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Background Chinese cabbage (Brassica rapa ssp. pekinensis) experienced a whole-genome triplication event and thus has three subgenomes: least fractioned, medium fractioned, and most fractioned subgenome. Environmental changes affect leaf development, which in turn influence the yield. To improve the yield and resistance to different climate scenarios, a comprehensive understanding of leaf development is required including insights into the full diversity of cell types and transcriptional networks underlying their specificity. Results Here, we generate the transcriptional landscape of Chinese cabbage leaf at single-cell resolution by performing single-cell RNA sequencing of 30,000 individual cells. We characterize seven major cell types with 19 transcriptionally distinct cell clusters based on the expression of the reported marker genes. We find that genes in the least fractioned subgenome are predominantly expressed compared with those in the medium and most fractioned subgenomes in different cell types. Moreover, we generate a single-cell transcriptional map of leaves in response to high temperature. We find that heat stress not only affects gene expression in a cell type-specific manner but also impacts subgenome dominance. Conclusions Our study highlights the transcriptional networks in different cell types and provides a better understanding of transcriptional regulation during leaf development and transcriptional response to heat stress in Chinese cabbage.

The TIR1/AFB family of proteins is a group of functionally diverse auxin receptors that are only found in plants. TIR1/AFB family members are characterized by a conserved N-terminal F-box domain followed by 18 leucine-rich repeats. In the past few decades, extensive research has been conducted on the role of these proteins in regulating plant development, metabolism, and responses to abiotic and biotic stress. In this review, we focus on TIR1/AFB proteins that play crucial roles in plant responses to diverse abiotic and biotic stress. We highlight studies that have shed light on the mechanisms by which TIR1/AFB proteins are regulated at the transcriptional and post-transcriptional as well as the downstream in abiotic or biotic stress pathways regulated by the TIR1/AFB family.

Properly regulated flowering time is pivotal for successful plant reproduction. The floral transition from vegetative growth to reproductive growth is regulated by a complex gene regulatory network that integrates environmental signals and internal conditions to ensure that flowering takes place under favorable conditions. Brassica rapa is a diploid Cruciferae species that includes several varieties that are cultivated as vegetable or oil crops. Flowering time is one of the most important agricultural traits of B. rapa crops because of its influence on yield and quality. The transition to flowering in B. rapa is regulated by several environmental and developmental cues, which are perceived by several signaling pathways, including the vernalization pathway, the autonomous pathway, the circadian clock, the thermosensory pathway, and gibberellin (GA) signaling. These signals are integrated to control the expression of floral integrators BrFTs and BrSOC1s to regulate flowering. In this review, we summarized current research advances on the molecular mechanisms that govern flowering time regulation in B. rapa and compare this to what is known in Arabidopsis.

Verticillium wilt is characterized by chlorosis in leaves and is a devastating disease in eggplant. Early diagnosis, prior to the manifestation of symptoms, enables targeted management of the disease. In this study, we aim to detect early leaf wilt in eggplant leaves caused by Verticillium dahliae by integrating multispectral imaging with machine learning and deep learning techniques. Multispectral and chlorophyll fluorescence images were collected from leaves of the inbred eggplant line 11-435, including data on image texture, spectral reflectance, and chlorophyll fluorescence. Subsequently, we established a multispectral data model, fusion information model, and multispectral image–information fusion model. The multispectral image–information fusion model, integrated with a two-dimensional convolutional neural network (2D-CNN), demonstrated optimal performance in classifying early-stage Verticillium wilt infection, achieving a test accuracy of 99.37%. Additionally, transfer learning enabled us to diagnose early leaf wilt in another eggplant variety, the inbred line 14-345, with an accuracy of 84.54 ± 1.82%. Compared to traditional methods that rely on visible symptom observation and typically require about 10 days to confirm infection, this study achieved early detection of Verticillium wilt as soon as the third day post-inoculation. These findings underscore the potential of the fusion model as a valuable tool for the early detection of pre-symptomatic states in infected plants, thereby offering theoretical support for in-field detection of eggplant health.

Heat shock proteins protect plants from abiotic stress, such as salt, drought, heat, and cold stress. HSP70 is one of the major members of the heat shock protein family. To explore the mechanism of HSP70 in Brassica rapa, we identified 28 putative HSP70 gene family members using state-of-the-art bioinformatics-based tools and methods. Based on chromosomal mapping, HSP70 genes were the most differentially distributed on chromosome A03 and the least distributed on chromosome A05. Ka/Ks analysis revealed that B. rapa evolution was subjected to intense purifying selection of the HSP70 gene family. RNA-sequencing data and expression profiling showed that heat and cold stress induced HSP70 genes. The qRT-PCR results verified that the HSP70 genes in Chinese cabbage (Brassica rapa ssp. pekinensis) are stress-inducible under both cold and heat stress. The upregulated expression pattern of these genes indicated the potential of HSP70 to mitigate environmental stress. These findings further explain the molecular mechanism underlying the responses of HSP70 to heat and cold stress.

