Reverse engineering environmental metatranscriptomes clarifies best practices for eukaryotic assembly

Krinos, Arianna I.; Cohen, Natalie R.; Follows, Michael J.; Alexander, Harriet

doi:10.1186/s12859-022-05121-y

Reverse engineering environmental metatranscriptomes clarifies best practices for eukaryotic assembly

Journal Article · Fri Mar 03 04:00:00 EST 2023 · BMC Bioinformatics

DOI:https://doi.org/10.1186/s12859-022-05121-y· OSTI ID:1959841

; ; Follows, Michael J.;

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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Sponsoring Organization:: USDOE

Grant/Contract Number:: SC0020347

OSTI ID:: 1959841

Journal Information:: BMC Bioinformatics, Journal Name: BMC Bioinformatics Journal Issue: 1 Vol. 24; ISSN 1471-2105

Publisher:: Springer Science + Business MediaCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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