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.

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.

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.

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.

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.

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 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.

Panoramic comparison between NK cells in healthy and cancerous liver through single-cell RNA sequencing

Objective:NK cells play crucial roles in the immune defense mechanisms against viral infections and transformed cells.However,the developmental progression,transcriptomic landscape,and functional subtypes of liver NK cells are not well defined.Hepatocellular carcinoma(HCC)accounts for approximately 80%of primary liver cancer worldwide,yet the biological characteristics of NK cells in the HCC environment are unclear.Therefore,we aimed to determine these cells’roles in tumorigenesis and prognosis.Methods:We compared the single-cell RNA sequencing profiles of NK cells purified from blood(n=1),healthy liver tissues(n=3),HCC tumor tissues(n=4),and peritumor liver tissues(n=1)to identify NK cell subsets.Furthermore,we performed bioinformatics analysis by using The Cancer Genome Atlas(TCGA)data to identify prognostic biomarkers simultaneously overexpressed in the blood and tumor tissues of patients with HCC.Results:Transcriptomic analysis revealed 5 NK cell subsets(L1-NK-CD56bright,L2-NK-CD56dim,L3-NK-HLA,L4-LrNK-FCGR3A,and L5-LrNK-XCL1)in the healthy liver tissues.However,the transitional L3 subset and the CXCR6+CD16+L4 subset with strong anti-tumor activity were absent in the HCC and peritumor liver tissues.Furthermore,4 common prognosis-associated genes(RHOB,TALDO1,HLA-DPA1,and TKT)were significantly overexpressed in the paired tumor tissue and blood.Conclusions:Our study revealed 5 specific subsets of NK cells in healthy human liver tissues.However,only 3 of the 5 NK cell subsets were present in HCC and peritumor tissues.The cytotoxic NK cell subsets were absent in HCC tissues.Furthermore,we identified 4 potential non-invasive prognostic biomarkers in patients with HCC.

Recent advances of single-cell RNA sequencing technology in mesenchymal stem cell research

Mesenchymal stem cells(MSCs)are multipotent stromal cells with great potential for clinical applications.However,little is known about their cell heterogeneity at a single-cell resolution,which severely impedes the development of MSC therapy.In this review,we focus on advances in the identification of novel surface markers and functional subpopulations of MSCs made by single-cell RNA sequencing and discuss their participation in the pathophysiology of stem cells and related diseases.The challenges and future directions of single-cell RNA sequencing in MSCs are also addressed in this review.

Prudent application of single-cell RNA sequencing in understanding cellular features and functional phenotypes in cancer studies

This decade has seen remarkable advances in the field of high-throughput single cell techniques.Single-cell RNA sequencing(sc RNA-seq)has proven to be a powerful strategy to study the heterogeneity in clinical samples,providing an unbiased approach to uncover the characteristics in different cell subsets.To ensure the reproducibility and robustness of biological discoveries,researchers need to be aware of hidden caveats in tissue dissociation,cell capturing and transcripts measurement which may affect cell composition assessment and cellular function annotation.With measured interpretation of data and innovations in experimental and technical approaches,sc RNA-seq can greatly unravel the heterogeneity in complex system and improve our understandings in tissue homeostasis and cancer biology.

Characteristics of alveolar macrophages in bronchioalveolar lavage fluids from active tuberculosis patients identified by single-cell RNA sequencing

