The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
A Single-Cell RNA Sequencing Profiles the Developmental Landscape of Arabidopsis Root
Open accessAbstract
Cells of eukaryotic multicellular organisms have inherent heterogeneity. Recent advances in single-cell gene expression studies enable us to explore transcriptional regulation in dynamic development processes and highly heterogeneous cell populations. In this study, using a high-throughput single-cell RNA-sequencing assay, we found that the cells in Arabidopsis root are highly heterogeneous in their transcriptomes. A total of 24 putative cell clusters and the cluster-specific marker genes were identified. The spatial distribution and temporal ordering of the individual cells at different developmental stages illustrate their hierarchical structures and enable the reconstruction of continuous differentiation trajectory of root development. Moreover, we found that each root cell cluster exhibits distinct patterns of ion assimilation and hormonal responses. Collectively, our study reveals a high degree of heterogeneity of root cells and identifies the expression signatures of intermediate states during root cell differentiation at single-cell resolution. We also established a web server (http://wanglab.sippe.ac.cn/rootatlas/) to facilitate the use of the datasets generated in this study.
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Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
STAR: ultrafast universal RNA-seq aligner
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Salmon provides fast and bias-aware quantification of transcript expression
Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017) · Nature Methods · doi:10.1038/nmeth.4197 · Cited by 12,700
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314
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
Scenic: single-cell regulatory network inference and clustering.
Aibar, S., González-Blas, C. B., Moerman, T., Huynh-Thu, V. A., Imrichova, H., Hulselmans, G., Rambow, F., Marine, J.-C., Geurts, P., Aerts, J., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4463 · Cited by 6,520
Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types
Jaitin, D. A., Kenigsberg, E., Keren-Shaul, H., Elefant, N., Paul, F., Zaretsky, I., Mildner, A., Cohen, N., Jung, S., Tanay, A., et al. (2014) · Science · doi:10.1126/science.1247651 · Cited by 1,795
Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq
Treutlein, B., Brownfield, D. G., Wu, A. R., Neff, N. F., Mantalas, G. L., Espinoza, F. H., Desai, T. J., Krasnow, M. A., & Quake, S. R. (2014) · Nature · doi:10.1038/nature13173 · Cited by 1,342
Quantitative single-cell RNA-seq with unique molecular identifiers
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“Recent advances in single-cell RNA sequencing (scRNA-seq) technology provide unprecedented opportunities to systematically identify the entire cellular and molecular differentiation trajectory of stem cells at the single-cell level (Islam et al., 2014; Macosko et al., 2015).”
Background
Cited by
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
- Zhang, T.-Q., Xu, Z.-G., Shang, G.-D., & Wang, J.-W.
- Venue
- Molecular Plant
- Publisher
- Elsevier BV
- Published
- 2019-05
- Volume
- 12
- Issue
- 5
- Pages
- 648-660
- ISSN
- 1674-2052 (ISSN-L)
- OpenAlex
- W2938221109
- Cited by
- 505
- References
- 13
- FWCI
- 17.04
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Zhang, T.-Q., Xu, Z.-G., Shang, G.-D., & Wang, J.-W. (2019). A Single-Cell RNA Sequencing Profiles the Developmental Landscape of Arabidopsis Root. Molecular Plant. https://doi.org/10.1016/j.molp.2019.04.004
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