Re-assembly, quality evaluation, and annotation of 678 microbial eukaryotic reference transcriptomes

dc.contributor.author Johnson, Lisa K.
dc.contributor.author Alexander, Harriet
dc.contributor.author Brown, C. Titus
dc.date.accessioned 2019-09-05T20:55:06Z
dc.date.available 2019-09-05T20:55:06Z
dc.date.issued 2019-04
dc.description © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Johnson, L. K., Alexander, H., & Brown, C. T. Re-assembly, quality evaluation, and annotation of 678 microbial eukaryotic reference transcriptomes. Gigascience, 8(4), (2019): giy158, doi: 10.1093/gigascience/giy158. en_US
dc.description.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. en_US
dc.description.sponsorship Funding was provided by the Gordon and Betty Moore Foundation under award number GBMF4551 to C.T.B. Jetstream cloud platform was used with XSEDE allocation TG-BIO160028 [66, 67]. en_US
dc.identifier.citation Johnson, L. K., Alexander, H., & Brown, C. T. (2019). Re-assembly, quality evaluation, and annotation of 678 microbial eukaryotic reference transcriptomes. Gigascience, 8(4), giy158. en_US
dc.identifier.doi 10.1093/gigascience/giy158
dc.identifier.uri https://hdl.handle.net/1912/24513
dc.publisher Oxford University Press en_US
dc.relation.uri https://doi.org/10.1093/gigascience/giy158
dc.rights Attribution 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ *
dc.subject marine microbial eukaryote en_US
dc.subject transcriptome assembly en_US
dc.subject automated pipeline en_US
dc.subject re-analysis en_US
dc.title Re-assembly, quality evaluation, and annotation of 678 microbial eukaryotic reference transcriptomes en_US
dc.type Article en_US
dspace.entity.type Publication
relation.isAuthorOfPublication e4b91e8f-672d-407b-83ed-b9fec64cc480
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relation.isAuthorOfPublication 6954fbae-53a5-4823-8462-66615c297004
relation.isAuthorOfPublication.latestForDiscovery e4b91e8f-672d-407b-83ed-b9fec64cc480
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