Keywords: paralog processing, ascorbate, transcriptomics, machine learning, bread wheat, VPZ construct

Latest 47 Papers

Welcome pathogens: transient heat dampens the responses to acibenzolar-S-methyl beyond defenses in apple plants

Authors: Chavonet, E., Nguyen, B.-h., Heintz, C., Cournol, R., Siroka, J., Novak, O., Larbat, R., Gaucher, M., Brisset, M.-N., Pantin, F., Degrave, A.

Date: 2025-04-06 · Version: 1

DOI: 10.1101/2025.04.03.647103

Model Organism: Malus domestica

heat stress acibenzolar‑S‑methyl (ASM)induced immunity apple (Malus domestica)transcriptomics

High Density Phenotypic Map of Natural Variation for Intermediate Phenotypes Associated with Stalk Lodging Resistance in Maize

Authors: Kunduru, B., Bokros, N. T., Tabaracci, K., Kumar, R., Brar, M. S., Stubbs, C. J., Oduntan, Y., DeKold, J., Bishop, R. H., Woomer, J., Verges, V. L., McDonald, A., McMahan, C. S., DeBolt, S., Robertson, D. J., Sekhon, R.

Date: 2025-04-06 · Version: 1

DOI: 10.1101/2025.04.03.647088

Model Organism: Zea mays

stalk lodging resistance maize phenomics genetic architecture intermediate phenotypes machine learning

Omics-driven Identification of Candidate Genes and SNP markers in a Major QTL Controlling Early Heading in Rice

Authors: Rao, D., T, N. S., CG, G., Gaur, N., Jamaloddin, M., Maganti, S. M., Raman, M. S., Patel, H. K., Tiwari, S., Sonti, R. V.

Date: 2025-03-27 · Version: 1

DOI: 10.1101/2025.03.25.645207

Model Organism: Oryza sativa

heading date rice (Oryza sativa)QTL-seq SNP markers transcriptomics

Multilevel analysis of response to plant growth promoting and pathogenic bacteria in Arabidopsis roots and the role of CYP71A27 in this response

Authors: Koprivova, A., Ristova, D., Berka, M., Berkova, V., Türksoy, G. M., Andersen, T. G., Westhoff, P., Cerny, M., Kopriva, S.

Date: 2025-03-27 · Version: 1

DOI: 10.1101/2025.03.26.645393

Model Organism: Arabidopsis thaliana

CYP71A27 plant‑microbe interaction Pseudomonas fluorescens CH267 Burkholderia glumeae PG1 transcriptomics

The genome of the vining fern Lygodium microphyllum highlights genomic and functional differences between life phases of an invasive plant

Authors: Pelosi, J., Davenport, R., Kuo, L.-Y., Gray, L. N., Dant, A. J., Kim, E. H., Li, F.-W., Dlugosch, K. M., Krabbenhoft, T. J., Barbazuk, W. B., Sessa, E. B.

Date: 2025-03-07 · Version: 1

DOI: 10.1101/2025.03.06.640867

Model Organism: Lygodium microphyllum

Lygodium microphyllum alternation of generations transcriptomics methylome invasive species

Sunflower yield modeling with XAI: Historical weather impacts and forecasting

Authors: Majumder, S., Mason, C.

Date: 2025-02-28 · Version: 1

DOI: 10.1101/2025.02.27.640573

Model Organism: Helianthus annuus

explainable AI sunflower yield climate variability machine learning Shared Socioeconomic Pathways

Transcriptomic insights into the role of miR394 in the regulation of flowering time in Arabidopsis thaliana

Authors: Belen, F., Bernardi, Y., Reutemann, A., Vegetti, A., Dotto, M. C.

Date: 2025-02-20 · Version: 1

DOI: 10.1101/2025.02.15.638417

Model Organism: Arabidopsis thaliana

miR394 flowering time Arabidopsis thaliana transcriptomics lncRNA

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