Spatially resolved transcriptomics reveals plant host responses to pathogens

Plant Methods - 2019
Michael Giolai1, Walter Verweij2, Ashleigh Lister2, Darren Heavens2, Iain C. Macaulay2, Matt Clark2
1John Innes Centre, Norwich Research Park, Norwich, UK
2Earlham Institute, Norwich Research Park, Norwich, UK

Tóm tắt

Abstract 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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Tài liệu tham khảo

Müller B, Grossniklaus U. Model organisms—a historical perspective. J Proteomics. 2010;73:2054–63.

Mincarelli L, Lister A, Lipscombe J, Macaulay IC. Defining cell identity with single-cell omics. Proteomics. 2018;18:1700312.

Crosetto N, Bienko M, van Oudenaarden A. Spatially resolved transcriptomics and beyond. Nat Rev Genet. 2015;16:57–66.

Stahl PL, Salmen F, Vickovic S, Lundmark A, Navarro JF, Magnusson J, et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science. 2016;353:78–82.

Junker JP, Noël ES, Guryev V, Peterson KA, Shah G, Huisken J, et al. Genome-wide RNA tomography in the Zebrafish Embryo. Cell. 2014;159:662–75.

Giacomello S, Salmén F, Terebieniec BK, Vickovic S, Navarro JF, Alexeyenko A, et al. Spatially resolved transcriptome profiling in model plant species. Nat Plants. 2017;3:17061.

Genomics Rusk N. Spatial transcriptomics. Nat Methods. 2016;13:710–1.

Mulema JMK, Denby KJ. Spatial and temporal transcriptomic analysis of the Arabidopsis thaliana–Botrytis cinerea interaction. Mol Biol Rep. 2012;39:4039–49.

Ghawana S, Paul A, Kumar H, Kumar A, Singh H, Bhardwaj PK, et al. An RNA isolation system for plant tissues rich in secondary metabolites. BMC Res Notes. 2011;4:85.

Borges F, Gardner R, Lopes T, Calarco JP, Boavida LC, Slotkin R, et al. FACS-based purification of Arabidopsis microspores, sperm cells and vegetative nuclei. Plant Methods. 2012;8:44.

Deal RB, Henikoff S. The INTACT method for cell type-specific gene expression and chromatin profiling in Arabidopsis thaliana. Nat Protoc. 2010;6:56.

Gaiero P, Šimková H, Vrána J, Santiñaque FF, López-Carro B, Folle GA, et al. Intact DNA purified from flow-sorted nuclei unlocks the potential of next-generation genome mapping and assembly in Solanum species. MethodsX. 2018;5:328–36.

Duncan S, Olsson T, Hartley M, Dean C, Rosa S. Single molecule RNA FISH in Arabidopsis root cells. BIO-Protoc. 2017;7. https://bio-protocol.org/e2240 . Accessed 5 July 2018.

Kerk NM. Laser capture microdissection of cells from plant tissues. Plant Physiol. 2003;132:27–35.

Chan AC, Khan D, Girard IJ, Becker MG, Millar JL, Sytnik D, et al. Tissue-specific laser microdissection of the Brassica napus funiculus improves gene discovery and spatial identification of biological processes. J Exp Bot. 2016;67:3561–71.

Martin LBB, Nicolas P, Matas AJ, Shinozaki Y, Catalá C, Rose JKC. Laser microdissection of tomato fruit cell and tissue types for transcriptome profiling. Nat Protoc. 2016;11:2376–88.

Jones JDG, Dangl JL. The plant immune system. Nature. 2006;444:323–9.

Navarro L. The Transcriptional Innate Immune Response to flg22 Interplay and overlap with Avr gene-dependent defense responses and bacterial pathogenesis. Plant Physiol. 2004;135:1113–28.

Farmer E, Farmer E, Mousavi S, Lenglet A. Leaf numbering for experiments on long distance signalling in Arabidopsis. Protoc Exch. 2013. http://www.nature.com/protocolexchange/protocols/2787 . Accessed 3 Nov 2016.

Supek F, Bošnjak M, Škunca N, Šmuc T. REVIGO Summarizes and visualizes long lists of gene ontology terms. PLoS ONE. 2011;6:e21800.

Frey BJ, Dueck D. Clustering by passing messages between data points. Science. 2007;315:972–6.

Berardini TZ, Reiser L, Li D, Mezheritsky Y, Muller R, Strait E, et al. The arabidopsis information resource: Making and mining the “gold standard” annotated reference plant genome: Tair: Making and Mining the “Gold Standard” Plant Genome. Genesis. 2015;53:474–85.

Pandey SP, Somssich IE. The role of WRKY transcription factors in plant immunity. Plant Physiol. 2009;150:1648–55.

