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.

Applications of single cell RNA sequencing to research of stem cells

Stem cells(SCs)with their self-renewal and pluripotent differentiation potential,show great promise for therapeutic applications to some refractory diseases such as stroke,Parkinsonism,myocardial infarction,and diabetes.Furthermore,as seed cells in tissue engineering,SCs have been applied widely to tissue and organ regeneration.However,previous studies have shown that SCs are heterogeneous and consist of many cell subpopulations.Owing to this heterogeneity of cell states,gene expression is highly diverse between cells even within a single tissue,making precise identification and analysis of biological properties difficult,which hinders their further research and applications.Therefore,a defined understanding of the heterogeneity is a key to research of SCs.Traditional ensemble-based sequencing approaches,such as microarrays,reflect an average of expression levels across a large population,which overlook unique biological behaviors of individual cells,conceal cell-to-cell variations,and cannot understand the heterogeneity of SCs radically.The development of high throughput single cell RNA sequencing(scRNA-seq)has provided a new research tool in biology,ranging from identification of novel cell types and exploration of cell markers to the analysis of gene expression and predicating developmental trajectories.scRNA-seq has profoundly changed our understanding of a series of biological phenomena.Currently,it has been used in research of SCs in many fields,particularly for the research of heterogeneity and cell subpopulations in early embryonic development.In this review,we focus on the scRNA-seq technique and its applications to research of SCs.

Single-cell RNA sequencing in cornea research:Insights into limbal stem cells and their niche regulation

The corneal epithelium is composed of stratified squamous epithelial cells on the outer surface of the eye,which acts as a protective barrier and is critical for clear and stable vision.Its continuous renewal or wound healing depends on the proliferation and differentiation of limbal stem cells(LSCs),a cell population that resides at the limbus in a highly regulated niche.Dysfunction of LSCs or their niche can cause limbal stem cell deficiency,a disease that is manifested by failed epithelial wound healing or even blindness.Nevertheless,compared to stem cells in other tissues,little is known about the LSCs and their niche.With the advent of single-cell RNA sequencing,our understanding of LSC characteristics and their microenvironment has grown considerably.In this review,we summarized the current findings from single-cell studies in the field of cornea research and focused on important advancements driven by this technology,including the heterogeneity of the LSC population,novel LSC markers and regulation of the LSC niche,which will provide a reference for clinical issues such as corneal epithelial wound healing,ocular surface reconstruction and interventions for related diseases.

Single cell RNA sequencing reveals mesenchymal heterogeneity and critical functions of Cd271 in tooth development

BACKGROUND Accumulating evidence suggests that the maxillary process,to which cranial crest cells migrate,is essential to tooth development.Emerging studies indicate that Cd271 plays an essential role in odontogenesis.However,the underlying mechanisms have yet to be elucidated.AIM To establish the functionally heterogeneous population in the maxillary process,elucidate the effects of Cd271 deficiency on gene expression differences.METHODS p75NTR knockout(Cd271-/-)mice(from American Jackson laboratory)were used to collect the maxillofacial process tissue of p75NTR knockout mice,and the wildtype maxillofacial process of the same pregnant mouse wild was used as control.After single cell suspension,the cDNA was prepared by loading the single cell suspension into the 10x Genomics Chromium system to be sequenced by NovaSeq6000 sequencing system.Finally,the sequencing data in Fastq format were obtained.The FastQC software is used to evaluate the quality of data and CellRanger analyzed the data.The gene expression matrix is read by R software,and Seurat is used to control and standardize the data,reduce the dimension and cluster.We search for marker genes for subgroup annotation by consulting literature and database;explore the effect of p75NTR knockout on mesenchymal stem cells(MSCs)gene expression and cell proportion by cell subgrouping,differential gene analysis,enrichment analysis and protein-protein interaction network analysis;understand the interaction between MSCs cells and the differentiation trajectory and gene change characteristics of p75NTR knockout MSCs by cell communication analysis and pseudo-time analysis.Last we verified the findings single cell sequencing in vitro.RESULTS We identified 21 cell clusters,and we re-clustered these into three subclusters.Importantly,we revealed the cell–cell communication networks between clusters.We clarified that Cd271 was significantly associated with the regulation of mineralization.CONCLUSION This study provides comprehensive mechanistic insights into the maxillary-process-derived MSCs and demonstrates that Cd271 is significantly associated with the odontogenesis in mesenchymal populations.

