Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes.

Single-cell analysis has become an essential tool in modern biological research, providing unprecedented insights into cellular behavior and heterogeneity. By examining individual cells, this approach surpasses conventional population-based methods, revealing critical variations in cellular states, responses to environmental cues, and molecular signatures. In the context of cancer, with its diverse cell populations, single-cell analysis is critical for investigating tumor evolution, metastasis, and therapy resistance. Understanding the phenotype-genotype relationship at the single-cell level is crucial for deciphering the molecular mechanisms driving tumor development and progression. This review highlights innovative strategies for selective cell isolation based on desired phenotypes, including robotic aspiration, laser detachment, microraft arrays, optical traps, and droplet-based microfluidic systems. These advanced tools facilitate high-throughput single-cell phenotypic analysis and sorting, enabling the identification and characterization of specific cell subsets, thereby advancing therapeutic innovations in cancer and other diseases.

Comprehensive review on single-cell RNA sequencing: A new frontier in Alzheimer's disease research.

Alzheimer's disease (AD) is a multifaceted neurodegenerative condition marked by gradual cognitive deterioration and the loss of neurons. While conventional bulk RNA sequencing techniques have shed light on AD pathology, they frequently obscure the cellular diversity within brain tissues. The advent of single-cell RNA sequencing (scRNA-seq) has transformed our capability to analyze the cellular composition of AD, allowing for the detection of unique cell populations, rare cell types, and gene expression alterations at an individual cell level. This review examines the use of scRNA-seq in AD research, focusing on its contributions to understanding cellular diversity, disease progression, and potential therapeutic targets. We discuss key technological innovations, data analysis techniques, and challenges associated with scRNA-seq in studying AD. Furthermore, we highlight recent studies that have utilized scRNA-seq to identify novel biomarkers, uncover disease-associated pathways, and elucidate the role of non-neuronal cells, such as microglia and astrocytes, in AD pathogenesis. By providing a comprehensive overview of advancements in scRNA-seq for unraveling cellular heterogeneity in AD, this review highlights the transformative impact of scRNA-seq on our comprehension of disease mechanisms and the creation of targeted treatments.

Deciphering the cellular landscape and potential targets of nasopharyngeal and oral cancers using single-cell RNA sequencing.

Cellular heterogeneity in nasopharyngeal cancer (NPC) and oral cancer remains unclear. In the current study, using single-cell RNA sequencing techniques, we investigated the cellular landscape in NPC and oral cancers. We identified a diverse range of cell types within the tumor microenvironment (TME) and variations in cell infiltration between NPC and oral cancer. In oral cancer, we observed a predominant infiltration of epithelial cells, fibroblasts, and endothelial cells (ECs), while T cells were the main infiltrating cell population in NPCs. We further classified these infiltrating cells into subclusters. Additionally, we observed complex interactions among cells that led to distinct trajectories. In particular, a unique epithelial subcluster with high expression of major histocompatibility complex class II (MHC-II) molecules was correlated with a favorable outcome and infiltration of CD4+ T cells. In addition, MHC-II+ epithelial cells inhibited mouse tumor growth and promoted T-cell infiltration. Consequently, our findings provide a deep understanding of the TME showing a significant prognostic value and therapeutic potential.

Similarities and differences of bone marrow and peripheral blood samples from acute myeloid leukemia patients in terms of cellular heterogeneity and ex-vivo drug sensitivity.

