The study introduces the Botanical Spectrum Analyzer (BSA), a GUI that incorporates a modified U‑Net deep neural network for accurate segmentation of plant images from RGB and hyperspectral (VNIR and SWIR) data. BSA was tested on wheat, barley, and Arabidopsis datasets, achieving >99% accuracy and F1‑scores above 98%, and markedly outperformed commercial tools on root segmentation tasks.
Light on its feet: Acclimation to high and low diurnal light is flexible in Chlamydomonas reinhardtii
Authors: Dupuis, S., Chastain, J. L., Han, G., Zhong, V., Gallaher, S. D., Nicora, C. D., Purvine, S. O., Lipton, M. S., Niyogi, K. K., Iwai, M., Merchant, S. S.
The study examined how prior light‑acclimation influences the fitness and rapid photoprotective reprogramming of Chlamydomonas during transitions between low and high diurnal light intensities. While high‑light‑acclimated cells struggled to grow and complete the cell cycle after shifting to low light, low‑light‑acclimated cells quickly remodeled thylakoid ultrastructure, enhanced photoprotective quenching, and altered photosystem protein levels, recovering chloroplast function within a single day. Transcriptomic and proteomic profiling revealed swift induction of stress‑response genes, indicating high flexibility in diurnal light acclimation.
DECREASE IN DNA METHYLATION 1-mediated epigenetic regulation maintains gene expression balance required for heterosis in Arabidopsis thaliana
Authors: Matsuo, K., Wu, R., Yonechi, H., Murakami, T., Takahashi, S., Kamio, A., Akter, M. A., Kamiya, Y., Nishimura, K., Matsuura, T., Tonosaki, K., Shimizu, M., Ikeda, Y., Kobayashi, H., Seki, M., Dennis, E. S., Fujimoto, R.
The study demonstrates that the chromatin remodeler DDM1 is essential for biomass heterosis in Arabidopsis thaliana hybrids, as loss of DDM1 function leads to reduced rosette growth and extensive genotype‑specific transcriptomic and DNA methylation changes. Whole‑genome bisulfite sequencing revealed widespread hypomethylation in ddm1 mutants, while salicylic acid levels were found unrelated to heterosis, indicating that epigenetic divergence, rather than SA signaling, underpins hybrid vigor.
The study isolated an endophytic Pseudomonas aeruginosa strain (SPT08) from tomato cotyledon seedlings that suppressed the wilt pathogen Ralstonia pseudosolanacearum and promoted plant growth, increasing height by 20% and root biomass by 60%. GFP labeling confirmed endophytic colonization, and genomic analysis revealed multiple secretion systems and secondary‑metabolite gene clusters associated with biocontrol and growth‑promoting traits.
The study applied spatial transcriptomics to map the transcriptional landscape of wheat (Triticum aestivum) inflorescences during spikelet development, revealing two distinct regions—a RAMOSA2‑active primordium and an ALOG1‑expressing boundary. Developmental assays showed that spikelets arise from meristematic zones accompanied by vascular rachis formation, identifying key regulators that could be targeted to improve spikelet number and yield.
The study applied a progressive, sublethal drought treatment to Arabidopsis thaliana, collecting time‑resolved phenotypic and transcriptomic data. Machine‑learning analysis revealed distinct drought stages driven by multiple overlapping transcriptional programs that intersect with plant aging, and identified high‑explanatory‑power transcripts as biomarkers rather than causal agents.
Salt stress strongly suppresses root growth in Festuca rubra while sparing shoot development. Transcriptome profiling identified over 68,000 differentially expressed genes, with up‑regulated genes enriched in methionine, melatonin, and suberin biosynthesis and down‑regulated genes involved in gibberellin, ABA, and sugar signaling, indicating extensive hormonal and metabolic reprogramming. Paradoxical regulation of gibberellin and ethylene pathways suggests a finely tuned balance between growth and stress responses.
An optimized workflow was developed to apply the Xenium in situ sequencing platform to formalin‑fixed paraffin‑embedded (FFPE) sections of Medicago truncatula roots and nodules, incorporating customized tissue preparation, probe design, and imaging to overcome plant‑specific challenges such as cell wall autofluorescence. The protocol was validated across nodule developmental stages using both a 50‑gene panel for mature cell identity and an expanded 480‑gene panel covering multiple cell types, providing a scalable high‑resolution spatial transcriptomics method adaptable to other plant systems.
Phenotypic scoring of Canola Blackleg severity using machine learning image analysis
Authors: Hu, Q., Anderson, S. N., Gardner, S., Ernst, T. W., Koscielny, C. B., Bahia, N. S., Johnson, C. G., Jarvis, A. C., Hynek, J., Coles, N., Falak, I., Charne, D. R., Ruidiaz, M. E., Linares, J. N., Mazis, A., Stanton, D. J.
The study introduces a deep‑learning based image analysis pipeline that scores blackleg disease severity from stem cross‑section images of canola species, achieving greater consistency than median expert raters while preserving comparable heritability of susceptibility traits. This standardized scoring method aims to improve selection of resistant varieties in breeding programs.
The study examined how single and repeated mechanical disturbances (whole‑pot drops) affect leaf folding in Mimosa pudica, using chlorophyll fluorescence to track photosystem II efficiency and transcriptome profiling to identify responsive genes. A single drop mainly up‑regulated flavonoid biosynthesis genes, whereas multiple drops triggered broader biotic and abiotic stress pathways, indicating a shift in the plant’s gene regulatory network under repeated stress.