Extensive exploration of T cell heterogeneity in cancers by single cell sequencing

Human T cells are a highly heterogeneous population and can recognize a wide variety of antigens by their T cell receptors(TCRs). Tumor cells display a large repertoire of antigens that serve as potential targets for recognition,thus making T cells in the tumor micro-environment more complicated. Making a connection between TCRs and the transcriptional information of individual T cells will be interesting for investigating clonal expansion within T cell populations under pathologic conditions. Advances in single cell RNA-sequencing(scRNA-seq) have allowed for comprehensive analysis of T cells. In this review, we briefly describe the research progress on tumor microenvironment T cells using single cell RNA sequencing, and then discuss how scRNA-seq can be used to resolve immune system heterogeneity in health and disease. Finally, we point out future directions in this field and potential for immunotherapy.

Biological significance of RNA-seq and single-cell genomic research in woody plants

RNA-seq and single-cell genomic research emerge as an important research area in the recent years due to its ability to examine genetic information of any number of single cells in all living organisms.The knowledge gained from RNA-seq and single-cell genomic research will have a great impact in many aspects of plant biology.In this review,we summary and discuss the biological significance of RNA-seq and single-cell genomic research in plants including the single-cell DNA-sequencing,RNA-seq and single-cell RNA sequencing in woody plants,methods of RNA-seq and single-cell RNA-sequencing,single-cell RNA-sequencing for studying plant development,and single-cell RNA-sequencing for elucidating cell type composition.We will focus on RNA-seq and single-cell RNA sequencing in woody plants,understanding of plant development through single-cell RNAsequencing,and elucidation of cell type composition via single-cell RNA-sequencing.Information presented in this review will be helpful to increase our understanding of plant genomic research in a way with the power of plant single-cell RNA-sequencing analysis.

Single-cell transcriptomic dissection of the cellular and molecular events underlying the triclosan-induced liver fibrosis in mice

Background: Triclosan [5-chloro-2-(2,4-dichlorophenoxy) phenol, TCS], a common antimicrobial additive in many personal care and health care products, is frequently detected in human blood and urine. Therefore, it has been considered an emerging and potentially toxic pollutant in recent years. Long-term exposure to TCS has been suggested to exert endocrine disruption effects, and promote liver fibrogenesis and tumorigenesis. This study was aimed at clarifying the underlying cellular and molecular mechanisms of hepatotoxicity effect of TCS at the initiation stage.Methods: C57BL/6 mice were exposed to different dosages of TCS for 2 weeks and the organ toxicity was evaluated by various measurements including complete blood count, histological analysis and TCS quantification. Single cell RNA sequencing(scRNA-seq) was then carried out on TCS-or mock-treated mice livers to delineate the TCS-induced hepatotoxicity. The acquired single-cell transcriptomic data were analyzed from different aspects including differential gene expression, transcription factor(TF) regulatory network, pseudotime trajectory, and cellular communication, to systematically dissect the cellular and molecular events after TCS exposure. To verify the TCS-induced liver fibrosis,the expression levels of key fibrogenic proteins were examined by Western blotting, immunofluorescence, Masson’s trichrome and Sirius red stainings. In addition, normal hepatocyte cell MIHA and hepatic stellate cell LX-2 were used as in vitro cell models to experimentally validate the effects of TCS by immunological, proteomic and metabolomic technologies.Results: We established a relatively short term TCS exposure murine model and found the TCS mainly accumulated in the liver. The scRNA-seq performed on the livers of the TCS-treated and control groups profiled the gene expressions of > 76,000 cells belonging to 13 major cell types. Among these types, hepatocytes and hepatic stellate cells(HSCs)were significantly increased in TCS-treated group. We found that TCS promoted fibrosis-associated proliferation of hepatocytes, in which Gata2 and Mef2c are the key driving TFs. Our data also suggested that TCS induced the proliferation and activation of HSCs, which was experimentally verified in both liver tissue and cell model. In addition,other changes including the dysfunction and capillarization of endothelial cells, an increase of fibrotic characteristics in B plasma cells, and M2 phenotype-skewing of macrophage cells, were also deduced from the scRNA-seq analysis, and these changes are likely to contribute to the progression of liver fibrosis. Lastly, the key differential ligand-receptor pairs involved in cellular communications were identified and we confirmed the role of GAS6_AXL interactionmediated cellular communication in promoting liver fibrosis.Conclusions: TCS modulates the cellular activities and fates of several specific cell types(including hepatocytes, HSCs,endothelial cells, B cells, Kupffer cells and liver capsular macrophages) in the liver, and regulates the ligand-receptor interactions between these cells, thereby promoting the proliferation and activation of HSCs, leading to liver fibrosis.Overall, we provide the first comprehensive single-cell atlas of mice livers in response to TCS and delineate the key cellular and molecular processes involved in TCS-induced hepatotoxicity and fibrosis.