Background: Bone marrow (BM) evaluation is the de facto standard for diagnosis, molecular analysis, risk stratification, and therapy response assessment in acute myeloid leukemia (AML), but in patients with a high number of circulating blast cells, the peripheral blood (PB) sample could provide similar information as BM. However, there is no large-scale molecular study comparing the two specimens in terms of their gene expression profiles, cellular heterogeneities, and ex-vivo drug sensitivity. Methodology: We used (i) the BEAT-AML cohort each with detailed molecular data; (ii) cell-type deconvolution to estimate leukemic and immune cell proportions between specimen types; (iii) differential expression (DE) and drug-cell type association analysis; and (iv) logistic regression models to assess the association between induction therapy response, cell-type composition and first-line drug treatment. Results: Results: We identified 207 patients having BM and 116 patients having PB samples. There was a total of 1271 DE genes (false discovery rate < 0.05) between BM and PB; the top enriched pathways in terms of DE genes belong to the immune system pathways. Aggregated ex-vivo drug response profiles from the two specimens were largely similar, as were the cellular components, except for the GMP-like cell type (17% in BM vs. 5% in PB, p-value = 2 × 10-7). Among the specimen-specific results, the GMP-like subtype was associated with multiple drug resistance in BM and the ProMono-like subtype in PB. Several cell types were associated with the response to induction therapy, but the impact of specimen type on the interaction of cell type and cytarabine-associated induction therapy was not statistically significant for most cell types. Results: Conclusions: Even though there are molecular and cellular differences between BM and PB samples, they show many similarities in ex-vivo drug response profiles, indicating the clinical utility of the substantially less-invasive PB samples.

Single-cell analysis of Crohn's disease: Unveiling heterogeneity and evaluating ustekinumab outcomes.

BACKGROUND: The present study aimed to dissect the cellular complexity of Crohn's disease (CD) using single-cell RNA sequencing, focusing on identifying key cell populations and their transcriptional profiles in inflamed tissue. METHODS: We applied scRNA-sequencing to compare the cellular composition of CD patients with healthy controls, utilizing Seurat for clustering and annotation. Differential gene expression analysis and protein-protein interaction networks were constructed to identify crucial genes and pathways. RESULTS: Our study identified eight distinct cell types in CD, highlighting crucial fibroblast and T cell interactions. The analysis revealed key cellular communications and identified significant genes and pathways involved in the disease's pathology. The role of fibroblasts was underscored by elevated expression in diseased samples, offering insights into disease mechanisms and potential therapeutic targets, including responses to ustekinumab treatment, thus enriching our understanding of CD at a molecular level. CONCLUSIONS: Our findings highlight the complex cellular and molecular interplay in CD, suggesting new biomarkers and therapeutic targets, offering insights into disease mechanisms and treatment implications.

Unveiling heterogeneity and prognostic markers in ductal breast cancer through single-cell RNA-seq.

BACKGROUND: Breast cancer (BC) is a heterogeneous disease, with the ductal subtype exhibiting significant cellular diversity that influences prognosis and response to treatment. Single-cell RNA sequencing data from the GEO database were utilized in this study to investigate the underlying mechanisms of cellular heterogeneity and to identify potential prognostic markers and therapeutic targets. METHODS: Bioinformatics analysis was conducted using R packages to analyze the single-cell sequencing data. The presence of highly variable genes and differences in malignant potency within the same BC samples were examined. Differential gene expression and biological function between Type 1 and Type 2 ductal epithelial cells were identified. Lasso regression and Cox proportional hazards regression analyses were employed to identify genes associated with patient prognosis. Experimental validation was performed in vitro and in vivo to confirm the functional relevance of the identified genes. RESULTS: The analysis revealed notable heterogeneity among BC cells, with the presence of highly variable genes and differences in malignant behavior within the same samples. Significant disparities in gene expression and biological function were identified between Type 1 and Type 2 ductal epithelial cells. Through regression analyses, CYP24A1 and TFPI2 were identified as pivotal genes associated with patient prognosis. Kaplan-Meier curves demonstrated their prognostic significance, and experimental validation confirmed their inhibitory effects on malignant behaviors of ductal BC cells. CONCLUSION: This study highlights the cellular heterogeneity in ductal subtype breast cancer and delineates the differential gene expressions and biological functions between Type 1 and Type 2 ductal epithelial cells. The genes CYP24A1 and TFPI2 emerged as promising prognostic markers and therapeutic targets, exhibiting inhibitory effects on BC cell malignancy in vitro and in vivo. These findings offer the potential for improved BC management and the development of targeted treatment strategies.

