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Abstract Grafting has been adopted for a wide range of crops to enhance productivity and resilience; for example, grafting of Solanaceous crops couples disease-resistant rootstocks with scions that produce high-quality fruit. However, incompatibility severely limits the application of grafting and graft incompatibility remains poorly understood. In grafts, immediate incompatibility results in rapid death, but delayed incompatibility can take months or even years to manifest, creating a significant economic burden for perennial crop production. To gain insight into the genetic mechanisms underlying this phenomenon, we developed a model system using heterografting of tomato (Solanum lycopersicum) and pepper (Capsicum annuum). These grafted plants express signs of anatomical junction failure within the first week of grafting. By generating a detailed timeline for junction formation, we were able to pinpoint the cellular basis for this delayed incompatibility. Furthermore, we inferred gene regulatory networks for compatible self-grafts and incompatible heterografts based on these key anatomical events, which predict core regulators for grafting. Finally, we examined the role of vascular development in graft formation and uncovered SlWOX4 as a potential regulator of graft compatibility. Following this predicted regulator up with functional analysis, we show that Slwox4 homografts fail to form xylem bridges across the junction, demonstrating that indeed, SlWOX4 is essential for vascular reconnection during grafting, and may function as an early indicator of graft failure. 

The acquisition of quantitative information on plant development across a range of temporal and spatial scales is essential to understand the mechanisms of plant growth. Recent years have shown the emergence of imaging methodologies that enable the capture and analysis of plant growth, from the dynamics of molecules within cells to the measurement of morphometricand physiological traits in field-grown plants. In some instances, these imaging methods can be parallelized across multiple samples to increase throughput. When high throughput is combined with high temporal and spatial resolution, the resulting image-derived data sets could be combined with molecular large-scale data sets to enable unprecedented systems-level computational modeling. Such image-driven functional genomics studies may be expected to appear at an accelerating rate in the near future given the early success of the foundational efforts reviewed here. We present new imaging modalities and review how they have enabled a better understanding of plant growth from the microscopic to the macroscopic scale.