Decreased GATA3 levels cause changed mouse cutaneous innate lymphoid cell fate, facilitating hair follicle recycling.

In mice, skin-resident type 2 innate lymphoid cells (ILC2s) exhibit some ILC3-like characteristics. However, the underlying mechanism remains elusive. Here, we observed lower expression of the ILC2 master regulator GATA3 specifically in cutaneous ILC2s (cILC2s) compared with canonical ILC2s, in line with its functionally divergent role in transcriptional control in cILC2s. Decreased levels of GATA3 enabled the expansion of RORγt fate-mapped (RORγtfm+) cILC2s after postnatal days, displaying certain similarities to ILC3s. Single-cell trajectory analysis showed a sequential promotion of the RORγtfm+ cILC2 divergency by RORγt and GATA3. Notably, during hair follicle recycling, these RORγtfm+ cILC2s accumulated around the hair follicle dermal papilla (DP) region to facilitate the process. Mechanistically, we found that GATA3-mediated integrin α3ß1 upregulation on RORγtfm+ cILC2s was required for their positioning around the DP. Overall, our study demonstrates a distinct regulatory role of GATA3 in cILC2s, particularly in promoting the divergence of RORγtfm+ cILC2s to facilitate hair follicle recycling.

Single cell analyses of cancer cells identified two regulatorily and functionally distinct categories in differentially expressed genes among tumor subclones.

To explore the feature of cancer cells and tumor subclones, we analyzed 101,065 single-cell transcriptomes from 12 colorectal cancer (CRC) patients and 92 single cell genomes from one of these patients. We found cancer cells, endothelial cells and stromal cells in tumor tissue expressed much more genes and had stronger cell-cell interactions than their counterparts in normal tissue. We identified copy number variations (CNVs) in each cancer cell and found correlation between gene copy number and expression level in cancer cells at single cell resolution. Analysis of tumor subclones inferred by CNVs showed accumulation of mutations in each tumor subclone along lineage trajectories. We found differentially expressed genes (DEGs) between tumor subclones had two populations: DEGCNV and DEGreg. DEGCNV, showing high CNV-expression correlation and whose expression differences depend on the differences of CNV level, enriched in housekeeping genes and cell adhesion associated genes. DEGreg, showing low CNV-expression correlation and mainly in low CNV variation regions and regions without CNVs, enriched in cytokine signaling genes. Furthermore, cell-cell communication analyses showed that DEGCNV tends to involve in cell-cell contact while DEGreg tends to involve in secreted signaling, which further support that DEGCNV and DEGreg are two regulatorily and functionally distinct categories.

Progress in single-cell multimodal sequencing and multi-omics data integration.

With the rapid advance of single-cell sequencing technology, cell heterogeneity in various biological processes was dissected at different omics levels. However, single-cell mono-omics results in fragmentation of information and could not provide complete cell states. In the past several years, a variety of single-cell multimodal omics technologies have been developed to jointly profile multiple molecular modalities, including genome, transcriptome, epigenome, and proteome, from the same single cell. With the availability of single-cell multimodal omics data, we can simultaneously investigate the effects of genomic mutation or epigenetic modification on transcription and translation, and reveal the potential mechanisms underlying disease pathogenesis. Driven by the massive single-cell omics data, the integration method of single-cell multi-omics data has rapidly developed. Integration of the massive multi-omics single-cell data in public databases in the future will make it possible to construct a cell atlas of multi-omics, enabling us to comprehensively understand cell state and gene regulation at single-cell resolution. In this review, we summarized the experimental methods for single-cell multimodal omics data and computational methods for multi-omics data integration. We also discussed the future development of this field.

The chromatin accessibility dynamics during cell fate specifications in zebrafish early embryogenesis.

Chromatin accessibility plays a critical role in the regulation of cell fate decisions. Although gene expression changes have been extensively profiled at the single-cell level during early embryogenesis, the dynamics of chromatin accessibility at cis-regulatory elements remain poorly studied. Here, we used a plate-based single-cell ATAC-seq method to profile the chromatin accessibility dynamics of over 10 000 nuclei from zebrafish embryos. We investigated several important time points immediately after zygotic genome activation (ZGA), covering key developmental stages up to dome. The results revealed key chromatin signatures in the first cell fate specifications when cells start to differentiate into enveloping layer (EVL) and yolk syncytial layer (YSL) cells. Finally, we uncovered many potential cell-type specific enhancers and transcription factor motifs that are important for the cell fate specifications.

