Transcriptional dynamics reveals the asymmetrical events underlying graft union formation in pecan (Carya illinoinensis)

Tree Physiol. 2024 Apr 10:tpae040. doi: 10.1093/treephys/tpae040. Online ahead of print.

Abstract

Grafting is a widely used technique for pecan propagation, however, the background molecular events underlying grafting are still poorly understood. In our study, the graft partners during pecan graft union formation were separately sampled for RNA-seq, and the transcriptional dynamics were described via weighted gene co-expression network analysis (WGCNA). To reveal the main events underlying grafting, the correlations between modules and grafting traits were analyzed. Functional annotation showed that during the entire graft process, signal transduction was activated in the scion, while mRNA splicing was induced in the rootstock. At 2 DAG, the main processes occurred in the scion were associated with protein synthesis and processing, while the primary processes happened in the rootstock were energy release-related. During the period of 7-14 DAG, defense response was a critical process worked in the scion, however, the main process functioned in the rootstock was photosynthesis. From 22 to 32 DAG, the principal processes taken place in the scion were jasmonic acid biosynthesis and defense response, whereas the highly activated processes associated with the rootstock were auxin biosynthesis and plant-type secondary cell wall biogenesis. Detection of hydrogen peroxide contents as well as peroxidase and β-1,3-glucanase activities showed that their levels were increased in the scion not the rootstock at certain time points after grafting. Our study reveals that the scion and rootstock might response asymmetrically to grafting in pecan, and the scion was likely associated with stress response, while the rootstock was probably involved in energy supply and xylem bridge differentiation during graft union formation.

Keywords: Grafting; Molecular mechanism; Scion and rootstock; Time-series gene expression; Weighted gene co-expression network analysis.