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AI-summarized plant biology research papers from bioRxiv

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Integrative genomic and transcriptomic analyses uncover regulatory landscape of symbiotic nitrogen fixation in soybean natural population

Authors: Li, Y., Feng, w., Feng, X., Liu, X., Hao, S., Lian, L., Gao, L., Shao, Y., Chen, H., Chen, Z., Yuan, J., Qin, L., Li, X., Li, X., Wang, X.

Date: 2025-07-23 · Version: 1
DOI: 10.1101/2025.07.18.665310

Category: Plant Biology

Model Organism: Glycine max

AI Summary

The study integrates genome, transcriptome, and chromatin accessibility data from 380 soybean accessions to dissect the genetic and regulatory basis of symbiotic nitrogen fixation (SNF). Using GWAS, TWAS, eQTL mapping, and ATAC-seq, the authors identify key loci, co‑expression modules, and regulatory elements, and validate the circadian clock gene GmLHY1b as a negative regulator of nodulation via CRISPR and CUT&Tag. These resources illuminate SNF networks and provide a foundation for soybean improvement.

symbiotic nitrogen fixation GWAS TWAS eQTL mapping ATAC-seq

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

NCR13 peptide protects soybean against Cercospora sojina by multiple modes of action and additive interaction with chemical fungicides

Authors: Pokhrel, A., Nath, V. S., Godwin, J., Kalunke, R., TETORYA, M., Czymmek, K. J., Shah, D. M.

Date: 2025-04-30 · Version: 1
DOI: 10.1101/2025.04.29.651315

Category: Plant Biology

Model Organism: Glycine max

AI Summary

The chickpea-derived cysteine‑rich peptide NCR13_PFV1 exhibited nanomolar antifungal activity against both QoI‑sensitive and -resistant isolates of the soybean pathogen Cercospora sojina, protecting sprayed soybean leaves without phytotoxicity and showing additive effects with azoxystrobin. The peptide disrupts fungal plasma membranes, induces ROS, is rapidly internalized, binds fungal rRNA, and inhibits protein translation, with iron availability modulating its activity. These multifaceted mechanisms suggest NCR13_PFV1 as a promising bio‑fungicide for durable FLS management.

NCR13_PFV1 peptide Cercospora sojina soybean leaf spot QoI resistance reactive oxygen species

Iron retention coupled with trade-offs in localized symbiotic effects confers tolerance to combined iron deficiency and drought in soybean

Authors: Hasan, M. R., Thapa, A., Kabir, A. H.

Date: 2025-03-24 · Version: 2
DOI: 10.1101/2025.01.02.631154

Category: Plant Biology

Model Organism: Glycine max

AI Summary

The study compares iron deficiency and drought tolerance between two soybean genotypes, Clark (tolerant) and Arisoy (sensitive), using multi‑omics analyses. Clark maintains iron homeostasis, higher antioxidant protein expression, and recruits beneficial root microbes (Variovorax, Paecilomyces) that support nutrient uptake and nodule function, while Arisoy shows impaired physiological and microbial responses. The findings identify host‑microbe interactions and specific molecular pathways as potential targets for breeding and microbiome‑based biofertilizers.

soybean (Glycine max) iron deficiency drought stress root microbiome multi‑omics