Decoding ecosystem heterogeneity and transcriptional regulation characteristics of multi-subtype renal cell carcinoma.

Background: Renal cell carcinoma (RCC) is characterized by its heterogeneity and the complexity of its tumor microenvironment. This study addresses the need to understand RCC at a cellular level, with a focus on its three main subtypes: clear cell (ccRCC), chromophobe (chRCC), and papillary renal cell carcinoma (pRCC). Objective: This study aims to comprehensively characterize the cellular diversity and intercellular communication networks of RCC subtypes using scRNA-seq technology. By focusing on macrophages and cancer-associated fibroblasts (CAFs), we seek to reveal their functional states, developmental trajectories, and signaling pathways. Methodology: We utilized single-cell RNA sequencing (scRNA-seq) data from various kidney cancer subtypes. Advanced analytical techniques, including Uniform Manifold Approximation and Projection (UMAP) and Reactome Gene Set Variation Analysis (ReactomeGSA), were employed to assess cellular heterogeneity and pathway activities. The developmental dynamics of macrophages were studied using CytoTRACE, and cell-to-cell communication was analyzed to identify subtype-specific interaction networks. Results: Our comprehensive analysis revealed significant cellular diversity within RCC. Distinct macrophage and CAF subpopulations were identified, each exhibiting unique gene expression profiles and pathway activities. Notably, ccRCC showed prominent bidirectional communication between macrophages and CAFs, while chRCC and pRCC displayed disrupted signaling pathways. Metabolic pathway analysis reflected the adaptability of macrophages and CAFs to the tumor microenvironment, and the MIF signaling pathway was identified as a key mediator of cellular interactions. Conclusion: The study highlights the cellular heterogeneity and the intricate communication networks within RCC subtypes, underscoring the complexity of the tumor microenvironment. Our findings suggest that targeting specific cellular interactions and pathways may offer new avenues for therapeutic intervention in RCC. The unique macrophage and CAF profiles across RCC subtypes provide valuable insights for the development of personalized and targeted treatment strategies.

High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment.

Single-cell analyses can be confounded by assigning unrelated groups of cells to common developmental trajectories. For instance, cancer cells and admixed normal epithelial cells could adopt similar cell states thus complicating analyses of their developmental potential. Here, we develop and benchmark CCISM (for Cancer Cell Identification using Somatic Mutations) to exploit genomic single nucleotide variants for the disambiguation of cancer cells from genomically normal non-cancer cells in single-cell data. We find that our method and others based on gene expression or allelic imbalances identify overlapping sets of colorectal cancer versus normal colon epithelial cells, depending on molecular characteristics of individual cancers. Further, we define consensus cell identities of normal and cancer epithelial cells with higher transcriptome cluster homogeneity than those derived using existing tools. Using the consensus identities, we identify significant shifts of cell state distributions in genomically normal epithelial cells developing in the cancer microenvironment, with immature states increased at the expense of terminal differentiation throughout the colon, and a novel stem-like cell state arising in the left colon. Trajectory analyses show that the new cell state extends the pseudo-time range of normal colon stem-like cells in a cancer context. We identify cancer-associated fibroblasts as sources of WNT and BMP ligands potentially contributing to increased plasticity of stem cells in the cancer microenvironment. Our analyses advocate careful interpretation of cell heterogeneity and plasticity in the cancer context and the consideration of genomic information in addition to gene expression data when possible.

Investigating cellular similarities and differences between upper tract urothelial carcinoma and bladder urothelial carcinoma using single-cell sequencing.