Discovering myeloid cell heterogeneity in the lung by means of next generation sequencing

The lung plays a vital role in maintaining homeostasis,as it is responsible for the exchange of oxygen and carbon dioxide.Pulmonary homeostasis is maintained by a network of tissue-resident cells,including epithelial cells,endothelial cells and leukocytes.Myeloid cells of the innate immune system and epithelial cells form a critical barrier in the lung.Recently developed unbiased next generation sequencing(NGS)has revealed cell heterogeneity in the lung with respect to physiology and pathology and has reshaped our knowledge.New phenotypes and distinct gene signatures have been identified,and these new findings enhance the diagnosis and treatment of lung diseases.Here,we present a review of the new NGS findings on myeloid cells in lung development,homeostasis,and lung diseases,including acute lung injury(ALI),lung fibrosis,chronic obstructive pulmonary disease(COPD),and lung cancer.

FSPAM:A Feature Construction Method to Identifying Cell Populations in ScRNA-seq Data

The emergence of single-cell RNA-sequencing(scRNA-seq)technology has introduced new information about the structure of cells,diseases,and their associated biological factors.One of the main uses of scRNA-seq is identifying cell populations,which sometimes leads to the detection of rare cell populations.However,the new method is still in its infancy and with its advantages comes computational challenges that are just beginning to address.An important tool in the analysis is dimensionality reduction,which transforms high dimensional data into a meaningful reduced subspace.The technique allows noise removal,visualization and compression of high-dimensional data.This paper presents a new dimensionality reduction approach where,during an unsupervised multistage process,a feature set including high valuable markers is created which can facilitate the isolation of cell populations.Our proposed method,called fusion of the Spearman and Pearson affinity matrices(FSPAM),is based on a graph-based Gaussian kernel.Use of the graph theory can be effective to overcome the challenge of the nonlinear relations between cellular markers in scRNA-seq data.Furthermore,with a proper fusion of the Pearson and Spearman correlation coefficient criteria,it extracts a set of the most important features in a new space.In fact,the FSPAM aggregates the various aspects of cell-to-cell similarity derived from the Pearson and Spearman metrics,and reveals new aspects of cell-to-cell similarity,which can be used to extract new features.The results of the identification of cell populations via k-means++clustering method based on the features extracted from the FSPAM and different datasets of scRNA-seq suggested that the proposed method,regardless of the characteristics that govern each dataset,enjoys greater accuracy and better quality compared to previous methods.

