ScRNA-seq reveals the correlation between M2 phenotype of tumorassociated macrophages and lymph node metastasis of breast cancer

The process of lymphatic metastasis was proved to be associated with podoplanin-expressing macrophages in breast cancer(BC).This study aimed to investigate the role of the M2 phenotype of tumor-associated macrophages and mine the key M2 macrophages-related genes for lymph node metastasis in BC.We downloaded the GSE158399 dataset from the Gene Expression Omnibus(GEO)database,which includes transcriptomic profiles of individual cells from primary tumors,negative lymph nodes(NLNs),and positive lymph nodes(PLNs)of breast cancer patients.The cell subsets were identified by clustering analysis after quality control of the scRNA-seq using Seurat.The activation and migration capability of M2 macrophages were evaluated with R package“GSVA”.The key M2 macrophages-related genes were screened from the differential expressed genes(DEGs)and M2 macrophages activation and migration gene sets collected from MSigDB database.Our analysis identified three main cell types in primary tumors,NLNs,and PLNs:basal cells,luminal cells,and immune cell subsets.The further cell type classification of immune cell subsets indicated M2 macrophages accumulation in NLs and PLs.The GSVA enrichment scores for activation and migration capability were increased significantly in M2 macrophages from primary tumors than NLNs and PLNs(pvalue<0.001).Seven M2 macrophages activation-related and 15 M2 macrophages migration-related genes were significantly up-regulated in primary tumors than NLNs and PLNs.The proportion and GSVA enrichment scores for activation and migration of M2 macrophages may be potential markers for lymph node metastasis in breast cancer.Our study demonstrated that twenty-two up-regulated mRNA may be possible therapeutic targets for lymph node metastasis in breast cancer.

Integration of scRNA-Seq and Bulk RNA-Seq to analyze the heterogeneity ofcolorectal cancer immune cells and establish a molecular risk model

Background:Colorectal cancer(CRC)is a highly heterogeneous malignant tumor that significantly impacts clinical diagnosis and treatment.Single-cell RNA sequencing is an innovative method for exploring tumor heterogeneity and understanding its role at cellular and genetic levels.Method:The colorectal cancer Single-cell RNA sequencing data were analysed on the immune.RNA-seq data in bulk form was utilized to assess the major genes of the immune cell subsets linked to CRC.We conducted an analysis of the abundance of immune cells in the microenvironment of CRC,and also performed weighted gene co-expression network analysis.Gene set enrichment analysis helped perform two analytical procedures of subtype groups.Furthermore,Least absolute shrinkage and selection operator regression was employed to analyse and screen for a gene signature.Finally,quantitative PCR Was performed to detect the expression levels of signature genes in CRC.Results:The Single-cell RNA sequencing(GSE146771)dataset was integrated to obtain 9 cell clusters.The Single-sample gene set enrichment analysis showed that the related gene expression of T-cell subsets of different functional statuses could vary greatly between patients with GSE146771.Immune cell analysis of TCGA-CRC indicated an improved overall survival rate for patients with elevated Th2 cell abundance.Five-gene signature(Risk Score=-0.205×CDC25C-0.231×GSTCD-0.010×KPNA2-0.002×KIF15-0.171×ORC1)was developed by weighted correlation network analysis,and lasso Cox regression.Then,the risk prediction efficacy of the signature was validated in four GSE datasets.Furthermore,the expression of five genes was reduced in CRC tissue by quantitative PCR.Conclusion:Five-gene signature based on CRC heterogeneity was developed as a prognosis predictor,which can serve as a potential treatment target.