Sirpα on tumor-associated myeloid cells restrains antitumor immunity in colorectal cancer independent of its interaction with CD47.

Immunosuppressive myeloid cells hinder immunotherapeutic efficacy in tumors, but the precise mechanisms remain undefined. Here, by performing single-cell RNA sequencing in colorectal cancer tissues, we found tumor-associated macrophages and granulocytic myeloid-derived suppressor cells increased most compared to their counterparts in normal tissue and displayed the highest immune-inhibitory signatures among all immunocytes. These cells exhibited significantly increased expression of immunoreceptor tyrosine-based inhibitory motif-bearing receptors, including SIRPA. Notably, Sirpa-/- mice were more resistant to tumor progression than wild-type mice. Moreover, Sirpα deficiency reprogramed the tumor microenvironment through expansion of TAM_Ccl8hi and gMDSC_H2-Q10hi subsets showing strong antitumor activity. Sirpa-/- macrophages presented strong phagocytosis and antigen presentation to enhance T cell activation and proliferation. Furthermore, Sirpa-/- macrophages facilitated T cell recruitment via Syk/Btk-dependent Ccl8 secretion. Therefore, Sirpα deficiency enhances innate and adaptive immune activation independent of expression of CD47 and Sirpα blockade could be a promising strategy to improve cancer immunotherapy efficacy.

The bone-liver interaction modulates immune and hematopoietic function through Pinch-Cxcl12-Mbl2 pathway.

Mesenchymal stromal cells (MSCs) are used to treat infectious and immune diseases and disorders; however, its mechanism(s) remain incompletely defined. Here we find that bone marrow stromal cells (BMSCs) lacking Pinch1/2 proteins display dramatically reduced ability to suppress lipopolysaccharide (LPS)-induced acute lung injury and dextran sulfate sodium (DSS)-induced inflammatory bowel disease in mice. Prx1-Cre; Pinch1f/f; Pinch2-/- transgenic mice have severe defects in both immune and hematopoietic functions, resulting in premature death, which can be restored by intravenous injection of wild-type BMSCs. Single cell sequencing analyses reveal dramatic alterations in subpopulations of the BMSCs in Pinch mutant mice. Pinch loss in Prx1+ cells blocks differentiation and maturation of hematopoietic cells in the bone marrow and increases production of pro-inflammatory cytokines TNF-α and IL-1ß in monocytes. We find that Pinch is critical for expression of Cxcl12 in BMSCs; reduced production of Cxcl12 protein from Pinch-deficient BMSCs reduces expression of the Mbl2 complement in hepatocytes, thus impairing the innate immunity and thereby contributing to infection and death. Administration of recombinant Mbl2 protein restores the lethality induced by Pinch loss in mice. Collectively, we demonstrate that the novel Pinch-Cxcl12-Mbl2 signaling pathway promotes the interactions between bone and liver to modulate immunity and hematopoiesis and may provide a useful therapeutic target for immune and infectious diseases.

Proline uptake promotes activation of lymphoid tissue inducer cells to maintain gut homeostasis.

Metabolic regulation is integral to the proper functioning of innate lymphoid cells, yet the underlying mechanisms remain elusive. Here, we show that disruption of exogenous proline uptake, either through dietary restriction or by deficiency of the proline transporter Slc6a7, in lymphoid tissue inducer (LTi) cells, impairs LTi activation and aggravates dextran sodium sulfate-induced colitis in mice. With an integrative transcriptomic and metabolomic analysis, we profile the metabolic characteristics of various innate lymphoid cell subsets and reveal a notable enrichment of proline metabolism in LTi cells. Mechanistically, defective proline uptake diminishes the generation of reactive oxygen species, previously known to facilitate LTi activation. Additionally, LTi cells deficient in Slc6a7 display downregulation of Cebpb and Kdm6b, resulting in compromised transcriptional and epigenetic regulation of interleukin-22. Furthermore, our study uncovers the therapeutic potential of proline supplementation in alleviating colitis. Therefore, these findings shed light on the role of proline in facilitating LTi activation and ultimately contributing to gut homeostasis.

