Spatially resolved transcriptomics reveals plant host responses to pathogens

Abstract

Background 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 GaST-seq (Grid-assisted, Spatial Transcriptome sequencing), 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. Results We compare the GaST-seq method with widely used library preparation methods (Illumina TruSeq). In spatial experiments we show that the GaST-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, and show that with eukaryotic (Albugo laibachii) infection both host and pathogen spatial transcriptomes are obtained. Conclusion 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.

Precision transcriptomics of viral foci reveals the spatial regulation of immune‐signaling genes and identifies RBOHD as an important player in the incompatible interaction between potato virus Y and potato

“…The progressive and asynchronous effects of viral infection on host gene expression in relation to the spatial distribution of the virus have been investigated previously, but in compatible interactions (Aranda et al, 1996;Escaler et al, 2000;Maule et al, 2002;Yang et al, 2007). In resistance, however, the spatial distribution of a limited number of components has been studied only in model plants (Antoniw and White, 1986;Mur et al, 1997;Betsuyaku et al, 2018;Giolai et al, 2019). Our approach to the analysis of small tissue sections presents a step forward in studying the resistance response against the virus, and enabled the identification of a novel key player and the interconnectivity of components of immune signaling.…”

High expression of the MADS-box gene VRT2 increases the number of rudimentary basal spikelets in wheat

“…To investigate transcriptional differences between the apical, central, and basal section of developing wheat spikes, we adapted the low-input GG&T-seq method for RNA-seq of small plant tissue sections. G&T has been developed for single-cell RNA and DNA sequencing of mammalian systems ( Macaulay et al, 2015) and was previously adapted for Arabidopsis thaliana (GaST-seq; Giolai et al, 2019) . We collected four individual developing wheat (cv Paragon) spikes at both the DR and GP stage and hand-dissected them into apical, central, and basal sections ( Figure 1A ).…”

“…To address this challenge, we adapted the G&T method for micro-scale spatial-transcriptomics workflow ( Macaulay et al, 2015 ; Giolai et al, 2019) , to conduct RNA-seq of the apical, central, and basal sections of individual, hand-dissected wheat spikes. This highly automated workflow requires low tissue input and allowed us to combine 24 Nextera libraries into a single Illumina NovaSeq lane.…”

“…We adapted G enome and T ranscriptome sequencing (G&T-seq), a low-input sequencing approach to sequence the transcriptome of the sections. Recently, Giolai et al (2019) adapted the protocol to identify expression differences across single leaves of Arabidopsis ( Arabidopsis thaliana ; GaST-seq), demonstrating that the G&T-seq method can be readily used for sequencing of hand harvested, small input plant material without the need of previous tissue dissociation or treatment. G&T-seq is thus comparable to methods using laser-micro dissection followed by sequencing to achieve spatially resolved transcriptome-wide sequencing data.…”