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.

Single-cell RNA sequencing facilitates the elucidation of the complete biosynthesis of the antidepressant hyperforin in St. John's wort

Hyperforin is the compound responsible for the effectiveness of St.John's wort(Hypericum perforatum)as an antidepressant,but its complete biosynthetic pathway remains unknown.Gene discovery based on co-expression analysis of bulk RNA-sequencing data or genome mining failed to discover the missing steps in hyperforin biosynthesis.In this study,we sequenced the 1.54-Gb tetraploid H.perforatum genome assem-bled into 32 chromosomes with the scaffold N50 value of 42.44 Mb.By single-cell RNA sequencing,we iden-tified a type of cell,“Hyper cells”,wherein hyperforin biosynthesis de novo takes place in both the leaves and flowers.Through pathway reconstitution in yeast and tobacco,we identified and characterized four transmembrane prenyltransferases(HpPT1-4)that are localized at the plastid envelope and complete the hyperforin biosynthetic pathway.The hyperforin polycyclic scaffold is created by a reaction cascade involving an irregular isoprenoid coupling and a tandem cyclization.Our findings reveal how and where hy-perforin is biosynthesized,enabling synthetic-biology reconstitution of the complete pathway.Thus,this study not only deepens our comprehension of specialized metabolism at the cellularlevel but also provides strategic guidance for elucidation of the biosynthetic pathways of other specializied metabolites in plants.

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.

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.

Food nutrition and toxicology targeting on specific organs in the era of single-cell sequencing

Due to the complex natures of dietary food components,it is difficult to elucidate how the compounds affect host health.Dietary food often selectively presents its mechanism of action on different cell types,and participates in the modulation of targeted cells and their microenvironments within organs.However,the limitations of traditional in vitro assays or in vivo animal experiments cannot comprehensively examine cellular heterogeneity and the tissue-biased influences.Single-cell RNA sequencing(sc RNA-seq)has emerged as an indispensable methodology to decompose tissues into different cell types for the demonstration of transcriptional profiles of individual cells.Sc RNA-seq applications has been summarized on three typical organs(brain,liver,kidney),and two representative immune-and tumor related health problems.The everincreasing role of sc RNA-seq in dietary food research with further improvement can provide sub-cellular information and the coupling between other cellular modalities.In this review,we propose utilizing sc RNAseq to more effectively capture the subtle and complex effects of food chemicals,and how they may lead to health problems at single-cell resolution.This novel technique will be valuable to elucidate the underlying mechanism of both the health benefits of food nutrients and the detrimental consequences food toxicants at the cellular level.

Single-cell sequencing technology in diabetic wound healing:New insights into the progenitors-based repair strategies

Diabetes mellitus(DM),an increasingly prevalent chronic metabolic disease,is characterised by prolonged hyperglycaemia,which leads to long-term health consequences.Although much effort has been put into understanding the pathogenesis of diabetic wounds,the underlying mechanisms remain unclear.The advent of single-cell RNA sequencing(scRNAseq)has revolutionised biological research by enabling the identification of novel cell types,the discovery of cellular markers,the analysis of gene expression patterns and the prediction of develop-mental trajectories.This powerful tool allows for an in-depth exploration of pathogenesis at the cellular and molecular levels.In this editorial,we focus on progenitor-based repair strategies for diabetic wound healing as revealed by scRNAseq and highlight the biological behaviour of various healing-related cells and the alteration of signalling pathways in the process of diabetic wound healing.ScRNAseq could not only deepen our understanding of the complex biology of diabetic wounds but also identify and validate new targets for inter-vention,offering hope for improved patient outcomes in the management of this challenging complication of DM.