基于生成对抗网络的scRNA-seq批次效应校正方法

单细胞转录组测序是一种在单细胞水平上测量基因表达的技术,已经广泛应用于生命科学研究领域.由于实验条件、技术平台、样本来源等因素的差异,单细胞转录组数据的批次效应会影响数据的可靠性和准确性.因此,批次效应校正是单细胞转录组数据分析的一个重要预处理步骤.提出了一种基于生成对抗网络的单细胞转录组测序数据批次效应校正算法scBCMGAN,结合自编码器和零膨胀负二项分布等对数据进行重构,在潜在层部分通过生成对抗网络使目标批次数据向源批次数据进行学习,达到校正批次效应的目标.实验结果表明该方法在真实数据集上具有显著优势,能够有效校正批次效应,且校正后数据适用于下游分析.

A Feature Extraction Method for scRNA-seq Processing and Its Application on COVID-19 Data Analysis

Single-cell RNA-sequencing(scRNA-seq)is a rapidly increasing research area in biomed-ical signal processing.However,the high complexity of single-cell data makes efficient and accurate analysis difficult.To improve the performance of single-cell RNA data processing,two single-cell features calculation method and corresponding dual-input neural network structures are proposed.In this feature extraction and fusion scheme,the features at the cluster level are extracted by hier-archical clustering and differential gene analysis,and the features at the cell level are extracted by the calculation of gene frequency and cross cell frequency.Our experiments on COVID-19 data demonstrate that the combined use of these two feature achieves great results and high robustness for classification tasks.

scRNA-seq技术及其在动物研究中的应用与进展

传统动物转录组的研究主要是在器官或者组织水平上进行转录组测序,忽略了单个细胞在遗传方面的特殊性。scRNA-seq能够在单个细胞水平上揭示细胞内整体水平的基因表达状态和基因结构信息,帮助理解其基因型和表型之间的相互关系。本文主要就scRNA-seq技术的发展历史、在生物学研究中的作用、技术方法特点综述了现阶段在动物研究中的具体应用领域及具体案例,分析了其将来在动物及野生动物研究中更广泛应用前景,以期为动物的研究,特别是野生动物的研究提供方法指导。

基于对抗约束自编码器的scRNA-seq数据聚类模型

近年来,单细胞RNA测序技术(scRNA-seq)已经被广泛使用。使用scRNA-seq技术获取的单细胞RNA数据集日益增多,数据集中的细胞数目和基因数目也不断提高。随着数据集维度的提升,支撑聚类分析所需的数据量和计算量呈指数形式剧增,传统的单细胞聚类分析方法难以应对高维度、高噪声的scRNA-seq数据。基于对抗约束自编码器的scRNA-seq数据聚类模型(Adversarially Constrained ScRNA-seq data Clustering,ACSC)通过引入自编码器的方法,对原始的高维度稀疏数据集进行降维,能够在公开单细胞数据集上具有更好的聚类准确率。

scRNA-seq reveals that origin recognition complex subunit 6 regulates mouse spermatogonial cell proliferation and apoptosis via activation of Wnt/β-catenin signaling

The regulation of spermatogonial proliferation and apoptosis is of great significance for maintaining spermatogenesis.The single-cell RNA sequencing(scRNA-seq)analysis of the testis was performed to identify genes upregulated in spermatogonia.Using scRNAseq analysis,we identified the spermatogonia upregulated gene origin recognition complex subunit 6(Orc6),which is involved in DNA replication and cell cycle regulation;its protein expression in the human and mouse testis was detected by western blot and immunofluorescence.To explore the potential function of Orc6 in spermatogonia,the C18-4 cell line was transfected with control or Orc6 siRNA.Subsequently,5-ethynyl-2-deoxyuridine(EdU)and terminal deoxynucleotidyl transferase dUTP nick end labeling(TUNEL)assays,flow cytometry,and western blot were used to evaluate its effects on proliferation and apoptosis.It was revealed that ORC6 could promote proliferation and inhibit apoptosis of C18-4 cells.Bulk RNA sequencing and bioinformatics analysis indicated that Orc6 was involved in the activation of wingless/integrated(Wnt)/β-catenin signaling.Western blot revealed that the expression ofβ-catenin protein and its phosphorylation(Ser675)were significantly decreased when silencing the expression of ORC6.Our findings indicated that Orc6 was upregulated in spermatogonia,whereby it regulated proliferation and apoptosis by activating Wnt/β-catenin signaling.

