S01 - Session O2 - Identification of genes responding to apple replant disease (ARD) using an RNAseq approach

Authors: Stefanie Reim *, Alessandro Cestaro, Traud Winkelmann, Henryk Flachowsky

Apple Replant Disease (ARD) is a soil-borne disease in apple that poses an economic risk for fruit tree nurseries and fruit growers worldwide. After replanting the same plant species, the soil loses its capacity to support the healthy growth of plants of the species, which results in reduced yields in terms of quantity and quality of the replanted plants. Several studies on the reaction of apple plants to ARD are documented, but less is known about the genetic mechanisms behind this symptomatology. However, understanding the molecular basis provides important information for establishing appropriate control measures and for rootstock breeding. RNAseq analysis is a powerful tool for revealing candidate genes that are involved in the plant molecular responses to biotic stresses. The aim of our work was to find differentially expressed genes (DEGs) in response to ARD in Malus . For this, we compared transcriptome data of the rootstock 'M9' (susceptible) and the tolerant wild apple genotype M. × robusta 5 (Mr5) after cultivation in both ARD soil and disinfected ARD soil. Comparing the two soils, 1,206 DEGs were identified based on a log2 fold change (LFC) ≥ 1 for upn, and ≤ n1 for downregulation ( p < 0.05). Subsequent validation revealed a highly significant positive correlation ( r = 0.92; p < 0.0001) between RNAseq and RT-qPCR results, indicating a high reliability of the RNAseq data. PageMan analysis showed that transcripts of genes involved in gibberellin biosynthesis were significantly enriched in the DEG dataset. Most of these GA biosynthesis genes were associated with functions in cell wall stabilization. Further genes were related to detoxification processes. These genes were significantly higher expressed in Mr5, suggesting that the lower susceptibility to ARD in Mr5 is not due to a single mechanism. Future research is needed to find the defense mechanisms that are most effective in overcoming ARD.