Tuberculosis(TB),is an infectious disease caused by Mycobacterium tuberculosis(M.tuberculosis),and presents with high morbidity and mortality.Alveolar macrophages play an important role in TB pathogenesis although there is heterogeneity and functional plasticity.This study aimed to show the characteristics of alveolar macrophages from bronchioalveolar lavage fluid(BALF)in active TB patients.Single-cell RNA sequencing(scRNA-seq)was performed on BALF cells from three patients with active TB and additional scRNA-seq data from three healthy adults were established as controls.Transcriptional profiles were analyzed and compared by differential gene expression and functional enrichment analysis.We applied pseudo-temporal trajectory analysis to investigate correlations and heterogeneity within alveolar macrophage subclusters.Alveolar macrophages from active TB patients at the single-cell resolution are described.We found that TB patients have higher cellular percentages in five macrophage subclusters.Alveolar macrophage subclusters with increased percentages were involved in inflammatory signaling pathways as well as the basic macrophage functions.The TB-increased alveolar macrophage subclusters might be derived from M1-like polarization state,before switching to an M2-like polarization state with the development of M.tuberculosis infection.Cell-cell communications of alveolar macrophages also increased and enhanced in active TB patients.Overall,our study demonstrated the characteristics of alveolar macrophages from BALF in active TB patients by using scRNA-seq.

Single-cell RNA sequencing reveals classical monocytes are the major precursors of rat osteoclasts

To dissect which subset of bone marrow monocyte is the major precursor of osteoclast,3-month-old rat bone marrow was obtained for single-cell RNA sequencing.A total of 6091 cells were acquired for detailed analysis,with a median number of 1206 genes detected per cell and 17,959 genes detected in total.A total of 19 cell clusters were recognized,with the main lineages identified as B cells,Granulocytes,Monocytes,T cells,Erythrocytes and Macrophages.Monocytes were further divided into classical monocytes and non-classical monocytes.Compared with non-classical monocytes,classical monocytes highly expressed osteoclast differentiation related genes Mitf,Spi1,Fos and Csf1r.Additionally,biological processes of classical monocytes were related to osteoclast differentiation.qPCR revealed differentially expressed genes of classical monocytes played a role in osteoclast differentiation.In conclusion,classical monocytes were identified as the main precursors of osteoclasts in rats,and may contribute to osteoclast differentiation by regulating S100a4,S100a6,S100a10,Fn1,Vcan and Bcl2a1.The results of this study contribute to the understanding of the origin of osteoclasts and may provide potential biomarkers for early diagnosis of bone metabolic diseases,as well as molecular and cellular targets for clinical intervention in bone metabolic diseases.

Landscape of cell heterogeneity and evolutionary trajectory in ulcerative colitis-associated colon cancer revealed by single-cell RNA sequencing

Objective:The goal of this study was to get preliminary insight on the intra-tumor heterogeneity in colitisassociated cancer(CAC)and to reveal a potential evolutionary trajectory from ulcerative colitis(UC)to CAC at the single-cell level.Methods:Fresh samples of tumor tissues and adjacent UC tissues from a CAC patient with pT3N1M0 stage cancer were examined by single-cell RNA sequencing(scRNA-seq).Data from The Cancer Genome Atlas(TCGA)and The Human Protein Atlas were used to confirm the different expression levels in normal and tumor tissues and to determine their relationships with patient prognosis.Results:Ultimately,4,777 single-cell transcriptomes(1,220 genes per cell)were examined,of which 2,250(47%)and 2,527(53%)originated from tumor and adjacent UC tissues,respectively.We defined the composition of cancer-associated stromal cells and identified six cell clusters,including myeloid,T and B cells,fibroblasts,endothelial and epithelial cells.Notable pathways and transcription factors involved in these cell clusters were analyzed and described.Moreover,the precise cellular composition and developmental trajectory from UC to UCassociated colon cancer were graphed,and it was predicted that CD74,CLCA1,and DPEP1 played a potential role in disease progression.Conclusions:scRNA-seq technology revealed intra-tumor cell heterogeneity in UC-associated colon cancer,and might provide a promising direction to identify novel potential therapeutic targets in the evolution from UC to CAC.