Single-cell RNA sequencing analysis of the retina under acute high intraocular pressure

High intraocular pressure causes retinal ganglion cell injury in primary and secondary glaucoma diseases,yet the molecular landscape characteristics of retinal cells under high intraocular pressure remain unknown.Rat models of acute hypertension ocular pressure were established by injection of cross-linked hyaluronic acid hydrogel(Healaflow■).Single-cell RNA sequencing was then used to describe the cellular composition and molecular profile of the retina following high intraocular pressure.Our results identified a total of 12 cell types,namely retinal pigment epithelial cells,rod-photoreceptor cells,bipolar cells,Müller cells,microglia,cone-photoreceptor cells,retinal ganglion cells,endothelial cells,retinal progenitor cells,oligodendrocytes,pericytes,and fibroblasts.The single-cell RNA sequencing analysis of the retina under acute high intraocular pressure revealed obvious changes in the proportions of various retinal cells,with ganglion cells decreased by 23%.Hematoxylin and eosin staining and TUNEL staining confirmed the damage to retinal ganglion cells under high intraocular pressure.We extracted data from retinal ganglion cells and analyzed the retinal ganglion cell cluster with the most distinct expression.We found upregulation of the B3gat2 gene,which is associated with neuronal migration and adhesion,and downregulation of the Tsc22d gene,which participates in inhibition of inflammation.This study is the first to reveal molecular changes and intercellular interactions in the retina under high intraocular pressure.These data contribute to understanding of the molecular mechanism of retinal injury induced by high intraocular pressure and will benefit the development of novel therapies.

Action of circulating and infiltrating B cells in the immune microenvironment of colorectal cancer by single-cell sequencing analysis

BACKGROUND The complexity of the immune microenvironment has an impact on the treatment of colorectal cancer(CRC),one of the most prevalent malignancies worldwide.In this study,multi-omics and single-cell sequencing techniques were used to investigate the mechanism of action of circulating and infiltrating B cells in CRC.By revealing the heterogeneity and functional differences of B cells in cancer immunity,we aim to deepen our understanding of immune regulation and provide a scientific basis for the development of more effective cancer treatment strategies.AIM To explore the role of circulating and infiltrating B cell subsets in the immune microenvironment of CRC,explore the potential driving mechanism of B cell development,analyze the interaction between B cells and other immune cells in the immune microenvironment and the functions of communication molecules,and search for possible regulatory pathways to promote the anti-tumor effects of B cells.METHODS A total of 69 paracancer(normal),tumor and peripheral blood samples were collected from 23 patients with CRC from The Cancer Genome Atlas database(https://portal.gdc.cancer.gov/).After the immune cells were sorted by multicolor flow cytometry,the single cell transcriptome and B cell receptor group library were sequenced using the 10X Genomics platform,and the data were analyzed using bioinformatics tools such as Seurat.The differences in the number and function of B cell infiltration between tumor and normal tissue,the interaction between B cell subsets and T cells and myeloid cell subsets,and the transcription factor regulatory network of B cell subsets were explored and analyzed.RESULTS Compared with normal tissue,the infiltrating number of CD20+B cell subsets in tumor tissue increased significantly.Among them,germinal center B cells(GCB)played the most prominent role,with positive clone expansion and heavy chain mutation level increasing,and the trend of differentiation into memory B cells increased.However,the number of plasma cells in the tumor microenvironment decreased significantly,and the plasma cells secreting IgA antibodies decreased most obviously.In addition,compared with the immune microenvironment of normal tissues,GCB cells in tumor tissues became more closely connected with other immune cells such as T cells,and communication molecules that positively regulate immune function were significantly enriched.CONCLUSION The role of GCB in CRC tumor microenvironment is greatly enhanced,and its affinity to tumor antigen is enhanced by its significantly increased heavy chain mutation level.Meanwhile,GCB has enhanced its association with immune cells in the microenvironment,which plays a positive anti-tumor effect.

Recent developments in application of single-cell RNA sequencing in the tumour immune microenvironment and cancer therapy

The advent of single-cell RNA sequencing(scRNA-seq)has provided insight into the tumour immune microenvironment(TIME).This review focuses on the application of scRNA-seq in investigation of the TIME.Over time,scRNA-seq methods have evolved,and components of the TIME have been deciphered with high resolution.In this review,we first introduced the principle of scRNA-seq and compared different sequencing approaches.Novel cell types in the TIME,a continuous transitional state,and mutual intercommunication among TIME components present potential targets for prognosis prediction and treatment in cancer.Thus,we concluded novel cell clusters of cancerassociated fibroblasts(CAFs),T cells,tumour-associated macrophages(TAMs)and dendritic cells(DCs)discovered after the application of scRNA-seq in TIME.We also proposed the development of TAMs and exhausted T cells,as well as the possible targets to interrupt the process.In addition,the therapeutic interventions based on cellular interactions in TIME were also summarized.For decades,quantification of the TIME components has been adopted in clinical practice to predict patient survival and response to therapy and is expected to play an important role in the precise treatment of cancer.Summarizing the current findings,we believe that advances in technology and wide application of single-cell analysis can lead to the discovery of novel perspectives on cancer therapy,which can subsequently be implemented in the clinic.Finally,we propose some future directions in the field of TIME studies that can be aided by scRNA-seq technology.

