Solanum pimpinellifolium is a wild tomato species that is considered among the closest relatives of the cultivated tomato. Different accessions of S. pimpinellifolium have been reported to show resistance against several diseases that threaten the production of cultivated tomato [86]. In this study, we have investigated transcriptional reprogramming triggered by P. solani in resistant S. pimpinellifolium accessions LA2039 (Sp-R) and susceptible cultivar, Brandywine (BW-S) with an aim to identify genes and SNPs putatively involved in resistance development in Sp-R against P. solani.
It has been reported that Phytoplasma infection in Arabidopsis tends to disrupt the transport of carbohydrates which ultimately interferes with the condensation of phloem protein filaments [87, 88]. In tomato leaves infected by Candidatus Phytoplasma solani, the presence of callose deposits and phloem hyperplasia has also been observed [89–91]. Furthermore, Phytoplasma infection has been found to affect the accumulation of secondary metabolites, organic acids and amino acids [92]. These alterations in metabolite profiles indicate the impact of Phytoplasma infection on the plant's metabolic pathways, potentially affecting its overall health and growth. In the present study, the BSR-Seq method was used to screen and identify the putative genes involved in resistance to P. solani.
We here harnessed the power of NGS in combination with BSA to compare the expression level of the whole transcriptome in two bulks of different tomato accessions showing contrasting response to P. solani infection. Our approach allowed us to identify the genes contributing more to the observed resistance and successfully identified “expression markers” i.e., SNPs in comparison to the traditional DNA markers linked to disease resistance.
Recently, it has been demonstrated that in stolbur-diseased tomato plants, Ca. P. solani infection changes iron distribution in tomato leaves, affects the photosynthetic machinery, and perturbs the orchestration of root-mediated transport processes by compromising shoot-to-root communication [89] confirming our results. Phytoplasma infection has also been demonstrated to affect net photosynthesis rate, stomatal closure, transpiration and mineral nutrient concentration. [93].
In the present study, analyses of identified DEGs revealed that most of the genes upregulated in both comparisons are involved in abiotic stress response, signaling, and secondary metabolism and include some heat shock proteins as well. We found Solyc03g095650 upregulated which is MLO genes involved in plant resistance, such as Ralstonia solanacearum infection in tomato, Pseudomonas syringae infection in Arabidopsis and Phytophthora parasitica infection in tomato [44]. Three pathogenesis related genes (Solyc08g080660, Solyc10g074440 and Solyc09g091000) were downregulated in both comparisons. Solyc08g080660 encodes the PR-5 precursor. Three genes (Solyc01g095080, Solyc05g051200 and Solyc09g089680) related to ethylene biosynthesis and ripening of tomato fruits [56, 67, 68, 83] were downregulated. Six genes reported to be involved in drought stress tolerance, out of which four DEGs (Solyc01g107370, Solyc02g084850, Solyc11g020960 and Solyc12g006530) [38, 41, 50, 51] were upregulated in both comparisons and two (Solyc08g080630 and Solyc08g080660) [50, 79, 80] were downregulated. Three genes (Solyc03g026040, Solyc02g090210 and Solyc07g008240) related to scavenging nitrogen and tolerance were differentially expressed. Solyc07g008240 was found downregulated which is responsible for scavenging NO [94]. Solyc02g090210 is reported for low nitrogen tolerance [59] and it was downregulated while Solyc03g026040 is involved in tomato response to low nitrogen [42, 43] and it was upregulated. Solyc02g076980 reported for resistance to Cladosporium fulvum [40] and Solyc03g095650 involved in plant resistance, such as Ralstonia solanacearum infection in tomato, Pseudomonas syringae infection in Arabidopsis and Phytophthora parasitica infection in tomato [44]. Both of these genes were upregulated in both comparisons. Solyc03g025380, Solyc05g051200, Solyc07g008560 and Solyc08g080670 reported to be associated with resistance to early blight [62], Clavibacter michiganensis [67], Pseudomonas syringae [82] and Phomopsis viticola and Botrytis cinerea mycelia [82] diseases respectively, were downregulated. Solyc08g080630 is reported to be upregulated under Tomato Spotted Wilt Virus infection was found downregulated in our results. Our results suggest that P. solani infection triggers the transcriptional changes in key genes ultimately altering the response of plant towards different biotic and abiotic stresses. Downregulation of genes responsible for tolerance against stresses like high temperature, drought, salt stress and different pathogens shows the extent of vulnerability of plants when infected with P. solani. This makes tomato plants more prone to other environmental factors, bacterial, fungal and viral diseases. Moreover, P. solani infection disturbs the nutrient uptake like nitrogen and ultimately affects the photosynthesis process of the plants [93].
The mechanism of plant’s response to pathogens is a complex phenomenon that involves interconnected network of change in normal developmental and physiological processes [95]; evident from the transcriptome based studies of several diverse plant-pathogen systems [96–100]. In this study, we identified several differentially expressed genes involved in multiple plant defense mechanisms in Sp-R against P. solani. The technique of BSR-Seq often cannot obtain the induced expression information of disease-resistance genes taking the RNA-seq into consideration [101]. To identify the putative genes involved in P. solani resistance in tomato, we compared the DEGs and the genes selected from the BSR-seq analysis performed by using PyBSASeq. All the genes selected through sliding window analysis had conserved variants or alleles in resistant or susceptible genotypes. Of all these conserved variant, identification of putative variants responsible for resistance involved comparison of genes of these conserved regions with DEGs [102]. So the selection of significant variants with DEGs revealed the potential factors for resistance in tomato which also meets the objectives of using bulk segregant analysis with RNA-seq data. In this way, only two genes, Solyc01g079140 and Solyc07g017980, were obtained after screening, both are unknown proteins. Therefore, in-depth studies are imperative to reveal the potential function of these two genes. However, the distribution of ΔAllele_Frequency, G` statistics and their differential expression reveal their potential role against P. solani infection. Solyc01g079140 has five missense variants and its significant differential expression in both resistant samples under P. solani infection, might indicates that this gene is a positive regulator of P. solani resistance in tomato plant. While Solyc07g017980 shows downregulation in both resistant parent and F2 bulk. Solyc07g017980 has one insertion which reduced the length of its protein from 122 amino acids to 21 amino acids, and also it’s down regulation in susceptible samples makes this gene closely linked to P. solani resistance in tomato. True nature of the mechanisms controlled by these two genes and the selected variants in P. solani infected plants is yet to be discovered. However our experiment of using bulk segregant analysis along with RNA-seq data proved to be fruitful in identifying the putative genetic and polymorphism factors responsible for P. solani resistance in tomato.
Transcriptional reprogramming of many cellular and physiological processes and all components of biotic stress responses especially high induction of several defense related genes, suppression of susceptibility factors, modulation of phytohormone signaling, proteolysis and signaling in resistant samples indicates significant activation of multiple defense mechanisms leading to resistant outcome against P. solani. Functional significance of defense related genes identified here needs further investigation. It should also be pointed out that the sampling for BSR-Seq was only from the stage at which disease symptoms were visible, and did not represent the early stages of infection, so these genes were selected not solely based on one differential expression analysis or significant SNP analysis. Understanding the functions of these proteins opens up new avenues for exploring their potential applications in agriculture, pharmaceuticals, and other biotechnological fields.