Single-cell RNA sequencing reveals the landscape of maize root tips and assists in identification of cell type-specific nitrate-response genes

The root system is fundamental for maize growth and yield.Characterizing its heterogeneity and cell type-specific response to nitrate at the single-cell level will shed light on root development and nutrient uptake.We profiled the transcriptomes of>7000 cells derived from root tips of maize seedlings grown on media with or without nitrate,and identified 11 major cell types or tissues and 85 cell type-specific nitrate-response genes,including several known nitrate metabolic genes.A pseudotime analysis showed a continuous pseudotime series with the beginning at meristematic zone cells and showed that the root hair cell was derived by differentiation of a subset of epidermal cells.Interspecies comparison of root cells between maize and rice revealed the conservation and divergence of the root cell types and identified 57,216,and 80 conserved orthologous genes in root hair,endodermis,and phloem cells respectively.This study provides a global view of maize root tip developmental processes and responses to nitrate at the single-cell level.The genes described in the present work could serve as targets for further genetic analyses and accurate regulation of gene expression and phenotypic variation in specific cell types or tissues.

Examining heterogeneity of stromal cells in tumor microenvironment based on pan-cancer single-cell RNA sequencing data

Tumor tissues contain both tumor and non-tumor cells,which include infiltrated immune cells and stromal cells,collectively called the tumor microenvironment(TME).Single-cell RNA sequencing(sc RNAseq)enables the examination of heterogeneity of tumor cells and TME.In this review,we examined sc RNAseq datasets for multiple cancer types and evaluated the heterogeneity of major cell type composition in different cancer types.We further showed that endothelial cells and fibroblasts/myofibroblasts in different cancer types can be classified into common subtypes,and the subtype composition is clearly associated with cancer characteristic and therapy response.

Single-cell RNA sequencing of mitoticarrested prospermatogonia with DAZL::GFP chickens and revealing unique epigenetic reprogramming of chickens

Background:Germ cell mitotic arrest is conserved in many vertebrates,including birds,although the time of entry or exit into quiescence phase differs.Mitotic arrest is essential for the normal differentiation of male germ cells into spermatogonia and accompanies epigenetic reprogramming and meiosis inhibition from embryonic development to post-hatch.However,mitotic arrest was not well studied in chickens because of the difficulty in obtaining pure germ cells from relevant developmental stage.Results:We performed single-cell RNA sequencing to investigate transcriptional dynamics of male germ cells during mitotic arrest in DAZL::GFP chickens.Using differentially expressed gene analysis and K-means clustering to analyze cells at different developmental stages(E12,E16,and hatch),we found that metabolic and signaling pathways were regulated,and that the epigenome was reprogrammed during mitotic arrest.In particular,we found that histone H3K9 and H3K14 acetylation(by HDAC2)and DNA demethylation(by DNMT3B and HELLS)led to a transcriptionally permissive chromatin state.Furthermore,we found that global DNA demethylation occurred gradually after the onset of mitotic arrest,indicating that the epigenetic-reprogramming schedule of the chicken genome differs from that of the mammalian genome.DNA hypomethylation persisted after hatching,and methylation was slowly re-established 3 weeks later.Conclusions:We found a unique epigenetic-reprogramming schedule of mitotic-arrested chicken prospermatogonia and prolonged hypomethylation after hatching.This will provide a foundation for understanding the process of germ-cell epigenetic regulation in several species for which this process is not clearly described.Our findings on the biological processes related to sex-specific differentiation of prospermatogonia could help studying germline development in vitro more elaborately.

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.

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.

Advances in single-cell sequencing:insights from organ transplantation

Single-cell RNA sequencing(scRNA-seq)is a comprehensive technical tool to analyze intracellular and intercellular interaction data by whole transcriptional profile analysis.Here,we describe the application in biomedical research,focusing on the immune system during organ transplantation and rejection.Unlike conventional transcriptome analysis,this method provides a full map of multiple cell populations in one specific tissue and presents a dynamic and transient unbiased method to explore the progression of allograft dysfunction,starting from the stress response to final graft failure.This promising sequencing technology remarkably improves individualized organ rejection treatment by identifying decisive cellular subgroups and cell-specific interactions.