Keywords: paralog processing, deep learning, comparative transcriptomics, drought tolerance

Latest 41 Papers

Comparative transcriptomics uncovers plant and fungal genetic determinants of mycorrhizal compatibility

Authors: Marques-Galvez, J. E., de Freitas Pereira, M., Nehls, U., Ruytinx, J., Barry, K., Peter, M., Martin, F., Grigoriev, I. V., Veneault-Fourrey, C., Kohler, A.

Date: 2025-04-14 · Version: 1

DOI: 10.1101/2025.04.11.648352

Model Organism: Populus

ectomycorrhizal symbiosis poplar comparative transcriptomics gene regulons compatibility

High radiosensitivity in the conifer Norway spruce (Picea abies) due to lesscomprehensive mobilisation of protection and repair responses compared to the radiotolerant Arabidopsis thaliana

Authors: Bhattacharjee, P., Blagojevic, D., Lee, Y., Gillard, G. B., Gronvold, L., Hvidsten, T. R., Sandve, S. R., Lind, O. C., Salbu, B., Brede, D. A., Olsen, J. E.

Date: 2025-04-14 · Version: 3

DOI: 10.1101/2023.11.20.562501

Model Organism: Multi-species

ionising radiation radiosensitivity comparative transcriptomics DNA damage repair antioxidant response

Loss-of-function of the drought-induced genes GASA3 and AFP1 confers enhanced drought tolerance in Arabidopsis thaliana

Authors: Bhattacharyya, S., Turysbek, B., Lorenz, S. D., Rosales, D. C., Shoaib, Y., Gutbrod, K., Doermann, P., Chigri, F., Vothknecht, U. C.

Date: 2025-04-06 · Version: 1

DOI: 10.1101/2025.04.03.647048

Model Organism: Arabidopsis thaliana

drought tolerance GASA3 AFP1 abscisic acid (ABA)stomatal aperture

Developing the Grapevine Hydric Stress Atlas: A Meta-Analysis Resource for Exploring transcriptome Responses to Drought

Authors: VALENZUELA, A. V., Navarro-Paya, D., Santiago, A., Sonego, P., Gainza-Cortes, F., Malnoy, M., Matus, J. T.

Date: 2025-04-01 · Version: 1

DOI: 10.1101/2025.03.31.646369

Model Organism: Vitis vinifera

drought tolerance grapevine (Vitis vinifera)transcriptomic meta-analysis gene co‑expression network molecular breeding

Transcriptional plasticity of fast core chromosomes governs establishment of a fungal pathogen on evolutionarily distant plant lineages

Authors: Srivastava, V., Kaushik L S, S., Pullagurla, N. J., Zechmann, B., Di Pietro, A., Laha, D., Redkar, A.

Date: 2025-03-28 · Version: 1

DOI: 10.1101/2025.03.27.645276

Model Organism: Marchantia polymorpha

Fusarium oxysporum Marchantia polymorpha effector genes fast core chromosomes comparative transcriptomics

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.

Date: 2025-03-19 · Version: 1

DOI: 10.1101/2025.03.18.642594

Model Organism: Triticum aestivum

wheat semantic segmentation computer vision deep learning phenotyping

Priming of retrograde signaling in wheat across multiple natural environments reveal how responses to dynamic stimuli can be integrated to alter yield, yield stability and water productivity

Authors: Bowerman, A. F., Moore, M., Yadav, A., Zhang, J., Mortimer, M. D., Plskova, Z., Tee, E. E., Au, E. K., Collinge, D. P., Estavillo, G. M., Howitt, C. A., Chan, K. X., Rebetzke, G. J., Pogson, B. J.

Date: 2025-03-13 · Version: 1

DOI: 10.1101/2025.03.10.642515

Model Organism: Triticum aestivum

retrograde signaling SAL gene deletions wheat (Triticum aestivum)drought tolerance field trial validation

Fiber Bragg grating based sensing system for non-destructive root phenotyping using ResNet prediction

Authors: Binder, S., Hossain, K., Bucksch, A., Fok, M.

Date: 2025-02-28 · Version: 2

DOI: 10.1101/2024.09.17.613457

Model Organism: Zea mays

root architecture fiber Bragg grating real-time phenotyping deep learning Zea mays

Genome sequence and RNA-seq analysis reveal genetic basis of flower coloration in the giant water lily Victoria cruziana

Authors: Nowak, M. S., Harder, B., Meckoni, S. N., Friedhoff, R., Wolff, K., Pucker, B.

Date: 2025-02-28 · Version: 2

DOI: 10.1101/2024.06.15.599162

Model Organism: Victoria cruziana

Victoria cruziana flower color change anthocyanin biosynthesis comparative transcriptomics genome assembly

Herbaria provide a valuable resource for obtaining informative mRNA

Authors: Tyszka, A. S., Chia, K.-S., Bretz, E. C., Mansour, L., Larson, D. A., Carella, P., Walker, J. F.

Date: 2025-02-17 · Version: 1

DOI: 10.1101/2025.02.12.637878

Model Organism: General

archival RNA herbarium transcriptomics transcriptome assembly plant immune receptor comparative transcriptomics

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