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TaxMapper: an analysis tool, reference database and workflow for metatranscriptome analysis of eukaryotic

Daniela Beisser1, Nadine Graupner2, Lars Grossmann2

  • 1Biodiversity, University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, Germany. daniela.beisser@uni-due.de.

BMC Genomics
|October 18, 2017
PubMed
Summary

A new tool, TaxMapper, and workflow improve eukaryotic metatranscriptome analysis by enhancing taxonomic assignment accuracy for microbial communities. This advances high-throughput sequencing applications in marine microbial ecology.

Keywords:
Metatranscriptome analysisProtistsTaxonomic assignment

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Area of Science:

  • Microbial Ecology
  • Bioinformatics
  • Marine Biology

Background:

  • High-throughput sequencing (HTS) enables metatranscriptome analysis of microbial communities.
  • Current eukaryotic metatranscriptome analysis is limited by fragmented reference databases and lack of automated workflows.
  • Accurate taxonomic profiling of eukaryotes in complex microbial ecosystems remains challenging.

Purpose of the Study:

  • To develop an improved method for taxonomic assignment in eukaryotic metatranscriptomics.
  • To create a comprehensive reference database for microeukaryotic transcriptomes.
  • To establish an automated workflow for robust metatranscriptome data analysis.

Main Methods:

  • Compilation of 142 eukaryotic reference transcriptomes/genomes covering major supergroups.
  • Development of the TaxMapper tool for reliable read mapping and assignment filtering.
  • Integration of TaxMapper into a Snakemake workflow for quality assessment, annotation, and statistical analysis.

Main Results:

  • Creation of an annotated microeukaryotic reference database.
  • TaxMapper demonstrated superior performance in taxonomic assignment compared to standard methods.
  • The Snakemake workflow facilitates comprehensive metatranscriptome analysis, including environmental data integration.

Conclusions:

  • TaxMapper significantly increases the accuracy of true positive taxonomic assignments in eukaryotic metatranscriptomes.
  • The developed tool and workflow provide an open-source solution for researchers.
  • This advancement empowers broader application of metatranscriptomics to study eukaryotic microbial communities.