The study integrated 16 Arabidopsis thaliana whole‑genome bisulfite sequencing datasets from 13 stress experiments using a unified bioinformatic pipeline to map common and stress‑specific DNA methylation changes. Differentially methylated regions varied by stress type and methylation context, with CG DMRs enriched in gene bodies and CHG/CHH DMRs in transposable elements, some of which overlapped loci prone to stable epimutations. Gene ontology and TE enrichment analyses highlighted shared stress pathways and suggest environmental stress can generate heritable epigenetic variation.

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 short‑term and transannual drought memory in cambium tissues of two Populus genotypes and four epitypes with modified DNA‑methylation machinery, revealing persistent hormone, transcript, and methylation changes one week after stress relief. Trees previously stressed in Year 1 displayed distinct physiological and molecular responses to a second drought in Year 2, indicating long‑term memory linked to stable CG‑context DNA methylation, with genotype‑dependent differences in plasticity and stability. These findings position the cambium as a reservoir for epigenetic stress memory and suggest exploitable epigenetic variation for tree breeding under drought.

The study evaluates the use of single-cell RNA sequencing (scRNA-seq) data to predict plant metabolic pathway genes (MPGs) in Arabidopsis thaliana, comparing five multi-label machine‑learning algorithms against traditional bulk RNA‑seq approaches. scRNA‑seq generated co‑expression networks that, while different, yielded significantly higher MPG classification accuracy, especially when data were split by genetic background or tissue type, and deep learning outperformed classical methods. The authors conclude that scRNA‑seq offers superior predictive power and should be incorporated into future MPG discovery pipelines.

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 examined molecular responses in grapevine leaves with and without esca symptoms, using metabolite profiling, RNA‑seq and whole‑genome bisulfite sequencing. Metabolic and transcriptomic changes were confined to symptomatic leaves and linked to local DNA‑methylation alterations, while asymptomatic leaves showed distinct but overlapping methylation patterns, some present before symptoms, indicating potential epigenetic biomarkers for early disease detection.

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 identifies GyrB3 as a novel nuclear factor that interacts with histone deacetylases to regulate transposable element silencing in plants, acting as a suppressor of IBM1 deficiency–induced epigenetic defects. Loss of GyrB3 reduces DNA methylation and increases H3 acetylation at TEs, demonstrating the importance of histone deacetylation for genome stability.

The study examined gene expression, DNA methylation, and small RNA profiles in a Citrus hybrid (C. reticulata × C. australasica) using haplotype‑resolved subgenome assemblies, revealing allele‑specific expression and asymmetric CHH methylation that correlated with increased transcription and 24‑nt siRNA accumulation at promoters. This unconventional association suggests RNA‑directed DNA methylation (RdDM) can activate transcription in citrus fruit and provides a pipeline for epigenomic analysis of complex hybrids relevant to disease resistance breeding.