To understand the genetic mechanisms underlying wood anatomical and morphological traits in Populus trichocarpa, we used 869 unrelated genotypes from a common garden in Clatskanie, OR that were previously collected from across the distribution range in western North America. Using GEMMA mixed model analysis, we tested for the association of 25 phenotypic traits and 9 multitrait combinations with 6.741 million SNPs covering the entire genome. Broad-sense trait heritabilities ranged from 0.117 to 0.477. Most traits were significantly correlated with geoclimatic variables suggesting a role of climate and geography in shaping the variation of this species. We identified a total of 21 and 13 gene models from single and multitrait GWAS, respectively. Fifty-seven SNPs from single trait GWAS and 11 SNPs from multitrait GWAS passed an FDR threshold of 0.05, leading to the identification of eight and seven nearby candidate genes, respectively. Using network-based methods, we further examined support for these gene
models and investigated their putative functions. We performed a breadth-first search in a multi-omic network containing five additional data sets, including metabolomic and py-MBMS GWAS layers. We also performed a functional enrichment analysis on coexpression nearest neighbors for each gene model identified by the wood anatomical and morphological trait GWAS analysis. Based on these networks, the genes associated with wood anatomy and leaf morphology likely play roles in photosynthetic processes, defense mechanisms, abiotic stress tolerance, light and hormone signaling pathways, transport functions, and growth and development. The abundance of cell wall and transport related coexpressed or comethylated genes for wood anatomy and stomatal density traits compared to the leaf morphological traits underscores the potential importance of these genes in wood formation, and stomatal and hydraulic conductance. Signaling and metabolism related genes were also common in networks for stomatal density. For leaf morphology traits (leaf dry and wet weight) the networks were significantly enriched for GO terms related to photosynthetic processes as well as cellular homeostasis. The identified genes have great potential for optimizing traits for lignocellulosic biofuel production.