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Benchmarking second and third-generation sequencing platforms for microbial metagenomics

Shotgun metagenomic sequencing is a common approach for studying the taxonomic diversity and metabolic potential of complex microbial communities. Current methods primarily use second generation short read sequencing, yet advances in third generation long read technologies provide opportunities to o...

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Autores principales: Meslier, Victoria, Quinquis, Benoit, Da Silva, Kévin, Plaza Oñate, Florian, Pons, Nicolas, Roume, Hugo, Podar, Mircea, Almeida, Mathieu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652401/
https://www.ncbi.nlm.nih.gov/pubmed/36369227
http://dx.doi.org/10.1038/s41597-022-01762-z
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author Meslier, Victoria
Quinquis, Benoit
Da Silva, Kévin
Plaza Oñate, Florian
Pons, Nicolas
Roume, Hugo
Podar, Mircea
Almeida, Mathieu
author_facet Meslier, Victoria
Quinquis, Benoit
Da Silva, Kévin
Plaza Oñate, Florian
Pons, Nicolas
Roume, Hugo
Podar, Mircea
Almeida, Mathieu
author_sort Meslier, Victoria
collection PubMed
description Shotgun metagenomic sequencing is a common approach for studying the taxonomic diversity and metabolic potential of complex microbial communities. Current methods primarily use second generation short read sequencing, yet advances in third generation long read technologies provide opportunities to overcome some of the limitations of short read sequencing. Here, we compared seven platforms, encompassing second generation sequencers (Illumina HiSeq 300, MGI DNBSEQ-G400 and DNBSEQ-T7, ThermoFisher Ion GeneStudio S5 and Ion Proton P1) and third generation sequencers (Oxford Nanopore Technologies MinION R9 and Pacific Biosciences Sequel II). We constructed three uneven synthetic microbial communities composed of up to 87 genomic microbial strains DNAs per mock, spanning 29 bacterial and archaeal phyla, and representing the most complex and diverse synthetic communities used for sequencing technology comparisons. Our results demonstrate that third generation sequencing have advantages over second generation platforms in analyzing complex microbial communities, but require careful sequencing library preparation for optimal quantitative metagenomic analysis. Our sequencing data also provides a valuable resource for testing and benchmarking bioinformatics software for metagenomics.
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spelling pubmed-96524012022-11-15 Benchmarking second and third-generation sequencing platforms for microbial metagenomics Meslier, Victoria Quinquis, Benoit Da Silva, Kévin Plaza Oñate, Florian Pons, Nicolas Roume, Hugo Podar, Mircea Almeida, Mathieu Sci Data Data Descriptor Shotgun metagenomic sequencing is a common approach for studying the taxonomic diversity and metabolic potential of complex microbial communities. Current methods primarily use second generation short read sequencing, yet advances in third generation long read technologies provide opportunities to overcome some of the limitations of short read sequencing. Here, we compared seven platforms, encompassing second generation sequencers (Illumina HiSeq 300, MGI DNBSEQ-G400 and DNBSEQ-T7, ThermoFisher Ion GeneStudio S5 and Ion Proton P1) and third generation sequencers (Oxford Nanopore Technologies MinION R9 and Pacific Biosciences Sequel II). We constructed three uneven synthetic microbial communities composed of up to 87 genomic microbial strains DNAs per mock, spanning 29 bacterial and archaeal phyla, and representing the most complex and diverse synthetic communities used for sequencing technology comparisons. Our results demonstrate that third generation sequencing have advantages over second generation platforms in analyzing complex microbial communities, but require careful sequencing library preparation for optimal quantitative metagenomic analysis. Our sequencing data also provides a valuable resource for testing and benchmarking bioinformatics software for metagenomics. Nature Publishing Group UK 2022-11-11 /pmc/articles/PMC9652401/ /pubmed/36369227 http://dx.doi.org/10.1038/s41597-022-01762-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Meslier, Victoria
Quinquis, Benoit
Da Silva, Kévin
Plaza Oñate, Florian
Pons, Nicolas
Roume, Hugo
Podar, Mircea
Almeida, Mathieu
Benchmarking second and third-generation sequencing platforms for microbial metagenomics
title Benchmarking second and third-generation sequencing platforms for microbial metagenomics
title_full Benchmarking second and third-generation sequencing platforms for microbial metagenomics
title_fullStr Benchmarking second and third-generation sequencing platforms for microbial metagenomics
title_full_unstemmed Benchmarking second and third-generation sequencing platforms for microbial metagenomics
title_short Benchmarking second and third-generation sequencing platforms for microbial metagenomics
title_sort benchmarking second and third-generation sequencing platforms for microbial metagenomics
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652401/
https://www.ncbi.nlm.nih.gov/pubmed/36369227
http://dx.doi.org/10.1038/s41597-022-01762-z
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