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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

Heat Stress and Soil Microbial Disturbance Influence Soybean Root Metabolite, Microbiome Profiles, and Nodulation

Authors: Elango, D., Van der Laan, L., Gholizadeh, S., Premarathne, M. D. G. P., Dutter, C. R., DePew, C., McDaniel, M., Singh, A. K.

Date: 2025-07-14 · Version: 1
DOI: 10.1101/2025.07.13.664636

Category: Plant Biology

Model Organism: Glycine max

AI Summary

The study investigated how native soil microbes affect heat tolerance in soybean (Glycine max) by comparing plants grown in natural versus microbiome‑disturbed soils under optimal and elevated temperatures. Using 16S rRNA and ITS sequencing alongside non‑targeted root metabolomics, the authors found significant shifts in bacterial and fungal communities, suppressed nodule‑forming bacteria, and altered root metabolites that correlated with reduced nodulation efficiency under heat stress. Integrated multi‑omics analyses linked microbial composition to metabolite profiles and nitrogen‑fixation traits, highlighting a coordinated response of the root physiological system to combined heat and microbiome perturbations.

heat stress rhizosphere microbiome soybean root metabolomics nitrogen fixation

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

Transcriptomic and physiological responses of soybean plants subjected to a combination of water deficit and heat stress under field conditions

Authors: Sinha, R., Pelaez-Vico, M. A., Dhakal, S., Ghani, A., Myers, R., Verma, M., Shostak, B., Ogden, A., Krueger, C. B., Costa Netto, J. R., Zandalinas, S. I., Joshi, T., Fritschi, F. B., Mittler, R.

Date: 2025-05-11 · Version: 1
DOI: 10.1101/2025.05.07.652738

Category: Plant Biology

Model Organism: Glycine max

AI Summary

A two‑year field study examined how soybean (Glycine max) vegetative and reproductive tissues respond transcriptionally and physiologically to water deficit, heat, and their combination. The field‑grown plants showed distinct transcriptomic patterns compared with controlled‑environment studies, especially under single stresses, while differential leaf‑pod transpiration observed in growth chambers was also present in the field. The generated transcriptomic dataset highlights the importance of field‑based omics for understanding crop stress responses.

water deficit heat stress combined stress field transcriptomics soybean