Analysis Of Developmental Trajectories Research Articles

Single-cell profiling of intrahepatic immune cells reveals an expansion of tissue-resident cytotoxic CD4+ T lymphocyte subset associated with pathogenesis of alcoholic-associated liver diseases

The immunological mechanisms underpinning the pathogenesis of alcoholic-associated liver disease (ALD) remain incompletely elucidated. This study aims to explore the transcriptomic profiles of hepatic immune cells in ALD compared to healthy individuals and those with metabolic dysfunction-associated steatotic liver disease (MASLD). We utilized single-cell RNA sequencing to analyze liver samples from healthy subjects, MASLD, and ALD patients, focusing on the immune cell landscapes within the liver. Key alterations in immune cell subsets were further validated using liver biopsy samples from additional patient cohorts. We observed a significant accumulation of CD4+ T cells in ALD patients' livers, surpassing the prevalence of CD8+ T cells, in contrast to MASLD and healthy counterparts, while natural killer (NK) cells and γδT cells exhibited reduced intrahepatic infiltration. In-depth transcriptional and developmental trajectory analyses unveiled that a distinct CD4+ subset characterized by granzyme K (GZMK) expression, displaying a tissue-resident signature and terminal effector state, prominently enriched among CD4+ T cells infiltrating the livers of ALD patient. Subsequent examination of an independent ALD patient cohort corroborated the substantial enrichment of GZMK+CD4+ T lymphocytes, primarily within liver fibrotic zones, suggesting their potential involvement in disease progression. Additionally, we noted shifts in myeloid populations, with expanded APOE+ macrophage and FCGR3B+ monocyte subsets in ALD samples relative to MASLD and healthy tissues. In summary, this study unravels the intricate cellular diversity within hepatic immune cell populations, highlighting the pivotal immune pathogenic role of the GZMK+CD4+ T lymphocyte subset in ALD pathogenesis.

UQCRB and LBH are correlated with Gleason score progression in prostate cancer: Spatial transcriptomics and experimental validation

Prostate cancer (PCa) is a multifocal disease characterized by genomic and phenotypic heterogeneity within a single gland. In this study, Visium spatial transcriptomics (ST) analysis was applied to PCa tissues with different histological structures to infer the molecular events involved in Gleason score (GS) progression. The spots in tissue sections were classified into various groups using Principal Component Analysis (PCA) and Louvain clustering analysis based on transcriptome data. Anotation of the spots according to GS revealed notable similarities between transcriptomic profiles and histologically identifiable structures. The accuracy of macroscopic GS determination was bioinformatically verified through malignancy-related feature analysis, specifically inferred copy number variation (inferCNV), as well as developmental trajectory analyses, such as diffusion pseudotime (DPT) and partition-based graph abstraction (PAGA). Genes related to GS progression were identified from the differentially expressed genes (DEGs) through pairwise comparisons of groups along a GS gradient. The proteins encoded by the representative oncogenes UQCRB and LBH were found to be highly expressed in advanced-stage PCa tissues. Knockdown of their mRNAs significantly suppressed PCa cell proliferation and invasion. These findings were validated using The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset, as well as through histological and cytological experiments. The results presented here establish a foundation for ST-based evaluation of GS progression and provide valuable insights into the GS progression-related genes UQCRB and LBH.

Beyond average outcomes: A latent profile analysis of diverse developmental trajectories in preterm and early term-born children from the Adolescent Brain Cognitive Development study.

Preterm birth poses a major public health challenge, with significant and heterogeneous developmental impacts. Latent profile analysis was applied to the National Institutes of Health Toolbox performance of 1891 healthy prematurely born children from the Adolescent Brain and Cognitive Development study (970 boys, 921 girls; 10.00 ± 0.61 years; 1.3% Asian, 13.7% Black, 17.5% Hispanic, 57.0% White, 10.4% Other). Three distinct neurocognitive profiles emerged: consistently performing above the norm (19.7%), mixed scores (41.0%), and consistently performing below the norm (39.3%). These profiles were associated with lasting cognitive, neural, behavioral, and academic differences. These findings underscore the importance of recognizing diverse developmental trajectories in prematurely born children, advocating for personalized diagnosis and intervention to enhance care strategies and long-term outcomes for this heterogeneous population.

A developmental trajectory of latent inhibition.

