Meger Joanna, Ulaszewski Bartosz, Pałucka Małgorzata, Kozioł Czesław, Burczyk Jarosław
Department of Genetics, Faculty of Biological Sciences Kazimierz Wielki University Bydgoszcz Poland.
Kostrzyca Forest Gene Bank Miłków Poland.
Evol Appl. 2024 May 3;17(5):e13694. doi: 10.1111/eva.13694. eCollection 2024 May.
The increase in introduced insect pests and pathogens due to anthropogenic environmental changes has become a major concern for tree species worldwide. Common ash ( L.) is one of such species facing a significant threat from the invasive fungal pathogen . Some studies have indicated that the susceptibility of ash to the pathogen is genetically determined, providing some hope for accelerated breeding programs that are aimed at increasing the resistance of ash populations. To address this challenge, we used a genomic selection strategy to identify potential genetic markers that are associated with resistance to the pathogen causing ash dieback. Through genome-wide association studies (GWAS) of 300 common ash individuals from 30 populations across Poland (ddRAD, dataset A), we identified six significant SNP loci with a -value ≤1 × 10 associated with health status. To further evaluate the effectiveness of GWAS markers in predicting health status, we considered two genomic prediction scenarios. Firstly, we conducted cross-validation on dataset A. Secondly, we trained markers on dataset A and tested them on dataset B, which involved whole-genome sequencing of 20 individuals from two populations. Genomic prediction analysis revealed that the top SNPs identified via GWAS exhibited notably higher prediction accuracies compared to randomly selected SNPs, particularly with a larger number of SNPs. Cross-validation analyses using dataset A showcased high genomic prediction accuracy, predicting tree health status with over 90% accuracy across the top SNP sets ranging from 500 to 10,000 SNPs from the GWAS datasets. However, no significant results emerged for health status when the model trained on dataset A was tested on dataset B. Our findings illuminate potential genetic markers associated with resistance to ash dieback, offering support for future breeding programs in Poland aimed at combating ash dieback and bolstering conservation efforts for this invaluable tree species.
由于人为环境变化导致外来害虫和病原体增加，已成为全球树种面临的主要问题。欧洲白蜡树（Fraxinus excelsior L.）就是面临入侵性真菌病原体重大威胁的此类树种之一。一些研究表明，白蜡树对该病原体的易感性是由基因决定的，这为旨在提高白蜡树种群抗性的加速育种计划带来了一些希望。为应对这一挑战，我们采用了基因组选择策略来识别与导致白蜡树枯梢病的病原体抗性相关的潜在遗传标记。通过对来自波兰30个种群的300株欧洲白蜡树个体进行全基因组关联研究（GWAS，ddRAD，数据集A），我们确定了6个与健康状况相关的显著SNP位点，其P值≤1×10⁻⁶。为了进一步评估GWAS标记在预测健康状况方面的有效性，我们考虑了两种基因组预测方案。首先，我们在数据集A上进行了交叉验证。其次，我们在数据集A上训练标记，并在数据集B上进行测试，数据集B涉及来自两个种群的20个个体的全基因组测序。基因组预测分析表明，与随机选择的SNP相比，通过GWAS鉴定出的顶级SNP表现出显著更高的预测准确性，尤其是在SNP数量较多时。使用数据集A进行的交叉验证分析显示出较高的基因组预测准确性，在GWAS数据集中从500到10000个SNP的顶级SNP集上，预测树木健康状况的准确率超过90%。然而，当在数据集A上训练的模型在数据集B上进行测试时，未得出关于健康状况的显著结果。我们的研究结果揭示了与白蜡树枯梢病抗性相关的潜在遗传标记，为波兰未来旨在对抗白蜡树枯梢病并加强对这种珍贵树种保护工作的育种计划提供了支持。
