Plant Biology最新文献

Grasses and Epichloë endophytes often form mutualistic symbiotic defence systems. Studies have shown Epichloë endophytes improve resistance of host plants to airborne diseases. However, whether endophytes affect soil-borne disease resistance of host or neighbouring non-host plants remains unclear. We used endophyte-infected (EI) and endophyte-free (EF) Achnatherum sibiricum as host grass, Leymus chinensis as non-host grass, and Rhizoctonia solani as pathogen to explore the effects of endophyte infection on disease resistance of host and neighbouring non-host grasses. To clarify the contribution of root exudates to disease resistance of the non-host grass, three different root separation methods were employed between host and non-host plants: plastic barrier (PB), nylon mesh barrier (NL, allowing root exudates to pass through), or no barrier (NB). Epichloë endophytes decreased the disease index (DI) of the host A. sibiricum and reduced pathogen abundance in both host roots and soil. The DI of L. chinensis was affected by the interaction between root separation and endophyte infection. Under NL and NB treatments, the DI of L. chinensis with an EI neighbour was significantly lower than that with an EF neighbour, indicating that endophytic fungi can alleviate disease in non-host plants by influencing root exudates. Additionally, endophytic fungi increased the content of total phenolic compounds and salicylic acid in L. chinensis through activation of host root exudates, which could be one reason for the reduced DI of L. chinensis. Upon analysing root exudate components of the host, we found 2,4-di-tert-butylphenol (DTBP) and dibutyl phthalate (DBP) were the main antifungal compounds mediated by endophyte infection. Epichloë endophytes improved soil-borne disease resistance of the host and enhanced resistance of the neighbouring non-host grass through host root exudates; overall, host and non-host plants showed "associational resistance" to soil-borne diseases. This study highlights that Epichloë endophytes could potentially serve as efficient biological control agents against R. solani-associated diseases in grassland communities.

Single-cell RNA sequencing (scRNA-seq) has emerged as a revolutionary technology that has significantly increased our understanding of plant cellular diversity and gene expression. Unlike bulk RNA sequencing, scRNA-seq reveals gene expression profiles at the cellular level and identifies rare cell populations and complex regulatory networks. Innovations in single-cell isolation have addressed previous challenges unique to plant cells, such as large cell sizes and rigid walls. Data analysis pipelines have also improved quality control, normalization, clustering, and downstream analyses of high-dimension scRNA-seq data. These improvements enhance our understanding of plant morphogenesis and cellular heterogeneity, opening avenues for further investigation into the complex interplay between gene expression and plant development. This review explores recent advances in sample preparation, such as protoplast preparation and nuclei isolation, library preparation, sequencing, and a detailed data analysis pipeline. Further, we explored the diverse applications of scRNA-seq in the field of cotton research, such as fibre development, gland development, salt and stress responses, as well as elucidating molecular mechanisms in anther development and uncovering critical regulatory networks involved in plant regeneration. Despite the potential and recent advances of scRNA-seq, some challenges, such as protoplast preparation, cell size variability, and the requirement for reliable marker genes, still need to be addressed. Thus, future research should prioritize optimizing scRNA-seq methodologies, enhancing high-throughput capabilities, and integrating multi-omics approaches to address changing environmental conditions.

It is necessary to assess the adaptive potential of European beech populations to climate change. Environmental association analysis is a powerful tool for identifying gene loci that contribute to local adaptation to environmental pressures. Genotypic data were collected from ~100 adult beech trees per stand in five locations in the south-eastern Romanian Carpathians along an altitudinal gradient associated with precipitation and temperature. In total, 53 environmental variables, e.g., temperature and precipitation, were used to perform environmental association analysis using LFMM (latent factor mixed models) to identify Single Nucleotide Polymorphism (SNP) markers associated with these. In addition, the principal components (PC) from a principal components analysis (PCA) performed on all environmental variables were used to perform an environmental association analysis. We identified 446 SNP markers significantly associated with the first PC. These overlapped with the SNP markers significantly associated with most environmental variables. The first PC was correlated with all temperature-based variables at |r| ~0.989 to ~0.997. A high peak on chromosome 2 from ~4.56 to ~16.27 Mb appeared in all results. This region was ~3.47 Mb downstream of a region for local adaptation identified by Lazic et al. (2024). In this peak, 273 markers located in the coding region of 22 genes were found. The two genes, polygalacturonase QRT3-like and NRT1/PTR_FAMILY 5.4-like, may be involved in local adaptation based on our literature review. Polygalacturonase QRT3-like plays a role in pollen development in Arabidopsis. At the corresponding SNP markers, there was a correlation of the minor allele frequency and temperature-based environmental variables.