Abstract
BackgroundMany conifer breeding programs are paying increasing attention to breeding for resistance to needle disease due to the increasing importance of climate change. Phenotyping of traits related to resistance has many biological and temporal constraints that can often confound the ability to achieve reliable phenotypes and consequently, reliable genetic progress. The development of next generation sequencing platforms has also enabled implementation of genomic approaches in species lacking robust reference genomes. Genomic selection is, therefore, a promising strategy to overcome the constraints of needle disease phenotyping.ResultsWe found high accuracy in the prediction of genomic breeding values in the disease-related traits that were well characterized, reaching 0.975 for genotyped individuals and 0.587 for non-genotyped individuals. This compared well with pedigree-based accuracies of up to 0.746. Surprisingly, poorly phenotyped disease traits also showed very high accuracy in terms of correlation of predicted genomic breeding values with pedigree-based counterparts. However, this was likely caused by the fact that both were clustered around the population mean, while deviations from the population mean caused by genetic effects did not appear to be well described. Caution should therefore be taken with the interpretation of results in poorly phenotyped traits.ConclusionsImplementation of genomic selection in this test population of Pinus radiata resulted in a relatively high prediction accuracy of needle loss due to Dothistroma septosporum compared with a pedigree-based approach. Using genomics to avoid biological/temporal constraints where phenotyping is reliable appears promising. Unsurprisingly, reliable phenotyping, resulting in good heritability estimates, is a fundamental requirement for the development of a reliable prediction model. Furthermore, our results are also specific to the single pathogen mating-type that is present in New Zealand, and may change with future incursion of other pathogen varieties. There is no doubt, however, that once a robust genomic prediction model is built, it will be invaluable to not only select for host tolerance, but for other economically important traits simultaneously. This tool will thus future-proof our forests by mitigating the risk of disease outbreaks induced by future changes in climate.
Highlights
Many conifer breeding programs are paying increasing attention to breeding for resistance to needle disease due to the increasing importance of climate change
Dothistroma needle blight is caused by the pathogen Dothistroma septospora (Dorog.) Morelet and characterized by 1–3 mm wide brick-red bands around the needles, caused by the release of a mycotoxin [5]
Genetic parameters and model fit A visual exploration of spatial patterns in the level of phenotypic expression of disease found the lowest level at an early age across all investigated sites with exception of Kaingaroa (Figs. 1, 2 and 3)
Summary
Many conifer breeding programs are paying increasing attention to breeding for resistance to needle disease due to the increasing importance of climate change. Dothistroma needle blight (DNB), known as red band needle blight, is one of the most important needle diseases that affect conifer species (pines) across the world [1,2,3,4]. The severity of DNB has put pressure on the productivity of pine plantations and led to the abandonment of further deployment of a number of pine species across the world [3]. The disease causes large losses in growth, the loss increasing in proportion with the degree of affected crown, with van der Pas [9] reporting 1% loss in productivity for each 1% increase in disease level and a significant reduction in stand growth once defoliation exceeds 25 percent [9]
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