The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Analysis of plant microbe interactions in the era of next generation sequencing technologies
Open accessAbstract
Next generation sequencing (NGS) technologies have impressively accelerated research in biological science during the last years by enabling the production of large volumes of sequence data to a drastically lower price per base, compared to traditional sequencing methods. The recent and ongoing developments in the field allow addressing research questions in plant-microbe biology that were not conceivable just a few years ago. The present review provides an overview of NGS technologies and their usefulness for the analysis of microorganisms that live in association with plants. Possible limitations of the different sequencing systems, in particular sources of errors and bias, are critically discussed and methods are disclosed that help to overcome these shortcomings. A focus will be on the application of NGS methods in metagenomic studies, including the analysis of microbial communities by amplicon sequencing, which can be considered as a targeted metagenomic approach. Different applications of NGS technologies are exemplified by selected research articles that address the biology of the plant associated microbiota to demonstrate the worth of the new methods.
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Citations
Cites
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Cited by
A new view of the fish gut microbiome: advances from next-generation sequencing
Ghanbari, M., Kneifel, W., & Domig, K. J. (2015) · Aquaculture · doi:10.1016/j.aquaculture.2015.06.033 · Cited by 669
Impact of Next-Generation Sequencing Technology in Plant–Microbe Interaction Study
Kumari, A., Sumer, S., Jalan, B., Nongbri, P. L., & Laskar, M. A. (2017) · Microbial Applications Vol.1 · doi:10.1007/978-3-319-52666-9_13 · Cited by 13
Stapleton, A. E. (2014) · Frontiers in Plant Science · doi:10.3389/fpls.2014.00250 · Cited by 2
Metadata
- Authors
- Knief, C.
- Venue
- Frontiers in Plant Science
- Publisher
- Frontiers Media SA
- Published
- 2014-05-21
- Volume
- 5
- Pages
- 216-216
- ISSN
- 1664-462X (ISSN-L)
- OpenAlex
- W1971955401
- Cited by
- 253
- References
- 14
- FWCI
- 8.64
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