Microbiota-mediated shaping of mouse spleen structure and immune function characterized by scRNA-seq and Stereo-seq

Gut microbes exhibit complex interactions with their hosts and shape an organism's immune system throughout its lifespan.As the largest secondary lymphoid organ,the spleen has a wide range of immunological functions.To explore the role of microbiota in regulating and shaping the spleen,we employ scRNA-seq and Stereo-seq technologies based on germ-free(GF)mice to detect differences in tissue size,anatomical structure,cell types,functions,and spatial molecular characteristics.We identify 18 cell types,9 subtypes of T cells,and 7 subtypes of B cells.Gene differential expression analysis reveals that the absence of microorganisms results in alterations in erythropoiesis within the red pulp region and congenital immune deficiency in the white pulp region.Stereo-seq results demonstrate a clear hierarchy of immune cells in the spleen,including marginal zone(MZ)macrophages,MZ B cells,follicular B cells and T cells,distributed in a well-defined pattern from outside to inside.However,this hierarchical structure is disturbed in GF mice.Ccr7 and Cxcl13 chemokines are specifically expressed in the spatial locations of T cells and B cells,respectively.We speculate that the microbiota may mediate the structural composition or partitioning of spleen immune cells by modulating the expression levels of chemokines.

Unveiling mitophagy-mediated molecular heterogeneity and development of a risk signature model for colorectal cancer by integrated scRNA-seq and bulk RNA-seq analysis

Background:Accumulating researchers have recognized mitophagy as a key player in tumors,but few studies have investigated its role in the tumor microenvironment(TME).Advances in the technology of single-cell RNA sequencing(scRNA-seq)have allowed unveiling the concealed features of the TME at cellular resolution.This study aimed to elucidate the role of mitophagy within the TME of colorectal cancer(CRC)and to establish a mitophagy-mediated risk model.Methods:We assessed mitophagy-related pathway activities at both single-cell and tissue levels.Subsequently,an unsupervised clustering algorithm was employed to identify mitophagy-mediated subtypes.Furthermore,we developed a mitophagy-mediated risk signature(MMRS)using least absolute shrinkage and selection operator(LASSO)Cox analysis and constructed a MMRS model incorporating the risk score and clinical variables.Subsequently,we used quantitative reverse transcription polymerase chain reaction analysis to verify the expression of the screened genes.Results:We retrieved and annotated a total of 14,719 cells from eight samples in the scRNA-seq GSE132465 data set.The activities of mitophagy-related pathways were uniformly upregulated in cancer cells.Integrating with bulk RNA-seq data,we identified two mitophagy-mediated clusters(C1 and C2)with distinct characteristics and prognoses.C2 was identified as a mitophagy-high cluster.Then,we developed a five-gene MMRS via LASSO Cox analysis in The Cancer Genome Atlas(TCGA)cohort.We utilized the GSE39582 cohort to validate the efficacy of our model.The expression of CX3CL1 and INHBB was upregulated in CRC tissues.Conclusions:The present study identified two mitophagy-mediated CRC subtypes with distinct features.Our MMRS may provide potential therapeutic strategies for CRC.The findings of our work offer novel insights into the involvement of mitophagy in CRC.

