ArticlePlant biotechnology journal2026
Serial Spatial Transcriptomes Reveal Regulatory Transitions in Maize Leaf Development.
Article in Plant biotechnology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Unlocking the full potential of spatial omics in plants: practical challenges, solutions, and a path forward.The Plant cell · 2026Review
- Profiling maize embryonic leaf development and discovering new genes using high-resolution spatial long-read isoform sequencing.Nature plants · 2026Article
- Tomato Leaf Color Diversity as a Functional Trait: Molecular Mechanisms, Physiological Significance, and Environmental Responses.International journal of molecular sciences · 2026Review
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Authors and funding
12 authors.
Funding
Abstract
Plant leaves originate from the shoot apical meristem (SAM) and undergo a developmental process of highly coordinated gene expression regulation. To date, only a few key regulators have been identified and characterised, so the gene expression cascades responsible for leaf cell specification and differentiation from SAM remain largely elusive. Here, we optimised a spatial transcriptomics protocol using the 10× Genomics Visium system and developed computational pipelines to reconstruct three-dimensional gene expression profiles of the SAM and sequentially developing leaves in maize seedlings. These enabled positional indexing of cells sampled from consecutive developmental stages, revealing dynamic transitions from undifferentiated stem cells in the SAM to functionally differentiated leaf structures. Through spatial-temporal transcriptome analysis, we identified distinct transcriptional programs and key regulatory genes involved in meristem maintenance, leaf primordia initiation, vascular tissue differentiation, and cellular heterogeneity. This approach outperforms the single-cell transcriptome profiling, which lacks temporal and spatial contexts. Our optimised experimental pipeline, which goes from section preparation to data processing, enables the spatial resolution and 3-dimensional mapping of gene expression profiles. The established pipeline is readily applicable to delineating molecular events underlying developmental transitions, cell type specifications, and differentiation in plants.
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