Genetius

The study examined how natural environmental cues, particularly temperature and light, adjust the circadian clock in a wild plant population, revealing that temperature cues can shift circadian timing and that light and temperature have unbalanced effects on clock entrainment across seasons. Genome-wide analyses combined with machine-learning interpretation uncovered extensive modulation of temperature responses by the clock, highlighting the plasticity of circadian timing under field conditions.

The authors applied semi‑supervised deep‑learning to super‑resolution images of modern and fossil grass pollen, training convolutional neural networks to extract abstract morphological features. These features were used to quantify past grass community diversity and C3:C4 ratios in a 25,000‑year lake‑sediment record, revealing a marked diversity loss during the last glacial and a gradual decline of C4 grasses in the Holocene.

The study introduces PAiD, a plant-optimized genome‑editing platform based on the AI‑designed nuclease OpenCRISPR‑1, which efficiently enables NHEJ‑mediated indels, adenine and cytosine base editing, and prime editing across multiple plant loci with performance comparable to SpCas9. These findings demonstrate the translational potential of AI‑designed nucleases for versatile plant genome engineering.

The authors introduce AdaPoinTr, a geometry-aware transformer that predicts the alpha‑shape of coniferous tree crowns from incomplete terrestrial or mobile laser‑scanning point clouds, focusing on crown reconstruction rather than full tree completion. Trained on synthetically generated partial crowns, the model consistently improves crown shape similarity and reduces height estimation bias across three diverse forest datasets, providing a cost‑effective solution for enhanced 3D forest structural monitoring.

The study genotyped 182 Phytophthora infestans isolates from Bolivia, Peru, Ecuador, Colombia, and Uruguay to assess their clonal lineages, mitochondrial haplotypes, and mating types, revealing distinct regional patterns and the presence of a new lineage (CO4) in Colombia. These findings update the understanding of the pathogen's genetic diversity and distribution in South America, informing improved late blight management strategies.

The study introduces a low-cost, smartphone-based image capture system coupled with two user-friendly analysis pipelines (PlantCV and Biodock AI) to enhance throughput of field phenotyping. Image quality from the smartphone was sufficient for both pipelines, which generated phenotype measurements comparable to manual annotation, demonstrating a scalable approach for large spaced plant populations.

The authors have withdrawn their manuscript, indicating that substantial revisions are needed and requesting that the work not be cited.

The study used biochemical assays and untargeted LC‑MS metabolomics to profile metabolic changes in released pollen subjected to cold (15 °C) and heat (35 °C) stress, identifying 147 significantly altered metabolites across various classes. Pathway enrichment revealed key perturbations in amino acid, purine, arginine, and glutathione metabolism, highlighting temperature‑dependent metabolic adjustments that underpin pollen thermotolerance. These results provide a metabolomic framework for understanding and potentially improving reproductive resilience under climate change.

The study employed an integrated in silico workflow to screen neem-derived phytochemicals for inhibition of the Fusarium oxysporum effector protein Avr1, identifying nimbiol as the top binder with a -6.3 kcal/mol affinity. Molecular docking, ADME profiling, and toxicity predictions highlighted favorable pharmacokinetic properties and moderate safety concerns for several compounds, especially nimbiol and gedunin, suggesting them as promising leads for experimental validation against Fusarium wilt.

The study identifies seven nanoscale deformation modes of cellulose fibrils within a rectangular cell-wall domain and provides geometric descriptions for each, highlighting how these modes contribute to cell wall expansion under stress. It shows that the applicability of deformation functions depends on the domain's aspect ratio, with moderate aspect ratios matching typical in‑vivo cell dimensions, and emphasizes the need for scale‑independent geometry to predict mesoscale growth outcomes.