Application of single-cell RNA sequencing in head and neck squamous cell carcinoma

Single-cell RNA sequencing has been broadly applied to head and neck squamous cell carcinoma(HNSCC) for characterizing the heterogeneity and genomic mutations of HNSCC benefiting from the advantage of single-cell resolution. We summarized most of the current studies and aimed to explore their research methods and ideas, as well as how to transform them into clinical applications. Through single-cell RNA sequencing, we found the differences in tumor cells’ expression programs and differentiation tracks. The studies of immune microenvironment allowed us to distinguish immune cell subpopulations, the extensive expression of immune checkpoints, and the complex crosstalk network between immune cells and non-immune cells. For cancerassociated fibroblasts(CAFs), single-cell RNA sequencing had made an irreplaceable contribution to the exploration of their differentiation status, specific CAFs markers, and the interaction with tumor cells and immune cells. In addition, we demonstrated in detail how single-cell RNA sequencing explored the HNSCC epithelial-tomesenchymal transition(EMT) model and the mechanism of drug resistance, as well as its clinical value.

Prognostic-related genes for pancreatic cancer typing and immunotherapy response prediction based on single-cell sequencing data and bulk sequencing data

Pancreatic cancer is associated with high mortality and is one of the most aggressive of malignancies,but studies have not fully evaluated its molecular subtypes,prognosis and response to immunotherapy of different subtypes.The purpose of this study was to explore the molecular subtypes and the key genes associated with the prognosis of pancreas cancer patients and study the clinical phenotype,prognosis and response to immunotherapy using single-cell seq data and bulk RNA seq data,and data retrieved from GEO and TCGA databases.Methods:Single-cell seq data and bioinformatics methods were used in this study.Pancreatic cancer data were retrieved from GEO and TCGA databases,the molecular subtypes of pancreatic cancer were determined using the six cGAS-STING related pathways,and the clinical phenotype,mutation,immunological characteristics and pathways related to pancreatic cancer were evaluated.Results:Pancreatic cancer was classified into 3 molecular subtypes,and survival analysis revealed that patients in Cluster3(C3)had the worst prognosis,whereas Cluster1(C1)had the best prognosis.The clinical phenotype and gene mutation were statistically different among the three molecular subtypes.Analysis of immunotherapy response revealed that most immune checkpoint genes were differentially expressed in the three subtypes.A lower risk of immune escape was observed in Cluster1(C1),indicating higher sensitivity to immunotherapeutic drugs and subjects in this Cluster are more likely to benefit from immunotherapy.The pathways related to pancreatic cancer were differentially enriched among the three subtypes.Five genes,namely SFRP1,GIPR,EMP1,COL17A and CXCL11 were selected to construct a prognostic signature.Conclusions:Single-cell seq data were to classify pancreatic cancer into three molecular subtypes based on differences in clinical phenotype,mutation,immune characteristics and differentially enriched pathways.Five prognosis-related genes were identified for prediction of survival of pancreatic cancer patients and to evaluate the efficacy of immunotherapy in various subtypes.

Single-cell RNA sequencing reveals the dynamics of hepatic non-parenchymal cells in autoprotection against acetaminophen-induced hepatotoxicity

