Combining single-cell RNA-sequencing and bulk data to reveal immunity-related genes expression pattern in the systemic lupus erythematosus and target organ kidney

Background:Systemic lupus erythematosus(SLE)is a complex chronic autoimmune disease with no known cure.However,the regulatory mechanism of immunity-related genes is not fully understood in SLE.In order to explore new therapeutic targets,we used bioinformatical methods to analyze a series of data.Methods:After downloading and processing the data from Gene Expression Omnibus database,the differentially expressed genes of SLE were analyzed.CIBERSORT algorithm was used to analyze the immune infiltration of SLE.Based on single-cell RNA-sequencing data,the role of immune-related genes in SLE and its target organ(kidney)were analyzed.Key transcription factors affecting immune-related genes were identified.Cell-cell communication networks in SLE were analyzed.Results:In total,15 hub genes and 4 transcription factors were found in the bulk data.Monocytes and macrophages in GSE81622(SLE)showed more infiltration.There were four cell types were annotated in scRNA sequencing dataset(GSE135779),as follows T cells,monocyte,NK cells and B cells.Immunity-related genes were overexpressed in monocytes.Conclusion:The present study shows that immune-related genes affect SLE through monocytes and play an important role in target organ renal injury.

Single-cell RNA-sequencing combined with bulk RNA-sequencing analysis of peripheral blood reveals the characteristics and key immune cell genes of ulcerative colitis

BACKGROUND Ulcerative colitis(UC)is a complicated disease caused by the interaction between genetic and environmental factors that affects mucosal homeostasis and triggers an inappropriate immune response.Single-cell RNA sequencing(scRNA-seq)can be used to rapidly obtain the precise gene expression patterns of thousands of cells in the intestine,analyze the characteristics of cells with the same phenotype,and provide new insights into the growth and development of intestinal organs,the clonal evolution of cells,and immune cell changes.These findings can provide new ideas for the diagnosis and treatment of intestinal diseases.To identify clinical phenotypes and biomarkers that can predict the response of UC patients to specific therapeutic drugs and thus aid the diagnosis and treatment of UC.METHODS Using the Gene Expression Omnibus(GEO)database,we analyzed peripheral blood cell subtypes of patients with UC by scRNA-seq combined with bulk RNA sequencing(RNA-seq)to reveal the core genes of UC.We then combined weighted gene correlation network analysis(WGCNA)and least absolute shrinkage and selection operator(LASSO)analysis to reveal diagnostic markers of UC.RESULTS After processing the scRNA-seq data,we obtained data from approximately 24340 cells and identified 17 cell types.Through intercellular communication analysis,we selected monocyte marker genes as the candidate gene set for the prediction model.Construction of a WGCNA coexpression network identified RhoB,cathepsin D(CTSD)and zyxin(ZYX)as core genes.Immune infiltration analysis showed that these three core genes were strongly correlated with immune cells.Functional enrichment analysis showed that the differentially expressed genes were closely related to immune and inflammatory responses,which are associated with many challenges in the diagnosis and treatment of UC.CONCLUSION Through scRNA-seq analysis,LASSO diagnostic model building and WGCNA,we identified RhoB,CTSD and ZYX as core genes of UC that are closely related to monocyte infiltration that may serve as diagnostic markers and molecular targets for UC therapeutic intervention.

Distinct immune escape and microenvironment between RG-like and pri-OPC-like glioma revealed by single-cell RNA-seq analysis

The association of neurogenesis and gliogenesis with glioma remains unclear.By conducting single-cell RNA-seq analyses on 26 gliomas,we reported their classification into primitive oligodendrocyte precursor cell(pri-OPC)-like and radial glia(RG)-like tumors and validated it in a public cohort and TCGA glioma.The RG-like tumors exhibited wild-type isocitrate dehydrogenase and tended to carry EGFR mutations,and the pri-OPC-like ones were prone to carrying TP53 mutations.Tumor subclones only in pri-OPC-like tumors showed substantially down-regulated MHC-I genes,suggesting their distinct immune evasion programs.Furthermore,the two subgroups appeared to extensively modulate glioma-infiltrating lymphocytes in distinct manners.Some specific genes not expressed in normal immune cells were found in glioma-infiltrating lymphocytes.For example,glial/glioma stem cell markers OLIG1/PTPRZ1 and B cell-specific receptors IGLC2/IGKC were expressed in pri-OPC-like and RG-like glioma-infiltrating lymphocytes,respectively.Their expression was positively correlated with those of immune checkpoint genes(e.g.,LGALS33)and poor survivals as validated by the increased expression of LGALS3 upon IGKC overexpression in Jurkat cells.This finding indicated a potential inhibitory role in tumor-infiltrating lymphocytes and could provide a new way of cancer immune evasion.

