The review examines the genetic networks governing spikelet number per spike (SNS) in wheat, highlighting how the balance between inflorescence meristem activity and the timing of terminal spikelet transition determines yield potential. It discusses how mutations affecting meristem identity can create supernumerary spikelets, the trade-offs of such traits, and recent advances using spatial transcriptomics, single‑cell analyses, and multi‑omics to identify new SNS genes for breeding.

The authors used a bottom‑up thermodynamic modelling framework to investigate how plants decode calcium signals, starting from Ca2+ binding to EF‑hand proteins and extending to higher‑order decoding modules. They identified six universal Ca2+-decoding modules that can explain variations in calcium sensitivity among kinases and provide a theoretical basis for interpreting calcium signal amplitude and frequency in plant cells.

The study applied dual-species spatial transcriptomics at single-cell resolution to map plant and fungal gene activity in rice roots colonized by Rhizophagus irregularis, revealing transcriptional heterogeneity among morphologically similar arbuscules. By pioneering an AM-inducible TRAP-seq using stage‑specific promoters, the authors uncovered stage‑specific reprogramming of nutrient transporters and defence genes, indicating dynamic regulation of nutrient exchange and arbuscule lifecycle.

The study evaluates the use of single-cell RNA sequencing (scRNA-seq) data to predict plant metabolic pathway genes (MPGs) in Arabidopsis thaliana, comparing five multi-label machine‑learning algorithms against traditional bulk RNA‑seq approaches. scRNA‑seq generated co‑expression networks that, while different, yielded significantly higher MPG classification accuracy, especially when data were split by genetic background or tissue type, and deep learning outperformed classical methods. The authors conclude that scRNA‑seq offers superior predictive power and should be incorporated into future MPG discovery pipelines.

The study characterizes the single-copy S-nitrosoglutathione reductase 1 (MpGSNOR1) in the liverwort Marchantia polymorpha, showing that loss-of-function mutants generated via CRISPR/Cas9 exhibit marked morphological defects and compromised SNO homeostasis and immune responses. These findings indicate that GSNOR-mediated regulation of S‑nitrosylation is an ancient mechanism linking development and immunity in early land plants.

The study applied spatial transcriptomics to map the transcriptional landscape of wheat (Triticum aestivum) inflorescences during spikelet development, revealing two distinct regions—a RAMOSA2‑active primordium and an ALOG1‑expressing boundary. Developmental assays showed that spikelets arise from meristematic zones accompanied by vascular rachis formation, identifying key regulators that could be targeted to improve spikelet number and yield.

The study used single‑cell transcriptomics to compare Arabidopsis thaliana leaf cell responses during pattern‑triggered and effector‑triggered immunity, revealing that core defense modules are broadly shared but differ in timing, intensity, and cell‑type specific receptor dynamics. Distinct mesophyll subpopulations showed divergent resilience patterns, and gene regulatory network analysis identified WRKY‑regulated and salicylic‑acid biosynthesis modules, with the cue1-6 mutant confirming robustness of core immune responses while exposing cryptic sucrose‑responsive pathways.

An optimized workflow was developed to apply the Xenium in situ sequencing platform to formalin‑fixed paraffin‑embedded (FFPE) sections of Medicago truncatula roots and nodules, incorporating customized tissue preparation, probe design, and imaging to overcome plant‑specific challenges such as cell wall autofluorescence. The protocol was validated across nodule developmental stages using both a 50‑gene panel for mature cell identity and an expanded 480‑gene panel covering multiple cell types, providing a scalable high‑resolution spatial transcriptomics method adaptable to other plant systems.

The study applied the STOmics spatial transcriptomics platform to map gene expression at subcellular resolution in developing wheat (Triticum aestivum) seeds during grain filling, analyzing over four million transcripts. Eight functional cellular groups were identified, including four distinct endosperm clusters with radial expression patterns and novel marker genes, and subgenome‑biased expression was observed among specific paralogs. These results highlight spatial transcriptomics as a powerful tool for uncovering tissue‑specific and polyploid‑specific gene regulation in seeds.

The study combined spatial transcriptomics and single-nuclei RNA sequencing to map soybean (Glycine max) responses to Asian soybean rust caused by Phakopsora pachyrhizi, revealing two distinct host cell states: pathogen‑occupied regions and adjacent non‑infected regions that show heightened defense gene expression. Gene co‑expression network analysis identified a key immune‑related module active in the stressed cells, highlighting a cell‑non‑autonomous defense mechanism.