Cell specialization and coordination in Arabidopsis leaves upon pathogenic attack revealed by scRNA-seq

Plant defense responses involve several biological processes that allow plants to fight against pathogenic attacks.How these different processes are orchestrated within organs and depend on specific cell types is poorly known.Here,using single-cell RNA sequencing(scRNA-seq)technology on three independent biological replicates,we identified several cell populations representing the core transcriptional responses of wild-type Arabidopsis leaves inoculated with the bacterial pathogen Pseudomonas syringae DC3000.Among these populations,we retrieved major cell types of the leaves(mesophyll,guard,epidermal,companion,and vascular S cells)with which we could associate characteristic transcriptional reprogramming and regulators,thereby specifying different cell-type responses to the pathogen.Further analyses of transcriptional dynamics,on the basis of inference of cell trajectories,indicated that the different cell types,in addition to their characteristic defense responses,can also share similar modules of gene reprogramming,uncovering a ubiquitous antagonism between immune and susceptible processes.Moreover,it appears that the defense responses of vascular S cells,epidermal cells,and mesophyll cells can evolve along two separate paths,one converging toward an identical cell fate,characterized mostly by lignification and detoxification functions.As this divergence does not correspond to the differentiation between immune and susceptible cells,we speculate that this might reflect the discrimination between cellautonomous and non-cell-autonomous responses.Altogether our data provide an upgraded framework to describe,explore,and explain the specialization and the coordination of plant cell responses upon pathogenic challenge.

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测序在畜禽遗传育种中的研究进展

单细胞RNA测序(single cell RNA sequencing, scRNA-seq)是在单细胞水平上实现高通量测序的技术,可以用来研究特定细胞亚群基因表达的异质性,帮助我们识别未知或稀有的细胞类型,并为进一步的研究奠定基础。scRNA-seq技术的进步使其在肿瘤、临床医学和发育生物学等领域得到了广泛应用,但在畜禽育种中的研究还较少。本文介绍了scRNA-seq一般流程,着重阐述了其在畜禽的生殖分化、毛囊发育和肌肉生成等方面的研究现状以及前景,以期为scRNA-seq在畜禽遗传育种中的研究和应用提供理论依据。

单细胞测序筛选原发和复发胶质母细胞瘤中恒定存在的胶质瘤细胞

目的:胶质母细胞瘤是成人最常见、侵袭性最强的原发性高致死性脑肿瘤。基因表达似乎是预测胶质母细胞瘤患者生存和治疗反应的重要因素。然而,不同患者之间肿瘤细胞的异质性可能会阻碍找到一种癌症的恒定治疗靶点,因为不仅ndGBM和rGBM之间的遗传谱不同,不同患者之间甚至同一患者的肿瘤细胞亚群之间的遗传谱也不同。因此,在不同的ndGBM和rGBM患者中发现一种恒定的肿瘤细胞类型可能是更好地治疗胶质母细胞瘤的一种潜在方法。本文通过单细胞测序(single-cell RNA sequencing, scRNA-seq)筛选恒定的肿瘤细胞类型,比较新诊断的胶质母细胞瘤(ndGBM)和复发性胶质母细胞瘤(rGBM)组的遗传机制。方法:从Gene Expression Omnibus (GEO)数据库(GSE182109)下载3例ndGBM患者(3例样本)和2例rGBM患者(7例样本)胶质母细胞瘤样本的基因表达谱,并使用R包进行scRNA-seq。结果:共有59,400个胶母细胞瘤组织细胞及12,172个胶质瘤细胞最终通过质控,本研究成功筛选出了恒定的胶质瘤细胞亚型。此外,本研究还进行了拟时序分析、基因本体(Gene Ontology, GO)和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes, KEGG)富集分析、细胞–细胞相互作用和单细胞调控网络推测聚类。本研究还鉴定了ndGBM和rGBM组的关键基因基因和各组的不同功能。结论:本文筛选了WHO IV级、IDH野生型和甲基化的胶质母细胞瘤中存在于每个样本和每个发展阶段的一类肿瘤细胞亚型。进一步的研究需要通过分子实验来验证分子机制,并针对这些靶点开发诊断方法和药物治疗ndGBM和rGBM。

