Instituto de Recursos Biológicos, Centro de Investigación en Recursos Naturales, Instituto Nacional de Tecnología Agropecuaria (INTA), Hurlingham, Buenos Aires, Argentina.
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.
PLoS One. 2022 Mar 17;17(3):e0264549. doi: 10.1371/journal.pone.0264549. eCollection 2022.
Tree improvement programs often focus on improving productivity-related traits; however, under present climate change scenarios, climate change-related (adaptive) traits should also be incorporated into such programs. Therefore, quantifying the genetic variation and correlations among productivity and adaptability traits, and the importance of genotype by environment interactions, including defense compounds involved in biotic and abiotic resistance, is essential for selecting parents for the production of resilient and sustainable forests. Here, we estimated quantitative genetic parameters for 15 growth, wood quality, drought resilience, and monoterpene traits for Picea glauca (Moench) Voss (white spruce). We sampled 1,540 trees from three open-pollinated progeny trials, genotyped with 467,224 SNP markers using genotyping-by-sequencing (GBS). We used the pedigree and SNP information to calculate, respectively, the average numerator and genomic relationship matrices, and univariate and multivariate individual-tree models to obtain estimates of (co)variance components. With few site-specific exceptions, all traits examined were under genetic control. Overall, higher heritability estimates were derived from the genomic- than their counterpart pedigree-based relationship matrix. Selection for height, generally, improved diameter and water use efficiency, but decreased wood density, microfibril angle, and drought resistance. Genome-based correlations between traits reaffirmed the pedigree-based correlations for most trait pairs. High and positive genetic correlations between sites were observed (average 0.68), except for those pairs involving the highest elevation, warmer, and moister site, specifically for growth and microfibril angle. These results illustrate the advantage of using genomic information jointly with productivity and adaptability traits, and defense compounds to enhance tree breeding selection for changing climate.
树木改良计划通常侧重于提高与生产力相关的性状；然而，在当前的气候变化情景下，与气候变化相关的（适应性）性状也应纳入此类计划。因此，量化生产力和适应性性状之间的遗传变异和相关性，以及基因型与环境互作的重要性，包括参与生物和非生物抗性的防御化合物，对于选择生产有弹性和可持续森林的亲本至关重要。在这里，我们估计了 15 个生长、木材质量、耐旱性和单萜类化合物的数量遗传参数，这些参数来自白松（Picea glauca (Moench) Voss）的三个开放授粉后代试验。我们从三个开放授粉后代试验中采集了 1540 棵树，使用基因分型测序（GBS）技术，通过 467224 个 SNP 标记进行了基因型鉴定。我们分别使用系谱和 SNP 信息来计算平均分子和基因组关系矩阵，以及单变量和多变量个体树模型，以获得方差分量的估计值。除了少数特定地点的例外，所有检查的性状都受遗传控制。总体而言，基于基因组的关系矩阵比基于系谱的关系矩阵得出的遗传力估计值更高。选择高度通常会提高直径和水分利用效率，但会降低木材密度、微纤丝角和耐旱性。基于基因组的性状相关性再次证实了基于系谱的相关性，大多数性状对都存在这种相关性。除了涉及海拔最高、温度最高和湿度最高的地点对之外，观察到了站点之间的高度和正遗传相关性（平均为 0.68），特别是对生长和微纤丝角而言。这些结果说明了利用基因组信息与生产力和适应性性状以及防御化合物相结合来增强树木育种选择以适应气候变化的优势。
