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Integrated Single-Cell and Bulk RNA Sequencing Identifies SERPING1 as a Biomarker of Immune Infiltration and Prognosis in Triple-Negative Breast Cancer.
BACKGROUND: Triple-negative breast cancer (TNBC) is an aggressive malignancy that lacks effective treatment. Immune infiltration plays an important role in anti-tumor responses. Serpin family G1 (SERPING1), a biomarker associated with immune infiltration, has been implicated in multiple cancers, but its role in TNBC remains unclear. METHODS: RNA sequencing and clinical data for TNBC were obtained from the Gene Expression Omnibus, the Cancer Genome Atlas, and the Molecular Taxonomy of Breast Cancer International Consortium databases. First, the expression, prognostic value, and biological functions of SERPING1 were analyzed. Then, the tumor microenvironment (TME) was comprehensively characterized, and the relationship between SERPING1 expression and immunotherapy response was assessed. Immunohistochemical staining was performed to confirm SERPING1 expression and the abundance of CD4+ T cells and CD8+ T cells in clinical specimens. Finally, single-cell analysis was conducted to investigate the role of SERPING1 in immune cell activation. RESULTS: SERPING1 was downregulated in TNBC and was an independent predictor of survival. Functionally, SERPING1 activated the immune response in TNBC patients. Mechanistically, elevated SERPING1 levels lead to increased immune cell infiltration, particularly of CD4+ and CD8+ T cells, in the TME. Moreover, SERPING1 was primarily localized in cancer-associated fibroblasts (CAFs), with SERPING1+ apCAFs exhibiting increased communications with anti-tumor immune cells at the single-cell level. CONCLUSIONS: SERPING1 contributes to enhanced immune cell infiltration, desirable immunotherapy response, and improved prognosis. It thus can be utilized as a promising biomarker for immune infiltration and prognosis. These findings provide novel insights into TME-related immune regulation and may inform strategies to enhance immunotherapy efficacy in TNBC.
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A single-cell transcriptome atlas reveals the transcriptionally earliest state in rice callus.
BACKGROUND: The cell fate transition of pluripotent callus from somatic cells plays an important role in plant development studies and crop genetic improvement. Embryonic callus is a group of totipotent cells derived from the founder cells responsible for the initiation of callus. However, our understanding of the initial cellular states and regulatory factors of cell fate transition during callus development remains quite limited. RESULTS: Single-cell RNA sequencing was employed to generate a single-cell transcriptome atlas of the rice (Oryza sativa L.) embryonic and differentiated callus. We found that the callus founder cell represented the transcriptionally earliest state of embryonic callus, which could transit into the root meristem niche, a process associated with starch degradation, lipid transport, energy production and transfer, plant hormones and flavonoid metabolism. The shoot meristematic cell represented the transcriptionally earliest state of differentiated callus, and these shoot meristematic cells differentiated into mesophyll precursor cells via vascular parenchyma cells, a process associated with chromatin-related epigenetic regulation, enzymatic reactions, signal transduction, metabolic activity and photosynthesis. The expression patterns of the genes involved in plant hormones, and WUSCHEL RELATED HOMEOBOX (WOX) family gene DWARF TILLER1 (OsDWT1) across distinct cell populations suggested that gibberellin (GA) signaling and OsDWT1 were associated with the callus founder cell fate transition. CONCLUSIONS: Our results revealed that the callus founder cell and shoot meristematic cell represent the transcriptionally earliest states of embryonic callus and differentiated callus in rice, respectively. This study provides preliminary resources for understanding the development of callus cells and offers clues for improving plant genetic transformation efficiency in recalcitrant rice varieties by regulating cell fate transition.
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A Cell Atlas of Adult Aedes aegypti Midgut Revealed by Single Nucleus/Cell RNA Sequencing.
Single-cell RNA sequencing (scRNA-seq), which revolutionized the field of biology, is used to analyze gene expression at the individual cell level, providing insights into cellular heterogeneity and rare cell populations that are often masked by traditional bulk RNA sequencing. The technique has been applied in entomology to define cellular heterogeneity and response to pathogens in insects. In this chapter, we describe how to perform scRNA-seq of adult Aedes aegypti midgut.
