Re-assembly, quality evaluation, and annotation of 678 microbial eukaryotic reference transcriptomes
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Abstract
Background: De novo transcriptome assemblies are required prior to analyzing RNA sequencing data from a species without an existing reference genome or transcriptome. Despite the prevalence of transcriptomic studies, the effects of using different workflows, or “pipelines," on the resulting assemblies are poorly understood. Here, a pipeline was programmatically automated and used to assemble and annotate raw transcriptomic short-read data collected as part of the Marine Microbial Eukaryotic Transcriptome Sequencing Project. The resulting transcriptome assemblies were evaluated and compared against assemblies that were previously generated with a different pipeline developed by the National Center for Genome Research. Results: New transcriptome assemblies contained the majority of previous contigs as well as new content. On average, 7.8% of the annotated contigs in the new assemblies were novel gene names not found in the previous assemblies. Taxonomic trends were observed in the assembly metrics. Assemblies from the Dinoflagellata showed a higher number of contigs and unique k-mers than transcriptomes from other phyla, while assemblies from Ciliophora had a lower percentage of open reading frames compared to other phyla. Conclusions: Given current bioinformatics approaches, there is no single “best” reference transcriptome for a particular set of raw data. As the optimum transcriptome is a moving target, improving (or not) with new tools and approaches, automated and programmable pipelines are invaluable for managing the computationally intensive tasks required for re-processing large sets of samples with revised pipelines and ensuring a common evaluation workflow is applied to all samples. Thus, re-assembling existing data with new tools using automated and programmable pipelines may yield more accurate identification of taxon-specific trends across samples in addition to novel and useful products for the community.
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MMETSP transcriptomic samples cover a wide range of primary and complex algae and were recently re-assembled.
“MMETSP transcriptomic samples [9] cover a wide range of primary and complex algae and were recently re-assembled [10].”
From Decontamination, pooling and dereplication of the 678 samples of the Marine Microbial Eukaryote Transcriptome Sequencing Project (2021) · cites this paper as [10]
MMETSP transcriptomes represent a valuable resource for phylogenomic analyses, owing to their broad and rich taxonomic sampling, especially of photosynthetic species.
“MMETSP (Marine Microbial Eukaryote Transcriptome Sequencing Project) transcriptomes represent a valuable resource for phylogenomic analyses, owing to their broad and rich taxonomic sampling, especially of photosynthetic species.”
From Decontamination, pooling and dereplication of the 678 samples of the Marine Microbial Eukaryote Transcriptome Sequencing Project (2021) · cites this paper as [10]
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- [65]Johnson LK, Alexander H, Brown CT Supporting data for ‘re-assembly, quality evaluation, and annotation of 678 microbial eukaryotic reference transcriptomes’; GigaScience Database 2018 10.5524/100522. PMC6481552 30544207 · DOI
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- Authors
- Johnson, L. K., Alexander, H., & Brown, C. T.
- Affiliations
- University of California, Davis (US)
- Woods Hole Oceanographic Institution (US)
- Corresponding author
- Brown, C Titus
- Venue
- GigaScience
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-12-13
- Volume
- 8
- Issue
- 4
- ISSN
- 2047-217X (ISSN-L)
- PMC
- PMC6481552
- OpenAlex
- W2952126099
- Cited by
- 94
- References
- 68
- Citations by year
- 2026: 5 · 2025: 11 · 2024: 13 · 2023: 11 · 2022: 14 · 2021: 18 · 2020: 11 · 2019: 8 · 2018: 3
- FWCI
- 3.56
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- GigaScience (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Open Access Server of the Woods Hole Scientific Community (Woods Hole Scientific Community) (submittedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Funders
- Gordon and Betty Moore Foundation (GBMF4551)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protist diversity and phylogeny
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- de novo transcriptome assembly, reference transcriptome, automated bioinformatics pipeline, transcriptome annotation, gene discovery, dinoflagellates, ciliates, open reading frames
- MeSH terms
- Genome, Computational Biology, Gene Expression Profiling, Genomics, Databases, Genetic, Eukaryota, Workflow, High-Throughput Nucleotide Sequencing, Transcriptome
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