Spatially resolved transcriptomics reveals plant host responses to pathogens

Thorough understanding of complex model systems requires the characterisation of processes in different cell types of an organism. This can be achieved with high-throughput spatial transcriptomics at a large scale. However, for plant model systems this is still challenging as suitable transcriptomics methods are sparsely available. Here we present Grid-seq, an easy to adopt, micro-scale spatial-transcriptomics workflow that allows to study expression profiles across small areas of plant tissue at a fraction of the cost of existing sequencing-based methods. To benchmark Grid-seq, we compare the method with widely used library preparation methods (Illumina TruSeq). In spatial experiments we show that the Grid-seq method is sensitive enough to identify expression differences across a plant organ. We further assess the spatial transcriptome response of Arabidopsis thaliana leaves exposed to the bacterial molecule flagellin-22. In a series of RNA-seq experiments we show that our method can be used to identify known, rapidly flagellin-22 elicited genes, plant immune response pathways to bacterial attack and spatial expression patterns of genes associated with these pathways.