Latent inhibition is said to occur when learning about the relationship between a cue and an outcome proceeds more readily when the cue is novel relative to when the cue has been rendered familiar through mere preexposure. Previous studies suggest that latent inhibition, while evident in 4- to 5-year-old children, is attenuated or even absent in older children. There are, however, acknowledged shortcomings associated with previous demonstrations of this effect, which we attempted to overcome using a letter prediction task that has been employed in recent studies of latent inhibition in adults. One hundred and seventy-five 4- to 14-year-old children and 175 young adults completed a letter prediction task, with a latent inhibition manipulation embedded within it. Using developmental trajectory analysis we found, contrary to other studies, an increase in the magnitude of latent inhibition as children age, with the effect becoming significant when children were around 6.7 years of age. Model comparison revealed that a linear function best described the relationship between latent inhibition and age. We discuss these findings in the context of theories of learning and attention, and consider the role of concurrent task type as a factor that determines the developmental trajectory of latent inhibition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

ETMR-14. THE SINGLE-CELL LANDSCAPE OF PINEOBLASTOMA IDENTIFIES AN ONCOGENIC PHOTORECEPTOR PROGRAM AS A TUMORIGENIC VULNERABILITY UNIFYING DISTINCT EMBRYONAL CNS TUMOR ENTITIES

Abstract BACKGROUND Pineoblastoma (PB) is a rare and aggressive childhood brain tumor with highly variable outcomes. PB is diagnostically characterized by expression of the photoreceptor identity transcription factor CRX, while tumors can be further classified into molecular subgroups (PB-miRNA1, PB-miRNA2, PB-MYC/FOXR2, and PB-RB1), each marked by unique clinico-molecular features. However, developmental origins of PB subgroup heterogeneity and mechanisms governing malignancy remain unknown. METHODS We assembled a single-nucleus RNA-sequencing cohort (n=25) of primary PB tumors, including cases from all subgroups. A single-cell transcriptional atlas of the mouse pineal gland, covering 11 developmental stages (E11-P21), was created as a reference to map PB subgroup origins. Developmental trajectory analysis in the pineal gland showed a progression from pinealocyte progenitors to an early-, mid- and mature stage of pinealocyte differentiation. RESULTS Cross-species bioinformatics identified significant associations between PB subgroups and pinealocyte progenitors, mitotic cells expressing Crx, Otx2 and Neurod1. Single-nuclei gene regulatory networks in PB tumors identified CRX, OTX2, and NEUROD1 as master regulators of an oncogenic photoreceptor program conserved across PB subgroups. Surprisingly, this photoreceptor program was also highly expressed in retinoblastoma (RETB) and Group3 medulloblastoma (G3-MB). The molecular association between PB, RETB and G3-MB was further supported by DNA methylation and bulk RNA-seq, suggesting up-regulation of the oncogenic photoreceptor program is a unifying molecular connection of distinct CNS tumor entities. Querying this photoreceptor program across the developing pineal gland, retina, and cerebellum, identified conserved yet transient expression within each developmental lineage, suggesting the photoreceptor program may be a developmental vulnerability. In-vivo dependency assays for Otx2 and Neurod1 performed in a novel genetically engineered mouse model of the PB-RB subgroup confirmed their selective essentiality in photoreceptor-positive tumors. CONCLUSIONS Collectively, these findings uncover the photoreceptor program as a shared oncogenic dependency underlying anatomically distinct embryonal CNS tumors and provide a path towards rational clinical translation.

Unraveling Divergent Transcriptomic Profiles: A Comparative Single-Cell RNA Sequencing Study of Epithelium, Gingiva, and Periodontal Ligament Tissues.

