Identification of genes responding in apple replant disease (ARD) affected Malus roots using an RNA-sequencing approach
Apple replant disease (ARD) is a soil-borne disease in apple that poses an economic risk for fruit tree nurseries and fruit growers worldwide. When replanting the same plant species, the soil will have lost its capacity to support the growth of plants of the respective species. This results in reduced yields in terms of quantity and quality of the replanted trees. Several studies on the reaction of apple trees to ARD have been 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. RNA-sequencing (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 roots. For this, we compared root transcriptome data of the rootstock ‘M9’ (susceptible) and the wild apple genotype M. ×robusta 5 (Mr5, tolerant) after cultivation in ARD soil and disinfected ARD soil, respectively. Comparing ARD soil versus disinfected ARD soil, 1,206 DEGs were identified based on a log2 fold change, (LFC) ≥1 for up- and ≤-1 for downregulation (p<0.05). Subsequent validation revealed a highly significant positive correlation (r=0.91; 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 data set. Most of the GA biosynthesis genes were associated with functions in cell wall stabilization. Additional 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 identify the defence mechanisms, which are most effective in overcoming ARD.