Background: Upper tract urothelial carcinoma (UTUC) and bladder urothelial carcinoma (BLCA) both originate from uroepithelial tissue, sharing remarkably similar clinical manifestations and therapeutic modalities. However, emerging evidence suggests that identical treatment regimens may lead to less favorable outcomes in UTUC compared to BLCA. Therefore, it is imperative to explore molecular processes of UTUC and identify biological differences between UTUC and BLCA. Methods: In this study, we performed a comprehensive analysis using single-cell RNA sequencing (scRNA-seq) on three UTUC cases and four normal ureteral tissues. These data were combined with publicly available datasets from previous BLCA studies and RNA sequencing (RNA-seq) data for both cancer types. This pooled analysis allowed us to delineate the transcriptional differences among distinct cell subsets within the microenvironment, thus identifying critical factors contributing to UTUC progression and phenotypic differences between UTUC and BLCA. Results: scRNA-seq analysis revealed seemingly similar but transcriptionally distinct cellular identities within the UTUC and BLCA ecosystems. Notably, we observed striking differences in acquired immunological landscapes and varied cellular functional phenotypes between these two cancers. In addition, we uncovered the immunomodulatory functions of vein endothelial cells (ECs) in UTUC, and intercellular network analysis demonstrated that fibroblasts play important roles in the microenvironment. Further intersection analysis showed that MARCKS promote UTUC progression, and immunohistochemistry (IHC) staining revealed that the diverse expression patterns of MARCKS in UTUC, BLCA and normal ureter tissues. Conclusion: This study expands our multidimensional understanding of the similarities and distinctions between UTUC and BLCA. Our findings lay the foundation for further investigations to develop diagnostic and therapeutic targets for UTUC.

Studying the Dynamics of Tunneling Tubes and Cellular Spheres.

Cancer cytogenetic analyses often involve cell culture. However, many cytogeneticists overlook interesting phenotypes associated with cultured cells. Given that cytogeneticists need to focus more on phenotypes to comprehend the genotypes, the biological significance of seemingly trivial cellular variations deserves attention. One example is the formation of cellular tunneling tubes (TTs) in cultured cancer cells, which likely play a role in cell-to-cell communication and material transport. In this chapter, we describe protocols for studying these TTs as well as cellular spheres. In addition to diverse chromosomal variants, these different types of variations should be considered for understanding cancer heterogeneity and dynamics, as they illustrate the importance of various forms of fuzzy inheritance.

Unraveling the Drug Response Heterogeneity with Single-Cell Vibrational Phenomics.

Drug responses heterogeneity is often highlighted to justify the need for precision medicine. However, due to the highly complex nature of cell phenotypes in many diseases, one of key challenges is how to obtain the high content features in a cellular population. Here we present a single-cell vibrational phenomics approach, integrating synchrotron infrared microspectroscopy and multivariate calculation, for quantitatively evaluating the cellular responses to drug perturbation with single cell resolution. In a human hepatocellular carcinoma HepG2 cell model, the phenotypic changes induced by two types of drugs, taxol (TAX) and protopanaxadiol (PPD), were analyzed and revealed the response heterogeneity in drug concentration and chemical components. These findings not only provide a label-free strategy for determining the drug response at the single cell level, but also demonstrate the great potential of vibrational phenomics as a drug discovery platform.

From whole bodies to single cells: A guide to transcriptomic approaches for ecology and evolutionary biology.

RNA sequencing (RNAseq) methodology has experienced a burst of technological developments in the last decade, which has opened up opportunities for studying the mechanisms of adaptation to environmental factors at both the organismal and cellular level. Selecting the most suitable experimental approach for specific research questions and model systems can, however, be a challenge and researchers in ecology and evolution are commonly faced with the choice of whether to study gene expression variation in whole bodies, specific tissues, and/or single cells. A wide range of sometimes polarised opinions exists over which approach is best. Here, we highlight the advantages and disadvantages of each of these approaches to provide a guide to help researchers make informed decisions and maximise the power of their study. Using illustrative examples of various ecological and evolutionary research questions, we guide the readers through the different RNAseq approaches and help them identify the most suitable design for their own projects.

Extracellular matrices of stromal cell subtypes regulate phenotype and contribute to the stromal microenvironment in vivo.

