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Taxonomic and Functional Compositions Impacted by the Quality of Metatranscriptomic Assemblies

Lau, Maggie C. Y. and Harris, Rachel L. and Oh, Youmi and Yi, Min Joo and Behmard, Aida and Onstott, Tullis C. (2018) Taxonomic and Functional Compositions Impacted by the Quality of Metatranscriptomic Assemblies. Frontiers in Microbiology, 9 . Art. No. 1235. ISSN 1664-302X. http://resolver.caltech.edu/CaltechAUTHORS:20180705-083358686

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Abstract

Metatranscriptomics has recently been applied to investigate the active biogeochemical processes and elemental cycles, and in situ responses of microbiomes to environmental stimuli and stress factors. De novo assembly of RNA-Sequencing (RNA-Seq) data can reveal a more detailed description of the metabolic interactions amongst the active microbial communities. However, the quality of the assemblies and the depiction of the metabolic network provided by various de novo assemblers have not yet been thoroughly assessed. In this study, we compared 15 de novo metatranscriptomic assemblies for a fracture fluid sample collected from a borehole located at 1.34 km below land surface in a South African gold mine. These assemblies were constructed from total, non-coding, and coding reads using five de novo transcriptomic assemblers (Trans-ABySS, Trinity, Oases, IDBA-tran, and Rockhopper). They were evaluated based on the number of transcripts, transcript length, range of transcript coverage, continuity, percentage of transcripts with confident annotation assignments, as well as taxonomic and functional diversity patterns. The results showed that these parameters varied considerably among the assemblies, with Trans-ABySS and Trinity generating the best assemblies for non-coding and coding RNA reads, respectively, because the high number of transcripts assembled covered a wide expression range, and captured extensively the taxonomic and metabolic gene diversity, respectively. We concluded that the choice of de novo transcriptomic assemblers impacts substantially the taxonomic and functional compositions. Care should be taken to obtain high-quality assemblies for informing the in situ metabolic landscape.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.3389/fmicb.2018.01235DOIArticle
Additional Information:© 2018 Lau, Harris, Oh, Yi, Behmard and Onstott. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Received: 09 January 2018; Accepted: 22 May 2018; Published: 20 June 2018. We thank Matthew Cahn (Department of Molecular Biology, Princeton University), and staff of Research Computing (Office of Information Technology, Princeton University) for their technical support with the computational analyses. We express our appreciation to Cara Magnabosco for her feedback on the early drafts. We thank sincerely to the reviewers for their constructive comments that have greatly improved the overall quality of this manuscript. Author Contributions: ML: conceived the study. ML, RH, YO, MY, and TO: assembled metatranscriptomic data using different algorithms and performed post-assembly statistics analysis. ML: compared the assemblies. AB and ML: compiled the source codes for public release. All authors discussed the results and commented on the manuscripts drafted by ML. This work was supported by funding from National Science Foundation [Grants EAR-1739151 and DEB-1441646 (to TO)], and the Deep Carbon Observatory (Alfred P. Sloan Foundation) [Sloan 2013-10-03, subaward 48045 (to ML)]. RH was supported by NSF Graduate Research Fellowship (DGE-1148900). Disclaimer: Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Funders:
Funding AgencyGrant Number
NSFEAR-1739151
NSFDEB-1441646
Deep Carbon ObservatoryUNSPECIFIED
Alfred P. Sloan Foundation48045
NSF Graduate Research FellowshipDGE-1148900
Subject Keywords:RNA-Sequencing, de novo metatranscriptomics, taxonomic composition, metabolic functions, metaproteomics
Record Number:CaltechAUTHORS:20180705-083358686
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180705-083358686
Official Citation:Lau MCY, Harris RL, Oh Y, Yi MJ, Behmard A and Onstott TC (2018) Taxonomic and Functional Compositions Impacted by the Quality of Metatranscriptomic Assemblies. Front. Microbiol. 9:1235. doi: 10.3389/fmicb.2018.01235
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:87545
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:05 Jul 2018 17:31
Last Modified:05 Jul 2018 17:31

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