Metagenomic information recovery from human stool samples is influenced by sequencing depth and profiling method

Tasha M. Santiago-Rodriguez, Aaron Garoutte, Emmase Adams, Waleed Nasser, Matthew C. Ross, Alex La Reau, Zachariah Henseler, Tonya Ward, Dan Knights, Joseph F. Petrosino, Emily B. Hollister

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Sequencing of the 16S rRNA gene (16S) has long been a go-to method for microbiome characterization due to its accessibility and lower cost compared to shotgun metagenomic sequencing (SMS). However, 16S sequencing rarely provides species-level resolution and cannot provide direct assessment of other taxa (e.g., viruses and fungi) or functional gene content. Shallow shotgun metagenomic sequencing (SSMS) has emerged as an approach to bridge the gap between 16S sequencing and deep metagenomic sequencing. SSMS is cost-competitive with 16S sequencing, while also providing species-level resolution and functional gene content insights. In the present study, we evaluated the effects of sequencing depth on marker gene-mapping-and alignment-based annotation of bacteria in healthy human stool samples. The number of identified taxa decreased with lower sequencing depths, particularly with the marker gene-mapping-based approach. Other annotations, including viruses and pathways, also showed a depth-dependent effect on feature recovery. These results refine the understanding of the suitability and shortcomings of SSMS, as well as annotation tools for metagenomic analyses in human stool samples. Results may also translate to other sample types and may open the opportunity to explore the effect of sequencing depth and annotation method.

Original languageEnglish (US)
Article number1380
Pages (from-to)1-17
Number of pages17
JournalGenes
Volume11
Issue number11
DOIs
StatePublished - Nov 2020

Bibliographical note

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Alignment
  • Marker gene
  • Microbiome
  • Shallow sequencing
  • Shotgun metagenomic sequencing
  • Virome

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