PHYTOMap (Plant HYbridization-based Targeted Observation of gene expression Map) is a method that can spatially map expression of dozens of genes at the single-molecule resolution in 3D whole-mount plant tissues. PHYTOMap dramatically accelerates and advances spatial gene expression analysis in plants compared to traditional transgenic reporter approaches. It does not require tissue sectioning, a major bottleneck in commercial spatial transcriptomics assays. PHYTOMap experiments can be done in a standard molecular biology lab at a low cost without requiring a transgenic line; thus, the method can be applied to many plant species, including non-model species.
Single-cell and spatial dissection of plant-microbe interactions
Plant leaf intercellular space provides a nutrient-rich and heterogeneous niche for microbes that have a critical impact on plant health. However, how individual plant cells respond to heterogeneous microbial colonization remains largely elusive. By time-resolved simultaneous single-cell transcriptome and epigenome profiling of plants (Arabidopsis thaliana) infected by virulent and avirulent bacterial pathogens (Pseudomonas syringae), we present cell atlases with gene regulatory logic involving transcription factors, putative cis-regulatory elements, and target genes associated with disease and immunity. Our study provided a molecularly-defined spatiotemporal map of plant-microbe interaction at the single-cell resolution.
Plant cell atlas
Extensive studies of the reference plant Arabidopsis have enabled deep understandings of tissues throughout development, yet a census of cell types and states throughout development are lacking. We created a single-nucleus transcriptome atlas of seed-to-seed development employing over 800,000 nuclei, encompassing a diverse set of tissues across ten developmental stages, with spatial transcriptomic validation of the dynamic seed and silique. This atlas provided a resource for the study of cell type specification throughout the continuum of development, and a reference for stimulus response and genetic perturbations at the single-cell resolution.
In planta bacterial omics
How do hosts influence bacterial responses during interactions? This is a difficult question to answer due to challenges in analyzing bacterial responses in plants because bacterial RNA and protein are present in much lower quantities than those of plants. We overcame this bottleneck by developing a new method that physically isolates bacteria from plant leaves and enriches bacterial information for transcriptome and proteome assays. We applied this approach to study bacterial pathogens and discovered the following: (1) bacterial transcriptome patterns at an early stage of infection can predict their future virulence, (2) plant immunity suppresses the bacterial iron acquisition system at an early stage of infection to inhibit pathogen growth, and (3) in planta co-expression analysis of bacterial genes can identify novel virulence-related genes. We further applied this method to investigate diverse members of the plant microbiota. In a single strain-inoculated setup, we profiled the co-transcriptome of both plants and bacteria. This allowed us to address a vital question in microbiome research: how do hosts discriminate against different microbes in the microbiota? We identified bacterial processes that showed strain-specific regulation during colonization in plants, which may explain their niche specification