Keywords: paralog processing, transcriptomics, deep learning, Fusarium Head Blight

Latest 48 Papers

An experimental approach to study multi-species interactions implicated in Fusarium-Head Blight complex assembly in wheat.

Authors: Corrales Gutierrez, M. A., Kaur, H., Desiderio, F., Douchkov, D., Zhan, J., Velez, H., Bourras, S.

Date: 2025-04-14 · Version: 3

DOI: 10.1101/2024.04.14.589412

Fusarium Head Blight systemic immune signaling Zymoseptoria tritici species composition resistance breeding

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

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 Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset

Authors: Wang, Z., Zenkl, R., Greche, L., De Solan, B., Bernigaud Samatan, L., Ouahid, S., Visioni, A., Robles-Zazueta, C. A., Pinto, F., Perez-Olivera, I., Reynolds, M. P., Zhu, C., Liu, S., D'argaignon, M.-P., Lopez-Lozano, R., Weiss, M., Marzougui, A., Roth, L., Dandrifosse, S., Carlier, A., Dumont, B., Mercatoris, B., Fernandez, J., Chapman, S., Najafian, K., Stavness, I., Wang, H., Guo, W., Virlet, N., Hawkesford, M., Chen, Z., David, E., Gillet, J., Irfan, K., Comar, A., Hund, A.

Date: 2025-03-19 · Version: 1

DOI: 10.1101/2025.03.18.642594

Model Organism: Triticum aestivum

wheat semantic segmentation computer vision deep learning phenotyping

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

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

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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