A fast and globally optimal solution for RNA-seq quantification.

Alignment-based RNA-seq quantification methods typically involve a time-consuming alignment process prior to estimating transcript abundances. In contrast, alignment-free RNA-seq quantification methods bypass this step, resulting in significant speed improvements. Existing alignment-free methods rely on the Expectation-Maximization (EM) algorithm for estimating transcript abundances. However, EM algorithms only guarantee locally optimal solutions, leaving room for further accuracy improvement by finding a globally optimal solution. In this study, we present TQSLE, the first alignment-free RNA-seq quantification method that provides a globally optimal solution for transcript abundances estimation. TQSLE adopts a two-step approach: first, it constructs a k-mer frequency matrix A for the reference transcriptome and a k-mer frequency vector b for the RNA-seq reads; then, it directly estimates transcript abundances by solving the linear equation ATAx = ATb. We evaluated the performance of TQSLE using simulated and real RNA-seq data sets and observed that, despite comparable speed to other alignment-free methods, TQSLE outperforms them in terms of accuracy. TQSLE is freely available at https://github.com/yhg926/TQSLE.

Exploring the dynamics and influencing factors of CD4 T cell activation using single-cell RNA-seq.

T cell activation is a key event in adaptive immunity. However, the dynamics and influencing factors of T cell activation remain unclear. Here, we analyzed CD4 T cells that were stimulated with anti-CD3/CD28 under several conditions to explore the factors affecting T cell activation. We found a stimulated T subset (HSPhi T) highly expressing heat shock proteins, which was derived from stimulated naive T. We identified and characterized inert T, a stimulated T cell subset in transitional state from resting T to activated T. Interestingly, resting CXCR4low T responded to stimulation more efficiently than resting CXCR4hi T. Furthermore, stimulation of CD4 T in the presence of CD8 T resulted in more effector T and more homogeneous expressions of CD25, supporting that presence of CD8 T reduces the extreme response of T cells, which can be explained by regulation of CD4 T activation through CD8 T-initiated cytokine signaling and FAS/FASLG signaling.

Glucose-induced CRL4COP1-p53 axis amplifies glycometabolism to drive tumorigenesis.

The diabetes-cancer association remains underexplained. Here, we describe a glucose-signaling axis that reinforces glucose uptake and glycolysis to consolidate the Warburg effect and overcome tumor suppression. Specifically, glucose-dependent CK2 O-GlcNAcylation impedes its phosphorylation of CSN2, a modification required for the deneddylase CSN to sequester Cullin RING ligase 4 (CRL4). Glucose, therefore, elicits CSN-CRL4 dissociation to assemble the CRL4COP1 E3 ligase, which targets p53 to derepress glycolytic enzymes. A genetic or pharmacologic disruption of the O-GlcNAc-CK2-CSN2-CRL4COP1 axis abrogates glucose-induced p53 degradation and cancer cell proliferation. Diet-induced overnutrition upregulates the CRL4COP1-p53 axis to promote PyMT-induced mammary tumorigenesis in wild type but not in mammary-gland-specific p53 knockout mice. These effects of overnutrition are reversed by P28, an investigational peptide inhibitor of COP1-p53 interaction. Thus, glycometabolism self-amplifies via a glucose-induced post-translational modification cascade culminating in CRL4COP1-mediated p53 degradation. Such mutation-independent p53 checkpoint bypass may represent the carcinogenic origin and targetable vulnerability of hyperglycemia-driven cancer.

Anti-PD-1 therapy achieves favorable outcomes in HBV-positive non-liver cancer.

