Keywords: paralog processing, GWAS, transcriptomics, leaf senescence

Latest 59 Papers

SnRK2.4 and SnRK2.10 redundantly control developmental leaf senescence by sustaining ABA production and signaling

Authors: Anielska-Mazur, A., Rachowka, J., Polkowska-Kowalczyk, L., Krzyszton, M., Cieslak, D., Mazur, R., Bucholc, M., Rakowska, J., Trzmiel, D., Stachula, P., Olechowski, M., Swiezewski, S., Dobrowolska, G., Kulik, A.

Date: 2025-03-27 · Version: 1

DOI: 10.1101/2025.03.25.645185

Model Organism: Arabidopsis thaliana

SnRK2.4 SnRK2.10 leaf senescence ABA signaling MAPK cascade

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

Temporal analysis of physiological phenotypes identifies novel metabolic and genetic underpinnings of senescence in maize

Authors: Brar, M. S., Kumar, R., Kunduru, B., McMahan, C. S., Tharayil, N., Sekhon, R. S.

Date: 2025-03-12 · Version: 1

DOI: 10.1101/2025.03.07.641920

Model Organism: Zea mays

leaf senescence staygreen metabolomics phenylpropanoids maize

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

Host genotype shapes root mycobiota in durum wheat

Authors: TRINQUIER, M., COLOMBO, M., FREVILLE, H., JACQUES, D., ROCHER, A., LEFEBVRE, B., ROUX, C.

Date: 2025-03-06 · Version: 3

DOI: 10.1101/2024.10.27.616629

Model Organism: Triticum aestivum

wheat genotype root endophytic mycobiota ITS2 barcoding GWAS QTL

MYB59 is linked to natural variation of water use associated with warmer temperatures in Arabidopsis thaliana

Authors: Ferguson, J. N., Brendel, O., Bechtold, U.

Date: 2025-02-28 · Version: 1

DOI: 10.1101/2025.02.27.640580

Model Organism: Arabidopsis thaliana

water-use variation Arabidopsis thaliana climate adaptation GWAS MYB59

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

Genetic control of the leaf ionome in pearl millet and correlation with root and agromorphological traits

Authors: Nakombo-Gbassault, P., Arenas, S., Affortit, P., Faye, A., Flis, P., Sine, B., Moukouanga, D., Gantet, P., Kosh Komba, E., Kane, N., Bennett, M., Wells, D., Cubry, P., Bailey, E., Vigouroux, Y., Grondin, A., Laplaze, L.

Date: 2025-02-03 · Version: 1

DOI: 10.1101/2025.01.30.635630

Model Organism: Pennisetum glaucum

ionomics nutrient acquisition pearl millet GWAS candidate genes

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