Plant biology explores the intricate lives of the green world, from the microscopic machinery inside a leaf to how entire forests adapt to a changing climate. This field investigates everything from how roots drink water to the complex chemical signals plants use to communicate, offering vital insights into food security and environmental resilience.

On Gist.Science, we make these discoveries accessible by processing every new preprint in this category directly from bioRxiv. For each study, we provide both a plain-language overview for curious minds and a detailed technical summary for researchers, ensuring that the latest findings in plant science are clear and actionable. Below are the most recent papers in plant biology, freshly summarized for you to explore.

📄 plant biology

A cross-kingdom interactome predicted by AlphaFold3 reveals a DNF2-centered interface required for symbiotic accommodation

This study utilizes AlphaFold3 to construct a cross-kingdom interactome between *Medicago truncatula* and *Sinorhizobium meliloti*, identifying a DNF2-centered molecular framework involving specific rhizobial proteins that is essential for maintaining symbiotic accommodation and nitrogen fixation in root nodules.

Gao, J.-P., Zhao, F., Zhang, G., Chen, Q., Wu, S., Huang, J., Liu, C., Wang, G., Yu, P., Eves-van den Akker, S., Tian, C (…)2026-09-08
📄 plant biology

BOTANIC-1: a series of long-context plant genomic foundation models in the agentic era

This paper introduces Botanic1, a family of long-context, agent-integrated genomic language models trained on unannotated plant data that outperform existing models in predicting trait-associated regions and provide biological insights through mechanistic interpretability, all while being made available to the research community to accelerate climate-resilient crop development.

Barozet, A., Cabeli, V., Ogier du Terrail, J., Rukhovich, A., Janssoone, T., Klajer, G., Sheikhitarghi, Z., Andrews, G. (…)2026-09-07
📄 plant biology

VLCFA-mediated inter-cell layer communication controls cellular pluripotency in Arabidopsis callus

This study reveals that very-long-chain fatty acids (VLCFAs) synthesized in the outermost layer of Arabidopsis callus non-cell-autonomously suppress cytokinin signaling to restrict procambium identity and establish the middle-cell layer, thereby controlling cellular pluripotency and shoot regeneration through inter-cell layer communication.

Doll, Y., Nobusawa, T., Kojima, M., Nagata, K., Matsuda-Ito, K., Mähönen, A. P., Matsuda, T., Abe, M., Sakakibara, H. (…)2026-09-03
📄 plant biology

Seed Microbiome Transfer Mitigates Intergenerational Dysbiosis, Modulates Plant Defenses and Suppresses Foliar Disease

This study demonstrates that transferring seed microbiomes from healthy donors can counteract the intergenerational legacy of antibiotic-induced dysbiosis in tomato plants by restoring rhizosphere community composition, reactivating defense gene expression, and suppressing foliar disease susceptibility.

Perina, F. J., Thomas, V., Ketehouli, T., Mudiyanselage, S., Jain, M., Schlathoelter, I., Goss, E., Martins, S. J.2026-09-01
📄 plant biology

Eucalyptus microRNA Archive (EMA): a multi-study and cross-condition curated database of microRNAs in Eucalyptus grandis

The Eucalyptus MicroRNA Archive (EMA) is a publicly accessible, curated database that integrates three independent small RNA sequencing datasets to establish a standardized, evidence-tiered catalog of 99 miRNAs and their functional target networks in *Eucalyptus grandis*, addressing previous fragmentation in annotations and providing a reproducible framework for research in non-model woody species.

Aires Teixeira, J. V., Motta Venancio, T., Quintanilha-Peixoto, G., Pimenta de Oliveira, K. K.2026-08-31
📄 plant biology

Time-resolved volatile organic compound profiling enables non-invasive detection of phenological progression in soybean

This study demonstrates that a framework combining automated time-resolved volatile organic compound (VOC) profiling and machine learning can accurately and non-invasively predict soybean phenological progression, offering a practical tool for crop monitoring that overcomes the limitations of visual observation after canopy closure.

Nakata, R., Hiraga, S., Ishimoto, M.2026-08-28