Literature DB >> 35979944

Metagenomics versus total RNA sequencing: most accurate data-processing tools, microbial identification accuracy and perspectives for ecological assessments.

Christopher A Hempel1,2, Natalie Wright1, Julia Harvie1, Jose S Hleap3, Sarah J Adamowicz1, Dirk Steinke1,2.   

Abstract

Metagenomics and total RNA sequencing (total RNA-Seq) have the potential to improve the taxonomic identification of diverse microbial communities, which could allow for the incorporation of microbes into routine ecological assessments. However, these target-PCR-free techniques require more testing and optimization. In this study, we processed metagenomics and total RNA-Seq data from a commercially available microbial mock community using 672 data-processing workflows, identified the most accurate data-processing tools, and compared their microbial identification accuracy at equal and increasing sequencing depths. The accuracy of data-processing tools substantially varied among replicates. Total RNA-Seq was more accurate than metagenomics at equal sequencing depths and even at sequencing depths almost one order of magnitude lower than those of metagenomics. We show that while data-processing tools require further exploration, total RNA-Seq might be a favorable alternative to metagenomics for target-PCR-free taxonomic identifications of microbial communities and might enable a substantial reduction in sequencing costs while maintaining accuracy. This could be particularly an advantage for routine ecological assessments, which require cost-effective yet accurate methods, and might allow for the incorporation of microbes into ecological assessments.
© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.

Entities:  

Year:  2022        PMID: 35979944      PMCID: PMC9458450          DOI: 10.1093/nar/gkac689

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   19.160


  73 in total

1.  Integrated metatranscriptomic and metagenomic analyses of stratified microbial assemblages in the open ocean.

Authors:  Yanmei Shi; Gene W Tyson; John M Eppley; Edward F DeLong
Journal:  ISME J       Date:  2010-12-09       Impact factor: 10.302

2.  De novo assembly and analysis of RNA-seq data.

Authors:  Gordon Robertson; Jacqueline Schein; Readman Chiu; Richard Corbett; Matthew Field; Shaun D Jackman; Karen Mungall; Sam Lee; Hisanaga Mark Okada; Jenny Q Qian; Malachi Griffith; Anthony Raymond; Nina Thiessen; Timothee Cezard; Yaron S Butterfield; Richard Newsome; Simon K Chan; Rong She; Richard Varhol; Baljit Kamoh; Anna-Liisa Prabhu; Angela Tam; YongJun Zhao; Richard A Moore; Martin Hirst; Marco A Marra; Steven J M Jones; Pamela A Hoodless; Inanc Birol
Journal:  Nat Methods       Date:  2010-10-10       Impact factor: 28.547

3.  From barcoding single individuals to metabarcoding biological communities: towards an integrative approach to the study of global biodiversity.

Authors:  Melania E Cristescu
Journal:  Trends Ecol Evol       Date:  2014-08-28       Impact factor: 17.712

Review 4.  Environmental DNA metabarcoding: Transforming how we survey animal and plant communities.

Authors:  Kristy Deiner; Holly M Bik; Elvira Mächler; Mathew Seymour; Anaïs Lacoursière-Roussel; Florian Altermatt; Simon Creer; Iliana Bista; David M Lodge; Natasha de Vere; Michael E Pfrender; Louis Bernatchez
Journal:  Mol Ecol       Date:  2017-10-26       Impact factor: 6.185

5.  Myth of the molecule: DNA barcodes for species cannot replace morphology for identification and classification.

Authors:  Kipling W Will; Daniel Rubinoff
Journal:  Cladistics       Date:  2004-02       Impact factor: 5.254

6.  The Sequence Alignment/Map format and SAMtools.

Authors:  Heng Li; Bob Handsaker; Alec Wysoker; Tim Fennell; Jue Ruan; Nils Homer; Gabor Marth; Goncalo Abecasis; Richard Durbin
Journal:  Bioinformatics       Date:  2009-06-08       Impact factor: 6.937

7.  Comparing and Evaluating Metagenome Assembly Tools from a Microbiologist's Perspective - Not Only Size Matters!

Authors:  John Vollmers; Sandra Wiegand; Anne-Kristin Kaster
Journal:  PLoS One       Date:  2017-01-18       Impact factor: 3.240

8.  Total RNA sequencing reveals multilevel microbial community changes and functional responses to wood ash application in agricultural and forest soil.

Authors:  Toke Bang-Andreasen; Muhammad Zohaib Anwar; Anders Lanzén; Rasmus Kjøller; Regin Rønn; Flemming Ekelund; Carsten Suhr Jacobsen
Journal:  FEMS Microbiol Ecol       Date:  2020-03-01       Impact factor: 4.194

9.  Trimmomatic: a flexible trimmer for Illumina sequence data.

Authors:  Anthony M Bolger; Marc Lohse; Bjoern Usadel
Journal:  Bioinformatics       Date:  2014-04-01       Impact factor: 6.937

10.  The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community.

Authors:  Maria A Sierra; Qianhao Li; Smruti Pushalkar; Bidisha Paul; Tito A Sandoval; Angela R Kamer; Patricia Corby; Yuqi Guo; Ryan Richard Ruff; Alexander V Alekseyenko; Xin Li; Deepak Saxena
Journal:  Genes (Basel)       Date:  2020-08-03       Impact factor: 4.096

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