Spatially resolved transcriptome profiling in model plant species

Abstract

Understanding complex biological systems requires functional characterization of specialized tissue domains. However, existing strategies for generating and analysing high-throughput spatial expression profiles were developed for a limited range of organisms, primarily mammals. Here we present the first available approach to generate and study high-resolution, spatially resolved functional profiles in a broad range of model plant systems. Our process includes high-throughput spatial transcriptome profiling followed by spatial gene and pathway analyses. We first demonstrate the feasibility of the technique by generating spatial transcriptome profiles from model angiosperms and gymnosperms microsections. In Arabidopsis thaliana we use the spatial data to identify differences in expression levels of 141 genes and 189 pathways in eight inflorescence tissue domains. Our combined approach of spatial transcriptomics and functional profiling offers a powerful new strategy that can be applied to a broad range of plant species, and is an approach that will be pivotal to answering fundamental questions in developmental and evolutionary biology.

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Figure 1: Spatially resolved transcriptome profiling in plants.
Figure 2: Method reproducibility in angiosperm and gymnosperm species.
Figure 3: Validation of the method on three A. thaliana tissue sections.
Figure 4: Types of gene expression studies allowed by spatial transcriptomics data in A. thaliana.

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Acknowledgements

We thank the Swedish National Genomics Infrastructure hosted at SciLifeLab, the National Bioinformatics Infrastructure Sweden (NBIS) for providing computational assistance, and the Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) for providing computational infrastructure. This work was supported by Knut and Alice Wallenberg Foundation, and Swedish Research Council. N.R.S. and B.K.T. are supported by the Trees and Crop for the Future (TC4F) project. This work was supported by a grant to N.R.S. from the Carl Tryggers Stiftelse för Vetenskaplig Forskning.

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Authors

Contributions

S.G. and J.L. designed the project. S.G. developed the plant-specific protocol, performed and guided experiments and data analyses, prepared figures and wrote the manuscript. F.S. and P.L.S. developed the original protocol for mammalian tissue. F.S. contributed to some code used for the analyses. B.K.T. performed experiments. S.V. developed barcoded arrays. J.F.N. developed the alignment and demultiplexing pipeline. A.A. developed the linear model and performed its computations. J.R. performed a part of data analysis and a part of figure preparation. L.S.M. and V.B. provided consultation on plant cell-wall degradation enzymes. C.M. developed the visualization and data sharing tool. J.F.S. provided A. thaliana and P. abies samples, contributed to data interpretation. N.S. provided P. tremula samples, contributed to data interpretation, and guided the development of the visualization tool. A.A., L.S.M., J.F.S., N.R.S. and J.L. edited the manuscript.

Corresponding authors

Correspondence to Stefania Giacomello or Joakim Lundeberg.

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Competing interests

P.L.S. and J.L are founders of a company that holds IP rights to the presented technology.

Supplementary information

Supplementary Information

Supplementary Figures 1-13. (PDF 19503 kb)

Supplementary Table 1

Differential expressed genes between developing and dormant Populus tremula leaf buds. (XLSX 327 kb)

Supplementary Table 2

Number of TP, TN, FP and FN per each tissue domain in A. thaliana replicates. (XLSX 44 kb)

Supplementary Table 3

Linear model P-values per genes and pathways at the macro- and micro-category level. (XLSX 1617 kb)

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Giacomello, S., Salmén, F., Terebieniec, B. et al. Spatially resolved transcriptome profiling in model plant species. Nature Plants 3, 17061 (2017). https://doi.org/10.1038/nplants.2017.61

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