Anti-PD-1 therapy has shown promising outcomes in the treatment of different types of cancer. It is of fundamental interest to analyze the efficacy of anti-PD-1 therapy in cancer patients infected with hepatitis B virus (HBV) since the comorbidity of HBV and cancer is widely documented. We designed a multicenter retrospective study to evaluate the efficacy of anti-PD-1 therapy on non-liver cancer patients infected with HBV. We found anti-PD-1 therapy achieved much better outcomes in HBV+ non-liver cancer patients than their HBV- counterparts. We performed single-cell RNA sequencing (scRNA-seq) on peripheral blood mononuclear cells (PBMCs) from esophageal squamous cell carcinoma (ESCC) patients. We found both cytotoxicity score of T cells and MHC score of B cells significantly increased after anti-PD-1 therapy in HBV+ ESCC patients. We also identified CX3CR1high TEFF, a subset of CD8+ TEFF, associated with better clinical outcome in HBV+ ESCC patients. Lastly, we found CD8+ TEFF from HBV+ ESCC patients showing higher fraction of Exhaustionhi T than their HBV- counterpart. In summary, anti-PD-1 therapy on HBV+ non-liver cancer patients is safe and achieves better outcomes than that on HBV- non-liver cancer patients, potentially because HBV+ patients had higher fraction of Exhaustionhi T, which made them more efficiently respond to anti-PD-1 therapy.

Dissecting Complex Traits Using Omics Data: A Review on the Linear Mixed Models and Their Application in GWAS.

Genome-wide association study (GWAS) is the most popular approach to dissecting complex traits in plants, humans, and animals. Numerous methods and tools have been proposed to discover the causal variants for GWAS data analysis. Among them, linear mixed models (LMMs) are widely used statistical methods for regulating confounding factors, including population structure, resulting in increased computational proficiency and statistical power in GWAS studies. Recently more attention has been paid to pleiotropy, multi-trait, gene-gene interaction, gene-environment interaction, and multi-locus methods with the growing availability of large-scale GWAS data and relevant phenotype samples. In this review, we have demonstrated all possible LMMs-based methods available in the literature for GWAS. We briefly discuss the different LMM methods, software packages, and available open-source applications in GWAS. Then, we include the advantages and weaknesses of the LMMs in GWAS. Finally, we discuss the future perspective and conclusion. The present review paper would be helpful to the researchers for selecting appropriate LMM models and methods quickly for GWAS data analysis and would benefit the scientific society.

Comprehensive mapping of alternative polyadenylation site usage and its dynamics at single-cell resolution.

Alternative polyadenylation (APA) plays an important role in posttranscriptional gene regulation such as transcript stability and translation efficiency. However, our knowledge about APA dynamics at the single-cell level is largely unexplored. Here, we developed single-cell polyadenylation sequencing, a strand-specific approach for sequencing the 3' end of transcripts, to investigate the landscape of APA at the single-cell level. By analyzing several cell lines, we found many genes using multiple polyA sites in bulk data are prone to use only one polyA site in each single cell. Interestingly, cell cycle genes were significantly enriched in genes with high variation in polyA site usages. Furthermore, the 414 genes showing a polyA site usage switch after cell synchronization enriched cell cycle genes, while the differentially expressed genes after cell synchronization did not enrich cell cycle genes. We further identified 812 genes showing polyA site usage changes between neighboring cell cycles, which were grouped into six clusters, with cell phase-specific functional categories enriched in each cluster. Deletion of one polyA site in MSL1 and SCCPDH results in slower and faster cell cycle progression, respectively, supporting polyA site usage switch played an important role in cell cycle. These results indicate that APA is an important layer for cell cycle regulation.

ISSAAC-seq enables sensitive and flexible multimodal profiling of chromatin accessibility and gene expression in single cells.

Joint profiling of chromatin accessibility and gene expression from the same single cell provides critical information about cell types in a tissue and cell states during a dynamic process. Here, we develop in situ sequencing hetero RNA-DNA-hybrid after assay for transposase-accessible chromatin-sequencing (ISSAAC-seq), a highly sensitive and flexible single-cell multi-omics method to interrogate chromatin accessibility and gene expression from the same single nucleus. We demonstrated that ISSAAC-seq is sensitive and provides high quality data with orders of magnitude more features than existing methods. Using the joint profiles from over 10,000 nuclei from the mouse cerebral cortex, we uncovered major and rare cell types and cell-type specific regulatory elements and identified heterogeneity at the chromatin level within established cell types defined by gene expression. Finally, we revealed distinct dynamics and relationships of gene expression and chromatin accessibility during an oligodendrocyte maturation trajectory.

