Keywords: decoding modules, transcriptome analysis, deep learning, QTL mapping

Latest 31 Papers

Parallel adaptation and admixture drive the evolution of virulence in the grapevine downy mildew pathogen

Authors: DVORAK, E., DUMARTINET, T., MAZET, I. D., CHATAIGNER, A., Paineau, M., CANTU, D., MESTRE, P., FOULONGNE-ORIOL, M., DELMOTTE, F.

Date: 2025-05-23 · Version: 1

DOI: 10.1101/2025.05.18.654733

Model Organism: Plasmopara viticola

Plasmopara viticola grapevine downy mildew QTL mapping AvrRpv12 RXLR effectors

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

Deciphering the Sequence Basis and Application of Transcriptional Initiation Regulation in Plant Genomes Through Deep Learning

Authors: Gao, P., Lian, L., Feng, W., Ma, Y., Lin, J., Qin, L., Hao, S., Zhao, H., Liu, X., Yuan, J., Lin, Z., Li, X., Guan, Y., Wang, X.

Date: 2025-04-24 · Version: 1

DOI: 10.1101/2025.04.22.649999

Model Organism: Glycine max

transcription start site promoter motifs deep learning soybean domestication plant gene regulation

Arabidopsis CNL receptor SUT1 confers immunity in hydathodes against the vascular pathogen Xanthomonas campestris pv. campestris

Authors: Taks, N. W., van Hulten, M., van Splunter-Berg, J. A., Chatterjee, S., Stevens, F. D., Paauw, M., Pfeilmeier, S., van den Burg, H. A.

Date: 2025-04-11 · Version: 2

DOI: 10.1101/2024.06.20.599835

Model Organism: Arabidopsis thaliana

hydathode Xanthomonas campestris pv. campestris Arabidopsis thaliana SUT1 QTL mapping

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

MYB93 regulates responses to environmental sulphur in Arabidopsis and tomato.

Authors: Cao, X., Wilkinson, H. B., Hutton, B., McMulkin, N., Graham, N. S., Etherington, R., Oliver, A. G., Clayton, C. M., Kaur, H., Coates, J. C.

Date: 2025-03-07 · Version: 1

DOI: 10.1101/2025.03.04.641362

Model Organism: Arabidopsis thaliana

sulfur nutrition AtMYB93 root development transcriptome analysis elemental analysis

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

Future flooding tolerant rice germplasm: resilience afforded beyond Sub1A gene

Authors: Anumalla, M., Khanna, A., Catolos, M., Ramos, J., Sta. Cruz, M. T., Venkateshwarlu, C., Konijerla, J., Pradhan, S. K., Dash, S. K., Das, Y., Chowdhury, D., Chetia, S. K., Das, J., Nath, P., Merugumala, G. R., Roy, B., Pradhan, N., Jana, M., Dana, I., Debnath, S., Nath, A., Prasad Singh, S., Iftekharuddaula, K. M., Ghosal, S., Ali, M., Khanam, S., Ul Islam, M. M., Faruquee, M., Tonny, H. J., Hasan, M. R., Rahman, A., Ali, J., Sinha, P., Singh, V., Rafiqul Islam, M., Bhosale, S., Kohli, A., Bhardwaj, H. R., Hussain, W.

Date: 2025-02-25 · Version: 1

DOI: 10.1101/2025.02.24.639789

Model Organism: Oryza sativa

flood tolerance rice (Oryza sativa)QTL mapping genomic selection Transition from Trait to Environment (TTE) breeding

Transcriptome differentiation in Cryptomeria japonica trees with different origins growing in the north and south of Japan

Authors: Ujino-Ihara, T., Uchiyama, K., Kanetani, S., Suyama, Y., Tsumura, Y.

Date: 2025-02-25 · Version: 1

DOI: 10.1101/2025.02.22.639673

Model Organism: Cryptomeria japonica

local adaptation transcriptome analysis weighted gene co‑expression network analysis (WGCNA)SNP differentiation defense response genes

Identification of QTLs linked to partial resistance to foot and root rot caused by Fusarium avenaceum and Fusarium oxysporum in faba bean (Vicia faba)

Authors: Webb, A., Thomas, J. E., Davis, H., McAdam, S., Angra, D., O'Sullivan, D. M., Gostkiewicz, K., Capozzi, M., Wood, T. A.

Date: 2025-02-25 · Version: 1

DOI: 10.1101/2025.02.21.639454

Model Organism: Vicia faba

Vicia faba Fusarium foot and root rot QTL mapping SNP array disease resistance

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