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Benchmarking and optimizing qualitative and quantitative pipelines in environmental metatranscriptomics using mixture

Weiyi Li1, Qilian Fan1, Yi Yang1

  • 1School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.

ISME Communications
|June 30, 2025
PubMed
Summary

Metatranscriptomic analysis reveals ecosystem gene expression. This study benchmarks computational methods, proposing an optimized pipeline (MT-Enviro) for accurate microbiome analysis, especially in extreme environments.

Keywords:
environmental microbiomemetatranscriptomic analysismock communitiesoptimizationpipelinequantitative analysistaxonomic profiling

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Area of Science:

  • Microbial ecology
  • Bioinformatics
  • Genomics

Background:

  • Metatranscriptomic analysis provides dynamic gene expression insights into ecosystems.
  • Existing computational methods lack comprehensive benchmarking, particularly for extreme environments with unculturable microbes and limited reference genomes.
  • Concerns exist regarding the accuracy of qualitative and quantitative profilers in metatranscriptomic studies.

Purpose of the Study:

  • To benchmark computational methods for metatranscriptomic analysis.
  • To address concerns about accuracy in profiling microbial communities, especially in challenging environments.
  • To propose an optimized and validated pipeline for environmental metatranscriptomic data analysis.

Main Methods:

  • Conducted a benchmark experiment using single-species and mixed samples with controlled compositions and varying evenness.
  • Sequenced 1 metagenome and 24 metatranscriptome samples.
  • Compared 36 combinations of analysis methods covering sample preparation, quality control, rRNA removal, alignment, taxonomic profiling, and transcript quantification.

Main Results:

  • Established metrics for assessing and comparing different stages of the metatranscriptomic analysis workflow.
  • Evaluated the performance of various computational methods under simulated low annotation rates and high heterogeneity.
  • Identified an optimized pipeline, MT-Enviro, for enhanced metatranscriptomic analysis.

Conclusions:

  • The study provides a comprehensive framework for benchmarking metatranscriptomic analysis tools.
  • The proposed MT-Enviro pipeline offers an optimized solution for environmental microbiome analysis.
  • The findings support improved accuracy and reliability in interpreting gene expression from complex microbial ecosystems.