Keywords: paralog processing, transcriptomics, machine learning, phosphorylation

Latest 56 Papers

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

A moss N-Acetyltransferase-MAPK protein controls 2D to 3D developmental transition via acetylation and phosphorylation changes

Authors: de Luxan Hernandez, C., Ammitsoe, T. J., Kanne, J. V., Stanimirovic, S., Roux, M., Weeks, Z., Schutzbier, M., Dürnberger, G., Roitinger, E., Zhang, L., Spadiut, O., Ishikawa, M., Hasebe, M., Moody, L., Dagdas, Y., Rodriguez, E., Petersen, M.

Date: 2025-05-03 · Version: 1

DOI: 10.1101/2025.05.02.650421

Model Organism: Physcomitrium patens

post-translational modifications acetylation phosphorylation 2D-to-3D transition Physcomitrium patens

Comparative multi-omics profiling of Gossypium hirsutum and Gossypium barbadense fibers at high temporal resolution reveals key differences in polysaccharide composition and associated glycosyltransferases

Authors: Swaminathan, S., Lee, Y., Grover, C. E., DeTemple, M. F., Mugisha, A. S., Sichterman, L. E., Yang, P., Xie, J., Wendel, J. F., Szymanski, D. B., Zabotina, O. A.

Date: 2025-04-30 · Version: 1

DOI: 10.1101/2025.04.26.650795

Model Organism: Multi-species

cotton fiber development polysaccharide composition glycome profiling transcriptomics glycosyltransferases

ERF transcription factor regulons underpin growth-defence trade-off under acute heat stress in rice seedlings

Authors: Nair, A. U., Vishwakarma, S., Guha, T., Kadumuri, R. V., Fritschi, F. B., Chavali, S., Allu, A. D.

Date: 2025-04-22 · Version: 1

DOI: 10.1101/2025.04.21.649784

Model Organism: Oryza sativa

heat stress Oryza sativa seedling transcriptomics ethylene responsive factors phytohormone treatment

A transcriptional dissection of the petty spurge (Euphorbia peplus L.) reproductive structure

Authors: Johnson, A. R., Bao, A., Frank, M. H.

Date: 2025-04-17 · Version: 2

DOI: 10.1101/2024.05.06.592779

Model Organism: Euphorbia peplus

cyathium transcriptomics floral development genes SEP1 paralogs Euphorbia peplus

TIR immune signaling is blocked by phosphorylation to maintain plant growth

Authors: Li, J., Chen, S., Yu, B., Li, Q., Liu, R., Wang, Z., Wan, L., Zhao, Y.

Date: 2025-04-10 · Version: 1

DOI: 10.1101/2025.04.09.647920

Model Organism: Multi-species

TIR domain NADase activity phosphorylation Ca2+-dependent protein kinase growth‑defense trade‑off

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

B4 Raf-like MAPKKK RAF24 regulates Arabidopsis thaliana flowering time through HISTONE MONO-UBIQUITINATION 2

Authors: Li, Q., Wang, L., Grubb, L. E., Talasila, M., Rodriguez Gallo, M. C., Mehta, D., Scandola, S., Uhrig, R. G.

Date: 2025-04-01 · Version: 2

DOI: 10.1101/2024.06.12.598286

Model Organism: Arabidopsis thaliana

flowering time RAF24 MAPKKK phosphorylation HUB2

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