286 papers
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.
This study presents high-quality gap-free genome assemblies of two elite waxy maize inbred lines to reveal how structural variations drive post-domestication divergence, heterosis, and the critical balance between yield and flavor in edible waxy maize.
This study demonstrates that the xylem safety-efficiency trade-off is not a universal rule but rather an emergent pattern driven by specific ecological and evolutionary constraints, as it was observed only in mesic broadleaved species while being suppressed in conifers and hydrophilic broadleaved species due to anatomical limitations and reduced selective pressures.
This study employs a global modelling framework to reconstruct nonlinear ordinary differential equation systems from environmental time series, revealing that chaotic dynamics driven by specific environmental conditions govern the blooms of the toxic dinoflagellate *Ostreopsis cf. ovata* and offering a potential basis for short-term prediction.
Over six years of field trials, this study demonstrates that while erect potato canopies can significantly slow late blight epidemics by modifying the microclimate, their efficacy is highly variable and dependent on environmental conditions, particularly irrigation, limiting their reliability as a standalone control method.
This study presents a comprehensive Arabidopsis transcription factor binding atlas derived from 681 curated datasets, revealing that deep learning models best predict binding while uncovering pervasive, family-dependent organizational principles such as specific promoter positioning and preferred spacing between binding sites that shape the plant regulatory landscape.
This study establishes the first systematic epidemiological baseline for Alternaria leaf spot in Tanzania's Lake Zone, revealing 100% field prevalence with significant district-level variations in incidence and severity that underscore the need for tailored integrated disease management strategies.
This paper introduces DAESIM2-Plant, a mechanistic wheat growth model that applies eco-evolutionary optimality theory to dynamically determine carbon allocation between leaves and roots, successfully reproducing observed plasticity patterns and threshold responses to environmental gradients without relying on fixed empirical coefficients.
This study introduces a regression-based framework that leverages a large dataset of UAV imagery to accurately predict plant flowering time from as few as a single observation per experiment, significantly reducing the data collection burden compared to traditional multi-observation methods.
This study reveals that elevated CO2 induces persistent, intergenerational 3D chromatin reorganization in *Arabidopsis thaliana* by modulating Local Chromatin Domains and loops through coordinated RNA-directed DNA methylation and Polycomb group pathways, thereby reshaping the plant's transcriptional landscape.
By using the early-diverging orchid *Glossodia major* as an evolutionary anchor, this study elucidates how the coordinated expression, functional diversification, and regulatory shifts of conserved terpene and apocarotenoid biosynthetic pathways drive the evolution of floral scent and pollination strategies within the Caladeniinae subtribe.