Keywords: decoding modules, SNP array, ascorbate, wheat, multi‑omics

Latest 24 Papers

Physics-Informed Neural Network Methods for Predicting Plant Height Development

Authors: Shao, Y., van Eeuwijk, F., Peeters, C., Zumsteg, O., Athanasiadis, I., van Voorn, G.

Date: 2026-01-14 · Version: 1

DOI: 10.64898/2026.01.14.699475

Physics-Informed Neural Network logistic ODE Long Short-Term Memory plant height prediction wheat

Evolution of HMA-integrated tandem kinases accompanied by expansion of target pathogens

Authors: Asuke, S., Tagle, A. G., Hyon, G.-S., Koizumi, S., Murakami, T., Horie, A., Niwamoto, D., Katayama, E., Shibata, M., Takahashi, Y., Islam, M. T., Matsuoka, Y., Yamaji, N., Shimizu, M., Terauchi, R., Hisano, H., Sato, K., Tosa, Y.

Date: 2025-12-16 · Version: 1

DOI: 10.64898/2025.12.15.692859

Model Organism: Multi-species

tandem kinase proteins HMA domain disease resistance barley wheat

Universal modules for decoding amplitude and frequency of Ca2+ signals in plants

Authors: Vergara-Valladares, F., Rubio-Melendez, M. E., Charpentier, M., Michard, E., Dreyer, I.

Date: 2025-12-16 · Version: 1

DOI: 10.64898/2025.12.13.694100

Model Organism: General

calcium signaling EF‑hand Ca2+ binding protein decoding modules plant calcium sensors signal amplitude and frequency

Targeting granule initiation and amyloplast structure to create giant starch granules in wheat

Authors: McNelly, R., Esch, L., Ngai, Q. Y., Pohan, K., Stringer, R., Fahy, B., Warren, F., Seung, D.

Date: 2025-12-15 · Version: 1

DOI: 10.64898/2025.12.12.693964

Model Organism: Triticum aestivum

starch granule size PARC6 BGC1 wheat giant starch granules

Glycosylated diterpenes associate with early containment of Fusarium culmorum infection across wheat (Triticum aestivum L.) genotypes under field conditions

Authors: Pieczonka, S. A., Dick, F., Bentele, M., Ramgraber, L., Prey, L., Kupczyk, E., Seidl-Schulz, J., Hanemann, A., Noack, P. O., Asam, S., Schmitt-Kopplin, P., Rychlik, M.

Date: 2025-12-04 · Version: 1

DOI: 10.64898/2025.12.02.691979

Model Organism: Triticum aestivum

wheat Fusarium head blight deoxynivalenol untargeted metabolomics diterpene conjugates

Dual recognition of structurally unrelated mildew effectors underlies the broad-spectrum resistance of Pm3e in wheat

Authors: Kunz, L., Bernasconi, Z., Heuberger, M., Isaksson, J., Sotiropoulos, A. G., Stirnemann, U., Jigisha, J., Menardo, F., Wicker, T., Mueller, M. C., Keller, B.

Date: 2025-10-30 · Version: 2

DOI: 10.1101/2025.10.26.683672

Model Organism: Triticum aestivum (wheat)

broad-spectrum resistance NLR receptors Pm3 alleles powdery mildew effectors wheat

A century of breeding has preserved genetic variation, accumulated favorable alleles, and shaped the Rht gene portfolio in North American spring wheat

Authors: Gill, H. S., Blecha, S., Conley, E., Brault, C., Fiedler, J., Cook, J., Glover, K., Green, A., Read, A. C., Anderson, J. A.

Date: 2025-09-23 · Version: 1

DOI: 10.1101/2025.09.22.677111

Model Organism: Triticum aestivum

Hard red spring wheat genetic diversity Rht dwarfing genes SNP array KASP genotyping

Multi-omics profiling with indoor-unmanned phenotyping reveals drought adaptation through constitutive ABF1 expression in wild rice

Authors: Soma, F., Kawahara, Y., Tanabata, T., Hayashi, A., Kitomi, Y., Kochi, N., Yamamoto, E., Tanaka, N., Negishi, M., Tokuda, K., Sakai, H., Uga, Y.

Date: 2025-09-12 · Version: 1

DOI: 10.1101/2025.09.08.674796

Model Organism: Oryza sativa

drought resistance ABF1 (ABSCISIC ACID RESPONSIVE ELEMENT-BINDING FACTOR 1)rice (Oryza sativa)wild rice relatives multi‑omics

Regenerative agriculture effects on biomass, drought resilience and 14C-photosynthate allocation in wheat drilled into ley compared to disc or ploughed arable soil

Authors: Austen, N., Short, E., Tille, S., Johnson, I., Summers, R., Cameron, D. D., Leake, J. R.

Date: 2025-09-07 · Version: 1

DOI: 10.1101/2025.09.04.674292

Model Organism: Triticum aestivum

regenerative agriculture soil macroaggregation wheat 14C pulse labeling drought resilience

Variations in the root-soil system influence the grapevine holobiont by shaping plant physiology and root microbiome

Authors: Guazzini, M., Marasco, R., Radovic, S., Pellegrini, E., Vuerich, M., Lodovici, A., De Wittenau, G. D., Paparelli, E., Magris, G., Zanin, L., Contin, M., De Luca, E., Daffonchio, D., Di Gaspero, G., Marroni, F.

Date: 2025-08-20 · Version: 1

DOI: 10.1101/2025.08.14.670050

Model Organism: Vitis vinifera

soil microbiome grapevine holobiont multi‑omics bacterial diversity leaf nutrient status

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