单细胞RNA测序技术在水产养殖动物上的应用

单细胞RNA测序技术是生命科学领域中的革命性技术,为动植物的细胞异质性图谱构建、细胞谱系追踪、免疫响应机制解析等研究提供了强有力的工具。近年来,单细胞RNA测序技术在水产养殖动物中也得到了广泛应用。本文就单细胞RNA测序技术的发展、原理及其在水产养殖动物研究中的应用进行综述,并对其目前存在的问题及未来发展趋势进行分析与展望,以期推动该技术在水产养殖动物研究中更广泛的应用,加速水产养殖动物单细胞水平生命活动的调控机制研究进程。

人脐带间充质干细胞的异质性探讨及基于单细胞RNA测序结果的亚群分析

目的探讨人脐带间充质干细胞(hUCMSCs)的异质性,并基于单细胞RNA测序结果进行亚群分析。方法选择两株由郑州奥博细胞医学实验室有限公司提供的hUCMSCs(分别命名为hUCMSCs-1和hUCMSCs-2),通过实时荧光定量聚合酶链反应(qPCR)进行干性基因[性别决定区Y-box 2(Sox2)、Nanog]检测。对hUCMSCs进行成骨诱导,3 d后检测成骨基因碱性磷酸酶(Alp)的表达,7 d后进行碱性磷酸酶染色,14 d后进行茜素红染色。对两株hUCMSCs进行成软骨诱导,21 d后检测成软骨基因二型胶原(COL2A1)的表达。用10 ng/mL白细胞介素-1β(IL-1β)刺激大鼠软骨细胞24 h,与hUCMSCs-1和hUCMSCs-2共培养后,检测软骨细胞合成代谢基因蛋白聚糖(ACAN)和分解代谢基因基质金属蛋白酶3(MMP3)的表达。对hUCMSCs-1进行单细胞RNA测序,并根据功能进行亚群分组,通过生物信息学分析方法描绘各个亚群标志基因热图、富集的信号通路。结果两株hUCMSCs的Sox2、Nanog、Alp、COL2A1表达水平差异有统计学意义(P<0.05)。在成骨诱导7 d后,hUCMSCs-1的碱性磷酸酶染色程度深于hUCMSCs-2。在成骨诱导14 d后,茜素红染色结果显示,hUCMSCs-1钙结节数量多于hUCMSCs-2。经IL-1β干预后,软骨细胞与两株hUCMSCs共培养后的MMP3表达水平差异有统计学意义(P<0.05),但ACAN表达水平差异不显著(P>0.05)。基于单细胞RNA测序结果,hUCMSCs-1可分为C1、C2、C3三个功能亚群。C1亚群的信号通路在细胞外基质受体相互作用上富集,与软骨细胞合成代谢相关;C2亚群信号通路在细胞衰老和凋亡上富集,与细胞的自我更新相关;C3亚群信号通路在DNA复制和减数分裂上富集,与细胞周期相关。结论不同个体来源的hUCMSCs存在异质性,其在成骨、成软骨和抗分解代谢能力方面可能存在差异。通过单细胞RNA测序可较好地根据hUCMSCs的功能特性对其进行分群,有助于提高间充质干细胞治疗的临床疗效。

基于单细胞RNA测序数据的基因调控网络推断算法综述

通过基因表达的变化可以推断基因调控网络.单细胞RNA测序(scRNA-seq)为推断细胞周期或分化等时间依赖性生物过程的基因调控网络提供了新的可能性,基于scRNA-seq数据的基因调控网络推断算法成为一个相对活跃的研究方向.本文首先对26种基因调控网络推断算法进行介绍,包括3种针对批量RNA测序数据的推断算法和23种针对scRNA-seq数据的推断算法(基于布尔网络的算法2种、基于微分方程的算法3种、基于伪时序基因相关性集成策略的算法5种、基于共表达基因的算法4种、基于细胞特异性的算法3种、基于深度学习的算法6种),详细描述了每类算法的方法原理和算法优缺点,对算法进行综合比较;然后分析了推断算法比较研究的相关成果,并使用scRNA-seq数据简单评估了26种算法的性能;最后探讨当前基因调控网络推断算法面临的机遇与挑战.