BACKGROUND: Bone marrow stromal cells (BMSCs) are highly heterogeneous, which may reflect their diverse biological functions, including tissue maintenance, haematopoietic support and immune control. The current understanding of the mechanisms that drive the onset and resolution of heterogeneity, and how BMSCs influence other cells in their environment is limited. Here, we determined how the secretome and importantly the extracellular matrix of BMSCs can influence cellular phenotype. METHODS: We used two immortalised clonal BMSC lines isolated from the same heterogeneous culture as model stromal subtypes with distinct phenotypic traits; a multipotent stem-cell-like stromal line (Y201) and a nullipotent non-stem cell stromal line (Y202), isolated from the same donor BMSC pool. Label-free quantitative phase imaging was used to track cell morphology and migration of the BMSC lines over 96 h in colony-forming assays. We quantified the secreted factors of each cell line by mass spectrometry and confirmed presence of proteins in human bone marrow by immunofluorescence. RESULTS: Transfer of secreted signals from a stem cell to a non-stem cell resulted in a change in morphology and enhanced migration to more closely match stem cell-like features. Mass spectrometry analysis revealed a significant enrichment of extracellular matrix (ECM) proteins in the Y201 stem cell secretome compared to Y202 stromal cells. We confirmed that Y201 produced a more robust ECM in culture compared to Y202. Growth of Y202 on ECM produced by Y201 or Y202 restored migration and fibroblastic morphology, suggesting that it is the deficiency of ECM production that contributes to its phenotype. The proteins periostin and aggrecan, were detected at 71- and 104-fold higher levels in the Y201 versus Y202 secretome and were subsequently identified by immunofluorescence at rare sites on the endosteal surfaces of mouse and human bone, underlying CD271-positive stromal cells. These proteins may represent key non-cellular components of the microenvironment for bona-fide stem cells important for cell maintenance and phenotype in vivo. CONCLUSIONS: We identified plasticity in BMSC morphology and migratory characteristics that can be modified through secreted proteins, particularly from multipotent stem cells. Overall, we demonstrate the importance of specific ECM proteins in co-ordination of cellular phenotype and highlight how non-cellular components of the BMSC microenvironment may provide insights into cell population heterogeneity and the role of BMSCs in health and disease.

Single-cell multiomics profiling reveals heterogeneous transcriptional programs and microenvironment in DSRCTs.

Desmoplastic small round cell tumor (DSRCT) is a rare, aggressive sarcoma driven by the EWSR1::WT1 chimeric transcription factor. Despite this unique oncogenic driver, DSRCT displays a polyphenotypic differentiation of unknown causality. Using single-cell multi-omics on 12 samples from five patients, we find that DSRCT tumor cells cluster into consistent subpopulations with partially overlapping lineage- and metabolism-related transcriptional programs. In vitro modeling shows that high EWSR1::WT1 DNA-binding activity associates with most lineage-related states, in contrast to glycolytic and profibrotic states. Single-cell chromatin accessibility analysis suggests that EWSR1::WT1 binding site variability may drive distinct lineage-related transcriptional programs, supporting some level of cell-intrinsic plasticity. Spatial transcriptomics reveals that glycolytic and profibrotic states specifically localize within hypoxic niches at the periphery of tumor cell islets, suggesting an additional role of tumor cell-extrinsic microenvironmental cues. We finally identify a single-cell transcriptomics-derived epithelial signature associated with improved patient survival, highlighting the clinical relevance of our findings.

A facile single-cell patterning strategy based on harbor-like microwell microfluidics.