cKBET:assessing goodness of batch effect correction for single-cell RNA-seq

Single-cell RNA sequencing reveals the gene structure and gene expression status of a single cell,which can reflect the heterogeneity between cells.However,batch effects caused by non-biological factors may hinder data integration and downstream analysis.Although the batch effect can be evaluated by visualizing the data,which actually is subjective and inaccurate.In this work,we propose a quantitative method cKBET,which considers the batch and cell type information simultaneously.The cKBET method accesses batch effects by comparing the global and local fraction of cells of different batches in different cell types.We verify the performance of our cKBET method on simulated and real biological data sets.The experimental results show that our cKBET method is superior to existing methods in most cases.In general,our cKBET method can detect batch effect with either balanced or unbalanced cell types,and thus evaluate batch correction methods.

Single-cell RNA-seq reveals the transcriptional program underlying tumor progression and metastasis in neuroblastoma

Neuroblastoma(NB)is one of the most common childhood malignancies.Sixty percent of patients present with widely disseminated clinical signs at diagnosis and exhibit poor outcomes.However,the molecular mechanisms triggering NB metastasis remain largely uncharacterized.In this study,we generated a transcriptomic atlas of 15447 NB cells from eight NB samples,including paired samples of primary tumors and bone marrow metastases.We used time-resolved analysis to chart the evolutionary trajectory of NB cells from the primary tumor to the metastases in the same patient and identified a common‘starter’subpopulation that initiates tumor development and metastasis.The‘starter’population exhibited high expression levels of multiple cell cycle-related genes,indicating the important role of cell cycle upregulation in NB tumor progression.In addition,our evolutionary trajectory analysis demonstrated the involvement of partial epithelial-to-mesenchymal transition(p-EMT)along the metastatic route from the primary site to the bone marrow.Our study provides insights into the program driving NB metastasis and presents a signature of metastasis-initiating cells as an independent prognostic indicator and potential therapeutic target to inhibit the initiation of NB metastasis.

Comprehensive transcriptional atlas of human adenomyosis deciphered by the integration of single-cell RNA-sequencing and spatial transcriptomics

Adenomyosis is a poorly understood gynecological disorder lacking effective treatments.Controversy persists regarding“invagination”and“metaplasia”theories.The endometrial-myometrial junction(EMJ)connects the endometrium and myometrium and is important for diagnosing and classifying adenomyosis,but its in-depth study is just beginning.Using single-cell RNA sequencing and spatial profiling,we mapped transcriptional alterations across eutopic endometrium,lesions,and EMJ.Within lesions,we identified unique epithelial(LGR5+)and invasive stromal(PKIB+)subpopulations,along with WFDC1+progenitor cells,supporting a complex interplay between“invagination”and“metaplasia”theories of pathogenesis.Further,we observed endothelial cell heterogeneity and abnormal angiogenic signaling involving vascular endothelial growth factor and angiopoietin pathways.Cell-cell communication differed markedly between ectopic and eutopic endometrium,with aberrant signaling in lesions involving pleiotrophin,TWEAK,and WNT cascades.This study reveals unique stem cell-like and invasive cell subpopulations within adenomyosis lesions identified,dysfunctional signaling,and EMJ abnormalities critical to developing precise diagnostic and therapeutic strategies.

