The study investigates the subfunctionalization of duplicated GIGANTEA paralogs in Petunia x hybrida, focusing on PhGI2's role in floral transition. While RNAi silencing of PhGI2 caused mixed vegetative and reproductive phenotypes, CRISPR/Cas9-generated loss‑of‑function alleles showed that PhGI2 specifically promotes flowering without affecting vegetative growth or scent. The findings reveal that PhGI2 is essential for maintaining circadian gene expression dynamics and regulating flowering time, separating vegetative growth from reproductive timing.

The study investigates the gene regulatory network (GRN) controlling flowering time in the allotetraploid crop Brassica napus by comparing its transcriptome to that of Arabidopsis thaliana. While most orthologous gene pairs show conserved expression dynamics, several flowering‑time genes display regulatory divergence, especially under cold conditions, indicating subfunctionalisation among paralogues. Despite these differences, the overall GRN topology remains similar to Arabidopsis, likely due to retention of multiple paralogues.

The study identifies MtFTb1 and MtFTb2 as essential, redundant regulators of long‑day flowering in the legume Medicago truncatula, demonstrating that they are required for up‑regulating MtFTa1 under vernalised long‑day conditions. Using CRISPR/Cas9‑generated single and double mutants, the authors show that double mutants are specifically delayed in flowering under long days while retaining vernalization responsiveness, and transcriptomic analyses reveal that MtFTb1/2 activate MADS‑box genes and other flowering regulators.

The authors used a bottom‑up thermodynamic modelling framework to investigate how plants decode calcium signals, starting from Ca2+ binding to EF‑hand proteins and extending to higher‑order decoding modules. They identified six universal Ca2+-decoding modules that can explain variations in calcium sensitivity among kinases and provide a theoretical basis for interpreting calcium signal amplitude and frequency in plant cells.

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 benchmarked over 20 web‑based gRNA on‑target efficiency prediction tools against an experimental plant CRISPR editing dataset, finding several machine‑learning based tools whose scores strongly correlated with observed InDel frequencies. Additionally, the performance of popular platforms such as CRISPOR and CRISPR‑P was assessed, offering guidance for improved gRNA design in plant genome editing.

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 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.

The study estimated genetic parameters for flowering and maturity time in almond (Prunus dulcis) using classical segregation analyses and Bayesian linear mixed models on a pedigree of over 17,500 individuals spanning 30 years. Heritability and repeatability were quantified, breeding values (EBVs) were computed for all genotypes, and trait-specific rankings were generated to improve parental selection. The results provide a foundation for integrating genomic selection into almond breeding programs.