The periodontium comprising periodontal ligament (PDL), gingiva, and epithelium play crucial roles in maintaining tooth integrity and function. Understanding tissue cellular composition and gene expression is crucial for illuminating periodontal pathophysiology. This study aimed to identify tissue-specific markers via scRNA-Seq. Primary human PDL, gingiva, and epithelium tissues (n = 7) were subjected to cell hashing and sorting. scRNA-Seq library preparation using 10× Genomics protocol and Illumina sequencing was conducted. The analysis was performed using Cellranger (v3.1.0), with downstream analysis via R packages Seurat (v5.0.1) and SCORPIUS (v1.0.9). Investigations identified eight distinct cellular clusters, revealing the ubiquitous presence of epithelial and gingival cells. PDL cells evolved in two clusters with numerical superiority. The other clusters showed varied predominance regarding gingival and epithelial cells or an equitable distribution of both. The cluster harboring most cells mainly consisted of PDL cells and was present in all donors. Some of the other clusters were also tissue-inherent, while the presence of others was environmentally influenced, revealing variability across donors. Two clusters exhibited genetic profiles associated with tissue development and cellular integrity, respectively, while all other clusters were distinguished by genes characteristic of immune responses. Developmental trajectory analysis uncovered that PDL cells may develop after epithelial and gingival cells, suggesting the inherent PDL cell-dominated cluster as a final developmental stage. This single-cell RNA sequencing study delineates the hierarchical organization of periodontal tissue development, identifies tissue-specific markers, and reveals the influence of environmental factors on cellular composition, advancing our understanding of periodontal biology and offering potential insights for therapeutic interventions.

Targeting nucleotide metabolic pathways in colorectal cancer by integrating scRNA-seq, spatial transcriptome, and bulk RNA-seq data

BackgroundColorectal cancer is a malignant tumor of the digestive system originating from abnormal cell proliferation in the colon or rectum, often leading to gastrointestinal symptoms and severe health issues. Nucleotide metabolism, which encompasses the synthesis of DNA and RNA, is a pivotal cellular biochemical process that significantly impacts both the progression and therapeutic strategies of colorectal cancerMethodsFor single-cell RNA sequencing (scRNA-seq), five functions were employed to calculate scores related to nucleotide metabolism. Cell developmental trajectory analysis and intercellular interaction analysis were utilized to explore the metabolic characteristics and communication patterns of different epithelial cells. These findings were further validated using spatial transcriptome RNA sequencing (stRNA-seq). A risk model was constructed using expression profile data from TCGA and GEO cohorts to optimize clinical decision-making. Key nucleotide metabolism-related genes (NMRGs) were functionally validated by further in vitro experiments.ResultsIn both scRNA-seq and stRNA-seq, colorectal cancer (CRC) exhibited unique cellular heterogeneity, with myeloid cells and epithelial cells in tumor samples displaying higher nucleotide metabolism scores. Analysis of intercellular communication revealed enhanced signaling pathways and ligand-receptor interactions between epithelial cells with high nucleotide metabolism and fibroblasts. Spatial transcriptome sequencing confirmed elevated nucleotide metabolism states in the core region of tumor tissue. After identifying differentially expressed NMRGs in epithelial cells, a risk prognostic model based on four genes effectively predicted overall survival and immunotherapy outcomes in patients. High-risk group patients exhibited an immunosuppressive microenvironment and relatively poorer prognosis and responses to chemotherapy and immunotherapy. Finally, based on data analysis and a series of cellular functional experiments, ACOX1 and CPT2 were identified as novel therapeutic targets for CRC.ConclusionIn this study, a comprehensive analysis of NMRGs in CRC was conducted using a combination of single-cell sequencing, spatial transcriptome sequencing, and high-throughput data. The prognostic model constructed with NMRGs shows potential as a standalone prognostic marker for colorectal cancer patients and may significantly influence the development of personalized treatment approaches for CRC.

Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis

We present a gene-level regulatory model, single-cell ATAC + RNA linking (SCARlink), which predicts single-cell gene expression and links enhancers to target genes using multi-ome (scRNA-seq and scATAC–seq co-assay) sequencing data. The approach uses regularized Poisson regression on tile-level accessibility data to jointly model all regulatory effects at a gene locus, avoiding the limitations of pairwise gene–peak correlations and dependence on peak calling. SCARlink outperformed existing gene scoring methods for imputing gene expression from chromatin accessibility across high-coverage multi-ome datasets while giving comparable to improved performance on low-coverage datasets. Shapley value analysis on trained models identified cell-type-specific gene enhancers that are validated by promoter capture Hi-C and are 11× to 15× and 5× to 12× enriched in fine-mapped eQTLs and fine-mapped genome-wide association study (GWAS) variants, respectively. We further show that SCARlink-predicted and observed gene expression vectors provide a robust way to compute a chromatin potential vector field to enable developmental trajectory analysis.