Single-Cell RNA Sequencing Unravels Upregulation of Immune Cell Crosstalk in Relapsed Pediatric Ependymoma.

Ependymoma (EPN) is a malignant glial tumor occurring throughout central nervous system, which commonly presents in children. Although recent studies have characterized EPN samples at both the bulk and single-cell level, intratumoral heterogeneity across subclones remains a confounding factor that impedes understanding of EPN biology. In this study, we generated a high-resolution single-cell dataset of pediatric ependymoma with a particular focus on the comparison of subclone differences within tumors and showed upregulation of cilium-associated genes in more highly differentiated subclone populations. As a proxy to traditional pseudotime analysis, we applied a novel trajectory scoring method to reveal cellular compositions associated with poor survival outcomes across primary and relapsed patients. Furthermore, we identified putative cell-cell communication features between relapsed and primary samples and showed upregulation of pathways associated with immune cell crosstalk. Our results revealed both inter- and intratumoral heterogeneity in EPN and provided a framework for studying transcriptomic signatures of individual subclones at single-cell resolution.

Reinvestigation of Classic T Cell Subsets and Identification of Novel Cell Subpopulations by Single-Cell RNA Sequencing.

Classic T cell subsets are defined by a small set of cell surface markers, while single-cell RNA sequencing (scRNA-seq) clusters cells using genome-wide gene expression profiles. The relationship between scRNA-seq clustered populations (scCPops) and cell surface marker-defined classic T cell subsets remains unclear. In this article, we integrated six bead-enriched T cell subsets with 62,235 single-cell transcriptomes from human PBMCs and clustered them into nine scCPops. Bead-enriched CD4+/CD45RA+/CD25- naive T and CD8+/CD45RA+ naive T cells were mainly clustered into their scCPop counterparts, while cells from the other T cell subsets were assigned to multiple scCPops, including mucosal-associated invariant T cells and NKT cells. The multiple T cell subsets forming one scCPop exhibit similar expression patterns, but not vice versa, indicating scCPop is a more homogeneous cell population with similar cell states. Interestingly, we discovered and named IFN signaling-associated gene (ISAG) high T (ISAGhi T) cells, a T cell subpopulation that highly expressed ISAGs. We further enriched ISAGhi T cells from human PBMCs by FACS of BST2 for scRNA-seq analyses. The ISAGhi T cell cluster disappeared on t-distributed stochastic neighbor embedding plot after removing ISAGs, whereas the ISAGhi T cell cluster showed up by analysis of ISAGs alone, indicating ISAGs are the major contributor of the ISAGhi T cell cluster. BST2+ and BST2- T cells showing different efficiencies of T cell activation indicate that a high level of ISAGs may contribute to quick immune responses.

A Comprehensive Characterization of Monoallelic Expression During Hematopoiesis and Leukemogenesis via Single-Cell RNA-Sequencing.

Single-cell RNA-sequencing (scRNA-seq) is becoming a powerful tool to investigate monoallelic expression (MAE) in various developmental and pathological processes. However, our knowledge of MAE during hematopoiesis and leukemogenesis is limited. In this study, we conducted a systematic interrogation of MAEs in bone marrow mononuclear cells (BMMCs) at single-cell resolution to construct a MAE atlas of BMMCs. We identified 1,020 constitutive MAEs in BMMCs, which included imprinted genes such as MEG8, NAP1L5, and IRAIN. We classified the BMMCs into six cell types and identified 74 cell type specific MAEs including MTSS1, MOB1A, and TCF12. We further identified 114 random MAEs (rMAEs) at single-cell level, with 78.1% single-allele rMAE and 21.9% biallelic mosaic rMAE. Many MAEs identified in BMMCs have not been reported and are potentially hematopoietic specific, supporting MAEs are functional relevance. Comparison of BMMC samples from a leukemia patient with multiple clinical stages showed the fractions of constitutive MAE were correlated with fractions of leukemia cells in BMMCs. Further separation of the BMMCs into leukemia cells and normal cells showed that leukemia cells have much higher constitutive MAE and rMAEs than normal cells. We identified the leukemia cell-specific MAEs and relapsed leukemia cell-specific MAEs, which were enriched in immune-related functions. These results indicate MAE is prevalent and is an important gene regulation mechanism during hematopoiesis and leukemogenesis. As the first systematical interrogation of constitutive MAEs, cell type specific MAEs, and rMAEs during hematopoiesis and leukemogenesis, the study significantly increased our knowledge about the features and functions of MAEs.

