Keywords: paralog processing, spatial transcriptomics, deep learning, drought stress

Latest 56 Papers

Contrasting needle physiological strategies to soil nutrient scarcity in radiata pine plantations

Authors: Ruiz de Larrinaga, L., San Miguel-Oti, F., Monasterio, A., Artetxe, U., Munne-Bosch, S., Mesa, T., Moreaux, C., Ortega-Barrueta, U., Sertutxa, U., Pena, L., Ametzaga, I., Yuste, J. C., Esteban, R.

Date: 2025-07-19 · Version: 1

DOI: 10.1101/2025.07.15.664982

Model Organism: Pinus radiata

Pinus radiata soil nutrient scarcity drought stress photosynthetic performance forest management

Integrative Multi-Omics Analysis Reveals Stress-Specific Molecular Architectures in Soybean under Drought and Rust Infection

Authors: Husein, G., Castro-Moretti, F. R., Prado, M., Amorim, L., Mazzafera, P., Canales, J., Monteiro-Vitorello, C. B.

Date: 2025-07-08 · Version: 1

DOI: 10.1101/2025.07.07.663534

Model Organism: Glycine max

Asian soybean rust drought stress transcriptomics metabolomics co-expression network

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

Drought stress modulates the molecular response of Arabidopsis plants to root-knot nematode infection

Authors: Refaiy, A., Lilley, C. J., Atkinson, N. J., Urwin, P. E.

Date: 2025-06-09 · Version: 1

DOI: 10.1101/2025.06.05.658137

Model Organism: Arabidopsis thaliana

combined biotic and abiotic stress drought stress root‑knot nematode (Meloidogyne incognita)RNA‑Seq transcriptomics Arabidopsis thaliana

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

Endophytes induce systemic spatial reprogramming of metabolism in poplar roots under drought

Authors: Aufrecht, J. A., Velickovic, D., Tournay, R., Couvillion, S. P., Balasubramanian, V. K., Winkler, T., Herrera, D., Stanley, R., Doty, S., Ahkami, A. H.

Date: 2025-06-06 · Version: 1

DOI: 10.1101/2025.06.02.657501

Model Organism: General

beneficial endophytes drought stress root metabolome chemical imaging machine learning

Prediction of harvest-related traits in barley using high-throughput phenotyping data and machine learning

Authors: Tietze, H., Abdelhakim, L., Pleskacova, B., Kurtz-Sohn, A., Fridman, E., Nikoloski, Z., Panzarova, K.

Date: 2025-06-02 · Version: 1

DOI: 10.1101/2025.05.29.656856

Model Organism: Hordeum vulgare

high‑throughput phenotyping drought stress temporal modeling Barley (Hordeum vulgare)RGB imaging

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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