Toggle Main Menu Toggle Search

Open Access padlockePrints

The impact of high throughput sequencing on plant health diagnostics

Lookup NU author(s): Professor Neil Boonham

Downloads


Licence

This is the authors' accepted manuscript of an article that has been published in its final definitive form by Springer Netherlands, 2018.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

© 2018, Koninklijke Nederlandse Planteziektenkundige Vereniging. High throughput sequencing informed diagnostics is revolutionising plant pathology. The application of this technology is most advanced in plant virology, where it is already becoming a front-line diagnostic tool and it is envisaged that for other types of pathogen and pests this will be the case in the near future. However, there are implications to deploying this technology due to a number of technical and scientific challenges. Firstly, interpretation of data and the assessment of plant health risk against a limited baseline of existing knowledge of the presence of pathogens in a given geographic region. Secondly, evidence of causality and the separation of pathogenic from commensal organisms in the sequence data, thirdly, the tension between the generation of a rapid sequence result with the necessary but laborious epidemiological characterisation in support of plant health risk assessment. Finally, the validation and accreditation of methods based on this rapidly evolving technology. These in turn present challenges for plant health policy and regulation. This review discusses the development of this technology, its application in plant health diagnostics, and explores the implications of applying this technology in the plant health setting.


Publication metadata

Author(s): Adams IP, Fox A, Boonham N, Massart S, De Jonghe K

Publication type: Article

Publication status: Published

Journal: European Journal of Plant Pathology

Year: 2018

Volume: 152

Issue: 4

Pages: 909-919

Print publication date: 01/12/2018

Online publication date: 11/09/2018

Acceptance date: 08/08/2018

Date deposited: 26/10/2018

ISSN (print): 0929-1873

ISSN (electronic): 1573-8469

Publisher: Springer Netherlands

URL: https://doi.org/10.1007/s10658-018-1570-0

DOI: 10.1007/s10658-018-1570-0


Altmetrics

Altmetrics provided by Altmetric


Share