肌源性细胞分化的单细胞转录谱变化及细胞间通讯分析

【目的】基于单细胞转录组测序(single-cell RNA sequencing,scRNA-seq)揭示牛肌源性细胞分化中的基因表达谱变化,并探究介导细胞间通讯的配体-受体互作机制,为构建成肌分化的动态调控网络奠定基础。【方法】利用Seurat、ClusterProfiler、STRING、Cytoscape、CellChatDB和Monocle2等数据库或软件,对NCBI-GEO公共数据库中牛肌源性细胞单细胞转录组测序的原始数据进行了深入分析,包括细胞分群鉴定及差异基因表达谱、相关性、GO富集、PPI、细胞间通讯和拟时序分析等。【结果】根据基因表达相关性及标志性基因共鉴定出4个具有独特转录特征的细胞群Myoblasts、Myocytes、Fibroblasts和FAPs,通过Myoblasts亚群的基因表达谱比较及拟时序分化轨迹分析发现,各亚群之间异质性很强,其中Myoblasts_1为分化轨迹起点,Myoblasts_0和3处于分化早期阶段,而Myoblasts_2是肌肉特征表现最为明显的亚群,可能是临近形成Myocytes的后期阶段的Myoblasts;Myoblasts_2和Myocytes差异基因富集的肌肉相关GO term存在差异,各基因间存在复杂的蛋白互作关系;Myoblasts_0-5、Myocytes、Fibroblasts和FAPs同型或异型细胞间的通讯机制,涉及到PTN-NCL、IGF2-IGF2R和ANGPTL2-(ITGA5+ITGB1)等多种不同的配体-受体作用。【结论】肌源性细胞在分化过程中存在不断变化的基因表达谱和细胞间通讯,反映了复杂的动态异质性及分子调控机制。

基于单细胞测序数据分析养阴活胃合剂下调AQP3对MC细胞表型的影响及机制

目的 观察养阴活胃合剂对MC细胞(MNNG诱导人胃黏膜上皮细胞GES-1恶性转化)增殖、迁移、侵袭及凋亡的影响,探讨其下调AQP3抑制IL-10/JAK1/STAT3信号通路激活进而阻断或逆转慢性萎缩性胃炎(CAG)病变的作用机制。方法 选取GEO数据库中的CAG单细胞转录组测序数据,绘制数据的表达矩阵。采用R语言的Seurat 4.3.0包进行处理后分群绘制UMAP可视化图谱。将MC细胞分为养阴活胃合剂组(YYHWM组)、AQP3低表达慢病毒转染组(AQP3低表达组)、养阴活胃合剂+AQP3高表达慢病毒转染组(YYHWM+AQP3高表达组)并以MC细胞和正常人胃黏膜上皮细胞GES-1分别作为模型组(MC组)和空白对照组(Control组)。采用平板克隆、划痕实验、Transwell及流式细胞术检测细胞表型变化情况,采用ELISA检测细胞培养上清IL-10表达水平,Western blot检测酪氨酸激酶1(JAK1)、信号转导和转录激活因子3(STAT3)蛋白表达水平。结果 单细胞测序数据集分析显示AQP3在CAG样本及上皮细胞群中表达升高,AQP3可能通过IL-10抗炎性信号通路影响胃癌前病变病理进程。与MC组相比,AQP3低表达组和YYHWM组细胞侵袭、迁移、增殖能力减弱,凋亡率增加,细胞培养上清中的IL-10水平降低,细胞中JAK1、STAT3蛋白表达下调(P<0.05或P<0.01),YYHWM+AQP3高表达组差异均不显著(P>0.05)。结论 养阴活胃合剂可通过下调AQP3表达抑制IL-10/JAK1/STAT3信号通路激活进而减弱MC细胞侵袭、迁移及增殖能力,促进细胞凋亡进而阻断或逆转CAG病理进程。

