The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Single-Cell Transcriptomics: A High-Resolution Avenue for Plant Functional Genomics
Open accessAbstract
Plant function is the result of the concerted action of single cells in different tissues. Advances in RNA-seq technologies and tissue processing allow us now to capture transcriptional changes at single-cell resolution. The incredible potential of single-cell RNA-seq lies in the novel ability to study and exploit regulatory processes in complex tissues based on the behaviour of single cells. Importantly, the independence from reporter lines allows the analysis of any given tissue in any plant. While there are challenges associated with the handling and analysis of complex datasets, the opportunities are unique to generate knowledge of tissue functions in unprecedented detail and to facilitate the application of such information by mapping cellular functions and interactions in a plant cell atlas.
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Cites
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
Massively parallel digital transcriptional profiling of single cells
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Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
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Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris
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Cited by
Napier, J. D., Heckman, R. W., & Juenger, T. E. (2023) · The Plant Cell · doi:10.1093/plcell/koac322 · Cited by 158
Plant synthetic biology innovations for biofuels and bioproducts
Yang, Y., Chaffin, T. A., Ahkami, A. H., Blumwald, E., & Stewart, C. N. (2022) · Trends in Biotechnology · doi:10.1016/j.tibtech.2022.09.007 · Cited by 59
Metadata
- Authors
- Rich-Griffin, C., Stechemesser, A., Finch, J., Lucas, E., Ott, S., & Schäfer, P.
- Venue
- Trends in Plant Science
- Publisher
- Elsevier BV
- Published
- 2020-02
- Volume
- 25
- Issue
- 2
- Pages
- 186-197
- ISSN
- 1360-1385 (ISSN-L)
- OpenAlex
- W2990071085
- Cited by
- 198
- References
- 17
- FWCI
- 1.77
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Rich-Griffin, C., Stechemesser, A., Finch, J., Lucas, E., Ott, S., & Schäfer, P. (2020). Single-Cell Transcriptomics: A High-Resolution Avenue for Plant Functional Genomics. Trends in Plant Science. https://doi.org/10.1016/j.tplants.2019.10.008
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
