Using a controlled field experiment on clonal 35‑year‑old Norway spruce trees, the study examined molecular defense responses to Ips typographus attacks. A multi‑omics approach revealed rapid local increases in jasmonic acid and other phytohormones, leading to differential expression of up to 1,900 genes and corresponding proteomic and metabolomic changes that elevated deterrent compounds such as phenolic aglycones, diterpene resin acids, terpenes, and lignin.

The study compared aphid resistance and Barley Yellow Dwarf Virus (BYDV) transmission among three wheat varieties (G1, RGT Wolverine, RGT Illustrious). G1 emits the repellent 2‑tridecanone, restricts aphid phloem access, and shows reduced BYDV transmission, whereas RGT Wolverine limits systemic viral infection despite high transmission efficiency. The authors suggest breeding the two resistance mechanisms together for improved protection.

Using integrated metabolomics, fluxomics, and proteomics, the study shows that Bamboo mosaic virus infection in Nicotiana benthamiana redirects carbon flux toward glycolysis and the TCA cycle, enhancing mitochondrial metabolism. Silencing the mitochondrial NAD⁺-dependent malic enzyme 1 disrupts cytoplasmic NADH/NAD⁺ balance and alters defense gene expression, indicating that mitochondrial redox regulation is crucial for antiviral defense.

The study investigated whether wheat homoeologous genes actively compensate for each other when one copy acquires a premature termination codon (PTC) mutation. By analyzing mutagenised wheat lines, the authors found that only about 3% of cases exhibited upregulation of the unaffected homoeolog, indicating that widespread active transcriptional compensation is absent in wheat.

Overexpression of the wheat bHLH transcription factor TaPGS1 leads to increased flavonol accumulation in the seed coat, which disrupts polar auxin transport and causes localized auxin accumulation, delaying endosperm cellularization and increasing cell number, thereby enlarging grain size. Integrated metabolomic and transcriptomic analyses identified upregulated flavonol biosynthetic genes, revealing a regulatory module that links flavonol-mediated auxin distribution to seed development in wheat.

The study uses a high‑throughput comparative multi‑omics strategy to profile transcript, metabolite, and protein dynamics in Arabidopsis thaliana seedlings throughout the heat‑stress memory (HSM) phase following acquired thermotolerance. Early recovery stages show rapid transcriptional activation of memory‑related genes, while protein levels stay elevated longer, and distinct metabolite patterns emerge, highlighting temporal layers of the memory process.

The study evaluated how alginate oligosaccharide (AOS) chain length influences the levels of seven key phytohormones in wheat seedlings challenged with Botrytis cinerea. Hormone profiling revealed that mid‑range oligomers (DP 4‑6) most strongly up‑regulate defense‑related hormones (JA, SA, ABA, CTK), whereas longer oligomers (DP 7) most effectively suppress ethylene. These findings suggest that tailoring AOS polymerization can optimize disease resistance and growth in cereal crops.

The study investigates the altered timing of the core circadian oscillator gene ELF3 in wheat compared to Arabidopsis, revealing that dawn-specific expression in wheat arises from repression by TOC1. An optimized computational model integrating experimental expression data and promoter architecture predicts that wheat’s circadian oscillator remains robust despite this shift, indicating flexibility in plant circadian network design.

The study employed a multi‑omics workflow (transcriptomics, ribosome profiling, and proteomics) to uncover small peptides encoded by long non‑coding RNAs (LSEPs) in rice, finding that over 40% of surveyed lncRNAs associate with ribosomes. An optimized small‑peptide extraction followed by LC‑MS/MS identified 403 LSEPs, confirming the peptide‑coding capacity of plant lncRNAs and providing a scalable pipeline for large‑scale screening.

The Global Wheat Dataset Consortium released a comprehensive semantic segmentation dataset (GWFSS) of wheat organs across developmental stages, comprising 1,096 fully annotated images and 52,078 unannotated images from 11 institutions. Models based on DeepLabV3Plus and Segformer were trained, with Segformer achieving ≈90% mIoU for leaves and spikes but lower precision (54%) for stems, while also enabling weed exclusion and discrimination of necrotic, senescent, and residue tissues.