The study introduces a hybrid modeling framework that integrates a logistic ordinary differential equation with a Long Short-Term Memory neural network to form a Physics-Informed Neural Network (PINN) for predicting wheat plant height. Using only time and temperature as inputs, the PINN outperformed other longitudinal growth models, achieving the lowest average RMSE and reduced variability across multiple random initializations. The results suggest that embedding biological growth constraints within data‑driven models can substantially improve prediction accuracy for plant traits.

The study generated a dataset of 420 sgRNAs targeting promoters, exons, and introns of 137 tomato genes in protoplasts, linking editing efficiency to chromatin accessibility, genomic context, and sequence features. Open chromatin sites showed higher editing rates, while transcriptional activity had little effect, and a subset of guides produced near‑complete editing with microhomology‑mediated deletions. Human‑trained prediction models performed poorly, highlighting the need for plant‑specific guide design tools.

The study examined how DNA methylation influences cold stress priming in Arabidopsis thaliana, revealing that primed plants exhibit distinct gene expression and methylation patterns compared to non-primed plants. DNA methylation mutants, especially met1 lacking CG methylation, showed altered cold memory and misregulation of the CBF gene cluster, indicating that methylation ensures transcriptional precision during stress recall.

Using genome‑wide association studies in Arabidopsis thaliana, the authors identified the chromatin‑associated protein CDCA7 as a trans‑regulator that specifically controls CG methylation (mCG) and TE silencing. CDCA7 and its paralog CDCA7β bind the remodeler DDM1, modulating its activity without broadly affecting non‑CG methylation or histone variant deposition, and natural variation in CDCA7 regulatory sequences correlates with local ecological adaptation.

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 integrates genome, transcriptome, and chromatin accessibility data from 380 soybean accessions to dissect the genetic and regulatory basis of symbiotic nitrogen fixation (SNF). Using GWAS, TWAS, eQTL mapping, and ATAC-seq, the authors identify key loci, co‑expression modules, and regulatory elements, and validate the circadian clock gene GmLHY1b as a negative regulator of nodulation via CRISPR and CUT&Tag. These resources illuminate SNF networks and provide a foundation for soybean improvement.

The study shows that silencing of NOR2 rRNA genes in Arabidopsis thaliana depends primarily on CHH-context cytosine methylation, particularly mediated by CMT2 and the chromatin remodeler DDM1, rather than CG or CHG methylation. Comparative promoter analysis revealed a prevalence of CHH sites in plant rDNA promoters, explaining why CHH methylation mutants disrupt NOR2 silencing more strongly, while NOR2 loci are hyper‑methylated and more condensed than NOR4.