基于单细胞测序技术解析冠状动脉粥样硬化患者平滑肌细胞的细胞间通信及关键基因

目的·利用单细胞RNA测序技术(single-cell RNA sequencing,scRNA-Seq)阐释冠状动脉粥样硬化(coronary atherosclerosis,CA)的细胞通信景观,挖掘主导细胞亚群及其关键基因。方法·下载GSE131778数据集并进行预处理、质控、降维聚类及注释;利用CellChat包进行细胞通信分析,识别主导细胞亚群。利用FindAllMarker函数,筛选主导细胞亚群与其他细胞亚群间的差异表达基因(differentially expressed genes,DEGs),并构建其蛋白相互作用(protein-protein interaction,PPI)网络,将Degree算法排序前五位的DEGs作为关键基因。将关键基因与CellChat分析出的细胞通信网络进行匹配和挖掘,获取关键基因参与的配体-受体对(ligand-receptor pair,L-R)及其介导的信号通路,并对结果进行可视化。构建动脉粥样硬化小鼠模型,并利用反转录聚合酶链式反应检测关键基因在颈动脉粥样硬化病变处的表达情况。结果·在CA病变处共鉴定出11个细胞亚群,包括平滑肌细胞、内皮细胞、巨噬细胞、单核细胞等。细胞通信分析结果显示,CellChat在11个细胞亚群中检测到70对显著的L-R和26条相关的信号通路;平滑肌细胞处于通信活跃状态,与其他细胞亚群间相互作用的次数和强度最显著,是主导细胞亚群。DEGs筛选结果显示,平滑肌细胞亚群和其他细胞亚群之间共有206个DEGs,其中ITGB2、PTPRC、CCL2、DCN、IGF1被识别为关键基因。关键基因介导的细胞通信分析结果显示:CCL2与ACKR1形成L-R,通过介导CCL信号通路参与平滑肌细胞与内皮细胞间的通信网络;ITGB2分别与ITGAM、ITGAX组成受体复合物,再与C3形成L-R介导补体信号通路,参与平滑肌细胞与巨噬细胞、单核细胞间的通信网络。动物实验对关键基因的验证结果同生物信息学分析的结果一致。结论·平滑肌细胞在CA病理过程中是主导细胞,与其他细胞间有广泛的通信网络,可通过CCL2-ACKR1、C3-(ITGAM+ITGB2)和C3-(ITGAX+ITGB2)介导的CCL和补体信号通路,与内皮细胞、巨噬细胞和单核细胞构建细胞通信网络。

基于单细胞转录组数据探究不同海拔牦牛心肌细胞通讯和基因表达差异

心脏作为血液循环最重要的器官在动物环境适应中发挥着重要的作用。心肌细胞是心脏主要的功能细胞,然而高海拔地区牦牛心肌细胞基因表达变化及细胞间通讯关系尚不清楚。为此,本研究以高海拔地区牦牛(青海祁连,海拔4000 m)和低海拔地区牦牛(青海循化,海拔2600 m)为研究对象,基于心脏组织10×单细胞转录组测序数据,对心肌细胞和心脏其他细胞进行细胞通讯及配体-靶基因调控预测,同时对高、低海拔牦牛心肌细胞差异表达基因进行功能注释分析,以期探究心肌细胞在牦牛适应高原环境过程中的作用。结果显示,牦牛心肌细胞与内皮细胞、上皮细胞的关联最强,心肌细胞-树突状细胞及心肌细胞-巨噬细胞两个“细胞对”中CD74_COAP和CD74_APP配受体表达量相对较高;配受体活力在TNF信号通路中相对较强;在免疫相关通路发挥重要作用的配体PTPRC、PECAM1、ITGB2、ANXA1、BDNF等对所有“细胞对”影响明显,且PI3K-Akt信号通路在配体-靶基因调控中潜力分值最高;高、低海拔牦牛心肌细胞中差异表达基因功能主要富集在代谢途径,其中氧化磷酸化、糖酵解代谢通路相关的基因表达明显增强。本研究结果提示,牦牛可通过加强心肌细胞与其他细胞之间的联系及调节免疫作用相关过程维持自身稳态;同时高海拔牦牛可通过增强心肌细胞有氧代谢和无氧代谢进而获取更多能量以适应高海拔严酷环境。

