Keywords: decoding modules, transcriptome, deep learning, ascorbate, metabolomics

Latest 35 Papers

Unravelling the intraspecific variation in drought responses in seedlings of European black pine (Pinus nigra J.F. Arnold)

Authors: Ahmad, M., Hammerbacher, A., Priemer, C., Ciceu, A., Karolak, M., Mader, S., Olsson, S., Schinnerl, J., Seitner, S., Schoendorfer, S., Helfenbein, P., Jakub, J., Breuer, M., Espinosa, A., Caballero, T., Ganthaler, A., Mayr, S., Grosskinsky, D. K., Wienkoop, S., Schueler, S., Trujillo-Moya, C., van Loo, M.

Date: 2025-10-21 · Version: 1

DOI: 10.1101/2025.10.20.683360

Model Organism: Pinus nigra

drought tolerance Pinus nigra metabolomics transcriptomics phenotyping

Additive and partially dominant effects from genomic variation contribute to rice heterosis

Authors: Dan, Z., Chen, Y., Zhou, W., Xu, Y., Huang, J., Chen, Y., Meng, J., Yao, G., Huang, W.

Date: 2025-10-17 · Version: 4

DOI: 10.1101/2024.07.16.603817

Model Organism: Oryza sativa

heterosis Oryza sativa additive and partially dominant effects metabolomics phenylpropanoid biosynthesis

In-depth phenotyping reveals unexpected floral trait variation in Mimulus cardinalis across a range-wide latitudinal gradient

Authors: Neequaye, M., Kennedy, E. B., Gunn, H., Wenzell, K. E., Byers, K. J. R. P.

Date: 2025-10-05 · Version: 1

DOI: 10.1101/2025.10.03.680188

Model Organism: Mimulus cardinalis

Mimulus cardinalis floral trait variation pollinator-mediated selection metabolomics genomic analysis

Candidatus Phytoplasma-induced Retrogressive Morphogenesis in Sesame (Sesamum indicum L.): Tissue-Specific Metabolic and Transcriptomic Reprogramming

Authors: Banerjee, S., Gangopadhyay, G.

Date: 2025-10-01 · Version: 1

DOI: 10.1101/2025.09.29.679221

Model Organism: Sesamum indicum

phytoplasma infection Sesamum indicum metabolomics transcriptomics tissue-specific response

A Multi-lensed Comparative Analysis of Select Secondary Metabolites Produced by Kale, Brassica oleracea, in Simulated Microgravity Versus Gravity Conditions

Authors: Osano, A., Dill, R., Li, Y., Yan, J., Ray, S., Ude, G., Iro, A.

Date: 2025-10-01 · Version: 1

DOI: 10.1101/2025.09.29.679299

Model Organism: Kale (Brassica oleracea var. acephala)

microgravity flavonoids metabolomics 1H NMR HPTLC

Botanic Spectrum Analyser: A Deep Learning GUI for Plant Image Segmentation in Hyperspectral and RGB Phenotyping

Authors: Walsh, J. J., Gorgu, L., Cavel, E., Poulain, V., Gutierrez, L., Mangina, E., Negrao, S.

Date: 2025-09-17 · Version: 1

DOI: 10.1101/2025.09.14.676080

Model Organism: Multi-species

plant phenotyping image segmentation U‑Net hyperspectral imaging deep learning

Adaptive Strategies of the invasive aquatic plant, Ludwigia grandiflora subps. hexapetala: Contrasting Plasticity Between Aquatic and Terrestrial Morphotypes.

Authors: Genitoni, J., Vassaux, D., RENAULT, D., Maury, S., BARLOY, D. H.

Date: 2025-09-01 · Version: 1

DOI: 10.1101/2025.08.27.672630

Model Organism: Ludwigia grandiflora subsp. hexapetala

phenotypic plasticity Ludwigia grandiflora invasive species metabolomics phytohormones

Stress-dependent responses of grapevine wood and fungal pathogen activity under esca and drought

Authors: Chambard, M., Cantu, D., Bortolami, G., Dell'Acqua, N., Ferrer, N., Gambetta, G., Garcia, J., Gastou, P., Massonnet, M., Moretti, S., Rochepeau, A., Petriacq, P., Foulongne-Oriol, M., Delmas, C. E. L.

Date: 2025-08-07 · Version: 1

DOI: 10.1101/2025.08.05.668645

Model Organism: Vitis vinifera

drought stress esca disease grapevine (Vitis vinifera)wood metatranscriptomics metabolomics

Drought and methyl jasmonate memory interact to determine plant functioning under current drought stress in a perennial grass

Authors: Bhatt, T., Rathore, N., Semerad, J., Cajthaml, T., Thakur, D., Munzbergova, Z.

Date: 2025-08-03 · Version: 1

DOI: 10.1101/2025.08.03.668340

Model Organism: Festuca rubra

drought memory methyl jasmonate Festuca rubra transgenerational priming metabolomics

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

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