Loss of chromosome Y in regulatory T cells

BackgroundMosaic loss of chromosome Y (LOY) in leukocytes is the most prevalent somatic aneuploidy in aging humans. Men with LOY have increased risks of all-cause mortality and the major causes of death, including many forms of cancer. It has been suggested that the association between LOY and disease risk depends on what type of leukocyte is affected with Y loss, with prostate cancer patients showing higher levels of LOY in CD4 + T lymphocytes. In previous studies, Y loss has however been observed at relatively low levels in this cell type. This motivated us to investigate whether specific subsets of CD4 + T lymphocytes are particularly affected by LOY. Publicly available, T lymphocyte enriched, single-cell RNA sequencing datasets from patients with liver, lung or colorectal cancer were used to study how LOY affects different subtypes of T lymphocyte. To validate the observations from the public data, we also generated a single-cell RNA sequencing dataset comprised of 23 PBMC samples and 32 CD4 + T lymphocytes enriched samples.ResultsRegulatory T cells had significantly more LOY than any other studied T lymphocytes subtype. Furthermore, LOY in regulatory T cells increased the ratio of regulatory T cells compared with other T lymphocyte subtypes, indicating an effect of Y loss on lymphocyte differentiation. This was supported by developmental trajectory analysis of CD4 + T lymphocytes culminating in the regulatory T cells cluster most heavily affected by LOY. Finally, we identify dysregulation of 465 genes in regulatory T cells with Y loss, many involved in the immunosuppressive functions and development of regulatory T cells.ConclusionsHere, we show that regulatory T cells are particularly affected by Y loss, resulting in an increased fraction of regulatory T cells and dysregulated immune functions. Considering that regulatory T cells plays a critical role in the process of immunosuppression; this enrichment for regulatory T cells with LOY might contribute to the increased risk for cancer observed among men with Y loss in leukocytes.

Abstract PR13: Single-cell mapping reveals a common origin for diverse subtypes of pancreatic cancer

Abstract The detailed understanding of the molecular basis of tumor initiation and progression is essential for the effective management and treatment of any cancer, including pancreatic cancer. To determine if the stem and progenitor cells can serve as cells of origin for pancreatic cancer, we have created a new mouse strain in which tamoxifen inducible Cre (CreERT2) is knocked into the endogenous locus encoding the stem cell regulator Musashi2 (Msi2). When crossed to a Cre-regulatable Myc transgenic (CAG-LSL-MycT58A) strain, Msi2-CreERT2 mice develop multiple pancreatic cancer subtypes: pancreatic ductal adenocarcinoma (PDAC), adenosquamous carcinoma of the pancreas (ASCP), and acinar cell carcinoma (ACC) following Myc activation in Msi2+ cells in the adult stage. A combination of single-cell genomics with computational analysis of developmental states and lineage trajectories of tumors in our model suggests that oncogenic Myc preferentially triggers the transformation of the most immature subset of Msi2+ cells, leading to the rise of a common pool of pre-cancer cells with multi-lineage potential. These pre-cancer cells subsequently take distinct fates within the same mice by activation of distinct transcriptional programs and large-scale genomic changes. Additionally, combining transcriptomic and functional genomic approaches, we have identified hyaluronan-mediated motility receptor (HMMR) as a potential novel dependency in mouse and human ASCP cells, providing a framework to develop interception strategies for this lethal disease. In summary, our study shows that multiple pancreatic cancer subtypes can arise from a common pool of Msi2+ cells and provides a powerful framework to understand and control the programs that shape divergent fates in pancreatic cancer. Citation Format: Nirakar Rajbhandari, Michael Hamilton, Tannishtha Reya. Single-cell mapping reveals a common origin for diverse subtypes of pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr PR13.

Mechanisms of Aging Vary with Developmental Stages in the Human Hematopoietic Trajectory

