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.
Spatial and single-cell transcriptomics capture two distinct cell states in plant immunity
Authors: Hu, Y., Schaefer, R., Rendleman, M., Slattery, A., Cramer, A., Nahiyan, A., Breitweiser, L., Shah, M., Kaehler, E., Yao, C., Bowling, A., Crow, J., May, G., Tabor, G., Thatcher, S., Uppalapati, S. R., Muppirala, U., Deschamps, S.
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.
The study introduced full-length SOC1 genes from maize and soybean, and a partial SOC1 gene from blueberry, into tomato plants under constitutive promoters. While VcSOC1K and ZmSOC1 accelerated flowering, all three transgenes increased fruit number per plant mainly by promoting branching, and transcriptomic profiling revealed alterations in flowering, growth, and stress‑response pathways.
Imputation integrates single-cell and spatial gene expression data to resolve transcriptional networks in barley shoot meristem development
Authors: Demesa-Arevalo, E., Dorpholz, H., Vardanega, I., Maika, J. E., Pineda-Valentino, I., Eggels, S., Lautwein, T., Kohrer, K., Schnurbusch, T., von Korff, M., Usadel, B., Simon, R.
The study uses an imputation strategy that integrates deep single-cell RNA sequencing with spatial gene expression data to map transcriptional dynamics across barley inflorescence development at cellular resolution. By leveraging the BARVISTA web interface, the authors identify key transcriptional events in meristem founder cells, characterize complex branching mutants, and reconstruct spatio‑temporal trajectories of flower organogenesis, offering insights for targeted trait manipulation.
The study investigates the altered timing of the core circadian oscillator gene ELF3 in wheat compared to Arabidopsis, revealing that dawn-specific expression in wheat arises from repression by TOC1. An optimized computational model integrating experimental expression data and promoter architecture predicts that wheat’s circadian oscillator remains robust despite this shift, indicating flexibility in plant circadian network design.
The Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset
Authors: Wang, Z., Zenkl, R., Greche, L., De Solan, B., Bernigaud Samatan, L., Ouahid, S., Visioni, A., Robles-Zazueta, C. A., Pinto, F., Perez-Olivera, I., Reynolds, M. P., Zhu, C., Liu, S., D'argaignon, M.-P., Lopez-Lozano, R., Weiss, M., Marzougui, A., Roth, L., Dandrifosse, S., Carlier, A., Dumont, B., Mercatoris, B., Fernandez, J., Chapman, S., Najafian, K., Stavness, I., Wang, H., Guo, W., Virlet, N., Hawkesford, M., Chen, Z., David, E., Gillet, J., Irfan, K., Comar, A., Hund, A.
The Global Wheat Dataset Consortium released a comprehensive semantic segmentation dataset (GWFSS) of wheat organs across developmental stages, comprising 1,096 fully annotated images and 52,078 unannotated images from 11 institutions. Models based on DeepLabV3Plus and Segformer were trained, with Segformer achieving ≈90% mIoU for leaves and spikes but lower precision (54%) for stems, while also enabling weed exclusion and discrimination of necrotic, senescent, and residue tissues.
RNA‑seq of 328 wheat lines using a pan‑genome reference uncovered over 20,000 additional transcripts beyond the Chinese Spring genome and enabled construction of a pan‑gene eQTL regulatory atlas. Multi‑omics integration identified 231 high‑confidence candidate genes influencing 34 agronomic traits and powdery mildew resistance, with functional validation showing 80% of candidates affecting trait phenotypes via an EMS mutant library.
This review compiles experimental studies on wheat to assess how elevated CO₂, higher temperatures, and water deficit interact and affect productivity and water use. By calculating plasticity indices, the authors find that despite CO₂‑induced gains, overall yield generally declines under combined stress, while water consumption often decreases. They highlight the need for more data to improve and validate crop models under future climate scenarios.
The study introduces Transposase-Accessible Chromosome Conformation Capture (TAC-C), which combines ATAC‑seq and Hi‑C to map fine‑scale chromatin interactions in rice, sorghum, maize, and wheat, revealing genome‑size‑correlated loop structures and distinct C3 vs. C4 patterns. Integration with population genetics shows that loops link distal regulatory elements to phenotypic variation, and SPL transcription factors (TaSPL7/15) modulate photosynthesis‑related genes via these interactions, enhancing photosynthetic efficiency and starch content in wheat mutants.