Home • Cryptodiaporthe populea CFL2025 v1.0
Pycnidia of Cryptodiaporthe populea, the causal agent of Dothichiza canker, under surface of poplar bark.
Image Credit: Bruce Watt, University of Maine
Pycnidia of Cryptodiaporthe populea, the causal agent of Dothichiza canker, under surface of poplar bark.
Image Credit: Bruce Watt, University of Maine, from Bugwood.org licensed under a Creative Commons Attribution-Noncommercial 3.0 License.
Dieback of a a Lombardy poplar (Populus nigra cv. Italica) due to infection by Cryptodiaporthe populea, the causal agent of Dothichiza canker. Image Credit: Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre.
Dieback of a a Lombardy poplar (Populus nigra cv. Italica) due to infection by Cryptodiaporthe populea, the causal agent of Dothichiza canker.
Image Credit: Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre.

The fungus Cryptodiaporthe populea (Ascomycota, Sordariomycetes) causes Dothichiza canker, a disease on the stems and branches of poplars. Hybrid and Lombardy poplars under stress, newly planted saplings, and large ornamental poplars are particularly susceptible to attacks by this pathogen. Canker development can result in stem breakage that provide points of entry for decay fungi and in death of branches or whole trees. Attacks by pathogens represent one of the most important threats to the sustainable growth of bioenergy trees in plantations. Outbreak prevention depends largely on a better understanding of how pathogens infect trees. This information can be used to develop more resistant trees and to design early detection, monitoring and surveillance tools to prevent spread. This can be challenging since pathogens can remain dormant or have endophytic stages in the host tissues. The genome sequencing of Cryptodiaporthe populea is part of a larger effort, the Pathobiome Database For Bioenergy Trees Project, that aims to sequence the genomes of multiple pathogens that share the same host trees in order to identify common and unique genomic signatures. These data will be used to create a database that will help the development of tools for the detection, monitoring and surveillance of pathogens in these economically and ecologically important trees.