SuperFeat:Quantitative Feature Learning from Single-cell RNA-seq Data Facilitates Drug Repurposing

In this study,we devised a computational framework called Supervised Feature Learning and Scoring(SuperFeat)which enables the training of a machine learning model and evaluates the canonical cellular statuses/features in pathological tissues that underlie the progression of disease.This framework also enables the identification of potential drugs that target the presumed detrimental cellular features.This framework was constructed on the basis of an artificial neural network with the gene expression profiles serving as input nodes.The training data comprised single-cell RNA sequencing datasets that encompassed the specific cell lineage during the developmental progression of cell features.A few models of the canonical cancer-involved cellular statuses/features were tested by such framework.Finally,we illustrated the drug repurposing pipeline,utilizing the training parameters derived from the adverse cellular statuses/features,which yielded successful validation results both in vitro and in vivo.SuperFeat is accessible at https://github.com/weilin-genomics/rSuperFeat.

Dissection of molecular mechanisms of liver injury induced by microcystin-leucine arginine via single-cell RNA-sequencing

The occurrence of poisoning incidents caused by cyanobacterial blooms has aroused wide public concern.Microcystin-leucine arginine(MC-LR)is a well-established toxin produced by cyanobacterial blooms,which is widely distributed in eutrophic waters.MC-LR is not only hazardous to the water environment but also exerts multiple toxic effects including liver toxicity in both humans and animals.However,the underlying mechanisms of MCLR-induced liver toxicity are unclear.Herein,we used advanced single-cell RNA sequencing technology to characterize MC-LR-induced liver injury in mice.We established the first single-cell atlas ofmouse livers in response to MC-LR.Our results showed that the differentially expressed genes and pathways in diverse cell types of liver tissues of mice treatedwith MC-LR are highly heterogeneous.Deep analysis showed that MC-LR induced an increase in a subpopulation of hepatocytes that highly express Gstm3,which potentially contributed to hepatocyte apoptosis in response to MC-LR.Moreover,MC-LR increased the proportion and multiple subtypes of Kupffer cells with M1 phenotypes and highly expressed proinflammatory genes.Furthermore,the MC-LR increased several subtypes of CD8+T cells with highly expressed multiple cytokines and chemokines.Overall,apart from directly inducing hepatocytes apoptosis,MC-LR activated proinflammatory Kupffer cell and CD8+T cells,and their interaction may constitute a hostile microenvironment that contributes to liver injury.Our findings not only present novel insight into underlying molecular mechanisms but also provide a valuable resource and foundation for additional discovery of MC-LR-induced liver toxicity.

HCCDB v2.0:Decompose Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma(HCC).Integrated 15 transcriptomic datasets of HCC clinical samples,the first version of HCC database(HCCDB v1.0)was released in 2018.Through the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets,it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness.With four years having passed,the database now needs integration of recently published datasets.Furthermore,the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial architecture.Here,we present HCCDB v2.0,an updated version that combines bulk,single-cell,and spatial transcriptomic data of HCC clinical samples.It dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples,thereby enhancing the reliability of transcriptomic meta-analysis.A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections,respectively.A novel single-cell level and 2-dimension(sc-2D)metric is proposed as well to summarize cell type-specific and dysregulated gene expression patterns.Results are all graphically visualized in our online portal,allowing users to easily retrieve data through a user-friendly interface and navigate between different views.With extensive clinical phenotypes and transcriptomic data in the database,we show two applications for identifying prognosis-associated cells and tumor microenvironment.HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

Single-cell profiling of the pig cecum at various developmental stages

The gastrointestinal tract is essential for food digestion,nutrient absorption,waste elimination,and microbial defense.Single-cell transcriptome profiling of the intestinal tract has greatly enriched our understanding of cellular diversity,functional heterogeneity,and their importance in intestinal tract development and disease.Although such profiling has been extensively conducted in humans and mice,the single-cell gene expression landscape of the pig cecum remains unexplored.Here,single-cell RNA sequencing was performed on 45572 cells obtained from seven cecal samples in pigs at four different developmental stages(days(D)30,42,150,and 730).Analysis revealed 12 major cell types and 38 subtypes,as well as their distinctive genes,transcription factors,and regulons,many of which were conserved in humans.An increase in the relative proportions of CD8^(+)T and Granzyme A(low expression)natural killer T cells(GZMA^(low)NKT)cells and a decrease in the relative proportions of epithelial stem cells,Tregs,RHEX^(+)T cells,and plasmacytoid dendritic cells(pDCs)were noted across the developmental stages.Moreover,the post-weaning period exhibited an up-regulation in mitochondrial genes,COX2 and ND2,as well as genes involved in immune activation in multiple cell types.Cell-cell crosstalk analysis indicated that IBP6^(+)fibroblasts were the main signal senders at D30,whereas IBP6^(−)fibroblasts assumed this role at the other stages.NKT cells established interactions with epithelial cells and IBP6^(+)fibroblasts in the D730 cecum through mediation of GZMA-F2RL1/F2RL2 pairs.This study provides valuable insights into cellular heterogeneity and function in the pig cecum at different development stages.

