Uncovering the genetic architecture of growth-defense tradeoffs in a foundation forest tree species

Intraspecific genetic variation in foundation species such as trembling aspen shapes their impact on forest structure and function. Identifying genes and genomic regions underlying ecologically relevant traits is key to understanding that impact. Previous studies using genome-wide association (GWA) analyses to identify candidate genes have identified fewer genes than anticipated for highly heritable traits. Mounting evidence suggests that polygenic control of quantitative traits is largely responsible for this "missing heritability" phenomenon. Our research characterized the genetic architecture of 40 functional traits using genomic and transcriptomic analyses in an association mapping population of aspen. A multi-marker association model revealed that most traits displayed a polygenic architecture, with most variation explained by loci with small effects (below the detection levels of single-marker GWA methods). Consistent with a polygenic architecture, our single-marker GWA analyses found only 35 significant SNPs in 22 genes across 15 trait/trait combinations. Next, we used differential expression analysis on a subset of aspen genets with divergent concentrations of salicinoid phenolic glycosides (key defense traits). This alternative method to traditional GWA discovered 1,243 differentially expressed genes for a polygenic trait. Soft clustering analysis revealed three gene clusters (246 candidate genes) involved in secondary metabolite biosynthesis and regulation. Our results support the omnigenic model that complex traits are largely controlled by many small effect loci, most of which may not have obvious connections to the traits of interest. Our work reveals that functional traits governing higher-order community- and ecosystem-level attributes of a foundation forest tree species have complex underlying genetic structures and will require methods beyond traditional GWA analyses to unravel.

在基础物种如颤杨中的种内遗传变异塑造了其对森林结构和功能的影响。识别生态相关性状背后的基因和基因组区域对于理解这种影响至关重要。先前利用全基因组关联（GWA）分析以识别候选基因的研究发现，对于高度可遗传性状而言，所识别的基因数量少于预期。日益增多的证据表明，数量性状的多基因控制是导致“缺失遗传力”现象的主要原因。我们的研究通过在颤杨的关联映射群体中运用基因组学和转录组学分析，对40个功能性状的遗传架构进行了表征。多标记关联模型揭示，大多数性状表现出多基因架构，其中大部分变异可由效应较小的位点（低于单标记GWA方法的检测水平）解释。与多基因架构一致，我们的单标记GWA分析仅在22个基因的15个性状/性状组合中发现了35个显著的SNPs。接下来，我们对具有不同水杨苷酚糖苷浓度（关键防御性状）的颤杨基因子集进行了差异表达分析。这种替代传统GWA分析的方法发现了针对多基因性状的1,243个差异表达基因。软聚类分析揭示了三个基因簇（246个候选基因），它们参与次生代谢物的生物合成和调控。我们的结果支持了全基因模型，即复杂性状在很大程度上由众多具有较小效应的位点所控制，其中大部分可能与感兴趣性状之间缺乏明显的联系。我们的研究揭示了支配基础森林树种高级社区和生态系统属性的功能性状具有复杂的遗传结构，并需要超越传统GWA分析的方法来解开。