Background : Hematopoietic stem and progenitor cells (HSPCs) undergo functional changes with age. An unresolved issue is whether aging is induced by a shift in intrinsic state in which all HSPCs undergo coordinated changes in functional potential, or by clonal evolution of a senescent population.Identification of senescent cells in human hematopoiesis poses another challenge. In this study, we have identified lineage-specific, senescence-associated pathways at different developmental stages of HSPCs and have developed an “aging signature HSC” for non-primed human HSCs. Methods: HSPCs (CD34+ cells) were isolated from the bone marrow of healthy human subjects (old = >60 years; young = 21 to <35 years). Single-cell RNA-sequencing (scRNAseq) studies and downstream analysis were performed using different R packages for normalization, dimension reduction, clustering, classification, pseudotime ordering, and developmental trajectory analyses. Gene Set Enrichment Analysis, GSEA (version 4.3.2., Broad Institute, Inc) was applied to identify pathways and processes that were coordinately up- or down-regulated with aging. Results: HSPCs (CD34+ cells) were derived from 13 healthy human subjects (old subjects n = 6; young subjects n = 7). There were 26,076 genes identified. The HSPCs were ordered and classified along their developmental trajectory during differentiation processes from (1) hematopoietic stem cells (HSC) to (2) myeloid-lymphoid progenitors (MLP), (3) megakaryocyte-erythrocyte progenitors (MEP), (4) granulocytic-monocytic progenitors (GMP), (5) granulocyte- (G), and (6) monocyte- (Mono) progenitors, (7) dendritic cell (DC), (8) erythroid progenitors (E), as well as various subsets of lymphocytes (Ly1 to Ly4). The results are depicted in Figure 1A. Remarkable are the increases in HSCs (p < 0.05) and in Ly4 (p < 0.001) in old subjects. The Kolmogorov-Smirnov test showed a significant delay in the developmental “pseudotimes” of HSCs (p < 0.001) and of Ly4 (p < 0.05). We then compared the differences in GSEA between old and young subjects in each of the following clusters: (A) whole HSPCs; (B) HSPCs along myeloid pathway (mye-HSPC); (C) HSC-MLP-MEP; (D) HSC. The major findings relevant to aging are summarized in Fig. 1B. Pathways that are significantly increased in the old subjects and throughout all comparisons include: “Formation of senescence associated heterochromatin foci”, “Aging signature HSC”, “DNA damage telomere stress induced senescence”, and “TNFR1 induced NFKB signaling pathway”. “Hypoxia”, “P53 pathway”, “IL2 signaling”, “TNFA signaling via NFKB” were elevated upon enrichment of the primitive HSC population, while other pathways decreased: “Senescence associated secretory phenotype (SASP)”, “DNA methylation”. “Cell cycle” and “DNA repair” are consistently more abundant in young subjects. We analyzed the 512 cells in the HSC cluster with higher resolution and were able to identify a sub-cluster “MPP2A” that is significantly increased in old subjects (4.5% of all HSPCs and 28.5% of HSCs, versus 1.9% and 12.9% respectively in young subjects; p < 0.005). The results are depicted in the highlighted circles in Fig. 1A. This population is quiescent and is highly enriched in “aging signature HSC” in old subjects (p <0.0001). Prominent examples of these signature genes within this list are shown in Fig. 1C). Further along the trajectory, a unique population of B cells “Ly4” was found predominantly in old subjects. The transcriptome profile Ly4 is similar to immature and age-associated B cells (ABCs). This cluster of lymphoid cells may represent the precursors of ABCs described thus far only in peripheral blood, providing another evidence that the aging mechanisms at various differentiation stages are different. Conclusions: In this study, we have defined specific pathways that distinctly separate aging HSCPs from young ones, and shown that the definition of “aging signature” varies with developmental stages. The accumulation a small cluster in the non-primed HSC compartment, with “aging signature HSC” and cell cycle arrest in old subjects indicates that aging of human hematopoiesis is induced by clonal evolution. The abundance of a unique population among lymphoid precursors with expression profiles similar to ABCs demonstrates that lymphoid and myeloid progenitors age differently.

A Single-Nucleus Resolution Atlas of Transcriptome and Chromatin Accessibility for Peanut (Arachis Hypogaea L.) Leaves.