Gaining a better understanding of autoprotection against drug-induced liver injury(DILI)may provide new strategies for its prevention and therapy.However,little is known about the underlying mechanisms of this phenomenon.We used single-cell RNA sequencing to characterize the dynamics and functions of hepatic non-parenchymal cells(NPCs)in autoprotection against DILI,using acetaminophen(APAP)as a model drug.Autoprotection was modeled through pretreatment with a mildly hepatotoxic dose of APAP in mice,followed by a higher dose in a secondary challenge.NPC subsets and dynamic changes were identified in the APAP(hepatotoxicity-sensitive)and APAP-resistant(hepatotoxicity-resistant)groups.A chemokine(C-C motif)ligand 2^(+)endothelial cell subset almost disappeared in the APAP-resistant group,and an R-spondin 3^(+)endothelial cell subset promoted hepatocyte proliferation and played an important role in APAP autoprotection.Moreover,the dendritic cell subset DC-3 may protect the liver from APAP hepatotoxicity by inducing low reactivity and suppressing the autoimmune response and occurrence of inflammation.DC-3 cells also promoted angiogenesis through crosstalk with endothelial cells via vascular endothelial growth factor-associated ligand-receptor pairs and facilitated liver tissue repair in the APAP-resistant group.In addition,the natural killer cell subsets NK-3 and NK-4 and the Sca-1^(-)CD62L^(+)natural killer T cell subset may promote autoprotection through interferon-γ-dependent pathways.Furthermore,macrophage and neutrophil subpopulations with anti-inflammatory phenotypes promoted tolerance to APAP hepatotoxicity.Overall,this study reveals the dynamics of NPCs in the resistance to APAP hepatotoxicity and provides novel insights into the mechanism of autoprotection against DILI at a high resolution.

Single-cell sequencing analysis reveals the molecular mechanism of promotion of SCAP proliferation upon AZD2858 treatment

The Wnt/β-catenin signaling pathway is the main target of tooth regeneration regulation.Treatment of cells with AZD2858 stimulates the Wnt/β-catenin signaling pathway,yet the function of this pathway in tooth regeneration remains unclear.Here,we found that AZD2858 promotes the accumulation ofβ-catenin in the nuclei of stem cells from the apical papilla(SCAPs)and enhances cell proliferation.Single-cell sequencing was performed on SCAPs treated with AZD2858.Eight clusters were identified,namely SCAPs-CNTNAP2,SCAPs-DTL,SCAPs-MYH11,SCAPs-MKI67,SCAPs-CXCL8,SCAPs-TPM2,SCAPs-IFIT2 and SCAPs-NEK10.The pseudo-time trajectory analysis showed that AZD2858 enhanced the evolution of SCAPs from SCAPs-TMP2 clusters to SCAPs-MYH11,SCAPs-CNTNAPs and SCAPs-NEK10 clusters via up-regulation of PRKCA,SMURF2,MAGI2,RBMS3,EXT1,CAMK2D,PLCB4,and PLCB1.These results demonstrate that AZD2858 enhances the proliferation of SCAPs-TPM2 cluster by activating the non-canonical Wnt/β-catenin signaling pathway.

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.

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 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 sequencing reveals the reproductive variations between primiparous and multiparous Hu ewes

Background In the modern sheep production systems,the reproductive performance of ewes determines the economic profitability of farming.Revealing the genetic mechanisms underlying differences in the litter size is important for the selection and breeding of highly prolific ewes.Hu sheep,a high-quality Chinese sheep breed,is known for its high fecundity and is often used as a model to study prolificacy traits.In the current study,animals were divided into two groups according to their delivery rates in three consecutive lambing seasons(namely,the high and low reproductive groups with≥3 lambs and one lamb per season,n=3,respectively).The ewes were slaughtered within 12 h of estrus,and unilateral ovarian tissues were collected and analyzed by 10×Genomics single-cell RNA sequencing.Results A total of 5 types of somatic cells were identified and corresponding expression profiles were mapped in the ovaries of each group.Noticeably,the differences in the ovary somatic cell expression profiles between the high and low reproductive groups were mainly clustered in the granulosa cells.Furthermore,four granulosa cell subtypes were identified.GeneSwitches analysis revealed that the abundance of JPH1 expression and the reduction of LOC101112291 expression could lead to different evolutionary directions of the granulosa cells.Additionally,the expression levels of FTH1 and FTL in mural granulosa cells of the highly reproductive group were significantly higher.These genes inhibit necroptosis and ferroptosis of mural granulosa cells,which helps prevent follicular atresia.Conclusions This study provides insights into the molecular mechanisms underlying the high fecundity of Hu sheep.The differences in gene expression profiles,particularly in the granulosa cells,suggest that these cells play a critical role in female prolificacy.The findings also highlight the importance of genes such as JPH1,LOC101112291,FTH1,and FTL in regulating granulosa cell function and follicular development.

