Comparative transcriptomics and eQTL mapping of response to Melampsora americana in selected Salix purpurea F2 progeny

Background: Melampsora spp. rusts are the greatest pathogen threat to shrub willow (Salix spp.) bioenergy crops. Genetic resistance is key to limit the effects of these foliar diseases on host response and biomass yield, however, the genetic basis of host resistance has not been characterized. The addition of new genomic resources for Salix provides greater power to investigate the interaction between S. purpurea and M. americana, species commonly found in the Northeast US. Here, we utilize 3' RNA-seq to investigate host-pathogen interactions following controlled inoculations of M. americana on resistant and susceptible F2S. purpurea genotypes identified in a recent QTL mapping study. Differential gene expression, network analysis, and eQTL mapping were used to contrast the response to inoculation and to identify associated candidate genes. Results: Controlled inoculation in a replicated greenhouse study identified 19 and 105 differentially expressed genes between resistant and susceptible genotypes at 42 and 66 HPI, respectively. Defense response gene networks were activated in both resistant and susceptible genotypes and enriched for many of the same defense response genes, yet the hub genes of these common response modules showed greater mean expression among the resistant plants. Further, eight and six eQTL hotspots were identified at 42 and 66 HPI, respectively. The combined results of three analyses highlight 124 candidate genes in the host for further analysis while analysis of pathogen RNA showed differential expression of 22 genes, two of which are candidate pathogen effectors. Conclusions: We identified two differentially expressed M. americana transcripts and 124 S. purpurea genes that are good candidates for future studies to confirm their role in conferring resistance.

Automated summary

This study investigated the host-pathogen interactions between S. purpurea and M. americana using 3' RNA-seq. Differentially expressed genes and eQTL hotspots were identified, and 124 candidate genes associated with resistance were identified.