Xie Z, Nolan TM, Jiang H, Yin Y. AP2/ERF transcription factor regulatory networks in hormone and abiotic stress responses in Arabidopsis. Front Plant Sci. 2019;10:228.

Dubos C, Stracke R, Grotewold E, Weisshaar B, Martin C, Lepiniec L. MYB transcription factors in Arabidopsis. Trends Plant Sci. 2010;15:573–81.

Kulkarni SR, Vaneechoutte D, Van de Velde J, Vandepoele K. TF2Network: predicting transcription factor regulators and gene regulatory networks in Arabidopsis using publicly available binding site information. Nucleic Acids Res. 2018;46:e31.

Ryu KH, Huang L, Kang HM, Schiefelbein J. Single-cell RNA sequencing resolves molecular relationships among individual plant cells. Plant Physiol. 2019;179:1444–56.

Denyer T, Ma X, Klesen S, Scacchi E, Nieselt K, Timmermans MCP. Spatiotemporal developmental trajectories in the Arabidopsis root revealed using high-throughput single-cell RNA sequencing. Dev Cell. 2019;48(840–852):e5.

Jean-Baptiste K, McFaline-Figueroa JL, Alexandre CM, Dorrity MW, Saunders L, Bubb KL, et al. Dynamics of gene expression in single root cells of A. thaliana. Plant Cell. 2019;31:933–1011.

Karasov TL, Almario J, Friedemann C, Ding W, Giolai M, Heavens D, et al. Arabidopsis thaliana and Pseudomonas pathogens exhibit stable associations over evolutionary timescales. Cell Host Microbe. 2018;24(168–179):e4.

Dangl JL, Horvath DM, Staskawicz BJ. Pivoting the plant immune system from dissection to deployment. Science. 2013;341:746–51.

Picelli S, Faridani OR, Björklund ÅK, Winberg G, Sagasser S, Sandberg R. Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc. 2014;9:171–81.

Macaulay IC, Haerty W, Kumar P, Li YI, Hu TX, Teng MJ, et al. G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nat Methods. 2015;12:519–22.

Jost R, Berkowitz O, Masle J. Magnetic quantitative reverse transcription PCR: a high-throughput method for mRNA extraction and quantitative reverse transcription PCR. Biotechniques. 2007;43:206–11.

Denoux C, Galletti R, Mammarella N, Gopalan S, Werck D, De Lorenzo G, et al. Activation of defense response pathways by OGs and Flg22 elicitors in Arabidopsis seedlings. Mol Plant. 2008;1:423–45.

Zipfel C. Pattern-recognition receptors in plant innate immunity. Curr Opin Immunol. 2008;20:10–6.

Bent A. Resistance from relatives. Nat Biotechnol. 2016;34:620–1.

Underwood W, Somerville SC. Perception of conserved pathogen elicitors at the plasma membrane leads to relocalization of the Arabidopsis PEN3 transporter. Proc Natl Acad Sci. 2013;110:12492–7.

Zhu YY, Machleder EM, Chenchik A, Li R, Siebert PD. Reverse transcriptase template switching: a SMART approach for full-length cDNA library construction. Biotechniques. 2001;30:892–7.

Picelli S, Björklund \AAsa K., Faridani OR, Sagasser S, Winberg G, Sandberg R. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods. 2013. http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.2639.html . Accessed 6 Jan 2015.

Beier S, Himmelbach A, Colmsee C, Zhang X-Q, Barrero RA, Zhang Q, et al. Construction of a map-based reference genome sequence for barley, Hordeum vulgare L. Sci Data. 2017;4:170044.

FastQC: a quality control tool for high throughput sequence data. 2010. http://www.bioinformatics.babraham.ac.uk/projects/fastqc . Accessed 31 Jan 2017.

Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17:10.

Dobin A, Gingeras TR. Mapping RNA-seq reads with STAR: mapping RNA-seq reads with STAR. In: Bateman A, Pearson WR, Stein LD, Stormo GD, Yates JR, editors. Curr Protoc Bioinforma. Hoboken: Wiley; 2015. https://doi.org/10.1002/0471250953.bi1114s51 .

Wang L, Wang S, Li W. RSeQC: quality control of RNA-seq experiments. Bioinforma Oxf Engl. 2012;28:2184–5.

Anders S, Pyl PT, Huber W. HTSeq–a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–9.

Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;1:15. https://doi.org/10.1186/s13059-014-0550-8 .

Love MI, Anders S, Kim V, Huber W. RNA-Seq workflow: gene-level exploratory analysis and differential expression. F1000 Res. 2016;4:1070.

Wickham H. Ggplot2: elegant graphics for data analysis. New York: Springer; 2009.

Yu G, Wang L-G, Han Y, He Q-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS J Integr Biol. 2012;16:284–7.

Carlson M. org.At.tair.db: Genome wide annotation for Arabidopsis. 2018.

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