Title |
Analysis of plant microbe interactions in the era of next generation sequencing technologies
|
---|---|
Published in |
Frontiers in Plant Science, May 2014
|
DOI | 10.3389/fpls.2014.00216 |
Pubmed ID | |
Authors |
Claudia Knief |
Abstract |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 22% |
France | 1 | 11% |
Switzerland | 1 | 11% |
Unknown | 5 | 56% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 56% |
Scientists | 3 | 33% |
Science communicators (journalists, bloggers, editors) | 1 | 11% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 1% |
Brazil | 4 | <1% |
France | 3 | <1% |
Chile | 2 | <1% |
Netherlands | 2 | <1% |
India | 2 | <1% |
Portugal | 1 | <1% |
Sweden | 1 | <1% |
South Africa | 1 | <1% |
Other | 5 | <1% |
Unknown | 572 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 152 | 25% |
Researcher | 121 | 20% |
Student > Master | 87 | 15% |
Student > Bachelor | 49 | 8% |
Student > Doctoral Student | 36 | 6% |
Other | 81 | 14% |
Unknown | 73 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 314 | 52% |
Biochemistry, Genetics and Molecular Biology | 91 | 15% |
Environmental Science | 31 | 5% |
Immunology and Microbiology | 13 | 2% |
Computer Science | 9 | 2% |
Other | 36 | 6% |
Unknown | 105 | 18% |