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Spatially resolved transcriptomics reveals plant host responses to pathogens
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 tr...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785889/ https://www.ncbi.nlm.nih.gov/pubmed/31624491 http://dx.doi.org/10.1186/s13007-019-0498-5 |
Sumario: | 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. |
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