ReviewPhysiology and molecular biology of plants : an international journal of functional plant biology2025
Opportunities and challenges in the application of single-cell transcriptomics in plant tissue research.
Review in Physiology and molecular biology of plants : an international journal of functional plant biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Go with the Phloem: A Review of the Methods to Collect Plant Phloem Tissue.Methods in molecular biology (Clifton, N.J.) · 2026Review
- MYB transcription factors as context-dependent regulatory modules for precision crop improvement.Frontiers in plant science · 2026Article
- Leveraging two novel droplet-based single-cell RNA Sequencing platforms: a comparative study with 10x genomics.BMC genomics · 2025Article
- Single-cell transcriptional decoding of iron deficiency responses in maize root tips.Plant cell reports · 2025Article
- Opportunities and challenges in the application of spatiotemporal transcriptomics in plant research.Frontiers in plant science · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell transcriptomics overcomes the limitations of conventional transcriptome methods by isolating and sequencing RNA from individual cells, thus capturing unique expression values for each cell. This technology allows unprecedented precision in observing the stochasticity and heterogeneity of gene expression within cells. However, single-cell RNA sequencing (scRNA-seq) experiments often fail to capture all cells and genes comprehensively, and single-modality data is insufficient to explain cell states and systemic changes. To address this, the integration of multi-source scRNA-seq and single-cell multi-modality data has emerged, enabling the construction of comprehensive cell atlases. These integration methods also facilitate the exploration of causal relationships and gene regulatory mechanisms across different modalities. This review summarizes the fundamental principles, applications, and value of these integration methods in revealing biological changes, and analyzes the advantages, disadvantages, and future directions of current approaches.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.