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Single-cell RNA sequencing provides a high-resolution roadmap for understanding the multicellular compartmentation of specialized metabolism


Monoterpenoid indole alkaloids (MIAs) are among the most diverse specialized metabolites in plants and are of great pharmaceutical importance. We leveraged single-cell transcriptomics to explore the spatial organization of MIA metabolism in Catharanthus roseus leaves, and the transcripts of 20 MIA genes were first localized, updating the model of MIA biosynthesis. The MIA pathway was partitioned into three cell types, consistent with the results from RNA in situ hybridization experiments. Several candidate transporters were predicted to be essential players shuttling MIA intermediates between inter- and intracellular compartments, supplying potential targets to increase the overall yields of desirable MIAs in native plants or heterologous hosts through metabolic engineering and synthetic biology. This work provides not only a universal roadmap for elucidating the spatiotemporal distribution of biological processes at single-cell resolution, but also abundant cellular and genetic resources for further investigation of the higher-order organization of MIA biosynthesis, transport and storage.

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Fig. 1: Anatomical features of C. roseus leaves and isolation of protoplasts.
Fig. 2: Chromosomal distribution of genomic features and cell clustering.
Fig. 3: Annotation of the C. roseus leaf cell types.
Fig. 4: Cell type-specific expression of genes involved in the MIA biosynthesis pathway and the spatial organization of MIA metabolism in C. roseus leaves.
Fig. 5: Reconstruction of the developmental trajectories of ECs and VCs.
Fig. 6: Comparison of C. roseus and A. thaliana data sets at single-cell resolution.

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Data availability

The single-cell and bulk RNA sequencing data generated in this study have been deposited to NCBI with the accession number PRJNA759937. The scRNA-seq data sets of A. thaliana were downloaded from the Beijing Institute of Genomics Data Center ( with the accession number PRJCA003094. The genome used in this study has been deposited to NCBI with the accession number PRJNA841429. The quantification results have been deposited to figshare with


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This work was supported by the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (grant no. 2021-I2M-1-032). The funders had no role in the design of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Author information

Authors and Affiliations



C.S., J.W. and S.C. conceived and designed the project. Yi Li, X.S., S.W., R.L. and H.Z. performed the experiments. S.S., Ying Li, J.X. and G.S. analysed the data. Yi Li, S.S. and X.S. wrote the manuscript draft. C.S., B.S.-P., B.G., J.W. and S.C. revised the manuscript.

Corresponding authors

Correspondence to Benoit St-Pierre, Shilin Chen or Chao Sun.

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The authors declare no competing interests.

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Nature Plants thanks Tetsuro Mimura, Silin Zhong, Tomáš Pluskal, Kenneth Birnbaum and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 The expression of genes quantified by Alevin and Cell Ranger.

EVM0030220, which was unique among genes, had similar expression, as estimated by Alevin or Cell Ranger. EVM0024889, which shared 77% identity with EVM0001360, showed slightly diminished expression using Cell Ranger compared with that obtained using Alevin. EVM0035115, which shared 99.00% identity with EVM0010963, exhibited remarkably reduced expression with Cell Ranger, and the expression of EVM0031539, which was 100% identical to EVM0012710, was relatively high according to Alevin but was quantified close to zero using Cell Ranger.

Extended Data Fig. 2 Cell cluster assignment of Cell Ranger expression matrices and correlation of cell cluster expression patterns derived from different quantification methods.

a, UMAP visualization of cell clusters based on gene expression matrices of high-quality cells. b, The expression patterns of representative cell type-specific marker genes. The dot diameter represents the proportion of cells expressing a particular gene in each cluster, whereas the color indicates the scaled average expression. The full names of selected genes are provided in Supplementary Table 5. c, Heatmap showing Spearman’s correlation between clusters from two quantification pipelines: Alevin (alv) and Cell Ranger (cr). IPAP: 12_alv/13_cr; VC: 8_alv/8_cr; IC: 11_alv/10_cr; PC: 10_alv/12_cr; UN: 7_alv/9_cr; MC: 0–5, 13_alv/0–5, 11, 15, 16_cr; EC: 6, 9_alv/6, 7, 14_cr.

Extended Data Fig. 3 Expression patterns of MIA genes in cell clusters derived from Alevin (a) and Cell Ranger (b).

The expression of GO1 was dramatically underestimated by Cell Ranger. The full names of the selected genes are provided in Supplementary Table 7.

Extended Data Fig. 4 RIH validation of marker genes used for cell type annotation.

Paraffin-embedded serial cross-sections from 1.8–2.0 cm leaves were hybridized with digoxigenin-labeled transcripts. Sections were hybridized with sense and antisense RNA probes for NLTP2, SABP2, CB21 and PRS2 to localize their mRNAs in C. roseus leaves. The identified cell types are indicated by yellow arrows: CB21, mesophyll cell; SABP2, internal phloem-associated parenchyma cell; NLTP2, epidermal cell; PRS2, vascular cell. le, lower epidermis; ue, upper epidermis; pm, palisade mesophyll cells; and sm, spongy mesophyll cells.

Extended Data Fig. 5 Reassignment of the EC population.

a, UMAP visualization of subclusters in the EC population. b, Dot plot showing the expression patterns of EC and GC marker genes in EC subclusters. Dot diameter indicates the proportion of cells expressing a given gene in each cluster, whereas the color indicates the scaled average expression. The full names of the selected genes are given in Supplementary Table 5.

Extended Data Fig. 6 Gene clusters containing transporter genes that are possibly involved in the shuttling of MIA intermediates.

a, A gene cluster containing STR, TDC and CrMATE1 on Pseudo-Chr5. b, A PUP cluster on Pseudo-Chr7. The PUPs are highlighted in purple.

Extended Data Fig. 7 Localization of TDC (a) and G10H (b) mRNAs in developing leaves using RIH.

Paraffin-embedded serial cross-sections from 1.8–2.0 cm leaves were hybridized with digoxigenin-labeled transcripts. Sections were hybridized with antisense and sense RNA probes. base, leaf base; middle, the middle area of the leaf at a distance of 6 mm from the base; tip, the tip portion of the leaf at 11 mm from the base; le, lower epidermis; ue, upper epidermis; pm, palisade mesophyll cells; sm, spongy mesophyll cells.

Supplementary information

Supplementary Information

Supplementary Figs. 1–16.

Reporting Summary

Supplementary Tables

Supplementary Tables 1–19

Supplementary Data 1

UMAP 3D scatter plots visualizing cell clustering based on gene expression matrices from Alevin and Cell Ranger.

Supplementary Data 2

Gene expression across cell types in different replicates and integrated data sets.

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Sun, S., Shen, X., Li, Y. et al. Single-cell RNA sequencing provides a high-resolution roadmap for understanding the multicellular compartmentation of specialized metabolism. Nat. Plants 9, 179–190 (2023).

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