Keywords: decoding modules, machine learning, transcriptome analysis, transcriptomics, SWI3, bread wheat, Zea mays

Latest 79 Papers

Genetic determinants of aerial root traits that support biological nitrogen fixation in maize

Authors: Laspisa, D., Venado, R. E., Diogo, R., Ane, J.-M., Wallace, J. G.

Date: 2025-06-02 · Version: 1

DOI: 10.1101/2025.05.30.657053

Model Organism: Zea mays

biological nitrogen fixation aerial roots Zea mays QTL mapping heritability

Thermotolerance in Chia (Salvia hispanica L.) is Mediated by Rapid Heat-Induced Transcriptomic Reprogramming and Lipid Remodelling in Leaves

Authors: Zare, T., Kehelpannala, C., Bhatnagar, A., Rupasinghe, T., Ebert, B., Fournier-Level, A., Roessner, U.

Date: 2025-06-02 · Version: 1

DOI: 10.1101/2025.05.30.656991

Model Organism: Salvia hispanica

heat stress Salvia hispanica transcriptomics lipidomics calcium signaling

Dynamic changes to the plastoglobule lipidome and proteome in water-deficient maize

Authors: Devadasu, E., Schilmiller, A. L., Gonzalez, N., Lundquist, P. K.

Date: 2025-05-30 · Version: 1

DOI: 10.1101/2025.05.26.656201

Model Organism: Zea mays

drought resilience plastoglobules lipidomics quantitative proteomics Zea mays

Characterization of the maize (Zea mays)-Ustilago maydis interaction in a warming climate

Authors: Schwarz, C. G., Hartmann, F., Zier, C., van der Linde, K.

Date: 2025-05-29 · Version: 1

DOI: 10.1101/2025.05.26.656155

Model Organism: Zea mays

Zea mays Ustilago maydis temperature stress RNA-seq GSL4

Physiological characterization in a somaclonal mutant for fruit shape derived from persimmon 'Hiratanenashi'

Authors: Horiuchi, A., Matsuzaki, R., Onoue, N., Ushijima, K., Kubo, Y., Akagi, T., Minamikawa, M. F.

Date: 2025-05-19 · Version: 1

DOI: 10.1101/2025.05.19.654774

Model Organism: Diospyros kaki

fruit shape persimmon (Diospyros kaki)elliptic Fourier descriptor transcriptome analysis WOX13

Diploid gametes in maize by mutation of A-Type cyclins: a step towards apomeiosis and synthetic apomixis.

Authors: Skinner, D. J., Gaikwad, A. H., Fenner, J. A., Green, J., Cho, M.-J., Kelliher, T., Sundaresan, V.

Date: 2025-05-19 · Version: 1

DOI: 10.1101/2025.05.16.654085

Model Organism: Zea mays

synthetic apomixis diploid gametes Zea mays A-type cyclin tetraploid progeny

Arabidopsis lines with modified ascorbate concentrations reveal a link between ascorbate and auxin biosynthesis

Authors: Fenech, M., Zulian, V., Moya-Cuevas, J., Arnaud, D., Morilla, I., Smirnoff, N., Botella, M. A., Stepanova, A. N., Alonso, J. M., Martin-Pizarro, C., Amorim-Silva, V.

Date: 2025-05-16 · Version: 1

DOI: 10.1101/2025.05.15.654287

Model Organism: Arabidopsis thaliana

ascorbate Arabidopsis thaliana auxin biosynthesis redox homeostasis transcriptomics

Multiplexed profiling of transcriptional regulators in plant cells

Authors: Alamos, S., Waldburger, L., Dee, A., Owens, L., Rattan, R., Ong, S., Shih, P.

Date: 2025-05-14 · Version: 1

DOI: 10.1101/2025.05.12.653590

Model Organism: General

transcriptional regulation high-throughput plant assay protein‑coding library machine learning synthetic protein engineering

Phylogenetic Analysis and Machine Learning Identify Signatures of Selection and Predict Deleterious Mutations in Common Bean

Authors: Cordoba-Novoa, H. A., Buckler, E. S., Romay, C., Berthel, A., Johnson, L., Balasubramanian, P., Hoyos Villegas, V.

Date: 2025-05-06 · Version: 1

DOI: 10.1101/2025.05.05.652309

Model Organism: Phaseolus vulgaris

deleterious mutations genetic load common bean MAGIC population machine learning

S2-PepAnalyst: A Web Tool for Predicting Plant Small Signalling Peptides

Authors: Vomo Donfack, K. L., Abaach, M., Luna, A. M., Ginot, G., Doblas, V. G., Morilla, I.

Date: 2025-05-06 · Version: 2

DOI: 10.1101/2024.08.02.606319

Model Organism: General

small signalling peptides machine learning protein language models geometric-topological analysis reinforcement learning

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