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From genomes to forest management – tackling invasive Phytophthora species in the era of genomics

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Version 2 2020-03-06, 15:01
Version 1 2019-07-26, 18:36
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posted on 2020-03-06, 15:01 authored by S. Keriö, H. A. Daniels, M. Gómez-Gallego, J. F. Tabima, R. R. Lenz, K. L. Søndreli, N. J. Grünwald, N. Williams, R. Mcdougal, J. M. LeBoldus

Species of Phytophthora pose one of the most serious biosecurity threats to forest ecosystems worldwide. Despite management efforts and increased awareness of forest pathogens, there is continued introduction and spread of Phytophthora species. Uncertainty about the center of origin for many of the invasive species hampers disease control efforts. Additionally, the management efforts are often made impossible either by the vast host range or the extreme susceptibility of naïve hosts. In this review, we discuss how genomics has shed light on the extent of spread and destruction caused by invasive Phytophthora species, and how approaches leveraged by genomics can be applied to enhance the management of these invasive forest pathogens. Four case studies, Phytophthora ramorum, Phytophthora lateralis, Phytophthora cinnamomi, and Phytophthora pluvialis are used to illustrate how genomics can be applied to forest management. We urge researchers, governmental research institutes, private companies, and citizens to collaborate in order to stop the spread of invasive Phytophthora species. To accomplish this, we see the following themes as critical parts of resolving this forest health crisis: i) integration of DNA-based pathogen detection into forest inventory programs; ii) development of practical and affordable DNA-based diagnostic methods; iii) sequence hosts as models for resistance gene identification; iv) prediction of pathogen impact based on genomic data; and v) increase collaborative projects and outreach to raise awareness of forest diseases.

Funding

This research was supported by the DOE Office of Science, Office of Biological and Environmental Research (BER), grant no. DE-SC0018196 to JML.

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