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AI-summarized plant biology research papers from bioRxiv

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Multi-Level Characterization Reveals Divergent Heat Response Strategies Across Wheat Genotypes of Different Ploidy

Authors: Arenas-M, A., Mino, I., Uauy, C., Calderini, D. F., Canales, J.

Date: 2026-01-23 · Version: 1
DOI: 10.64898/2026.01.22.701169

Category: Plant Biology

Model Organism: Multi-species

AI Summary

Field experiments combined with RNA sequencing revealed that wheat ploidy influences heat stress resilience, with tetraploid T. turgidum showing the smallest yield loss and hexaploid T. aestivum mounting the largest transcriptional response. Ploidy-dependent differences were observed in differential gene expression, alternative splicing—including hexaploid-specific exon skipping of NF‑YB—and co‑expression networks linked to grain traits, highlighting candidate pathways for breeding heat‑tolerant wheat.

heat stress wheat ploidy RNA sequencing differential gene expression alternative splicing

A drought stress-induced MYB transcription factor regulates pavement cell shape in leaves of European aspen (Populus tremula)

Authors: Liu, S., Doyle, S. M., Robinson, K. M., Rahneshan, Z., Street, N. R., Robert, S.

Date: 2026-01-16 · Version: 1
DOI: 10.64898/2026.01.16.699252

Category: Plant Biology

Model Organism: Populus tremula

AI Summary

The study examined leaf pavement cell shape complexity across a natural European aspen (Populus tremula) population, using GWAS to pinpoint the transcription factor MYB305a as a regulator of cell geometry. Functional validation showed that MYB305a expression is induced by drought and contributes to shape simplification, with cell complexity negatively correlated with water-use efficiency and climatic variables of the genotypes' origin.

leaf pavement cells Populus tremula MYB305a GWAS drought stress

Physics-Informed Neural Network Methods for Predicting Plant Height Development

Authors: Shao, Y., van Eeuwijk, F., Peeters, C., Zumsteg, O., Athanasiadis, I., van Voorn, G.

Date: 2026-01-14 · Version: 1
DOI: 10.64898/2026.01.14.699475

Category: Plant Biology

Model Organism: Triticum aestivum

AI Summary

The study introduces a hybrid modeling framework that integrates a logistic ordinary differential equation with a Long Short-Term Memory neural network to form a Physics-Informed Neural Network (PINN) for predicting wheat plant height. Using only time and temperature as inputs, the PINN outperformed other longitudinal growth models, achieving the lowest average RMSE and reduced variability across multiple random initializations. The results suggest that embedding biological growth constraints within data‑driven models can substantially improve prediction accuracy for plant traits.

Physics-Informed Neural Network logistic ODE Long Short-Term Memory plant height prediction wheat

Wheat diversity reveals new genomic loci and candidate genes for vegetation indices using genome-wide association analysis

Authors: Rustamova, S., Jahangirov, A., Leon, J., Naz, A. A., Huseynova, I.

Date: 2026-01-14 · Version: 1
DOI: 10.64898/2026.01.14.699455

Category: Plant Biology

Model Organism: Triticum aestivum

AI Summary

A genome‑wide association study of 187 bread wheat genotypes identified 812 significant loci linked to 25 spectral vegetation indices under rainfed drought conditions, revealing a major QTL hotspot on chromosome 2A that accounts for up to 20% of variance in greenness and pigment traits. Candidate gene analysis at this hotspot uncovered stress‑responsive genes, demonstrating that vegetation indices are heritable digital phenotypes useful for selection and genetic analysis of drought resilience.

Triticum aestivum drought stress spectral vegetation indices GWAS QTL hotspot

Root phenolics as potential drivers of preformed defenses and reduced disease susceptibility in a paradigm bread wheat mixture

Authors: Mathieu, L., Chloup, A., Marty, S., Savajols, J., Paysant-Le Roux, C., Launay-Avon, A., Martin, M.-L., Totozafy, J.-C., Perreau, F., Rochepeau, A., Rouveyrol, C., Petriacq, P., Morel, J.-B., Meteignier, L.-V., Ballini, E.

Date: 2026-01-14 · Version: 1
DOI: 10.64898/2026.01.13.699261

Category: Plant Biology

Model Organism: Triticum aestivum

AI Summary

The study created a system that blocks root‑mediated signaling between wheat varieties in a varietal mixture and used transcriptomic and metabolomic profiling to reveal that root chemical interactions drive reduced susceptibility to Septoria tritici blotch, with phenolic compounds emerging as key mediators. Disruption of these root signals eliminates both the disease resistance phenotype and the associated molecular reprogramming.

root-mediated interactions bread wheat Septoria tritici blotch transcriptomics metabolomics

Ultra large-scale 2D clinostats uncover environmentally derived variation in tomato responses to simulated microgravity

Authors: Hostetler, A. N., Kennebeck, E., Reneau, J. W., Birtell, E., Caldwell, D. L., Iyer-Pascuzzi, A. S., Sparks, E. E.

