ReviewFrontiers in plant science2025
Opportunities and challenges in the application of spatiotemporal transcriptomics in plant research.
Review in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
3 citing papers in PubMed.
- Spatiotemporal reprogramming of auxin signaling and resistance outputs across model plants and solanaceae crops underFrontiers in plant science · 2026Review
- Seed function in space and time: how spatial transcriptomics completes the picture.Frontiers in plant science · 2026Review
- Poly pipeline: a polyvalent spatial transcriptomics workflow validated across polyploid and diploid organisms.GigaByte (Hong Kong, China) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spatiotemporal heterogeneity is recognized as a key driver of functional diversity in tissues. Spatial transcriptomics, which integrates high-throughput transcriptomics with high-resolution tissue imaging, enables the precise mapping of gene expression patterns at the tissue section level. This technology overcomes the limitations of traditional transcriptomics by providing spatial context and applying unbiased bioinformatics approaches. With the rapid advancement of sequencing technologies, spatial transcriptomics is a pivotal tool for exploring cell fate determination, tissue development, and disease mechanisms, and its underlying principles, technical variations, practical performance, and future directions collectively provide robust theoretical and methodological support for systematically unveiling the spatiotemporal regulation of life processes.
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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.