Plant tissues exhibit a layered architecture that makes spatial context decisive for interpreting transcriptional changes. This review explains why the location of gene expression is as important as its magnitude and synthesizes advances uniting single-cell/nucleus RNA-seq with spatial transcriptomics in plants. Surveyed topics include platform selection and material preparation; plant-specific sample processing and quality control; integration with epigenomic assays such as single-nucleus Assay for Transposase-Accessible Chromatin using sequencing (ATAC) and Multiome; and computational workflows for label transfer, deconvolution, spatial embedding, and neighborhood-aware cell–cell communication. Protoplast-based single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling but introduces dissociation artifacts and cell-type biases, whereas ingle-nucleus RNA sequencing (snRNA-seq) improves the representation of recalcitrant lineages and reduces stress signatures while remaining compatible with multiomics profiling. Practical guidance is provided for mitigating ambient RNA, interpreting organellar and intronic metrics, identifying doublets, and harmonizing batches across chemistries and studies. Spatial platforms (Visium HD, Stereo-seq, bead arrays) and targeted imaging (Single-molecule fluorescence in situ hybridization (smFISH), Hairpin-chain-reaction FISH (HCR-FISH), Multiplexed Error-Robust Fluorescence In Situ Hybridization (MERFISH)) are contrasted with plant-specific adaptations and integration pipelines that anchor dissociated profiles in anatomical coordinates. Recent atlases in Arabidopsis, soybean, and maize illustrate how cell identities, chromatin accessibility, and spatial niches reveal developmental trajectories and stress responses jointly. A roadmap is outlined for moving from atlases to interventions by deriving gene regulatory networks, prioritizing cis-regulatory targets, and validating perturbations with spatial readouts in crops. Together, these principles support a transition from descriptive maps to mechanism-informed, low-pleiotropy engineering of agronomic traits.

Long noncoding RNAs (lncRNAs) have emerged as key regulators of gene expression during seed development and physiology. This review examines the diverse roles of lncRNAs in key stages of seed development, including embryogenesis, maturation, dormancy, germination, and aging. It integrates the current understanding of the biogenesis and classification of lncRNAs, emphasizing their functional mechanisms in seeds, particularly those acting in cis and trans. These mechanisms include the scaffolding of polycomb and SWI/SNF chromatin remodeling complexes, the guidance of RNA-directed DNA methylation, the ability to function as molecular decoys, and the modulation of small RNA pathways via competitive endogenous RNA activity. This review highlights the regulatory influence of lncRNAs on abscisic acid (ABA) and gibberellin (GA) signaling pathways, as well as light-responsive circuits that control dormancy and embryonic root formation. Endosperm imprinting processes that link parental origin to seed size and storage are also discussed. Emerging evidence for epitranscriptomic modifications, such as m6A methylation, and the formation of LncRNA–RNA-binding protein condensates that maintain resting states and coordinate reserve biosynthesis are also reviewed. Advances in methodologies, including single-cell and spatial transcriptomics, nascent transcription, direct RNA sequencing, and RNA–chromatin interaction mapping, are expanding the comprehensive lncRNA landscape during seed development and germination. These advances facilitate functional annotation. Finally, possible translational research applications are explored, with a focus on developing lncRNA-based biomarkers for seed vigor and longevity.

Drought is a leading constraint on plant productivity and will intensify with climate change. Plant acclimation emerges from a multilayered regulatory system that integrates signaling, transcriptional reprogramming, RNA-based control, and chromatin dynamics. Within this hierarchy, non-coding RNAs (ncRNAs) provide a unifying regulatory layer; microRNAs (miRNAs) modulate abscisic acid and auxin circuits, oxidative stress defenses, and root architecture. This balances growth with survival under water-deficient conditions. Small interfering RNAs (siRNAs) include 24-nucleotide heterochromatic populations that operate through RNA-directed DNA methylation, which positions ncRNA control at the transcription–chromatin interface. Long non-coding RNAs (lncRNAs) act in cis and trans, interact with small RNA pathways, and can serve as chromatin-associated scaffolds. Circular RNAs (circRNAs) are increasingly being detected as responsive to drought. Functional studies in Arabidopsis and maize (e.g., ath-circ032768 and circMED16) underscore their regulatory potential. This review consolidates ncRNA biogenesis and function, catalogs drought-responsive modules across model and crop species, especially cereals, and outlines methodological priorities, such as long-read support for isoforms and back-splice junctions, stringent validation, and integrative multiomics. The evidence suggests that ncRNAs are tractable entry points for enhancing drought resilience while managing growth–stress trade-offs.