Single-cell RNA-Seq reveals transcriptional regulatory networks directing the development of mouse maxillary prominence

During vertebrate embryonic development,neural crest-derived ectomesenchyme within the maxillary prominences undergoes precisely coordinated proliferation and differentiation to give rise to diverse craniofacial structures,such as tooth and palate.However,the transcriptional regulatory networks underpinning such an intricate process have not been fully elucidated.Here,we perform single-cell RNA-Seq to comprehensively characterize the transcriptional dynamics during mouse maxillary development from embryonic day(E)10.5eE14.5.Our single-cell transcriptome atlas of~28,000 cells uncovers mesenchymal cell populations representing distinct differentiating states and reveals their developmental trajectory,suggesting that the segregation of dental from the palatal mesenchyme occurs at E11.5.Moreover,we identify a series of key transcription factors(TFs)associated with mesenchymal fate transitions and deduce the gene regulatory networks directed by these TFs.Collectively,our study provides important resources and insights for achieving a systems-level understanding of craniofacial morphogenesis and abnormality.

Single-cell RNA-seq and bulk-seq identify RAB17 as a potential regulator of angiogenesis by human dermal microvascular endothelial cells in diabetic foot ulcers

Background:Angiogenesis is crucial in diabetic wound healing and is often impaired in diabetic foot ulcers(DFUs).Human dermal microvascular endothelial cells(HDMECs)are vital components in dermal angiogenesis;however,their functional and transcriptomic characteristics in DFU patients are not well understood.This study aimed to comprehensively analyse HDMECs from DFU patients and healthy controls and find the potential regulator of angiogenesis in DFUs.Methods:HDMECs were isolated from skin specimens of DFU patients and healthy controls via magnetic-activated cell sorting.The proliferation,migration and tube-formation abilities of the cells were then compared between the experimental groups.Both bulk RNA sequencing(bulk-seq)and single-cell RNA-seq(scRNA-seq)were used to identify RAB17 as a potential marker of angiogenesis,which was further confirmed via weighted gene co-expression network analysis(WGCNA)and least absolute shrink and selection operator(LASSO)regression.The role of RAB17 in angiogenesis was examined through in vitro and in vivo experiments.Results:The isolated HDMECs displayed typical markers of endothelial cells.HDMECs isolated from DFU patients showed considerably impaired tube formation,rather than proliferation or migration,compared to those from healthy controls.Gene set enrichment analysis(GSEA),fGSEA,and gene set variation analysis(GSVA)of bulk-seq and scRNA-seq indicated that angiogenesis was downregulated in DFU-HDMECs.LASSO regression identified two genes,RAB17 and CD200,as characteristic of DFU-HDMECs;additionally,the expression of RAB17 was found to be significantly reduced in DFU-HDMECs compared to that in the HDMECs of healthy controls.Overexpression of RAB17 was found to enhance angiogenesis,the expression of hypoxia inducible factor-1α and vascular endothelial growth factor A,and diabetic wound healing,partially through the mitogen-activated protein kinase/extracellular signal-regulated kinase signalling pathway.Conclusions:Our findings suggest that the impaired angiogenic capacity in DFUs may be related to the dysregulated expression of RAB17 in HDMECs.The identification of RAB17 as a potential molecular target provides a potential avenue for the treatment of impaired angiogenesis in DFUs.

