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Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies
In a large cohort of 1,772 participants from the Hispanic Community Health Study/Study of Latinos with overlapping 16SV4 rRNA gene (bacterial amplicon), ITS1 (fungal amplicon), and shotgun sequencing data, we demonstrate that 16SV4 amplicon sequencing and shotgun metagenomics offer the same level of...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9939430/ https://www.ncbi.nlm.nih.gov/pubmed/36814836 http://dx.doi.org/10.1016/j.crmeth.2022.100391 |
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author | Usyk, Mykhaylo Peters, Brandilyn A. Karthikeyan, Smruthi McDonald, Daniel Sollecito, Christopher C. Vazquez-Baeza, Yoshiki Shaffer, Justin P. Gellman, Marc D. Talavera, Gregory A. Daviglus, Martha L. Thyagarajan, Bharat Knight, Rob Qi, Qibin Kaplan, Robert Burk, Robert D. |
author_facet | Usyk, Mykhaylo Peters, Brandilyn A. Karthikeyan, Smruthi McDonald, Daniel Sollecito, Christopher C. Vazquez-Baeza, Yoshiki Shaffer, Justin P. Gellman, Marc D. Talavera, Gregory A. Daviglus, Martha L. Thyagarajan, Bharat Knight, Rob Qi, Qibin Kaplan, Robert Burk, Robert D. |
author_sort | Usyk, Mykhaylo |
collection | PubMed |
description | In a large cohort of 1,772 participants from the Hispanic Community Health Study/Study of Latinos with overlapping 16SV4 rRNA gene (bacterial amplicon), ITS1 (fungal amplicon), and shotgun sequencing data, we demonstrate that 16SV4 amplicon sequencing and shotgun metagenomics offer the same level of taxonomic accuracy for bacteria at the genus level even at shallow sequencing depths. In contrast, for fungal taxa, we did not observe meaningful agreements between shotgun and ITS1 amplicon results. Finally, we show that amplicon and shotgun data can be harmonized and pooled to yield larger microbiome datasets with excellent agreement (<1% effect size variance across three independent outcomes) using pooled amplicon/shotgun data compared to pure shotgun metagenomic analysis. Thus, there are multiple approaches to study the microbiome in epidemiological studies, and we provide a demonstration of a powerful pooling approach that will allow researchers to leverage the massive amount of amplicon sequencing data generated over the last two decades. |
format | Online Article Text |
id | pubmed-9939430 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99394302023-02-21 Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies Usyk, Mykhaylo Peters, Brandilyn A. Karthikeyan, Smruthi McDonald, Daniel Sollecito, Christopher C. Vazquez-Baeza, Yoshiki Shaffer, Justin P. Gellman, Marc D. Talavera, Gregory A. Daviglus, Martha L. Thyagarajan, Bharat Knight, Rob Qi, Qibin Kaplan, Robert Burk, Robert D. Cell Rep Methods Resource In a large cohort of 1,772 participants from the Hispanic Community Health Study/Study of Latinos with overlapping 16SV4 rRNA gene (bacterial amplicon), ITS1 (fungal amplicon), and shotgun sequencing data, we demonstrate that 16SV4 amplicon sequencing and shotgun metagenomics offer the same level of taxonomic accuracy for bacteria at the genus level even at shallow sequencing depths. In contrast, for fungal taxa, we did not observe meaningful agreements between shotgun and ITS1 amplicon results. Finally, we show that amplicon and shotgun data can be harmonized and pooled to yield larger microbiome datasets with excellent agreement (<1% effect size variance across three independent outcomes) using pooled amplicon/shotgun data compared to pure shotgun metagenomic analysis. Thus, there are multiple approaches to study the microbiome in epidemiological studies, and we provide a demonstration of a powerful pooling approach that will allow researchers to leverage the massive amount of amplicon sequencing data generated over the last two decades. Elsevier 2023-01-23 /pmc/articles/PMC9939430/ /pubmed/36814836 http://dx.doi.org/10.1016/j.crmeth.2022.100391 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Resource Usyk, Mykhaylo Peters, Brandilyn A. Karthikeyan, Smruthi McDonald, Daniel Sollecito, Christopher C. Vazquez-Baeza, Yoshiki Shaffer, Justin P. Gellman, Marc D. Talavera, Gregory A. Daviglus, Martha L. Thyagarajan, Bharat Knight, Rob Qi, Qibin Kaplan, Robert Burk, Robert D. Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies |
title | Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies |
title_full | Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies |
title_fullStr | Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies |
title_full_unstemmed | Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies |
title_short | Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies |
title_sort | comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies |
topic | Resource |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9939430/ https://www.ncbi.nlm.nih.gov/pubmed/36814836 http://dx.doi.org/10.1016/j.crmeth.2022.100391 |
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