Single‑cell RNA sequencing opens a new era for cotton genomic research and gene functional analysis

Single-cell RNA sequencing(scRNA-seq)is one of the most advanced sequencing technologies for studying transcriptome landscape at the single-cell revolution.It provides numerous advantages over traditional RNA-seq.Since it was first used to profile single-cell transcriptome in plants in 2019,it has been extensively employed to perform different research in plants.Recently,scRNA-seq was also quickly adopted by the cotton research community to solve lots of scientific questions which have been never solved.In this comment,we highlighted the significant progress in employing scRNA-seq to cotton genetic and genomic study and its future potential applications.

Clinical implications of single cell sequencing for bladder cancer

Bladder cancer(BC)is the 10th most common cancer worldwide,with about 0.5 million reported new cases and about 0.2 million deaths per year.In this scoping review,we summarize the current evidence regarding the clinical implications of single-cell sequencing for bladder cancer based on PRISMA guidelines.We searched PubMed,CENTRAL,Embase,and supplemented with manual searches through the Scopus,and Web of Science for published studies until February 2023.We included original studies that used at least one single-cell technology to study bladder cancer.Forty-one publications were included in the review.Twenty-nine studies showed that this technology can identify cell subtypes in the tumor microenvironment that may predict prognosis or response to immune checkpoint inhibition therapy.Two studies were able to diagnose BC by identifying neoplastic cells through single-cell sequencing urine samples.The remaining studies were mainly a preclinical exploration of tumor microenvironment at single cell level.Single-cell sequencing technology can discriminate heterogeneity in bladder tumor cells and determine the key molecular properties that can lead to the discovery of novel perspectives on cancer management.This nascent tool can advance the early diagnosis,prognosis judgment,and targeted therapy of bladder cancer.

Integrated analysis of single-cell and bulk RNA-seq establishes a novel signature for prediction in gastric cancer

BACKGROUND Single-cell sequencing technology provides the capability to analyze changes in specific cell types during the progression of disease.However,previous single-cell sequencing studies on gastric cancer(GC)have largely focused on immune cells and stromal cells,and further elucidation is required regarding the alterations that occur in gastric epithelial cells during the development of GC.AIM To create a GC prediction model based on single-cell and bulk RNA sequencing(bulk RNA-seq)data.METHODS In this study,we conducted a comprehensive analysis by integrating three singlecell RNA sequencing(scRNA-seq)datasets and ten bulk RNA-seq datasets.Our analysis mainly focused on determining cell proportions and identifying differentially expressed genes(DEGs).Specifically,we performed differential expression analysis among epithelial cells in GC tissues and normal gastric tissues(NAGs)and utilized both single-cell and bulk RNA-seq data to establish a prediction model for GC.We further validated the accuracy of the GC prediction model in bulk RNA-seq data.We also used Kaplan–Meier plots to verify the correlation between genes in the prediction model and the prognosis of GC.RESULTS By analyzing scRNA-seq data from a total of 70707 cells from GC tissue,NAG,and chronic gastric tissue,10 cell types were identified,and DEGs in GC and normal epithelial cells were screened.After determining the DEGs in GC and normal gastric samples identified by bulk RNA-seq data,a GC predictive classifier was constructed using the Least absolute shrinkage and selection operator(LASSO)and random forest methods.The LASSO classifier showed good performance in both validation and model verification using The Cancer Genome Atlas and Genotype-Tissue Expression(GTEx)datasets[area under the curve(AUC)_min=0.988,AUC_1se=0.994],and the random forest model also achieved good results with the validation set(AUC=0.92).Genes TIMP1,PLOD3,CKS2,TYMP,TNFRSF10B,CPNE1,GDF15,BCAP31,and CLDN7 were identified to have high importance values in multiple GC predictive models,and KM-PLOTTER analysis showed their relevance to GC prognosis,suggesting their potential for use in GC diagnosis and treatment.CONCLUSION A predictive classifier was established based on the analysis of RNA-seq data,and the genes in it are expected to serve as auxiliary markers in the clinical diagnosis of GC.