information

                Contributors
                nicola.segata@unitn.it
                Journal
                Nat Biotechnol
                Nat Biotechnol
                Nature Biotechnology
                Nature Publishing Group US (New York )
                1087-0156
                1546-1696
                23 February 2023
                23 February 2023
                2023
                : 41
                : 11
                : 1633-1644
                Affiliations
                [1 ]Department CIBIO, University of Trento, ( https://ror.org/05trd4x28) Trento, Italy
                [2 ]GRID grid.38142.3c, ISNI 000000041936754X, Harvard T.H. Chan School of Public Health, ; Boston, MA USA
                [3 ]The Broad Institute of MIT and Harvard, ( https://ror.org/05a0ya142) Cambridge, MA USA
                [4 ]IEO, European Institute of Oncology IRCCS, ( https://ror.org/02vr0ne26) Milan, Italy
                [5 ]Centre for Microbiology and Environmental Systems Science, University of Vienna, ( https://ror.org/03prydq77) Vienna, Austria
                [6 ]GRID grid.511027.0, Zoe Global, ; London, UK
                [7 ]Department of Nutritional Sciences, King’s College London, ( https://ror.org/0220mzb33) London, UK
                [8 ]Department of Twin Research, King’s College London, ( https://ror.org/0220mzb33) London, UK
                [9 ]GRID grid.4691.a, ISNI 0000 0001 0790 385X, Department of Agricultural Sciences, , University of Naples, ; Naples, Italy
                Author information
                http://orcid.org/0000-0001-7386-5572
                http://orcid.org/0000-0002-8105-9607
                http://orcid.org/0000-0003-2920-5838
                http://orcid.org/0000-0002-9074-9116
                http://orcid.org/0000-0001-6661-4046
                http://orcid.org/0000-0003-0846-6529
                http://orcid.org/0000-0001-8214-9746
                http://orcid.org/0000-0003-1947-1817
                http://orcid.org/0000-0001-9361-7875
                http://orcid.org/0000-0003-2050-3994
                http://orcid.org/0000-0002-9795-0365
                http://orcid.org/0000-0002-8798-7068
                http://orcid.org/0000-0003-3732-1468
                http://orcid.org/0000-0002-1110-0096
                http://orcid.org/0000-0002-1583-5794
                Article
                1688
                10.1038/s41587-023-01688-w
                10635831
                36823356
                9da41f70-9850-4b5c-8df5-1bd675ef0af1
                © The Author(s) 2023

                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/.

                History
                : 7 June 2022
                : 20 January 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: R24DK110499
                Award ID: 1U01CA230551
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100010663, EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council);
                Award ID: 101045015
                Award ID: 716575
                Award ID: 818368
                Award Recipient :
                Categories
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                Custom metadata
                © Springer Nature America, Inc. 2023

                Biotechnology
                data processing,metagenomics
                Biotechnology
                data processing, metagenomics

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