Single-cell analysis is an effective method for conducting comprehensive heterogeneity studies ranging from cell phenotype to gene expression. The ability to arrange different cells in a predetermined pattern at single-cell resolution has a wide range of applications in cell-based analysis and plays an important role in facilitating interdisciplinary research by researchers in various fields. Most existing microfluidic microwell chips is a simple and straightforward method, which typically use small-sized microwells to accommodate single cells. However, this method imposes certain limitations on cells of various sizes, and the single-cell capture efficiency is relatively low without the assistance of external forces. Moreover, the microwells limit the spatiotemporal resolution of reagent replacement, as well as cell-to-cell communication. In this study, we propose a new strategy to prepare a single-cell array on a planar microchannel based on microfluidic flip microwells chip platform with large apertures (50 µm), shallow channels (50 µm), and deep microwells (50 µm). The combination of three configuration characteristics contributes to multi-cell trapping and a single-cell array within microwells, while the subsequent chip flipping accomplishes the transfer of the single-cell array to the opposite planar microchannel for cells adherence and growth. Further assisted by protein coating of bovine serum albumin and fibronectin on different layers, the single-cell capture efficiency in microwells is achieved at 92.1% ± 1%, while ultimately 85% ± 3.4% on planar microchannel. To verify the microfluidic flip microwells chip platform, the real-time and heterogeneous study of calcium release and apoptosis behaviours of single cells is carried out. To our knowledge, this is the first time that high-efficiency single-cell acquisition has been accomplished using a circular-well chip design that combines shallow channel, large aperture and deep microwell together. The chip is effective in avoiding the shearing force of high flow rates on cells, and the large apertures better allows cells to sedimentation. Therefore, this strategy owns the advantages of easy preparation and user-friendliness, which is especially valuable for researchers from different fields.

Human Umbilical Cord Mesenchymal Stromal Cell-Derived Extracellular Vesicles Induce Fetal Wound Healing Features Revealed by Single-Cell RNA Sequencing.

The potential of human umbilical cord mesenchymal stromal cell-derived extracellular vesicles (hucMSC-EVs) in wound healing is promising, yet a comprehensive understanding of how fibroblasts and keratinocytes respond to this treatment remains limited. This study utilizes single-cell RNA sequencing (scRNA-seq) to investigate the impact of hucMSC-EVs on the cutaneous wound microenvironment in mice. Through rigorous single-cell analyses, we unveil the emergence of hucMSC-EV-induced hematopoietic fibroblasts and MMP13+ fibroblasts. Notably, MMP13+ fibroblasts exhibit fetal-like expressions of MMP13, MMP9, and HAS1, accompanied by heightened migrasome activity. Activation of MMP13+ fibroblasts is orchestrated by a distinctive PIEZO1-calcium-HIF1α-VEGF-MMP13 pathway, validated through murine models and dermal fibroblast assays. Organotypic culture assays further affirm that these activated fibroblasts induce keratinocyte migration via MMP13-LRP1 interactions. This study significantly contributes to our understanding of fibroblast heterogeneities as well as intercellular interactions in wound healing and identifies hucMSC-EV-induced hematopoietic fibroblasts as potential targets for reprogramming. The therapeutic targets presented by these fibroblasts offer exciting prospects for advancing wound healing strategies.

Single-Cell Data Analysis Reveals Critical Hepatic Cells Subpopulations in the Progression of Non-alcoholic Fatty Liver Disease to Non-Alcoholic Steatohepatitis.