A topology-preserving dimensionality reduction method for single-cell RNA-seq data using graph autoencoder.

Dimensionality reduction is crucial for the visualization and interpretation of the high-dimensional single-cell RNA sequencing (scRNA-seq) data. However, preserving topological structure among cells to low dimensional space remains a challenge. Here, we present the single-cell graph autoencoder (scGAE), a dimensionality reduction method that preserves topological structure in scRNA-seq data. scGAE builds a cell graph and uses a multitask-oriented graph autoencoder to preserve topological structure information and feature information in scRNA-seq data simultaneously. We further extended scGAE for scRNA-seq data visualization, clustering, and trajectory inference. Analyses of simulated data showed that scGAE accurately reconstructs developmental trajectory and separates discrete cell clusters under different scenarios, outperforming recently developed deep learning methods. Furthermore, implementation of scGAE on empirical data showed scGAE provided novel insights into cell developmental lineages and preserved inter-cluster distances.

The Tyrosine Kinase-Driven Networks of Novel Long Non-coding RNAs and Their Molecular Targets in Myeloproliferative Neoplasms.

Recent research has focused on the mechanisms by which long non-coding RNAs (lncRNAs) modulate diverse cellular processes such as tumorigenesis. However, the functional characteristics of these non-coding elements in the genome are poorly understood at present. In this study, we have explored several mechanisms that involve the novel lncRNA and microRNA (miRNA) axis participating in modulation of drug response and the tumor microenvironment of myeloproliferative neoplasms (MPNs). We identified novel lncRNAs via mRNA sequencing that was applied to leukemic cell lines derived from BCR-ABL1-positive and JAK2-mutant MPNs under treatment with therapeutic tyrosine kinase inhibitors (TKI). The expression and sequence of novel LNC000093 were further validated in both leukemic cells and normal primary and pluripotent cells isolated from human blood, including samples from patients with chronic myelogenous leukemia (CML). Downregulation of LNC000093 was validated in TKI-resistant CML while a converse expression pattern was observed in blood cells isolated from TKI-sensitive CML cases. In addition to BCR-ABL1-positive CML cells, the driver mutation JAK2-V617F-regulated lncRNA BANCR axis was further identified in BCR-ABL1-negative MPNs. Further genome-wide validation using MPN patient specimens identified 23 unique copy number variants including the 7 differentially expressed lncRNAs from our database. The newly identified LNC000093 served as a competitive endogenous RNA for miR-675-5p and reversed the imatinib resistance in CML cells through regulating RUNX1 expression. The extrinsic function of LNC000093 in exosomal H19/miR-675-induced modulation for the microenvironment was also determined with significant effect on VEGF expression.

A plate-based single-cell ATAC-seq workflow for fast and robust profiling of chromatin accessibility.

Profiling chromatin accessibility at the single-cell level provides critical information about cell type composition and cell-to-cell variation within a complex tissue. Emerging techniques for the interrogation of chromatin accessibility in individual cells allow investigation of the fundamental mechanisms that lead to the variability of different cells. This protocol describes a fast and robust method for single-cell chromatin accessibility profiling based on the assay for transposase-accessible chromatin using sequencing (ATAC-seq). The method combines up-front bulk Tn5 tagging of chromatin with flow cytometry to isolate single nuclei or cells. Reagents required to generate sequencing libraries are added to the same well in the plate where cells are sorted. The protocol described here generates data of high complexity and excellent signal-to-noise ratio and can be combined with index sorting for in-depth characterization of cell types. The whole experimental procedure can be finished within 1 or 2 d with a throughput of hundreds to thousands of nuclei, and the data can be processed by the provided computational pipeline. The execution of the protocol only requires basic techniques and equipment in a molecular biology laboratory with flow cytometry support.