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
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066
Accurate whole human genome sequencing using reversible terminator chemistry
Bentley, D. R., Balasubramanian, S., Swerdlow, H. P., Smith, G. P., Milton, J., Brown, C. G., Hall, K. P., Evers, D. J., Barnes, C. L., Bignell, H. R., et al. (2008) · Nature · doi:10.1038/nature07517 · Cited by 3,684
Structure and functions of the bacterial microbiota of plants
Bulgarelli, D., Schlaeppi, K., Spaepen, S., van Themaat, E. V. L., & Schulze-Lefert, P. (2013) · Annual Review of Plant Biology · doi:10.1146/annurev-arplant-050312-120106 · Cited by 3,308
PANDAseq: paired-end assembler for Illumina sequences
Masella, A. P., Bartram, A. K., Truszkowski, J. M., Brown, D. G., & Neufeld, J. D. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-31 · Cited by 2,132
Reducing the Effects of PCR Amplification and Sequencing Artifacts on 16S rRNA-Based Studies
Schloss, P. D., Gevers, D., & Westcott, S. L. (2011) · PLoS ONE · doi:10.1371/journal.pone.0027310 · Cited by 2,112
Quail, M., Smith, M. E., Coupland, P., Otto, T. D., Harris, S. R., Connor, T. R., Bertoni, A., Swerdlow, H. P., & Gu, Y. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-341 · Cited by 2,031
Ironing out the wrinkles in the rare biosphere through improved OTU clustering
Huse, S. M., Welch, D. M., Morrison, H. G., & Sogin, M. L. (2010) · Environmental Microbiology · doi:10.1111/j.1462-2920.2010.02193.x · Cited by 1,346
Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform
Kircher, M., Sawyer, S., & Meyer, M. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr771 · Cited by 1,106 · cited 3×
“…the use of a dual barcoding strategy is proposed for paired end sequencing in order to decrease sample misidentification rate or to decrease the number of individually tagged PCR primers (Gloor et al., 2010; Carlsen et al., 2012; Degnan and Ochman, 2012; Kircher et al., 2012; Kozich et al., 2013).”
BackgroundSequencing technologies and genome sequencing
Pareek, C. S., Smoczynski, R., & Tretyn, A. (2011) · Journal of Applied Genetics · doi:10.1007/s13353-011-0057-x · Cited by 868
Biases in Illumina transcriptome sequencing caused by random hexamer priming
Hansen, K. D., Brenner, S. E., & Dudoit, S. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq224 · Cited by 713
The impact of next-generation sequencing on genomics
Zhang, J., Chiodini, R., Badr, A., & Zhang, G. (2011) · Journal of Genetics and Genomics · doi:10.1016/j.jgg.2011.02.003 · Cited by 577 · cited 2×
“A detailed description of second generation sequencing platforms and principles can be found in dedicated reviews (e.g., Voelkerding et al., 2009; Metzker, 2010; Glenn, 2011; Pareek et al., 2011; Zhang et al., 2011; Liu et al., 2012; Shokralla et al., 2012; Mardis, 2013; Morey et al., 2013).”
BackgroundMicrobiome profiling by Illumina sequencing of combinatorial sequence-tagged PCR products
Gloor, G. B., Hummelen, R., Macklaim, J. M., Dickson, R. J., Fernandes, A. D., MacPhee, R., & Reid, G. (2010) · PLoS ONE · doi:10.1371/journal.pone.0015406 · Cited by 330
Effects of GC Bias in Next-Generation-Sequencing Data on De Novo Genome Assembly
Chen, Y.-C., Liu, T., Yu, C.-H., Chiang, T.-Y., & Hwang, C.-C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0062856 · Cited by 285
Unlocking short read sequencing for metagenomics
Rodrigue, S., Materna, A. C., Timberlake, S. C., Blackburn, M. C., Malmstrom, R. R., Alm, E. J., & Chisholm, S. W. (2010) · PLoS ONE · doi:10.1371/journal.pone.0011840 · Cited by 168
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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