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      Short- and long-read metagenomics of urban and rural South African gut microbiomes reveal a transitional composition and undescribed taxa

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          Abstract

          Human gut microbiome research focuses on populations living in high-income countries and to a lesser extent, non-urban agriculturalist and hunter-gatherer societies. The scarcity of research between these extremes limits our understanding of how the gut microbiota relates to health and disease in the majority of the world’s population. Here, we evaluate gut microbiome composition in transitioning South African populations using short- and long-read sequencing. We analyze stool from adult females living in rural Bushbuckridge ( n = 118) or urban Soweto ( n = 51) and find that these microbiomes are taxonomically intermediate between those of individuals living in high-income countries and traditional communities. We demonstrate that reference collections are incomplete for characterizing microbiomes of individuals living outside high-income countries, yielding artificially low beta diversity measurements, and generate complete genomes of undescribed taxa, including Treponema, Lentisphaerae, and Succinatimonas. Our results suggest that the gut microbiome of South Africans does not conform to a simple “western-nonwestern” axis and contains undescribed microbial diversity.

          Abstract

          In this study, Wits and Stanford researchers use short- and long-read DNA sequencing to profile the gut microbiome of women living in rural and urban South Africa and identify transitional composition, high inter-individual diversity, and many undescribed taxa.

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          Most cited references118

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

              The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
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                Author and article information

                Contributors
                Scott.Hazelhurst@wits.ac.za
                asbhatt@stanford.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                22 February 2022
                22 February 2022
                2022
                : 13
                : 926
                Affiliations
                [1 ]GRID grid.168010.e, ISNI 0000000419368956, Department of Genetics, , Stanford University, ; Stanford, CA USA
                [2 ]GRID grid.11951.3d, ISNI 0000 0004 1937 1135, Sydney Brenner Institute for Molecular Bioscience, , University of the Witwatersrand, ; Johannesburg, South Africa
                [3 ]GRID grid.168010.e, ISNI 0000000419368956, School of Medicine, , Stanford University, ; Stanford, CA USA
                [4 ]GRID grid.416657.7, ISNI 0000 0004 0630 4574, Division of Human Genetics, School of Pathology, Faculty of Health Sciences, , National Health Laboratory Service & University of the Witwatersrand, ; Johannesburg, South Africa
                [5 ]GRID grid.11951.3d, ISNI 0000 0004 1937 1135, SAMRC Developmental Pathways for Health Research Unit, Department of Paediatrics, , University of the Witwatersrand, ; Johannesburg, South Africa
                [6 ]GRID grid.5491.9, ISNI 0000 0004 1936 9297, School of Human Development and Health, , University of Southampton, ; Southampton, UK
                [7 ]GRID grid.11951.3d, ISNI 0000 0004 1937 1135, MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, , University of the Witwatersrand, ; Johannesburg, South Africa
                [8 ]GRID grid.420958.2, ISNI 0000 0001 0701 0189, INDEPTH Network, East Legon, ; Accra, Ghana
                [9 ]GRID grid.11951.3d, ISNI 0000 0004 1937 1135, School of Electrical and Information Engineering, , University of the Witwatersrand, ; Johannesburg, South Africa
                [10 ]GRID grid.168010.e, ISNI 0000000419368956, Department of Medicine (Hematology, Blood and Marrow Transplantation), , Stanford University, ; Stanford, CA USA
                Author information
                http://orcid.org/0000-0001-8877-2360
                http://orcid.org/0000-0002-3033-7873
                http://orcid.org/0000-0001-7124-3788
                http://orcid.org/0000-0003-0744-7588
                http://orcid.org/0000-0003-3339-3931
                http://orcid.org/0000-0002-4876-0848
                http://orcid.org/0000-0002-0581-149X
                http://orcid.org/0000-0001-8099-2975
                Article
                27917
                10.1038/s41467-021-27917-x
                8863827
                35194028
                ea593fbe-fc1a-4592-8718-30916ce8cf10
                © The Author(s) 2022

                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
                : 2 July 2021
                : 25 November 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000001, National Science Foundation (NSF);
                Award ID: GRFP
                Award Recipient :
                Funded by: Stanford CEHG
                Funded by: Stanford Graduate Fellowship
                Funded by: FundRef https://doi.org/10.13039/100000061, U.S. Department of Health & Human Services | NIH | Fogarty International Center (FIC);
                Funded by: FundRef https://doi.org/10.13039/100000060, U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (NIAID);
                Award ID: R01 AI148623
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: P30 CA124435
                Award Recipient :
                Funded by: Stanford Center for Innovation in Global Health; Rosenkranz Prize
                Categories
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                © The Author(s) 2022

                Uncategorized
                genomics,bacteria,developing world
                Uncategorized
                genomics, bacteria, developing world

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