The peanut is an important worldwide cash-crop for edible oil and protein. However, the kinetic mechanisms that determine gene expression and chromatin accessibility during leaf development in peanut represented allotetraploid leguminous crops are poorly understood at single-cell resolution. Here, a single-nucleus atlas of peanut leaves is developed by simultaneously profiling the transcriptome and chromatin accessibility in the same individual-cell using fluorescence-activated sorted single-nuclei. In total, 5930 cells with 50890 expressed genes are classified into 18 cell-clusters, and 5315 chromatin fragments are enriched with 26083 target genes in the chromatin accessible landscape. The developmental trajectory analysis reveals the involvement of the ethylene-AP2 module in leaf cell differentiation, and cell-cycle analysis demonstrated that genome replication featured in distinct cell-types with circadian rhythms transcription factors (TFs). Furthermore, dual-omics illustrates that the fatty acid pathway modulates epidermal-guard cells differentiation and providescritical TFs interaction networks for understanding mesophyll development, and the cytokinin module (LHY/LOG) that regulates vascular growth. Additionally, an AT-hook protein AhAHL11 is identified that promotes leaf area expansion by modulating the auxin content increase. In summary, the simultaneous profiling of transcription and chromatin accessibility landscapes using snRNA/ATAC-seq provides novel biological insights into the dynamic processes of peanut leaf cell development at the cellular level.

Single-cell mapping identifies MSI+ cells as a common origin for diverse subtypes of pancreatic cancer

Identifying the cells from which cancers arise is critical for understanding the molecular underpinnings of tumor evolution. To determine whether stem/progenitor cells can serve as cells of origin, we created a Msi2-CreERT2 knock-in mouse. When crossed to CAG-LSL-MycT58A mice, Msi2-CreERT2 mice developed multiple pancreatic cancer subtypes: ductal, acinar, adenosquamous, and rare anaplastic tumors. Combining single-cell genomics with computational analysis of developmental states and lineage trajectories, we demonstrate that MYC preferentially triggers transformation of the most immature MSI2+ pancreas cells into multi-lineage pre-cancer cells. These pre-cancer cells subsequently diverge to establish pancreatic cancer subtypes by activating distinct transcriptional programs and large-scale genomic changes, and enforced expression of specific signals like Ras can redirect subtype specification. This study shows that multiple pancreatic cancer subtypes can arise from a common pool of MSI2+ cells and provides a powerful model to understand and control the programs that shape divergent fates in pancreatic cancer.

SCAR: Single-cell and Spatially-resolved Cancer Resources.

Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell heterogeneity and develop new immunotherapy strategies for cancer research. There is an urgent need for a resource that effectively integrates a vast amount of transcriptomic profiling data to comprehensively explore cancer tissue heterogeneity and the tumor microenvironment. In this context, we developed the Single-cell and Spatially-resolved Cancer Resources (SCAR) database, a combined tumor spatial and single-cell transcriptomic platform, which is freely accessible at http://8.142.154.29/SCAR2023 or http://scaratlas.com. SCAR contains spatial transcriptomicdata from 21 tumor tissues and single-cell transcriptomic data from 11 301 352 cells encompassing 395 cancer subtypes and covering a wide variety oftissues, organoids, and cell lines. This resource offers diverse functional modules to address key cancer research questions at multiple levels, including the screening of tumor cell types, metabolic features, cell communication and gene expression patterns within the tumor microenvironment. Moreover, SCAR enables the analysis of biomarker expression patterns and cell developmental trajectories. SCAR also provides a comprehensive analysis of multi-dimensional datasets based on 34 state-of-the-art omics techniques, serving as an essential tool for in-depth mining and understanding of cell heterogeneity and spatial location. The implications of this resource extend to both cancer biology research and cancer immunotherapy development.

Single-cell resolution analysis reveals the preparation for reprogramming the fate of stem cell niche in cotton lateral meristem

BackgroundSomatic embryogenesis is a major process for plant regeneration. However, cell communication and the gene regulatory network responsible for cell reprogramming during somatic embryogenesis are still largely unclear. Recent advances in single-cell technologies enable us to explore the mechanism of plant regeneration at single-cell resolution.ResultsWe generate a high-resolution single-cell transcriptomic landscape of hypocotyl tissue from the highly regenerable cotton genotype Jin668 and the recalcitrant TM-1. We identify nine putative cell clusters and 23 cluster-specific marker genes for both cultivars. We find that the primary vascular cell is the major cell type that undergoes cell fate transition in response to external stimulation. Further developmental trajectory and gene regulatory network analysis of these cell clusters reveals that a total of 41 hormone response-related genes, including LAX2, LAX1, and LOX3, exhibit different expression patterns in the primary xylem and cambium region of Jin668 and TM-1. We also identify novel genes, including CSEF, PIS1, AFB2, ATHB2, PLC2, and PLT3, that are involved in regeneration. We demonstrate that LAX2, LAX1 and LOX3 play important roles in callus proliferation and plant regeneration by CRISPR/Cas9 editing and overexpression assay.ConclusionsThis study provides novel insights on the role of the regulatory network in cell fate transition and reprogramming during plant regeneration driven by somatic embryogenesis.

