A New RNA-Seq Method Reveals Plant Defence Responses at Higher Resolution

Transcript profiling is a powerful tool for unravelling biological mechanisms in many organisms. In general RNA is extracted from a collection of many heterogenic cells, e.g. whole leaves, the spatial information of the tissue is lost and detailed information about local stress responses (such as biotic and abiotic stresses) and potential molecular signals that alert neighboring cells are very difficult to detect. We use Arabidopsis as a model system and developed a method to generate a 2D transcriptome map of a leaf by dissecting the leaf into small sections (and keeping the spatial information) after local exposure to various (a)biotic stresses. In three independent experiments, Arabidopsis thaliana columbia-0 leaves were treated with 1) flg22 peptides 2) green peach aphids and 3) mechanical wounding. After the treatment the leaf was dissected into small sections (<1x1 mm) and mRNA was extracted from each section. We used a new method: LORIS, to generate libraries which were sequenced (50bp single reads) on Illumina HiSeq 2500. We could detect transcriptional changes in treated sections and identify transcriptional networks unique for each treatment, indicating that LORIS has the sensitivity to detect subtle transcriptional changes in very small amounts of tissue too small amounts for standard methods. 

Our goal is to further develop this technology to even higher spatial resolution, and streamline the process from challenging leaf tissue to detecting local transcriptional changes.