Plant Communications最新文献

Grain size, which encompasses grain length, width, and thickness, is a critical determinant of both grain weight and quality in rice. Despite the extensive regulatory networks known to determine grain length and width, the pathway(s) that regulate grain thickness remain to be clarified. Here, we present the map-based cloning and characterization of qGT3, a major quantitative trait locus for grain thickness in rice that encodes the MADS-domain transcription factor OsMADS1. Our findings demonstrate that OsMADS1 regulates grain thickness by affecting sugar delivery during grain filling, and we show that OsMADS1 modulates expression of the downstream monosaccharide transporter gene MST4. A natural variant leads to alternative splicing and thus to a truncated OsMADS1 protein with attenuated transcriptional repressor activity. The truncated OsMADS1 protein results in increased expression of MST4, leading to enhanced loading of monosaccharides into the developing endosperm and thereby increasing grain thickness and improving grain quality. In addition, our results reveal that NF-YB1 and NF-YC12 interact directly with OsMADS1, acting as cofactors to enhance its transcriptional activity toward MST4. Collectively, these findings reveal a novel molecular mechanism underlying grain thickness regulation that is controlled by the OsMADS1-NF-YB1-YC12 complex and has great potential for synergistic improvement of grain yield and quality in rice.

Maintaining a stable basal level of salicylic acid (SA) is crucial for plant growth, development, and stress response, although basal levels of SA vary significantly among plant species. However, the molecular mechanisms by which basal SA regulates plant growth and stress response remain to be clarified. In this study, we performed a genetic screen to identify suppressors of the root growth defect in Osaim1, a rice mutant deficient in basal SA biosynthesis. We found that mutation of the E3 ligase OsPRT6, a key component of the Arg/N-degron pathway, can rescue the root growth defect of Osaim1. Further analysis revealed that OsWRKY62 and OsWRKY76 act as substrates of the OsPRT6 N-degron pathway to modulate root growth. We demonstrated that reducing the basal SA level activates the PRT6 N-degron pathway and that basal SA modulates the stress response in part through the PRT6 N-degron pathway. Importantly, the effects of basal SA levels on the PRT6 N-degron pathway are conserved across plant species. Taken together, these findings reveal a novel regulatory mechanism by which basal SA represses the PRT6 N-degron pathway to modulate root growth and abiotic stress response in rice.

In the face of climate change and the growing global population, there is an urgent need to accelerate the development of high-yielding crop varieties. To this end, vast amounts of genotype-to-phenotype data have been collected, and many machine learning (ML) models have been developed to predict phenotype from a given genotype. However, the requirement for high densities of single-nucleotide polymorphisms (SNPs) and the labor-intensive collection of phenotypic data are hampering the use of these models to advance breeding. Furthermore, recently developed genomic selection (GS) models, such as deep learning (DL), are complicated and inconvenient for breeders to navigate and optimize within their breeding programs. Here, we present the development of an intelligent breeding platform named AutoGP (http://autogp.hzau.edu.cn), which integrates genotype extraction, phenotypic extraction, and GS models of genotype-to-phenotype data within a user-friendly web interface. AutoGP has three main advantages over previously developed platforms: 1) an efficient sequencing chip to identify high-quality, high-confidence SNPs throughout gene-regulatory networks; 2) a complete workflow for extraction of plant phenotypes (such as plant height and leaf count) from smartphone-captured video; and 3) a broad model pool, enabling users to select from five ML models (support vector machine, extreme gradient boosting, gradient-boosted decision tree, multilayer perceptron, and random forest) and four commonly used DL models (deep learning genomic selection, deep learning genomic-wide association study, deep neural network for genomic prediction, and SoyDNGP). For the convenience of breeders, we use datasets from the maize (Zea mays) complete-diallel design plus unbalanced breeding-like inter-cross population as a case study to demonstrate the usefulness of AutoGP. We show that our genotype chips can effectively extract high-quality SNPs associated with days to tasseling and plant height. The models show reliable predictive accuracy on different populations and can provide effective guidance for breeders. Overall, AutoGP offers a practical solution to streamline the breeding process, enabling breeders to achieve more efficient and accurate genomic selection.

