The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Distinct identities of leaf phloem cells revealed by single cell transcriptomics
Open accessAbstract
The leaf vasculature plays a key role in solute translocation. Veins consist of at least seven distinct cell types, with specific roles in transport, metabolism, and signaling. Little is known about leaf vascular cells, in particular the phloem parenchyma (PP). PP effluxes sucrose into the apoplasm as a basis for phloem loading, yet PP has been characterized only microscopically. Here, we enriched vascular cells from Arabidopsis leaves to generate a single-cell transcriptome atlas of leaf vasculature. We identified at least 19 cell clusters, encompassing epidermis, guard cells, hydathodes, mesophyll, and all vascular cell types, and used metabolic pathway analysis to define their roles. Clusters comprising PP cells were enriched for transporters, including SWEET11 and SWEET12 sucrose and UmamiT amino acid efflux carriers. We provide evidence that PP development occurs independently from ALTERED PHLOEM DEVELOPMENT, a transcription factor required for phloem differentiation. PP cells have a unique pattern of amino acid metabolism activity distinct from companion cells (CCs), explaining differential distribution/metabolism of amino acids in veins. The kinship relation of the vascular clusters is strikingly similar to the vein morphology, except for a clear separation of CC from the other vascular cells including PP. In summary, our single-cell RNA-sequencing analysis provides a wide range of information into the leaf vasculature and the role and relationship of the leaf cell types.
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Cites
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
Integrating single-cell transcriptomic data across different conditions, technologies, and species
Butler, A., Hoffman, P., Smibert, P., Papalexi, E., & Satija, R. (2018) · Nature Biotechnology · doi:10.1038/nbt.4096 · Cited by 13,174
Spatial reconstruction of single-cell gene expression data
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055 · cited 1×
“Dimensionality reduction, UMAP visualization, cell clustering analysis, and correlation analysis The Seurat R package (version 3.1.0; Satija et al., 2015; Butler et al., 2018) was used for dimensionality reduction analysis.”
InfluentialHafemeister, C., & Satija, R. (2019) · Genome Biology · doi:10.1186/s13059-019-1874-1 · Cited by 4,479 · cited 1×
“The SCTransform option was used for normalization, scaling the data and finding variable genes using default parameters (Hafemeister and Satija, 2019).”
MethodMetabolic landscape of the tumor microenvironment at single cell resolution
Xiao, Z., Dai, Z., & Locasale, J. W. (2019) · Nature Communications · doi:10.1038/s41467-019-11738-0 · Cited by 524
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Goel, M., Campoy, J. A., Krause, K., Baus, L. C., Sahu, A., Sun, H., Walkemeier, B., Marek, M., Beaudry, R., Ruiz, D., et al. (2024) · Genome Biology · doi:10.1186/s13059-024-03337-0 · Cited by 31
Metadata
- Authors
- Kim, J.-Y., Symeonidi, E., Pang, T. Y., Denyer, T., Weidauer, D., Bezrutczyk, M., Miras, M., Zöllner, N., Hartwig, T., Wudick, M. M., Lercher, M., Chen, L.-Q., Timmermans, M. C. P., & Frommer, W. B.
- Venue
- The Plant Cell
- Publisher
- Oxford University Press (OUP)
- Published
- 2021-01-07
- Volume
- 33
- Issue
- 3
- Pages
- 511-530
- ISSN
- 1040-4651 (ISSN-L)
- 1532-298X
- OpenAlex
- W3120025357
- Cited by
- 347
- References
- 5
- FWCI
- 10.30
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Kim, J.-Y., Symeonidi, E., Pang, T. Y., Denyer, T., Weidauer, D., Bezrutczyk, M., Miras, M., Zöllner, N., Hartwig, T., Wudick, M. M., Lercher, M., Chen, L.-Q., Timmermans, M. C. P., & Frommer, W. B. (2021). Distinct identities of leaf phloem cells revealed by single cell transcriptomics. The Plant Cell. https://doi.org/10.1093/plcell/koaa060
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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