AIMS: The aim of this study was to reveal the hepatic cell landscape and function in the progression of NAFLD to NASH. BACKGROUND: Non-alcoholic steatohepatitis (NASH) is the progressive form and turning point of nonalcoholic fatty liver disease (NAFLD), which severely causes irreversible cirrhosis as well as hepatocellular carcinoma. The mechanism underlying the progression of NAFLD to NASH has not been revealed. Unraveling the mechanism of action of NAFLD-NASH is an important goal in improving the survival of patients with liver disease. OBJECTIVE: The aim of this study is to discover heterogeneous hepatic cells during the progression of NAFLD to NASH. METHODS: Single-nucleus RNA-seq (snRNA-seq) data containing NASH in NAFLD samples were obtained from the Gene Expression Omnibus (GEO) database. Cell types in liver tissues from NASH and NAFLD were identified after dimensionality reduction analysis, cluster analysis, and cell annotation. The cell pathways in which differences existed were identified by analyzing metabolic pathways in Hepatic cells. We also identified cell subpopulations in Hepatic cells. The developmental trajectories of Hepatic cells were characterized by pseudotime trajectory analysis. Single-cell regulatory network inference and clustering analysis identified key transcription factors and gene regulatory networks in Hepatic cells. Moreover, cell communication analysis determined the potential interactions between Hepatic cells and immune cells, and heapatic stellate cells. RESULTS: Seven cell types were identified in NAFLD and NASH. The proportion of Hepatic cells was lower in NASH and showed greater energy metabolism and glucose metabolism activity. Hepatic cells exhibited heterogeneity, showing two cell subpopulations, Hepatic cells 1 and Hepatic cells 2. Dysregulation of lipid metabolism in Hepatic Cell 2 resulted in lipid accumulation in the liver, which might be involved in the progression of NAFLD. Four key transcription factors, BHLHE40, NFEL2L, RUNX1, and INF4A, were primarily found in Hepatic cells 2. The transcription factors within the hepatic cells 2 subpopulation mainly regulated genes related to lipid metabolism, energy metabolism, and inflammatory response. The cell communication analysis showed that hepatocyte interactions with immune cells were associated with inflammatory responses, while interactions with hepatic astrocytes were associated with liver injury and hepatocyte fibrosis. CONCLUSION: The hepatic cells 2 might promote the progression of NAFLD to NASH by regulating metabolic activity, which might contribute to liver injury through inflammation.

Advancing skeletal health and disease research with single-cell RNA sequencing.

Orthopedic conditions have emerged as global health concerns, impacting approximately 1.7 billion individuals worldwide. However, the limited understanding of the underlying pathological processes at the cellular and molecular level has hindered the development of comprehensive treatment options for these disorders. The advent of single-cell RNA sequencing (scRNA-seq) technology has revolutionized biomedical research by enabling detailed examination of cellular and molecular diversity. Nevertheless, investigating mechanisms at the single-cell level in highly mineralized skeletal tissue poses technical challenges. In this comprehensive review, we present a streamlined approach to obtaining high-quality single cells from skeletal tissue and provide an overview of existing scRNA-seq technologies employed in skeletal studies along with practical bioinformatic analysis pipelines. By utilizing these methodologies, crucial insights into the developmental dynamics, maintenance of homeostasis, and pathological processes involved in spine, joint, bone, muscle, and tendon disorders have been uncovered. Specifically focusing on the joint diseases of degenerative disc disease, osteoarthritis, and rheumatoid arthritis using scRNA-seq has provided novel insights and a more nuanced comprehension. These findings have paved the way for discovering novel therapeutic targets that offer potential benefits to patients suffering from diverse skeletal disorders.

OsMADS6-OsMADS32 and REP1 control palea cellular heterogeneity and morphogenesis in rice.

Precise regulation of cell proliferation and differentiation is vital for organ morphology. Rice palea, serving as sepal, comprises two distinct regions: the marginal region (MRP) and body of palea (BOP), housing heterogeneous cell populations, which makes it an ideal system for studying organ morphogenesis. We report that the transcription factor (TF) REP1 promotes epidermal cell proliferation and differentiation in the BOP, resulting in hard silicified protrusion cells, by regulating the cyclin-dependent kinase gene, OsCDKB1;1. Conversely, TFs OsMADS6 and OsMADS32 are expressed exclusively in the MRP, where they limit cell division rates by inhibiting OsCDKB2;1 expression and promote endoreduplication, yielding elongated epidermal cells. Furthermore, reciprocal inhibition between the OsMADS6-OsMADS32 complex and REP1 fine-tunes the balance between cell division and differentiation during palea morphogenesis. We further show the functional conservation of these organ identity genes in heterogeneous cell growth in Arabidopsis, emphasizing a critical framework for controlling cellular heterogeneity in organ morphogenesis.