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Novel forest tree breeding for tolerance to abiotic and biotic stress


Tree breeding is important to develop genetically improved genotypes for forestation through repeated cycles of selection, breeding and genetic testing. Dheeraj Rathore, Teagasc Research Officer, tells us about novel forest tree breeding for tolerance to abiotic and biotic stress.

Teagasc has tree improvement programmes for downy and silver birch, alder and ash for dieback disease tolerance, where national and international collaborations are helpful in expanding both the genetic diversity within the species as well as research knowledge and expertise. Recently, the TolerantTree and EVOLTREE meeting took place from 24-26th of August, 2022 at the Forest and Landscape College, Denmark where researchers from different EU countries shared their work on tree improvement. The meeting covered wide range of research topics from Genomic-based tree breeding to SNP genotyping, using drones and hyperspectral reflectance for speeding up the phenotyping in forest trees, and advances in breeding European ash for dieback disease tolerance.

Genomic-based tree breeding

Tree breeding programs are long-term undertakings that require significant financial, scientific, and organizational commitments. In addition, tree breeding programmes suffer from reduced efficiency as trees require substantial amount of time to reach:

1) sexual maturity for flowering and reproduction among selected trees to produce the offspring for further testing and evaluation, and

2) mature growth for reliable evaluation of economically important attributes such as size and wood quality through field testing.

“The rapid advancements and affordability of DNA sequencing technologies provide unprecedented unique opportunities to incorporate genomic-based techniques in tree breeding to unravel their genealogical relationships, thus the breeding phase could be effectively by-passed and offering considerable time saving” said Prof Yousry A El-Kassaby, The University of British Columbia, USA. Adding to this, Prof El-Kassaby introduced an efficient genomic-based tree breeding framework and evaluated its efficiency through comparison with the commonly used half-sib family genetic evaluation. The study further focused on: 1) theoretical accuracy of the generated genetic parameters (e.g., additive variance and heritability), 2) genetic gain – genetic diversity trade-off, and 3) genetic relationships among selected individuals destined for inclusion in the next breeding cycle and/or seed orchard(s) for the production of genetically improved seed for future reforestation programs.

Using drones for phenotyping

Dr Arne Steffenrem, NIBIO/Skogfrøverket, Norway presented their research on using Lidar drone for phenotyping of commercial forestry in Norway. Their research efforts are focused on stages of (1) Low cost but accurate phenotyping of the most important traits for large populations of candidate trees, and (2) Effective and reproducible genotyping protocols. Ms Samuli Junttila, University of Eastern Finland presented their work on Drone-based spectral measurements for tree stress estimation. This presentation focused on identifying remote sensing methods suitable for tree stress estimation in the context of phenotyping in tree breeding. Ms Junttila said that remote sensing provides opportunities for quantifying tree stress based on physical reflectance signals instead of visual tree stress estimation, which is prone to bias but has been traditionally used in forestry.

Dr Jing Xu from University of Copenhagen, Denmark stated that traditional phenotyping methods are normally slow, costly, and labour-intensive, thus limited to small-scale coverage, which is a major bottleneck for increasing the efficiency of breeding. The objective of their study was to develop drone-based phenotyping methods that can be used in combination with genetic data to identify promising genotypes for potential use within existing breeding programs. Through her presentation, Dr Xu emphasised on successful implementation of the high-throughput phenotyping methods to revolutionize the tree breeding efficiency for climate resilience and adding valuable tool for the health assessment of forest trees.

Breeding European ash (Fraxinus excelsior) for tolerance to the dieback disease

There were two presentations on this topic. Prof Erik D Kjaer (University of Copenhagen, Denmark) presented the results from a large; 15 research performing organisations from 9 EU countries, collaborative project on Genome-wide re-sequencing which revealed the adaptive potential of European ash (Fraxinus excelsior). The study found that there are significant genetic variation in tolerance to ash dieback among the European ash trees. However, the disease tolerance trait is heritable with relatively high level of narrow-sense heritability. The researchers analysed close to 500 F. excelsior replicated clones from nine clonal trials or seed orchards in six European countries (Austria, Denmark, Germany, Ireland, Lithuania, Sweden) with the objective to identify single nucleotide polymorphisms (SNPs) associated to fitness-related traits including tolerance to ash dieback. They identified a panel of >50 million genome-wide SNPs within these clones. The candidate SNPs identified from the association study in this research work are currently being used to reveal signs of selection within contemporary and historic natural ash populations across spatially concurrent geographic regions. These data will be further used to deduce the adaptive potential of common ash, particularly to the recent selection factor, Hymenoscyphus fraxineus - invasive fungal pathogen that causes ash dieback disease.

Dr Dheeraj Rathore of Teagasc, Ireland provided an overview of ash breeding in Ireland for dieback disease tolerance. In this presentation, Dr Rathore reported the performance of a total 208 European ash genotypes, selected for their higher level of tolerance to the ash dieback disease, from 16 European countries including Ireland. Three gene-banks have been established using this plant material multiplied by grafting technique. Preliminary data on ash dieback illustrated genotypic variance for level of disease tolerance. Interestingly, data collected over the last two years indicates that around 6.73% of the trees are category 6 (no visual sign of disease), ~16.8% belong category 5 or above (Sporadic disease symptoms on shoots) and ~14.4% fit in category 4 - 4.9 (Dieback of younger shoots, but no lesions on main stem). This research work continues to monitor and assess existing collection but also include new ash tree genotypes; mainly Irish, for further screening and breeding for ash dieback disease tolerance.

Concluding remarks

The benefits of collaboration are clear with researchers openly sharing their experiences. The key areas identified included high-throughput phenotyping platform that is reliable, reproducible and efficient but faster and less labour intensive. More emphasis was given to further incorporation of genomic tools to accelerate genotyping in forest tree breeding programs, with more collaboration between the tree breeders and research community in forestry.

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