Advanced Phenotyping Tools for Genetic Gain in Tree Breeding
- Reference number
- FID18-0012
- Project leader
- Liziniewicz, Mateusz
- Start and end dates
- 200101-210930
- Amount granted
- 848 053 SEK
- Administrative organization
- Skogforsk
- Research area
- Life Sciences
Summary
Genetically improved reforestation material is critically important to meet demands for sustainable biomass production and to improve the health and future resilience of forests against several threats. The proposed Research Institute PhD fellowship aims to build competence and skills in forest tree breeding and forest biotechnology including marker-assisted selection and high throughput phenotyping tools to be used in operational breeding practice. The project focuses on the development of a highly resistant population of European ash to the invasive fungal pathogen causing ash dieback which is currently devastating populations across most of Europe. Basic research in the PhD project will expand upon the understanding of tree defense mechanisms affecting plant phenotype, while applied research will explore the use of advancing phenotyping to identify biomarkers associated with resistance. The selection of superior, resistant trees based on data from advanced phenotyping techniques has substantial potential to increase the cost-efficiency of breeding by reducing breeding rotation times, reducing the need for expensive field testing, and increasing the intensity of selection. The proposed PhD project sets the foundation for a national research program aimed at ex situ conservation of ash and will serve as a model for safeguarding genetic resources to combat other forest health threats in the future, also for other economically and ecologically important tree species.
Popular science description
Forestry is one of the major economic engines of Sweden as well as a socio-cultural icon. Healthy forests are important for meeting many societal demands and challenges especially now in a time of growing bio-economy that requires a recognition of wood traits of many tree species as their potential has not been discovered. In recent decades, forests in Sweden have been threatened by new and emerging pests and pathogens. European ash is one of several noble broadleaved tree species that has been affected by deadly invasive fungal diseases. Commonly known as ‘ash dieback’, this disease is largely threatening the existence of ash trees in Swedish populations and the species has been included in a national “Red-list” as a critically endangered species. Ash is a highly-valued timber tree species that has ecological and cultural importance in natural and urban environments. Ash wood is a substrate for range of other organisms as beetles, lichens and vascular plants. There are several species that are explicitly dependent on ash presence which suggests other species declines if we lose ash a tree species. From previous research, we know that in nature, between 1% and 3% of trees show resistance against ash-dieback and they usually survive years of pathogen attacks. This information will be used to reach a project goal which is the development of a highly resistant population of European ash that will be used in restoration and regeneration projects. Potentially resistant individual trees will be identified in remaining natural stands. The clones and seedlings of them will be planted out in genetic field trials to test their actual resistance since the resistance observed in the field might be due to another reasons than genetics. For confirmation of resistance in genetic field trials we combine traditional techniques on a basis of observed disease symptoms and new methods that analyze chemical characteristics of tree that are related to resistance. To ensure the newly selected resistant population of ash are genetically diverse enough to promote resilience during restoration, we will study the genetic composition of the resistant trees using molecular genetics. The project will also develop and test rapid phenotyping techniques including a field hand held field device using infrared spectroscopy to discrimine resistance and susceptible ash, and an artificial intelligence algorithm that will be used for judging disease symptoms.