Date: 2026-01-13 · Version: 2
DOI: 10.1101/2025.05.16.654566

Category: Plant Biology

Model Organism: Solanum lycopersicum (tomato)

AI Summary

The study employed ultra large‑scale 2D clinostats to grow tomato (Solanum lycopersicum) plants beyond the seedling stage under simulated microgravity and upright control conditions across five sequential trials. Simulated microgravity consistently affected plant growth, but the magnitude and direction of the response varied among trials, with temperature identified as a significant co‑variant; moderate heat stress surprisingly enhanced growth under simulated microgravity. These results highlight the utility of large‑scale clinostats for dissecting interactions between environmental factors and simulated microgravity in plant development.

simulated microgravity ultra large-scale clinostat tomato (Solanum lycopersicum) heat stress plant growth interaction

The STA1-DOT2 interaction promotes nuclear speckle formation and splicing robustness in growth and heat stress responses

Authors: Kim, H., Yu, K.-j., Park, S. Y., Seo, D. H., Jeong, D.-H., Kim, W. T., Yun, D.-J., Lee, B.-h.

Date: 2026-01-12 · Version: 1
DOI: 10.64898/2026.01.11.698856

Category: Plant Biology

Model Organism: Arabidopsis thaliana

AI Summary

The study demonstrates that the interaction between spliceosomal proteins STA1 and DOT2 controls nuclear speckle organization, pre‑mRNA splicing efficiency, and heat‑stress tolerance in Arabidopsis thaliana. A missense mutation in DOT2 restores the weakened STA1‑DOT2 interaction in the sta1‑1 mutant, linking interaction strength to speckle formation and transcriptome‑wide intron retention under heat stress, while pharmacological inhibition of STA1‑associated speckles reproduces the mutant phenotypes. These findings reveal a heat‑sensitive interaction node that couples spliceosome assembly to nuclear speckle dynamics and splicing robustness.

spliceosome nuclear speckles STA1‑DOT2 interaction heat stress Arabidopsis thaliana

Physiological Characterization under the Influence of Drought Stress and Salicylic Acid in Valeriana wallichii DC

Authors: Ansari, S., Patni, B., Jangpangi, D., Joshi, H. C., Bhatt, M. K., Purohit, V.

Date: 2026-01-09 · Version: 1
DOI: 10.64898/2026.01.09.698547

Category: Plant Biology

Model Organism: Valeriana wallichii

AI Summary

The study investigated the ability of foliar-applied salicylic acid (SA) to alleviate drought stress in the high‑altitude medicinal plant Valeriana wallichii by measuring physiological and biochemical responses during vegetative and flowering stages. SA at specific concentrations improved photosynthetic rates, water‑use efficiency, chlorophyll content, membrane stability, and root biomass under both severe (25% field capacity) and moderate (50% field capacity) drought conditions. These results suggest that SA treatment enhances drought tolerance and productivity in this species.

drought stress salicylic acid Valeriana wallichii photosynthetic efficiency water use efficiency

A chloroplast-localized protein AT4G33780 regulates Arabidopsis development and stress-associated responses

Authors: Yang, Z.

Date: 2026-01-03 · Version: 1
DOI: 10.64898/2026.01.03.697459

Category: Plant Biology

Model Organism: Arabidopsis thaliana

AI Summary

The study characterizes the chloroplast‑localized protein AT4G33780 in Arabidopsis thaliana using CRISPR/Cas9 knockout and overexpression lines, revealing tissue‑specific expression and context‑dependent effects on seed germination, seedling growth, vegetative development, and root responses to nickel stress. Integrated transcriptomic (RNA‑seq) and untargeted metabolomic analyses show extensive transcriptional reprogramming—especially of cell‑wall genes—and altered central energy metabolism, indicating AT4G33780 coordinates metabolic state with developmental regulation rather than controlling single pathways.

AT4G33780 chloroplast regulator Arabidopsis thaliana transcriptomics metabolomics

Dynamic ASK1 proximity networks uncover SCF-dependent and noncanonical roles in ABA and drought adaptation

Authors: Rodriguez-Zaccaro, F. D., Moe-Lange, J., Malik, S., Montes-Serey, C., Hamada, N., Groover, A., Walley, J., Shabek, N.

Date: 2025-12-25 · Version: 1
DOI: 10.64898/2025.12.22.696057

Category: Plant Biology

Model Organism: Arabidopsis thaliana

AI Summary

The study maps the in vivo proximity interactome of Arabidopsis SKP1-LIKE 1 (ASK1) under acute abscisic acid (ABA) signaling and prolonged drought using TurboID-based proximity labeling and quantitative proteomics, revealing condition-specific networks that include both canonical SCF modules and diverse noncanonical partners. Overexpression of ASK1 shifts proteome composition toward drought‑protective and ABA‑responsive proteins while repressing immune and ROS‑scavenging pathways, highlighting ASK1 as a hub that integrates SCF‑dependent and independent pathways to reprogram transcription, translation, and proteostasis during stress adaptation.

ASK1 SCF ubiquitin ligases abscisic acid signaling drought stress TurboID proximity labeling
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