» Articles » PMID: 38381195

Plant Biotechnology Research with Single-cell Transcriptome: Recent Advancements and Prospects

Overview
Journal Plant Cell Rep
Publisher Springer
Date 2024 Feb 21
PMID 38381195
Authors
Affiliations
Soon will be listed here.
Abstract

Single-cell transcriptomic techniques have emerged as powerful tools in plant biology, offering high-resolution insights into gene expression at the individual cell level. This review highlights the rapid expansion of single-cell technologies in plants, their potential in understanding plant development, and their role in advancing plant biotechnology research. Single-cell techniques have emerged as powerful tools to enhance our understanding of biological systems, providing high-resolution transcriptomic analysis at the single-cell level. In plant biology, the adoption of single-cell transcriptomics has seen rapid expansion of available technologies and applications. This review article focuses on the latest advancements in the field of single-cell transcriptomic in plants and discusses the potential role of these approaches in plant development and expediting plant biotechnology research in the near future. Furthermore, inherent challenges and limitations of single-cell technology are critically examined to overcome them and enhance our knowledge and understanding.

Citing Articles

Harnessing Single-Cell and Spatial Transcriptomics for Crop Improvement.

Hu Y, Dash L, May G, Sardesai N, Deschamps S Plants (Basel). 2025; 13(24.

PMID: 39771174 PMC: 11728591. DOI: 10.3390/plants13243476.


Single-cell transcriptomics: a new frontier in plant biotechnology research.

Singh S, Praveen A, Dudha N, Sharma V, Bhadrecha P Plant Cell Rep. 2024; 43(12):294.

PMID: 39585480 DOI: 10.1007/s00299-024-03383-9.


Multi-Omics Approaches in Oil Palm Research: A Comprehensive Review of Metabolomics, Proteomics, and Transcriptomics Based on Low-Temperature Stress.

John Martin J, Song Y, Hou M, Zhou L, Liu X, Li X Int J Mol Sci. 2024; 25(14).

PMID: 39062936 PMC: 11277459. DOI: 10.3390/ijms25147695.

References
1.
Abdelaal T, Michielsen L, Cats D, Hoogduin D, Mei H, Reinders M . A comparison of automatic cell identification methods for single-cell RNA sequencing data. Genome Biol. 2019; 20(1):194. PMC: 6734286. DOI: 10.1186/s13059-019-1795-z. View

2.
Adrian J, Chang J, Ballenger C, Bargmann B, Alassimone J, Davies K . Transcriptome dynamics of the stomatal lineage: birth, amplification, and termination of a self-renewing population. Dev Cell. 2015; 33(1):107-18. PMC: 4390738. DOI: 10.1016/j.devcel.2015.01.025. View

3.
Aldridge S, Teichmann S . Single cell transcriptomics comes of age. Nat Commun. 2020; 11(1):4307. PMC: 7453005. DOI: 10.1038/s41467-020-18158-5. View

4.
Asp M, Giacomello S, Larsson L, Wu C, Furth D, Qian X . A Spatiotemporal Organ-Wide Gene Expression and Cell Atlas of the Developing Human Heart. Cell. 2019; 179(7):1647-1660.e19. DOI: 10.1016/j.cell.2019.11.025. View

5.
Bakken T, Hodge R, Miller J, Yao Z, Nguyen T, Aevermann B . Single-nucleus and single-cell transcriptomes compared in matched cortical cell types. PLoS One. 2018; 13(12):e0209648. PMC: 6306246. DOI: 10.1371/journal.pone.0209648. View