Reverse engineering environmental metatranscriptomes clarifies best practices for eukaryotic assembly.

Area of Science:

• Marine biology
• Microbial ecology
• Genomics

Background:

• Microbial eukaryotes in the ocean are vital for ecosystem services like primary production and carbon cycling.
• Omics tools, particularly metatranscriptomics, are revolutionizing the study of these diverse communities by revealing near real-time gene expression and metabolic activity.

Purpose of the Study:

• To present and validate a workflow for eukaryotic metatranscriptome assembly.
• To provide an open-source tool for simulating environmental metatranscriptomes for testing and validation.
• To reanalyze existing metatranscriptomic datasets using the developed approach.

Main Methods:

• Development of a novel workflow for eukaryotic metatranscriptome assembly.
• Validation using real and simulated (in-silico mock community) eukaryotic community-level expression data.
• Application of the analysis approach to previously published metatranscriptomic datasets.

Main Results:

• The workflow successfully recapitulates real and manufactured eukaryotic community-level expression data.
• A multi-assembler strategy was identified as superior for eukaryotic metatranscriptome assembly.
• The approach demonstrated improved taxonomic and functional annotations from an in-silico mock community.

Conclusions:

• A multi-assembler approach enhances the accuracy of eukaryotic metatranscriptome assembly.
• Systematic validation of assembly and annotation methods is crucial for reliable measurements of microbial eukaryotic community composition and function.