Clubroot, caused by Plasmodiophora brassicae, is a destructive disease of Chinese cabbage (Brassica rapa ssp. pekinensis) at all growing stages. Early detection of the disease is essential to mitigate the impact of clubroot. Here, we established an optimal algorithm for multispectral imaging combined with machine learning to detect leaf responses of highly susceptible cultivar YoulvNo.3 at different day after inoculation (DAI). Spectral data at 19 wavelengths were collected from leaf multispectral images, and key characteristic wavelengths were further extracted. Principal Component Analysis (PCA) revealed a clear separation between healthy and infected samples at 11 DAI. Four classification algorithms, including Random Forest (RF), Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM) and Extreme Learning Machine (ELM), were employed to construct early detection model for clubroot. SVM achieved over 81% accuracy with full-spectrum data, while ELM based on characteristic wavelengths provided the best performance, accuracy exceeding 84%. Stratified five-fold cross-validation was used to validate the optimal model. An average accuracy of 83.79% (±1.04%) and macro-averaged F1-score of 82.13% (±1.12%) across validation folds were obtained, confirming stable performance. Our findings, for the first time, identified detectable spectral differences between the healthy and infected plants at 11 DAI using leaf multispectral combined with machine learning, providing a potential application for early detection of clubroot and timely control in Chinese cabbage.

Chinese cabbage (Brassica rapa ssp. pekinensis) has a long cultivation history and is one of the vegetable crops with the largest cultivation area in China. However, salt stress severely damages photosynthesis and hormone metabolism, nutritional balances, and results in ion toxicity in plants. To better understand the mechanisms of salt-induced growth inhibition in Chinese cabbage, RNA-seq and physiological index determination were conducted to explore the impacts of salt stress on carbon cycle metabolism and photosynthesis in Chinese cabbage. Here, we found that the number of thylakoids and grana lamellae and the content of starch granules and chlorophyll in the leaves of Chinese cabbage under salt stress showed a time-dependent response, first increasing and then decreasing. Chinese cabbage increased the transcript levels of genes related to the photosynthetic apparatus and carbon metabolism under salt stress, probably in an attempt to alleviate damage to the photosynthetic system and enhance CO2 fixation and energy metabolism. The transcription of genes related to starch and sucrose synthesis and degradation were also enhanced; this might have been an attempt to maintain intracellular osmotic pressure by increasing soluble sugar concentrations. Soluble sugars could also be used as potential reactive oxygen species (ROS) scavengers, in concert with peroxidase (POD) enzymes, to eliminate ROS that accumulate during metabolic processes. Our study characterizes the synergistic response network of carbon metabolism and photosynthesis under salt stress.

Pectobacterium carotovorum ssp. carotovorum ( Pcc ) is a necrotrophic bacterial species that causes soft rot disease in Chinese cabbage. In this study, plants harboring the resistant mutant sr gene, which confers resistance against Pcc , were screened from an 800 M 2 population mutated by ethyl methane sulfonate (EMS) and scored in vitro and in vivo for lesion size. The transcript profiles showed ~512 differentially expressed genes (DEGs) between sr and WT plants occurring between 6 and 12 h postinoculation (hpi), which corresponded to the important defense regulation period (resistance) to Pcc in Chinese cabbage. The downstream defense genes ( CPK , CML , RBOH MPK3 , and MPK4 ) of pathogen pattern-triggered immunity (PTI) were strongly activated during infection at 12 hpi in resistant mutant sr ; PTI appears to be central to plant defense against Pcc via recognition by three putative pattern recognition receptors (PRRs; BrLYM1-BrCERK1, BrBKK1/SERK4-PEPR1, BrWAKs). Pcc triggered the upregulation of the jasmonic acid (JA) and ethylene (ET) biosynthesis genes in mutant sr , but auxins and other hormones may have affected some negative signals. Endogenous hormones (auxins, JAs, and SA), as well as exogenous auxins (MEJA and BTH), were also verified as functioning in the immune system. Concurrently, the expression of glucosinolate and lignin biosynthesis genes was increased at 12 hpi in resistant mutant sr , and the accumulation of glucosinolate and lignin also indicated that these genes have a functional defensive role against Pcc . Our study provides valuable information and elucidates the resistance mechanism of Chinese cabbage against Pcc infection.

Eggplant ( Solanum melongena L.) is a highly nutritious and economically important vegetable crop. However, the fruit peel of eggplant often shows poor coloration owing to low-light intensity during cultivation, especially in the winter. The less-photosensitive varieties produce anthocyanin in low light or even dark conditions, making them valuable breeding materials. Nevertheless, genes responsible for anthocyanin biosynthesis in less-photosensitive eggplant varieties are not characterized. In this study, an EMS mutant, named purple in the dark ( pind ), was used to identify the key genes responsible for less-photosensitive coloration. Under natural conditions, the peel color and anthocyanin content in pind fruits were similar to that of wildtype ‘14-345’. The bagged pind fruits were light purple, whereas those of ‘14-345’ were white; and the anthocyanin content in the pind fruit peel was significantly higher than that in ‘14-345’. Genetic analysis revealed that the less-photosensitive trait was controlled by a single dominant gene. The candidate gene was mapped on chromosome 10 in the region 7.72 Mb to 11.71 Mb. Thirty-five differentially expressed genes, including 12 structural genes, such as CHS , CHI , F3H , DFR , ANS , and UFGT , and three transcription factors MYB113 , GL3 , and TTG2 , were identified in pind using RNA-seq. Four candidate genes EGP21875 (myb domain protein 113), EGP21950 (unknown protein), EGP21953 (CAAX amino-terminal protease family protein), and EGP21961 (CAAX amino-terminal protease family protein) were identified as putative genes associated with less-photosensitive anthocyanin biosynthesis in pind . These findings may clarify the molecular mechanisms underlying less-photosensitive anthocyanin biosynthesis in eggplant.