The study investigates the roles of the receptor-like kinase CRK2 and the RNA-binding protein GRP7 in regulating gibberellin signaling and floral transition in Arabidopsis, using phenotypic analyses of single and double mutants. Exogenous gibberellic acid treatments and transcript profiling reveal that CRK2 and GRP7 jointly modulate GA-responsive pathways, highlighting a novel regulatory layer involving membrane kinases and RNA-binding proteins.

The study investigates how a small molecule that lengthens circadian period can quantitatively adjust the critical day length required for flowering in monocot plants. By modulating the clock's timing, the researchers provide evidence supporting the external coincidence model of photoperiodic control.

The study combined high-throughput image-based phenotyping with genome-wide association studies to uncover the genetic architecture of tolerance to the spittlebug Aeneolamia varia in 339 interspecific Urochloa hybrids. Six robust QTL were identified for plant damage traits, explaining up to 21.5% of variance, and candidate genes linked to hormone signaling, oxidative stress, and cell‑wall modification were highlighted, providing markers for breeding.

The study investigates how the timing of the vegetative phase change (VPC) in Arabidopsis thaliana influences drought adaptation, revealing strong genotype-by-environment interactions that create stage-specific fitness tradeoffs. Genotypes from warmer, drier Iberian climates transition earlier, and genome-wide association mapping identifies loci linked to VPC timing and drought response, with several candidates validated using T‑DNA insertion lines.

The study demonstrates that limonene, a natural essential‑oil component, strongly inhibits Fusarium oxysporum, the causal agent of potato dry rot, by impairing colony growth, hyphal morphology, spore viability, membrane integrity, and transcription/translation processes, as well as disrupting ion homeostasis. Combined treatments reveal additive effects with mancozeb and synergistic effects with hymexazol, highlighting limonene's potential as an eco‑friendly bio‑fungicide for potato disease management.

The study developed a high-throughput phenotyping platform to assess root infestation by Orobanche cumana in a diverse sunflower association mapping population and applied a dual GWAS using SNPs and k-mers to uncover resistance loci. It validated known QTLs with higher resolution, identified novel candidate genes such as leucine‑rich repeat receptor kinases, and highlighted introgressed segments from wild Helianthus species that contribute to broomrape resistance.

The study examined how allelic variation at three barley flowering-time genes (PPD‑H1, ELF3, and PHYC) influences photoperiod response parameters, revealing that ELF3 reduces intrinsic earliness and PhyC‑e lowers photoperiod sensitivity. By testing Near Isogenic Lines and HEB‑25 lines under 16–24 h photoperiods, the authors identified a 20‑h threshold for PPD‑H1 lines and proposed reduced photoperiod regimes (20 h and 16 h) for energy‑efficient speed breeding.

The study reports the creation and validation of a high‑density Axiom SNP array for Solanum tuberosum, based on 10X Genomics sequencing of 108 diverse clones and integration of existing Illumina markers. The array demonstrated high reproducibility and, after filtering, provided 206,616 informative markers for population structure analysis, GWAS of polyphenol oxidase activity, and genomic prediction with accuracies up to 0.86.

A genome-wide association study of 166 Iberian Arabidopsis accessions identified loci, including ABA3 and GA2ox2, that modulate the inhibitory effect of the auxin precursor indole-3-acetamide (IAM) on primary root elongation. Integrating sequence analysis, transcriptomics, 3D protein modeling, and mutant physiology revealed that IAM promotes ABA biosynthesis and signaling, uncovering a novel node of hormone crosstalk.

The study integrated weekly morphophysiological measurements with high-density genotyping-by-sequencing data and a machine‑learning pipeline to dissect flowering time variation in diverse Cannabis sativa landraces. By applying mutual information, recursive feature elimination, random forest, and support vector machine classifiers to over 234,000 combined genetic, phenotypic, and environmental features, the authors identified 53 key markers that classify early, medium, and late flowering types with 96.6% accuracy. Notable loci, including CsFT3 and CsCFL1, were highlighted as promising targets for breeding and smart‑crop strategies.