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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 |
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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. |
format | Online Article Text |
id | pubmed-6785889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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