Multi-tissue scRNA-seq reveals immune cell landscape of turbot (Scophthalmus maximus)

In vertebrates,bony fishes possess not only innate immune cells but also T and B cells that are equivalent to those in mammals.However,the precise sub-cluster of immune cells in teleost fish remains largely unknown.Herein,we developed a dynamic bacterial infection model in turbot(Scophthalmus maximus)and created a fish immune cell landscape(FICL)for a primary lymphoid organ(head kidney),a secondary lymphoid organ(spleen),and barrier tissues(gill and posterior intestine).Moreover,through comprehensive characterization of the expression profiles of 16 clusters,including dendritic cells-like(DCs-like),macrophages(Mos),neutrophils,NK cells,as well as 12 sub-clusters of T and B cells,we found that CD8+CTLs,CD4-CD8-T,Th17 and ILC3-2 like cells posssa bifunctional role associated with cytotoxicity and immunoregulation during bacterial infection.To our knowledge,these results could provide a useful resource for a better understanding of immune cells in teleost fish and could act as a comprehensive knowledge base for assessing the evolutionary mechanism of adaptive immunity in vertebrates.

Intrinsic entropy model for feature selection of scRNA-seq data

Recent advances of single-cell RNA sequencing(scRNA-seq)technologies have led to extensive study of cellular heterogeneity and cell-to-cell variation.However,the high frequency of dropout events and noise in scRNA-seq data confounds the accuracy of the downstream analysis,i.e.clustering analysis,whose accuracy depends heavily on the selected feature genes.Here,by deriving an entropy decomposition formula,we propose a feature selection method,i.e.an intrinsic entropy(IE)model,to identify the informative genes for accurately clustering analysis.Specifically,by eliminating the‘noisy’fluctuation or extrinsic entropy(EE),we extract the IE of each gene from the total entropy(TE),i.e.TE=IE+EE.We show that the IE of each gene actually reflects the regulatory fluctuation of this gene in a cellular process,and thus high-IE genes provide rich information on celltype or state analysis.To validate the performance of the high-IE genes,we conduct computational analysis on both simulated datasets and real single-cell datasets by comparing with other representative methods.The results show that our IE model is not only broadly applicable and robust for different clustering and classification methods,but also sensitive for novel cell types.Our results also demonstrate that the intrinsic entropy/fluctuation of a gene serves as information rather than noise in contrast to its total entropy/fluctuation.

基于肿瘤相关巨噬细胞的子宫内膜癌预后模型建立和验证

目的:利用生物信息学方法研究探讨肿瘤相关巨噬细胞(TAMs)相关基因在子宫内膜癌(EC)的发生发展,发现新的EC肿瘤生物标志物,构建新的EC风险模型。方法:从公共数据库中获得EC患者的单细胞RNA测序(scRNA-seq)数据集。在EC肿瘤和健康组织,检测组织和巨噬细胞中的差异表达基因(DEGs)。采用加权基因共表达网络分析(WGCNA)确定巨噬细胞相关的关键基因,通过多种算法筛选交叉基因,确定为新的EC生物标志物。根据这些生物标志物计算风险评分,从而将EC分为高风险组和低风险组。在单变量和多变量Cox分析中评估了风险评分和临床特征,为构建列线图提供了独立的预后因素。结果:发现805个巨噬细胞DEGs、5691个额外DEGs、733个关键基因和43个常见基因。筛选出FBP1、LTB、PTGER4、PARVG、CCR7和HLA-DMB共6个生物标志物,构建了EC风险模型。确定了风险评分、年龄和肿瘤分期,生成了UCEC直方图。结论:确定了六个与TAM相关的预后生物标志物,并构建了一个风险模型,可为子宫内膜癌的治疗和研究提供依据。