Keywords: paralog processing, deep learning, ascorbate, spatial transcriptomics, bread wheat, SWI3

Latest 23 Papers

Controlling GRF4-GIF1 Expression for Efficient, Genotype-Independent Transformation Across Wheat Cultivars

Authors: Hayta, S., Smedley, M. A., Bayraktar, M., Forner, M., Backhaus, A., Lister, C., Clarke, M., Uauy, C., Griffiths, S.

Date: 2025-09-02 · Version: 1

DOI: 10.1101/2025.08.29.673042

Model Organism: Triticum aestivum

GRF4‑GIF1 fusion Agrobacterium-mediated transformation genotype‑independent regeneration bread wheat transformation efficiency

Spatial transcriptomics identifies distinct domains regulating yield-related traits of the wheat ear

Authors: Qu, Y., Tan, C., Yang, L., Pasquariello, M., Alabdullah, A. K., Sun, S., Iqbal, M., Salamon, J., Boden, S.

Date: 2025-08-13 · Version: 1

DOI: 10.1101/2025.08.12.670006

Model Organism: Triticum aestivum

spikelet development spatial transcriptomics wheat inflorescence RAMOSA2 ALOG1

Plant-Compatible Xenium In Situ Sequencing: Optimised Protocol for Spatial Transcriptomics in Medicago truncatula Roots and Nodules

Authors: Jhu, M.-Y., Heffer, J., Deamer, A., Moraes, T. A., Piskorz, A. M., Xia, C.

Date: 2025-07-25 · Version: 1

DOI: 10.1101/2025.07.22.663073

Model Organism: Medicago truncatula

spatial transcriptomics Xenium in situ sequencing Medicago truncatula root nodules autofluorescence mitigation

Phenotypic scoring of Canola Blackleg severity using machine learning image analysis

Authors: Hu, Q., Anderson, S. N., Gardner, S., Ernst, T. W., Koscielny, C. B., Bahia, N. S., Johnson, C. G., Jarvis, A. C., Hynek, J., Coles, N., Falak, I., Charne, D. R., Ruidiaz, M. E., Linares, J. N., Mazis, A., Stanton, D. J.

Date: 2025-07-22 · Version: 1

DOI: 10.1101/2025.07.17.665372

Model Organism: Multi-species

blackleg disease canola (Brassica spp.)deep learning image-based phenotyping disease severity scoring

RegenPGC View: Semantic Segmentation of Perennial Groundcover Cropping Systems to Restore American Croplands

Authors: Meyering, B., Schlautman, B.

Date: 2025-07-06 · Version: 1

DOI: 10.1101/2025.07.03.663038

Model Organism: General

perennial groundcovers cover cropping deep learning convolutional neural network image‑based phenotyping

Spatial transcriptomics of developing wheat seed reveals radial expression patterns in endosperm and subgenome biased expression of key genes

Authors: Millsteed, T., Kainer, D., Sullivan, R., Sun, X., Li, K. L., Mao, L., Macdonald, A., Henry, R. J.

Date: 2025-06-08 · Version: 1

DOI: 10.1101/2025.06.08.658529

Model Organism: Triticum aestivum

spatial transcriptomics wheat seed development endosperm gene expression subgenome bias STOmics platform

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.

Date: 2025-06-06 · Version: 1

DOI: 10.1101/2025.06.03.657683

Model Organism: Glycine max

spatial transcriptomics single-nuclei RNA-seq plant immunity Phakopsora pachyrhizi cell non‑autonomous defense

Unraveling the cis-regulatory code controlling abscisic acid-dependent gene expression in Arabidopsis using deep learning

Authors: Opdebeeck, H., Smet, D., Thierens, S., Minne, M., De Beukelaer, H., Zuallaert, J., Van Bel, M., Van Montagu, M., Degroeve, S., De Rybel, B., Vandepoele, K.

Date: 2025-06-06 · Version: 1

DOI: 10.1101/2025.06.03.657584

Model Organism: Arabidopsis thaliana

Abscisic acid Arabidopsis thaliana deep learning promoter motifs ABF binding sites

Arabidopsis lines with modified ascorbate concentrations reveal a link between ascorbate and auxin biosynthesis

Authors: Fenech, M., Zulian, V., Moya-Cuevas, J., Arnaud, D., Morilla, I., Smirnoff, N., Botella, M. A., Stepanova, A. N., Alonso, J. M., Martin-Pizarro, C., Amorim-Silva, V.

Date: 2025-05-16 · Version: 1

DOI: 10.1101/2025.05.15.654287

Model Organism: Arabidopsis thaliana

ascorbate Arabidopsis thaliana auxin biosynthesis redox homeostasis transcriptomics

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.

Date: 2025-05-11 · Version: 1

DOI: 10.1101/2025.05.09.653223

Model Organism: Hordeum vulgare

Barley (Hordeum vulgare)inflorescence meristems single-cell RNA sequencing spatial transcriptomics developmental gene regulation

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