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AI-summarized plant biology research papers from bioRxiv

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Evaluating effects of elevated and accelerated NPQ relaxation on yield, physiology and transcription in soybean

Authors: Singh, D., de Souza, A. P., Doran, L., Hansen, J., Burgess, S. J.

Date: 2025-11-20 · Version: 1
DOI: 10.1101/2025.11.19.689310

Category: Plant Biology

Model Organism: Glycine max

AI Summary

The study evaluated a transgenic soybean line (VPZ-34A) expressing Arabidopsis VDE, PsbS, and ZEP for combined improvements in light‑use efficiency and carbon assimilation under ambient and elevated CO2 in a FACE experiment. While VPZ‑34A showed enhanced maximum quantum efficiency of PSII under fluctuating light, it did not increase carbon assimilation efficiency or yield, and transcriptome analysis revealed limited gene expression changes. The results suggest that VPZ‑mediated photosynthetic gains are insufficient to boost productivity under elevated CO2.

photosynthetic efficiency elevated CO2 transgenic soybean VPZ construct transcriptomics

Integrative Multi-Omics Analysis Reveals Stress-Specific Molecular Architectures in Soybean under Drought and Rust Infection

Authors: Husein, G., Castro-Moretti, F. R., Prado, M., Amorim, L., Mazzafera, P., Canales, J., Monteiro-Vitorello, C. B.

Date: 2025-07-08 · Version: 1
DOI: 10.1101/2025.07.07.663534

Category: Plant Biology

Model Organism: Glycine max

AI Summary

The study examined soybean (Glycine max) responses to simultaneous drought and Asian soybean rust infection using combined transcriptomic and metabolomic analyses. Weighted Gene Co-expression Network Analysis identified stress-specific gene modules linked to metabolites, while Copula Graphical Models uncovered sparse, condition‑specific networks, revealing distinct molecular signatures for each stress without overlapping genes or metabolites. The integrative approach underscores a hierarchical, modular defense architecture and suggests targets for breeding multi‑stress resilient soybeans.

Asian soybean rust drought stress transcriptomics metabolomics co-expression network