Single-cell RNA sequencing profiling of the effects of aging on alveolar stem cells

The aging of alveolar stem cells has been linked to many chronic lung diseases, including pulmonary fibrosis. However, the effects of aging on alveolar stem cells during homeostasis and post-injury alveolar repair have not been well characterized. Here we conducted a single-cell RNA sequencing(scRNA-seq) analysis of alveolar stem cells of 3-month-old and 12-month-old mice to characterize the aging effect on alveolar stem cells. Our results have shown that the transcriptomes of alveolar stem cells of 3-month-old and 12-month-old mice are not significantly different under the steady condition. However, after a bleomycin-induced lung injury, the alveolar stem cells of 12-month-old mice show enhanced inflammatory responses and decreased lipid metabolism. Our study suggests a close relationship among aging, lipid metabolism, inflammatory responses and chronic lung diseases.

单细胞RNA测序技术在肺癌肿瘤微环境研究中的进展

免疫微环境对肿瘤的发生发展起着关键作用。近年来,随着高通量测序技术的飞速发展,研究人员对肿瘤微环境中的免疫细胞组成及其功能有了更深入的了解。然而,传统的群体测序技术难以解析单个细胞层面的异质性,限制了对肿瘤微环境复杂性的全面理解。单细胞RNA测序技术的兴起,为揭示肺癌免疫微环境的异质性带来了新的机遇。当前以T细胞为中心的免疫治疗在临床中容易出现免疫原性耐药或者免疫相关性肺炎等影响预后的副作用,其关键因素是肿瘤微环境中免疫细胞与肿瘤细胞的相互作用发生了变化。而单细胞RNA测序技术可以从细胞间互作、拟时序分析等角度揭示肿瘤微环境中不同亚群间的起源与作用,进而发现新的细胞亚群或新生生物标志物,为揭示免疫治疗的耐药及疗效监测等提供新的途径。该综述系统回顾了单细胞RNA测序技术在揭示肺癌特别是免疫治疗后肺癌微环境异质性方面的最新研究进展,为促进肺癌免疫治疗的精准化与个体化提供参考。

单细胞RNA测序联合实验验证树突状细胞在慢性阻塞性肺疾病中的核心基因

目的 单细胞RNA测序(scRNA-Seq)联合实验验证树突状细胞在慢性阻塞性肺疾病(COPD)中的核心基因。方法从基因表达数据集(GEO)数据库下载单细胞数据GSE173896和芯片数据GSE38974。GSE173896进行质控、批次矫正、降维聚类、细胞类型注释及组间树突状细胞差异表达基因(DC-DEG)鉴定。GSE38974差异分析得到的差异基因(DEG)与DC-DEG取交集获取共有DC-DEG,评估共有DC-DEG对COPD的诊断效能和共有DC-DEG富集分析及其与GSE38974免疫细胞浸润中激活的树突状细胞(DC)、浆细胞样树突状细胞(pDC)和Th17细胞的相关性。肺气肿小鼠模型肺组织对共有DC-DEG的mRNA表达量进行实验验证。结果 GSE173896得到组间DC-DEG 18个,GSE38974得到646个DEG,两者取交集得到3个DC-DEG,包括白细胞介素1受体拮抗剂(IL1RN)、 S100钙结合蛋白A8(S100A8)和S100A9,曲线下面积(AUC)值分别为0.841、 0.804和0.966。基因本体论分析(GO)和京都基因与基因组百科全书(KEGG)主要富集于慢性炎症反应、含胶原蛋白的细胞外基质、晚期糖基化终产物受体(RAGE)结合、 Toll样受体(TLR)结合、白细胞介素17(IL-17)信号通路等。IL1RN、 S100A8和S100A9均与激活的DC、 pDC及Th17细胞呈正相关。实验验证结果显示肺气肿小鼠肺组织IL1RN、 S100A8和S100A9的mRNA相对表达量上调。结论 IL1RN、 S100A8和S100A9可能是DC在COPD发病机制中的核心基因,为后续COPD的免疫治疗提供潜在靶点和理论依据。