Roots absorb water and nutrients from the soil, support the plant's aboveground organs, and detect environmental changes, making them crucial targets for improving crop productivity. Particularly sensitive to soil salinity, a major abiotic stress, roots face significant challenges that threaten global agriculture. In response to salt stress, plants suppress root meristem size, thereby reducing root growth. However, the mechanisms underlying this growth restriction remain unclear. Here, we investigate the role of reactive oxygen species (ROS) in this process and reveal that LATERAL ORGAN BOUNDARIES DOMAIN 11 (LBD11) plays a central role in ROS-mediated regulation of meristem size and the salt stress-induced inhibition of root growth. Under normal conditions, LBD11 controls the expression of key ROS metabolic genes, maintaining ROS homeostasis within root developmental zones to control meristem size and overall root growth. Upon sensing salt stress, LBD11 undergoes rapid proteasome-mediated degradation, leading to decreased distribution of O₂^⋅-, which in turn curtails meristem size and limits root length. Our findings highlight an unexplored plant adaptation strategy, where the growth-promoting LBD11/ROS pathway is downregulated to finely regulate root growth under challenging conditions. We propose a strategy for developing crops with heightened resilience and increased yields in salt-affected environments.

Leaf angle is a major agronomic trait that determines plant architecture, which directly affects rice planting density, photosynthetic efficiency, and yield. The plant phytohormones brassinosteroids (BRs) and the MAPK signaling cascade are known to play crucial roles in regulating leaf angle, but the underlying molecular mechanisms are not fully understood. Here, we report a rice WRKY family transcription factor gene, OsWRKY72, which positively regulates leaf angle by affecting lamina joint development and BR signaling. Phenotypic analysis showed that oswrky72 mutants have smaller leaf angles and exhibit insensitivity to exogenous BRs, whereas OsWRKY72 overexpression lines show enlarged leaf angles and are hypersensitive to exogenous BRs. Histological sections revealed that the change in leaf inclination is due to asymmetric cell proliferation and growth at the lamina joint. Further investigation showed that OsWRKY72 binds directly to the promoter region of BR receptor kinase (OsBRI1), a key gene in the BR signaling pathway, and activates its expression to positively regulate rice BR signaling. In addition, we discovered that OsWRKY72 interacts with and is phosphorylated by OsMAPK6, and this phosphorylation event can enhance OsWRKY72 activity in promoting OsBRI1 expression. Genetic evidence confirmed that OsMAPK6, OsWRKY72, and OsBRI1 function in a common pathway to regulate leaf angle. Collectively, our findings clarify the critical role of the OsWRKY72 transcription factor in regulating rice leaf angle. These results provide valuable insights into the molecular regulatory networks that govern plant architecture in rice.

The Solanaceae family contains many agriculturally important crops, including tomato, potato, pepper, and tobacco, as well as other species with potential for agricultural development, such as the orphan crops groundcherry, wolfberry, and pepino. Research progress varies greatly among these species, with model crops like tomato being far ahead. This disparity limits the broader agricultural application of other Solanaceae species. In this study, we constructed an interspecies pan-genome for the Solanaceae family and identified various gene retention patterns. Our findings reveal that the activity of specific transposable elements is closely associated with gene fractionation and transposition. The pan-genome was further resolved at the level of T subgenomes, which were generated by Solanaceae-specific paleo-hexaploidization (T event). We demonstrate substantial gene fractionation (loss) and divergence events following ancient duplications. For example, all class A and E flower model genes in Solanaceae originated from two tandemly duplicated genes, which expanded through the γ and T events before fractionating into 10 genes in tomato, each acquiring distinct functions critical for fruit development. Based on these results, we developed the Solanaceae Pan-Genome Database (SolPGD, http://www.bioinformaticslab.cn/SolPGD), which integrates datasets from both inter- and intra-species pan-genomes of Solanaceae. These findings and resources will facilitate future studies of solanaceous species, including orphan crops.

In summary, PlantEMS is designed to advance plant epigenetics research by providing a comprehensive repository of multi-omics and multi-modification data. This resource enables detailed investigations into the epigenetic regulatory mechanisms underlying essential plant traits and responses, potentially informing innovative strategies for crop management, monitoring, and development.