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Reverse engineering environmental metatranscriptomes clarifies best practices for eukaryotic assembly
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12859_2022_Article_5121.pdf
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5.16 MB
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Adobe PDF
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5bd87e0c4ed92e5c13cc6dea49076cd6
Author(s)
Krinos, Arianna I.
Cohen, Natalie R.
Follows, Michael J.
Alexander, Harriet
Date Issued
March 3, 2023
Publisher
BioMed Central
Citation
BMC Bioinformatics. 2023 Mar 03;24(1):74
Version
Final published version
Abstract
Abstract
Background
Diverse communities of microbial eukaryotes in the global ocean provide a variety of essential ecosystem services, from primary production and carbon flow through trophic transfer to cooperation via symbioses. Increasingly, these communities are being understood through the lens of omics tools, which enable high-throughput processing of diverse communities. Metatranscriptomics offers an understanding of near real-time gene expression in microbial eukaryotic communities, providing a window into community metabolic activity.
Results
Here we present a workflow for eukaryotic metatranscriptome assembly, and validate the ability of the pipeline to recapitulate real and manufactured eukaryotic community-level expression data. We also include an open-source tool for simulating environmental metatranscriptomes for testing and validation purposes. We reanalyze previously published metatranscriptomic datasets using our metatranscriptome analysis approach.
Conclusion
We determined that a multi-assembler approach improves eukaryotic metatranscriptome assembly based on recapitulated taxonomic and functional annotations from an in-silico mock community. The systematic validation of metatranscriptome assembly and annotation methods provided here is a necessary step to assess the fidelity of our community composition measurements and functional content assignments from eukaryotic metatranscriptomes.
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1186/s12859-022-05121-y