Single-cell RNA-seq of Lotus japonicus provide insights into identification and function of root cell types of legume

The roots of legume plant play a crucial role in nitrogen fixation. However, the transcriptomes of different cell types of legume root and their functions remain largely unknown. Here, we performed single-cell RNA sequencing and profiled more than 22,000 single cells from root tips of Lotus japonicus, a model species of legume.We identified seven clusters corresponding to seven major cell types, which were validated by in situ hybridization. Further analysis revealed regulatory programs including phytohormone and nodulation associated with specific cell types, and revealed conserved and diverged features for the cell types. Our results represent the first single-cell resolution transcriptome for legume root tips and a valuable resource for studying the developmental and physiological functions of various cell types in legumes.

Distortion-free PCA on sample space for highly variable gene detection from single-cell RNA-seq data

Single-cell RNA-seq (scRNA-seq) allows the analysis of gene expression in each cell, which enables the detection of highly variable genes (HVG) that contribute to cell-to-cell variation within a homogeneous cell population. HVG detection is necessary for clustering analysis to improve the clustering result. scRNA-seq includes some genes that are expressed with a certain probability in all cells which make the cells indistinguishable. These genes are referred to as background noise. To remove the background noise and select the informative genes for clustering analysis, in this paper, we propose an effective HVG detection method based on principal component analysis (PCA). The proposed method utilizes PCA to evaluate the genes (features) on the sample space. The distortion-free principal components are selected to calculate the distance from the origin to gene as the weight of each gene. The genes that have the greatest distances to the origin are selected for clustering analysis. Experimental results on both synthetic and gene expression datasets show that the proposed method not only removes the background noise to select the informative genes for clustering analysis, but also outperforms the existing HVG detection methods.

Single-cell transcriptomic atlas of goat ovarian aging

Background The ovaries are one of the first organs that undergo degenerative changes earlier in the aging process,and ovarian aging is shown by a decrease in the number and quality of oocytes.However,little is known about the molecular mechanisms of female age-related fertility decline in different types of ovarian cells during aging,especially in goats.Therefore,the aim of this study was to reveal the mechanisms driving ovarian aging in goats at single-cell resolution.Results For the first time,we surveyed the single-cell transcriptomic landscape of over 27,000 ovarian cells from newborn,young and aging goats,and identified nine ovarian cell types with distinct gene-expression signatures.Functional enrichment analysis showed that ovarian cell types were involved in their own unique biological processes,such as Wnt beta-catenin signalling was enriched in germ cells,whereas ovarian steroidogenesis was enriched in granulosa cells(GCs).Further analysis showed that ovarian aging was linked to GCs-specific changes in the antioxidant system,oxidative phosphorylation,and apoptosis.Subsequently,we identified a series of dynamic genes,such as AMH,CRABP2,THBS1 and TIMP1,which determined the fate of GCs.Additionally,FOXO1,SOX4,and HIF1A were identified as significant regulons that instructed the differentiation of GCs in a distinct manner during ovarian aging.Conclusions This study revealed a comprehensive aging-associated transcriptomic atlas characterizing the cell typespecific mechanisms during ovarian aging at the single-cell level and offers new diagnostic biomarkers and potential therapeutic targets for age-related goat ovarian diseases.

Identification and validation of a pyroptosis-related prognostic model for colorectal cancer based on bulk and single-cell RNA sequencing data

BACKGROUND Pyroptosis impacts the development of malignant tumors,yet its role in colorectal cancer(CRC)prognosis remains uncertain.AIM To assess the prognostic significance of pyroptosis-related genes and their association with CRC immune infiltration.METHODS Gene expression data were obtained from The Cancer Genome Atlas(TCGA)and single-cell RNA sequencing dataset GSE178341 from the Gene Expression Omnibus(GEO).Pyroptosis-related gene expression in cell clusters was analyzed,and enrichment analysis was conducted.A pyroptosis-related risk model was developed using the LASSO regression algorithm,with prediction accuracy assessed through K-M and receiver operating characteristic analyses.A nomo-gram predicting survival was created,and the correlation between the risk model and immune infiltration was analyzed using CIBERSORTx calculations.Finally,the differential expression of the 8 prognostic genes between CRC and normal samples was verified by analyzing TCGA-COADREAD data from the UCSC database.RESULTS An effective pyroptosis-related risk model was constructed using 8 genes-CHMP2B,SDHB,BST2,UBE2D2,GJA1,AIM2,PDCD6IP,and SEZ6L2(P<0.05).Seven of these genes exhibited differential expression between CRC and normal samples based on TCGA database analysis(P<0.05).Patients with higher risk scores demonstrated increased death risk and reduced overall survival(P<0.05).Significant differences in immune infiltration were observed between low-and high-risk groups,correlating with pyroptosis-related gene expression.CONCLUSION We developed a pyroptosis-related prognostic model for CRC,affirming its correlation with immune infiltration.This model may prove useful for CRC prognostic evaluation.

