Transcriptomic insights into the epigenetic modulation of turnip mosaic virus evolution in Arabidopsis thaliana

Abstract

Abstract Background Plant-virus interaction models propose that a virus’s ability to infect a host genotype depends on the compatibility between virulence and resistance genes. Recently, we conducted an evolution experiment in which lineages of turnip mosaic virus (TuMV) were passaged in Arabidopsis thaliana genotypes carrying mutations in components of the DNA methylation and the histone demethylation epigenetic pathways. All evolved lineages increased infectivity, virulence and viral load in a host genotype-dependent manner. Results To better understand the underlying reasons for these evolved relationships, we delved into the transcriptomic responses of mutant and WT plant genotypes in mock conditions and infected with either the ancestral or evolved viruses. Such a comparison allowed us to classify every gene into nine basic expression profiles. Regarding the targets of viral adaptation, our analyses allowed the identification of common viral targets as well as host genotype-specific genes and categories of biological processes. As expected, immune response-related genes were found to be altered upon infection. However, we also noticed the pervasive over-representation of other functional groups, suggesting that viral adaptation was not solely driven by the level of expression of plant resistance genes. In addition, a significant association between the presence of transposable elements within or upstream the differentially expressed genes was observed. Finally, integration of transcriptomic data into a virus-host protein-protein interaction network highlighted the most impactful interactions. Conclusions These findings shed extra light on the complex dynamics between plants and viruses, indicating that viral infectivity depends on various factors beyond just the plant’s resistance genes.

Keywords

• Adaptation
• Epigenetics
• Experimental evolution
• Gene expression
• Potyvirus rapae
• Systems biology