Small interfering RNAs (siRNAs) are a distinct class of regulatory RNAs in plants and animals. Gene silencing by small interfering RNAs is one of the fundamental mechanisms for regulating gene expression. siRNAs are critical regulators during developmental processes. siRNAs have similar structures and functions to small RNAs but are derived from double-stranded RNA and may be involved in directing DNA methylation of target sequences. siRNAs are a less well-studied class than the miRNA group, and researchers continue to identify new classes of siRNAs that appear at specific developmental stages and in particular tissues, revealing a more complex mode of siRNA action than previously thought. This review characterizes the siRNA classes and their biogenesis process and focuses on presenting their known functions in the regulation of plant development and responses to biotic and abiotic stresses. The review also highlights the exciting potential for future research in this field, proposing methods for detecting plant siRNAs and a bioinformatic pathway for identifying siRNAs and their functions.

Common valerian (Valeriana officinalis L.) is an important medicinal plant revealing sedative, hypotensive, anti-spasmodic and anxiolytic activity. The purpose of the study was to determine the intraspecific variability of the common valerian growing wild in Poland and the ‘Lubelski’ landrace, as to their developmental traits, chemical composition and selected genetic parameters. Both wild-growing populations (19) and the landrace (1) were evaluated under ex situ conditions. Observations of the underground organs parameters, both developmental and chemical (according to the European Pharmacopoeia) were carried out in the first year of the plant’s development, while the characteristics of the aboveground organs, followed by the sowing value of seeds (according to the International Seed Testing Association)—in the second year. The genetic analyses were performed using the NGS-DArT-seq method. Results indicate the presence of five different gene pools covering the regions of population’s origin, with a gene flow within and between them. A high level of developmental and chemical variabilities among the wild-growing populations was noticed, however without a clear relation to the region of the origin. The mass of underground organs ranged from 107.4 to 403.6 g FW × plant⁻¹ with the content of sesquiterpenic acids at the level of 0.004–0.094%. Population no 18 was distinguished by the highest content of sesquiterpenic acids and the relatively high mass of underground organs, followed by the admixture of the gene pool, typical for the ‘Lubelski’ landrace. Unlike the ‘Lubelski’ landrace, the wild-growing populations were characterized by a high amount of an essential oils (3.90 to 10.04 mL/kg), which may be promising from the perspective of their potential use. In turn, the sowing value of the seeds obtained from the populations, expressed as the germinability, was rather low (25.25–62.25%).

Sand oat (Avena strigosa Schreb.), one of the four cultivated species of the genus Avena, could be considered as another alternative crop. In gene banks 865 germplasm samples of this species have been preserved that have not been thoroughly investigated so far. The results of phenotyping (36 traits), isoenzymatic (12 systems) and genetic (8 pairs of Sequence-related amplified polymorphism markers) variation were used to obtain the complete description of 56 accessions diversity originated from different parts of world. Breeded and weedy forms represented similar pool of morphological traits that indicated a short-term and extensive breeding process, albeit all accessions which we classified as cultivated were characterized by better grain and green mass parameters compared to the weedy ones. Isoenzymes showed relationships with geographical origin, which was not possible to detect by SRAP markers. There was no similarity between morphological and biochemical results. The polymorphism level of SRAP markers was lower than indicated by the available literature data for other species, however it may result from the analysis of pooled samples of accessions with a high internal variability. The extensive type of breeding and its relatively short duration was also reflected in the population structure results. Joint analysis revealed that a secondary centre of diversity is being created in South America and that it has its genealogy from the Iberian Peninsula. Despite the relatively large representation of this species is in various gene banks, it is highly probable that the vast majority of stored worldwide accessions are duplicates, and the protected gene pool is relatively narrow. Sand oat meets all the requirements for an alternative crop species, but further studies are needed to identify the genotypes/populations with the most favourable distribution of utility and quality parameters.