单细胞RNA测序和孟德尔随机化分析IgA肾病关键基因的调控作用

目的探讨IgA肾病(IgAnephropathy,IgAN)中重点细胞类型的基因表达及关键基因ADI1、BNIP3L、SERPINE2对IgAN发生、发展的调控作用。方法采用基因表达综合数据库(gene expression omnibus,GEO)和eQTLGen联盟数据库,通过孟德尔随机化(mendelian randomization,MR)和单细胞RNA测序(single-cell gene expression,scRNA-seq),探讨IgAN的关键细胞类型及ADI1、BNIP3L、SERPINE2与IgAN间的因果关系。使用Seurat软件包读取表达谱并筛选低表达基因,通过差异基因表达分析筛选TOP100高表达基因,采用敏感性分析和异质性检验选择显著的基因结果。最后,通过重要基因的调控网络分析和微小核糖核酸(microRNA,miRNA)网络构建对MR结果进行验证。结果ADI1(OR=0.946,95%CI:0.900~0.994,P=0.029)、BNIP3L(OR=0.820,95%CI:0.707~0.950,P=0.008)、SERPINE2(OR=0.958,95%CI:0.919~0.999,P=0.045)可能与IgAN风险降低相关。KLF6(OR=1.318,95%CI:1.036~1.678,P=0.025)与IgAN的风险升高相关。结论揭示包括近端肾小管细胞在内的18种关键细胞类型的基因特征,确定ADI1、BNIP3L、SERPINE2与IgAN发生、发展的调控作用密切相关。

单细胞RNA测序应用于继发性肾病的研究进展

糖尿病肾病、狼疮性肾炎是主要的继发性肾病,是导致终末期肾病的重要原因。探究继发性肾病发生发展过程有利于减少肾功能损害。肾脏细胞具有高度分化且结构复杂的特点,传统测序方法只能探究一类细胞的平均转录水平及关系。近年来,单细胞RNA测序(single-cell RNA-sequencing,scRNA-seq)技术迅猛发展,以高通量及高分辨率对肾组织、血液、尿液细胞样本进行分析,识别新的细胞类型和状态,绘制细胞图谱,从细胞水平维度揭示肾脏疾病的复杂机制,发现生物标志物和细胞特异性。该文就scRNA-seq技术在常见继发性肾病的应用进展进行综述。

单细胞RNA测序技术在肾病中的研究进展

单细胞转录组测序(scRNA-seq)技术为生物医学带来了许多新发现,能高分辨率、高通量和可重复地进行转录分析,识别新的细胞类型,形成细胞图谱。而传统测序方法只能反映样本中所有细胞基因表达的整体水平而无法揭示单个细胞之间的基因表达异质性。本文阐述了scRNA-seq技术发展史,概述该技术可能应用于揭示肾脏疾病的发生机制,有利于肾病诊断和治疗。

双自编码结合变分贝叶斯的单细胞RNA-Seq聚类

近年来单细胞RNA测序(scRNA-seq)技术的快速发展使得在单个细胞水平上研究组织器官的异质性成为可能。针对单细胞RNA测序数据中准确鉴定细胞类型问题,提出一种新的基于双自编码结合变分贝叶斯高斯混合模型的聚类方法,称之为sc-VBDAE。首先通过对抗自编码网络的编码和解码过程重构数据,然后使用经典自编码对数据进行降维,获得低维且有效的数据。最后使用变分贝叶斯高斯混合模型对细胞进行聚类,并可视化聚类结果。在10个scRNA-seq数据上的实验结果表明,该方法在6个数据集上ARI指标均优于其它方法,在数据集Biase和Klein上ARI指标值达到0.90及以上。

单细胞RNA测序技术在胶质母细胞瘤研究中的应用

胶质母细胞瘤是成人脑部最常见的原发恶性肿瘤,尽管近年来在改善预后方面做出了巨大的努力,其中位生存期仍低于20个月,且存活时间超过20个月的患者不到5%。胶质母细胞瘤的标准治疗方案为最大限度的手术切除,联合放疗及替莫唑胺化疗。单细胞RNA测序(scRNA-seq)技术精准分析每个独特的细胞,使我们能够更好地理解肿瘤的异质性、肿瘤细胞的演化过程、肿瘤免疫微环境中各类细胞的特殊功能及细胞间相互作用,从而为临床的个体化治疗提供新思路。该综述重点关注scRNA-seq技术在胶质母细胞瘤的异质性、肿瘤免疫微环境、细胞通讯以及治疗研究中的应用。