Single-cell RNA-seq reveals a microenvironment and an exhaustion state of T/NK cells in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a heterogeneous blood cancer. Effective immunotherapies for AML are hindered by a lack of understanding of the tumor microenvironment (TME). Here, we retrieved published single-cell RNA sequencing data for 128,688 cells derived from 29 bone marrow aspirates, including 21 AML patients and eight healthy donors. We established a global tumor ecosystem including nine main cell types. Myeloid, T, and NK cells were further re-clustered and annotated. Developmental trajectory analysis indicated that exhausted CD8+ T cells might develop via tissue residual memory T cells (TRM) in the AML TME. Significantly higher expression levels of exhaustion molecules in AML TRM cells suggested that these cells were influenced by the TME and entered an exhausted state. Meanwhile, the upregulation of checkpoint molecules and downregulation of granzyme were also observed in AML NK cells, suggesting an exhaustion state. In conclusion, our comprehensive profiling of T/NK subpopulations provides deeper insights into the AML immunosuppressive ecosystem, which is critical for immunotherapies.

Sox1a:eGFP transgenic line and single-cell transcriptomics reveal the origin of zebrafish intraspinal serotonergic neurons

Sox transcription factors are crucial for vertebrate nervous system development. In zebrafish embryo, sox1 genes are expressed in neural progenitor cells and neurons of ventral spinal cord. Our recent study revealed that the loss of sox1a and sox1b function results in a significant decline of V2 subtype neurons (V2s). Using single-cell RNA sequencing, we analyzed the transcriptome of sox1a lineage progenitors and neurons in the zebrafish spinal cord at four time points during embryonic development, employing the Tg(sox1a:eGFP) line. In addition to previously characterized sox1a-expressing neurons, we discovered the expression of sox1a in late-developing intraspinal serotonergic neurons (ISNs). Developmental trajectory analysis suggests that ISNs arise from lateral floor plate (LFP) progenitor cells. Pharmacological inhibition of the Notch signaling pathway revealed its role in negatively regulating LFP progenitor cell differentiation into ISNs. Our findings highlight the zebrafish LFP as a progenitor domain for ISNs, alongside known Kolmer-Agduhr (KA) and V3 interneurons.

LGG-13. GANGLIOGLIOMA DEEP TRANSCRIPTOMICS REVEALS A CD34+ PRIMITIVE NEUROECTODERM NEURAL PRECURSOR-LIKE POPULATION

Abstract Gangliogliomas are glioneuronal brain tumors that typically present in childhood or early adulthood. Though most often low-grade, new insights are needed to refine glioneuronal tumor classification and to identify therapeutic approaches, particularly for unresectable, high-grade, and/or recurrent disease. Gangliogliomas often possess a rare population of immature astrocyte-appearing CD34+ cells. CD34 is expressed in neuroectoderm neural precursor cells during embryogenesis. Neural cell CD34 expression is usually lost prior to birth. We hypothesized that CD34+ ganglioglioma cells represent tumor precursor/stem cells and closely resemble ganglioglioma cells of origin. To test this, we evaluated five gangliogliomas with single nucleus RNA-seq, cellular indexing of transcriptomes and epitopes by sequencing, and/or spatially-resolved RNA-seq. Developmental trajectory analyses uncovered a neoplastic cellular hierarchy, with CD34+PAX6+SOX2+MSI1+PECAM1-VWF-DCN-COL1A2- cells being the most primordial and precursor to neuron-like and macroglia-like neoplastic cell states. Gene regulatory network inference of CD34+ ganglioglioma cells indicated TCF7L2/MEIS1-PAX6 and SOX2-mediated transcriptional programming, similar to that found during neuroectodermal/neural development in utero. Spatially-resolved transcriptomics revealed a neuroectoderm neural precursor-like tumor cell niche relatively devoid of vascular and immune cells. We used these high-resolution results to deconvolute clinically-annotated transcriptomic data, confirming that CD34+ neural precursor-like cell-associated gene programs associate with gangliogliomas compared to other brain tumors. Together, these deep transcriptomic approaches characterized a ganglioglioma cellular hierarchy - identifying CD34+ neuroectoderm neural precursor-like tumor-initiating cells, corresponding regulatory transcriptional programs, cell signaling pathways, and associated immune cell states. These findings may facilitate improved ganglioglioma tumor classification, diagnosis, and therapeutic investigations.

