Ectomycorrhizal symbiosis is essential for the life and health of trees in temperate and boreal forests where it plays a major role in nutrient cycling and in functioning of the forest ecosystem. Trees with ectomycorrhizal root tips are more tolerant to environmental stresses, such as drought, and biotic stresses such as root pathogens. Detailed information on these molecular processes is essential for the understanding of symbiotic tissue development in order to optimize the benefits of this natural phenomenon. Next generation sequencing tools allow the analysis of non model ectomycorrhizal plant-fungal interactions that can contribute to find the "symbiosis toolkits" and better define the role of each partner in the mutualistic interaction. By using 454 pyrosequencing we compared ectomycorrhizal cork oak roots with non-symbiotic roots. From the two cDNA libraries sequenced, over 2 million reads were obtained that generated 19552 cork oak root unique transcripts. A total of 2238 transcripts were found to be differentially expressed when ECM roots were compared with non-symbiotic roots. Identification of up- and down-regulated gens in ectomycorrhizal roots lead to a number of insights into the molecular mechanisms governing this important symbiosis. In cork oak roots, ectomycorrhizal colonization resulted in extensive cell wall remodelling, activation of the secretory pathway, alterations in flavonoid biosynthesis, and expression of genes involved in the recognition of fungal effectors. In addition, we identified genes with putative roles in symbiotic processes such as nutrient exchange with the fungal partner, lateral root formation or root hair decay. These findings provide a global overview of the transcriptome of an ectomycorrhizal host root, and constitute a foundation for future studies on the molecular events controlling this important symbiosis.
Sebastiana, M., Vieira, B., Lino-Neto, T., Monteiro, F., Figueiredo, A., Sousa, L., … Paulo, O. S. (2014). Oak root response to ectomycorrhizal symbiosis establishment: RNA-seq derived transcript identification and expression profiling. PLoS ONE, 9(5). https://doi.org/10.1371/journal.pone.0098376