Cotton(Gossypium hirsutum)is one of the important economic crops in China,and the selection and application of new varieties are crucial for the development of the cotton industry.However,the breeding of new cotton varieties in China has been slow due to the lack of excellent germplasm resources with desirable traits,and the in-depth research on high yield,new anti-insect and anti-disease characteristics,etc.Therefore,it is essential to search for new stress-resistant genes to improve the international competitiveness of China’s cotton industry.In addition,the pigment gland is the main source of cotton secondary metabolites,but the molecular mechanism of its development is still unclear.In order to better understand the developmental mechanism of cotton gland cells,single-cell transcriptome sequencing technology was used to analyze different cell populations in the cotyledon glands of cotton.By analyzing differentially expressed genes,clustering analysis,cell subtype identification,and cell developmental trajectory reconstruction,the developmental mechanism of cotton glands was thoroughly investigated.The aim of this study was to investigate the specific development of cotton glands and screen differentially expressed genes by performing single-cell RNA sequencing on tissue samples obtained from cottonseed leaves.To achieve this goal,fresh cottonseed leaf tissue samples were collected and single-cell suspensions were prepared.Over ten thousand cells were then subjected to sc RNA-seq sequencing using the 10 x Genomics platform.High-throughput analysis of single-cell transcriptome data required the use of dimensionality reduction techniques to classify and visualize cell populations.In this study,principal component analysis(PCA),a commonly used linear dimensionality reduction technique,was employed to reduce the high-dimensional gene expression matrix to a low-dimensional principal component space.In addition to PCA,nonlinear dimensionality reduction techniques such as t SNE and UMAP were used for secondary dimensionality reduction and visualization to further illustrate differences and clustering patterns among cell populations.To analyze the differences in gene expression between cell populations,the Seurat package was used for marker gene identification.The Find All Markers function was utilized to identify marker genes for each cell population and to screen for differentially expressed genes that were significantly expressed across different samples.Furthermore,Monocle was used for pseudotime analysis to depict the dynamic trajectory of internal cell differentiation in cotton.GO enrichment analysis was employed to demonstrate significantly enriched functions and processes in the gene set of the 11 th cell population of Zhong 12.A co-expression network of differentially expressed genes in gland cell populations was constructed,and candidate genes affecting gland development were identified.Finally,q PCR and in situ hybridization were used to verify the expression of the relevant candidate genes.In this study,cotton cotyledons were used as materials.The results showed that a total of 16,434 and 11,783 cells were identified through single-cell sequencing analysis in Zhong12 and Ying 12 cotton varieties,respectively,providing a better understanding of cotton cells.We identified 11 cell clusters in Zhong 12,which is two more than in Ying 12.The11 th cell cluster is closely related to the 7th cluster(epidermis)and both clusters show consistent gene expression.However,the identity of the 11 th cluster requires further identification.By analyzing the expression levels of known glandular genes,we found that glandular genes are highly expressed in the 11 th cell cluster of Zhong 12,indicating it is a glandular cell group.These results provide a valuable foundation for further exploration of the types and functions of cotton cells.Further pseudotime analysis revealed that glandular cells in Zhong 12 develop and express in the mid-to-late stage,and the epidermal cell cluster also exhibits high expression during the same period.To identify potential glandular genes associated with Go PGF,we performed co-expression analysis and screened for candidate genes in Zhong 12.GO enrichment analysis identified the terpenoid metabolic process pathway as being related to glandular development.The transcription factor protein interaction network indicated that the b ZIP family may play an important role in cotton glandular growth and development.Subsequently,12 representative genes were selected and validated using q PCR,confirming their role in glandular development.In addition,two representative genes,Go PGF and Gh ERF102,were selected for in situ hybridization verification,and the results showed high specificity in glandular tissue expression for both genes.These candidate glandular genes play an important biological function in glandular development,providing a foundation for further investigation of the types and functions of cotton cells.This study comprehensively analyszed the developmental processes of two cotton materials(Zhong 12 and Ying 12)using single-cell transcriptome analysis.We established a model for the development of glandular cells and identified cell types and new marker genes in cotton cotyledons,providing a theoretical basis for revealing the glandular development mechanism and screening glandular candidate genes.Through this study,we not only gained insight into the dynamic process of glandular cell development but also provided theoretical support for cotton breeding and improvement.In summary,this study provides new ideas and methods for the field of cotton glandular development and has significant scientific significance and application value. |