MicroRNA-mediated post-transcriptional regulation of Pinus pinaster response and resistance to pinewood nematode

Abstract

Pine wilt disease (PWD), caused by the parasitic nematode Bursaphelenchus xylophilus, or pinewood nematode (PWN), is a serious threat to pine forests in Europe. Pinus pinaster is highly susceptible to the disease and it is currently the most affected European pine species. In this work, we investigated the role of small RNAs (sRNAs) in regulating P. pinaster-PWN interaction in an early stage of infection. After performing an artificial PWN inoculation assay, we have identified 105 plant microRNAs (miRNAs) responsive to PWN. Based on their predicted targets, part of these miRNAs was associated with roles in jasmonate-response pathway, ROS detoxification, and terpenoid biosynthesis. Furthermore, by comparing resistant and susceptible plants, eight miRNAs with putative functions in plant defence and resistance to PWN have been identified. Finally, we explored the possibility of bidirectional trans-kingdom RNA silencing, identifying several P. pinaster genes putatively targeted by PWN miRNAs, which was supported by degradome analysis. Targets for P. pinaster miRNAs were also predicted in PWN, suggesting a role for trans-kingdom miRNA transfer and gene silencing both in PWN parasitism as in P. pinaster resistance to PWD. Our results provide new insights into previously unexplored roles of sRNA post-transcriptional regulation in P. pinaster response and resistance to PWN.

Figure 1

Number of expressed Pinus pinaster miRNAs (a) and tasiRNAs (b) in susceptible (S), resistant (R), and control (C) samples. Pathway enrichment analysis^, of predicted target genes of the expressed miRNAs (c) and tasiRNAs (d). The x-axis represents the significance of pathway enrichment (− log10 of corrected p-values) (c,d). Venn diagrams were generated online (https://bioinformatics.psb.ugent.be/webtools/Venn/) and edited with Inkscape 1.1 (https://inkscape.org/). Bar plots were generated with R 4.1.0 (https://cran.r-project.org/) ggplot2 package (https://ggplot2.tidyverse.org/).

Figure 2

MiRNAs differentially expressed between inoculated (I) and control plants (C) and functional analysis of their target genes. (a) Average expression [log10(CPM)] for each conserved DE miRNA family, except for families where the miRNAs presented opposite expression patterns to each other, in which case isoform expression is represented. (b) GO terms and (c) pathways most represented in P. pinaster predicted target genes for the DE miRNAs. The y-axis represents the number of genes within each KEGG pathway^, or GO term. BP biological process, CC cellular component, MF molecular function. Plots were generated with R 4.1.0 (https://cran.r-project.org/) pheatmap package (https://cran.r-project.org/web/packages/pheatmap/) and ggplot2 package (https://ggplot2.tidyverse.org/). Inkscape 1.1 (https://inkscape.org/) was used to assemble the final figure.

Figure 3

MiRNAs differentially expressed between resistant (R) and susceptible (S) plants (a) and functional analysis of their target genes (b). (a) The heatmap represents average log10(CPM) values for each miRNA. (b) GO terms represented in the predicted target genes for the DE miRNAs. The y-axis represents the number of genes within each GO terms. BP biological process, CC cellular component, MF molecular function. Plots were generated with R 4.1.0 (https://cran.r-project.org/) pheatmap package (https://cran.r-project.org/web/packages/pheatmap/) and ggplot2 package (https://ggplot2.tidyverse.org/). Inkscape 1.1 (https://inkscape.org/) was used to assemble the final figure.

Figure 4

Functional analysis of the predicted target genes of miRNAs possibly involved in trans-kingdom interaction. (a) Gene set enrichment analysis (GSEA) of GO terms represented in P. pinaster predicted targets for PWN miRNAs. The y-axis represents the significance of pathway enrichment (− log10 of corrected p-values). (b) GO terms represented in PWN predicted target genes for P. pinaster miRNAs. The y-axis represents the number of genes within each GO terms. Plots were generated with R 4.1.0 (https://cran.r-project.org/) ggplot2 package (https://ggplot2.tidyverse.org/). Inkscape 1.1 (https://inkscape.org/) was used to assemble the final figure.