The early life immune dynamics and cellular drivers at single-cell resolution in lamb forestomachs and abomasum

Background Four-chambered stomach including the forestomachs(rumen,reticulum,and omasum)and abomasum allows ruminants convert plant fiber into high-quality animal products.The early development of this four-chambered stomach is crucial for the health and well-being of young ruminants,especially the immune development.However,the dynamics of immune development are poorly understood.Results We investigated the early gene expression patterns across the four-chambered stomach in Hu sheep,at 5,10,15,and 25 days of age.We found that forestomachs share similar gene expression patterns,all four stomachs underwent widespread activation of both innate and adaptive immune responses from d 5 to 25,whereas the metabolic function were significantly downregulated with age.We constructed a cell landscape of the four-chambered stomach using single-cell sequencing.Integrating transcriptomic and single-cell transcriptomic analyses revealed that the immune-associated module hub genes were highly expressed in T cells,monocytes and macrophages,as well as the defense-associated module hub genes were highly expressed in endothelial cells in the four-stomach tissues.Moreover,the non-immune cells such as epithelial cells play key roles in immune maturation.Cell communication analysis predicted that in addition to immune cells,non-immune cells recruit immune cells through macrophage migration inhibitory factor signaling in the forestomachs.Conclusions Our results demonstrate that the immune and defense responses of four stomachs are quickly developing with age in lamb's early life.We also identified the gene expression patterns and functional cells associated with immune development.Additionally,we identified some key receptors and signaling involved in immune regulation.These results help to understand the early life immune development at single-cell resolution,which has implications to develop nutritional manipulation and health management strategies based on specific targets including key receptors and signaling pathways.

Single-cell transcriptome sequencing reveals the mechanism regulating rice plumule development

Seed plumules comprise multiple developing tissues and are key sites for above-ground plant organ morphogenesis.Here,the spatial expression of genes in developing rice seed plumules was characterized by single-cell transcriptome sequencing in Zhongjiazao 17,a popular Chinese indica rice cultivar.Of 15 cell clusters,13 were assigned to cell types using marker genes and cluster-specific genes.Marker genes of multiple cell types were expressed in several clusters,suggesting a complex developmental system.Some genes for signaling by phytohormones such as abscisic acid were highly expressed in specific clusters.Various cis-elements in the promoters of genes specifically expressed in cell clusters were calculated,and some key hormone-related motifs were frequent in certain clusters.Spatial expression patterns of genes involved in rapid seed germination,seedling growth,and development were identified.These findings enhanced our understanding of cellular diversity and specialization within plumules of rice,a monocotyledonous model crop.

Single-cell and spatial omics:exploring hypothalamic heterogeneity

Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.

Applications of single-cell RNA sequencing in spermatogenesis and molecular evolution

Spermatogenic cell heterogeneity is determined by the complex process of spermatogenesis differentiation.However,effectively revealing the regulatory mechanisms underlying mammalian spermatogenic cell development and differentiation via traditional methods is difficult.Advances in technology have led to the emergence of many single-cell transcriptome sequencing protocols,which have partially addressed these challenges.In this review,we detail the principles of 10x Genomics technology and summarize the methods for downstream analysis of single-cell transcriptome sequencing data.Furthermore,we explore the role of single-cell transcriptome sequencing in revealing the heterogeneity of testicular ecological niche cells,delineating the establishment and disruption of testicular immune homeostasis during human spermatogenesis,investigating abnormal spermatogenesis in humans,and,ultimately,elucidating the molecular evolution of mammalian spermatogenesis.