Taxonomic and functional compositions impacted by the quality of metatranscriptomic assemblies

Maggie C.Y. Lau, Rachel L. Harris, Youmi Oh, Min Joo Yi, Aida Behmard, Tullis C. Onstott

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Metatranscriptomics has recently been applied to investigate the active biogeochemical processes and elemental cycles, and in situ responses of microbiomes to environmental stimuli and stress factors. De novo assembly of RNA-Sequencing (RNA-Seq) data can reveal a more detailed description of the metabolic interactions amongst the active microbial communities. However, the quality of the assemblies and the depiction of the metabolic network provided by various de novo assemblers have not yet been thoroughly assessed. In this study, we compared 15 de novo metatranscriptomic assemblies for a fracture fluid sample collected from a borehole located at 1.34 km below land surface in a South African gold mine. These assemblies were constructed from total, non-coding, and coding reads using five de novo transcriptomic assemblers (Trans-ABySS, Trinity, Oases, IDBA-tran, and Rockhopper). They were evaluated based on the number of transcripts, transcript length, range of transcript coverage, continuity, percentage of transcripts with confident annotation assignments, as well as taxonomic and functional diversity patterns. The results showed that these parameters varied considerably among the assemblies, with Trans-ABySS and Trinity generating the best assemblies for non-coding and coding RNA reads, respectively, because the high number of transcripts assembled covered a wide expression range, and captured extensively the taxonomic and metabolic gene diversity, respectively. We concluded that the choice of de novo transcriptomic assemblers impacts substantially the taxonomic and functional compositions. Care should be taken to obtain high-quality assemblies for informing the in situ metabolic landscape.

Original languageEnglish (US)
Article number1235
JournalFrontiers in Microbiology
Volume9
Issue numberJUN
DOIs
StatePublished - Jun 20 2018

All Science Journal Classification (ASJC) codes

  • Microbiology
  • Microbiology (medical)

Keywords

  • De novo metatranscriptomics
  • Metabolic functions
  • Metaproteomics
  • RNA-Sequencing
  • Taxonomic composition

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