Keywords: paralog processing, transcriptome reprogramming, Zea mays, drought tolerance

Latest 48 Papers

Volatiles from low R:FR-treated maize plants increase the emission of herbivore-induced plant volatiles in their neighbors

Authors: Escobar Bravo, R., Schimmel, B. C. J., Erb, M.

Date: 2025-04-02 · Version: 2

DOI: 10.1101/2024.10.05.616768

Model Organism: Zea mays

low R:FR light Zea mays herbivore‑induced plant volatiles volatile priming plant‑plant communication

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

High-resolution transcriptional atlas of growing maize shoot organs throughout plant development under well-watered and drought conditions

Authors: Zhang, J., Verbraeken, L., Sprenger, H., Mertens, S., Wuyts, N., Cannoot, B., De Block, J., Demuynck, K., Natran, A., Maleux, K., Merchie, J., Crafts-Brandner, S., Vogel, J., Bruce, W., Inze, D., Maere, S., Nelissen, H.

Date: 2025-03-13 · Version: 1

DOI: 10.1101/2025.03.12.642568

Model Organism: Zea mays

Zea mays leaf and internode development drought stress spatiotemporal transcriptome atlas gene regulatory networks

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

Interactive effect of Moringa oleifera mediated green nanoparticles and arbuscular mycorrhizal fungi on growth, root system architecture, and nutrient uptake in maize (Zea mays L.)

Authors: Ain, Q. u., Hussain, H. A., Rahman, L., Zhang, Q., Rehman, A., Hussain, S., Uddin, S., Imran, A.

Date: 2025-02-25 · Version: 1

DOI: 10.1101/2025.02.23.639791

Model Organism: Zea mays

arbuscular mycorrhizal fungi green nanoparticles Zea mays iron oxide (FeO)zinc oxide (ZnO)

Robustness of high-throughput prediction of leaf ecophysiological traits using near infra-red spectroscopy and poro-fluorometry

Authors: Coindre, E., Boulord, R., Chir, L., Freitas, V., Ryckewaert, M., Laisne, T., Bouckenooghe, V., Lis, M., Cabrera-Bosquet, L., Doligez, A., Simonneau, T., Pallas, B., Coupel-Ledru, A., Segura, V.

Date: 2025-02-07 · Version: 1

DOI: 10.1101/2025.02.07.636194

Model Organism: Vitis vinifera

drought tolerance high-throughput phenotyping spectroscopy poro-fluorometry leaf mass per area

A maize near-isogenic line population designed for gene discovery and characterization of allelic effects

Authors: Zhong, T., Mullens, A., Morales, L., Swarts, K., Stafstrom, W., He, Y., Sermons, S., Yang, Q., Lopez-Zuniga, L. O., Rucker, E., Thomason, W., Nelson, R., Jamann, T. M., Balint-Kurti, P., Holland, J. B.

Date: 2025-02-02 · Version: 1

DOI: 10.1101/2025.01.29.635337

Model Organism: Zea mays

Zea mays near‑isogenic lines genotyping‑by‑sequencing hidden Markov model QTL mapping

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