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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...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
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.
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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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