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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...

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Autores principales: Giolai, Michael, Verweij, Walter, Lister, Ashleigh, Heavens, Darren, Macaulay, Iain, Clark, Matthew D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
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
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author Giolai, Michael
Verweij, Walter
Lister, Ashleigh
Heavens, Darren
Macaulay, Iain
Clark, Matthew D.
author_facet Giolai, Michael
Verweij, Walter
Lister, Ashleigh
Heavens, Darren
Macaulay, Iain
Clark, Matthew D.
author_sort Giolai, Michael
collection PubMed
description 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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spelling pubmed-67858892019-10-17 Spatially resolved transcriptomics reveals plant host responses to pathogens Giolai, Michael Verweij, Walter Lister, Ashleigh Heavens, Darren Macaulay, Iain Clark, Matthew D. Plant Methods Methodology 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. BioMed Central 2019-10-10 /pmc/articles/PMC6785889/ /pubmed/31624491 http://dx.doi.org/10.1186/s13007-019-0498-5 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Giolai, Michael
Verweij, Walter
Lister, Ashleigh
Heavens, Darren
Macaulay, Iain
Clark, Matthew D.
Spatially resolved transcriptomics reveals plant host responses to pathogens
title Spatially resolved transcriptomics reveals plant host responses to pathogens
title_full Spatially resolved transcriptomics reveals plant host responses to pathogens
title_fullStr Spatially resolved transcriptomics reveals plant host responses to pathogens
title_full_unstemmed Spatially resolved transcriptomics reveals plant host responses to pathogens
title_short Spatially resolved transcriptomics reveals plant host responses to pathogens
title_sort spatially resolved transcriptomics reveals plant host responses to pathogens
topic Methodology
url 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
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