Comprehensive analysis of single-cell RNA-seq and bulk RNA-seq revealed the heterogeneity and convergence of the immune microenvironment in renal cell carcinoma.

Substantial progress has been made in cancer biology and treatment in recent years, but the clinical outcome of patients with renal cell carcinoma (RCC) remains unsatisfactory. The tumor microenvironment (TME) is a potential target. By analyzing single-cell RNA sequencing (sc-RNAseq) data from six RCC tumor samples, this study identified 11 different cell types in the RCC cellular microenvironment, indicating a high degree of intratumoral heterogeneity. Through re-dimensionality reduction clustering of epithelial cells, neutrophils, macrophages, and T cells, we deeply reveal differences in the RCC tumor microenvironment. By analyzing differentially expressed genes in normal epithelial cells and malignant epithelial cells, we identify RNASET2 and GATM as potential prognostic biomarkers in RCC. In addition, by transcriptional factor analysis, we found significant differences in the expression of GZMK-CD8 T cell and B cell transcription factors between cancer tissues and normal tissues. By cell correlation analysis, we found significant correlations between neutrophils and macrophages and between IL7R-CD4 T cells and T regulatory (Treg) cells in RCC, which may be involved in the formation of immune TMEs. By cell developmental trajectory analysis, we showed that macrophages may be derived from neutrophils, whereas Treg cells may be derived from IL7R-CD4 T cells. By cell communication analysis, we found a clear interaction between macrophages and endothelial cells, neutrophils, and GZMK-CD8 T cells. In addition, we found that ADGRE5 signaling was mainly derived from mast cells and GZMK-CD8 T cells, and had a significant communication effect with neutrophils. The COLLAGEN signaling pathway is mainly derived from fibroblasts and has a significant communication effect with mast cells. Finally, we verified that RNASET2, which is highly expressed in epithelial cells, promotes proliferation and migration of RCC in vitro. RNASET2 is likely to be a potential target for renal cell carcinoma therapy. The results based on sc-RNAseq data analysis help to further elucidate the cellular microenvironment of RCC and provide help for cancer heterogeneity studies. This will help to provide more accurate personalized treatment for patients in clinical diagnosis.

Single cell transcriptomes from HCMV +donors reveal a unique NKG2C Highsubset that represents true memory NK cells

Abstract Infection with human cytomegalovirus (HCMV) can result in severe morbidity and mortality to the developing fetus and immunocompromised individuals. Natural killer (NK) cells are cytotoxic lymphocytes that are required to manage and control HCMV infections. The NKG2C receptor expressed by NK cells recognizes and responds to infected cells expressing HLA-E loaded with HCMV UL40-derived peptide. These responding NKG2C +NK cells have been referred to as ‘adaptive NK’ because they possess features of adaptive immunity and are found at greater percentages in HCMV seropositive individuals. The molecular mechanisms by which adaptive NK cells are generated and their transcriptomic signatures remain unknown. To investigate this, we obtained healthy adult spleens from four HCMV +and four HCMV −donors and their NK cells were sorted and captured for single-cell RNA-sequencing (scRNA-seq). Donor median age was 59 [IQR 48.5–56.5], 50% (n=4) were female, 50% (n=2) of females were HCMV seropositive and 50% (n=2) of females were HCMV seronegative. Using scRNA-seq, we observed elevated expression and cell numbers of NKG2C in HCMV +donors when compared to HCMV-donors. We identified a distinct population of NKG2C +adaptive NK cells displaying elevated levels of CD52, B3GAT1, FCGR3A, CD3E, and IL7R. In addition, our developmental trajectory analysis of adaptive NKG2C +NK cells revealed a unique branchpoint of true memory NK cells expressing elevated levels of NKG2C and IL7R. Here, we demonstrate that HCMV infection can induce the formation of adaptive NKG2C +NK cells that display a unique transcriptional and developmental profile. These findings have the potential to influence the future application of adaptive NK cells in cellular immunotherapies. This work is supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through grant number TL1TR001437