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Integration of Bulk and Single-Cell RNA Sequencing Analyses in Biomedicine.
Transcriptome profiling is a cornerstone of functional genomics, enabling the detailed characterization of gene expression in health and disease. Bulk RNA sequencing (bulk RNAseq) remains the most widely used approach in clinical and large-cohort studies due to its cost-effectiveness, robustness, and comprehensive transcriptome coverage. However, bulk RNAseq inherently averages gene expression signals across heterogeneous cell populations, thereby masking cellular diversity and obscuring rare cell types. In contrast, single-cell RNA sequencing (scRNAseq) enables a high-resolution analysis of cellular heterogeneity, allowing the identification of distinct cell types, transitional states, and developmental trajectories. Nevertheless, scRNAseq is associated with higher cost, limited scalability, increased technical noise, sparse expression matrices, and protocol-dependent biases introduced during tissue dissociation or nuclear isolation. In this review, we summarize the conceptual and methodological foundations of integrating bulk RNAseq and scRNAseq data, emphasizing their complementary strengths and limitations. We discuss how scRNAseq-derived cell-type atlases can serve as reference matrices for computational reconstruction (deconvolution) of bulk RNAseq profiles and examine key sources of technical and biological variability. Furthermore, we outline major integration strategies, including reference-based deconvolution, pseudobulk aggregation, and Bayesian joint modeling to provide an overview of widely used analytical tools and essential components of scRNAseq data processing workflows.
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Single-cell multimodal profiling of pan-cancer cell lines uncovers gene regulatory principles underlying intrinsic cell states and environmental features.
Cancer arises from genetic and epigenetic alterations that reshape chromatin, transcriptional regulation, and malignant cell states. To chart cancer-intrinsic regulatory programs, we build a pan-cancer single-cell atlas of 60 cancer cell lines spanning 16 tissue origins and 20 cancer types, comprising 240,957 snRNA-seq and 223,347 snATAC-seq profiles. Integrative analyses reveal cell-state heterogeneity, core gene-regulatory networks, and a conserved EMT axis transcending tissue of origin; copy-number analysis identifies transcription factor amplification and hyperactivation as drivers of state reprogramming. Comparing cutaneous melanoma with acral melanoma, a rare subtype underrepresented in previous studies, uncovers a universal inflammation-suppressive program in acral and an inflamed landscape in cutaneous melanoma, with JAK-STAT activity as the central discriminator. Integrating data across models and patient cohorts links tumor-intrinsic regulation to microenvironmental composition and therapeutic response. By profiling rare alongside common subtypes, this atlas offers a resource for mapping pan-cancer and subtype-specific regulatory programs shaping cell-state plasticity.
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DISCERN: inferring drug sensitivity from single-cell transcriptomes using cell-type-specific genetic interaction networks.
BACKGROUND: Genetic interactions, including synthetic lethality (SL) and synthetic viability (SV), are crucial for understanding tumor-specific vulnerabilities and mechanisms of drug resistance. However, predicting drug response at single-cell resolution based on SL and SV remains challenging. METHODS: Here, we construct a large-scale atlas of cell-type-specific SL and SV networks across 14 human cancers using scRNA-seq datasets. Based on this atlas, we develop DISCERN (Drug response Inference from Single-Cell gEnetic inteRactioNs), a novel computational framework designed to infer single-cell drug sensitivity by utilizing malignant cell-specific genetic interactions. We also establish CellGIdb, an interactive portal that provides the cell-type-specific genetic interaction networks. RESULTS: We reconstruct cell-type-specific genetic interaction networks across cancers, revealing both shared and distinct patterns among cell types. Notably, SL and SV interactions derived from malignant cells and T cells exhibit prognostic value and correlate with response to immunotherapy. DISCERN effectively infers tumor cell-specific drug sensitivity in scRNA-seq datasets from lung and breast cancers. DISCERN demonstrates improved predictive performance compared with existing computational methods. CellGIdb provides user-friendly analytical tools to facilitate the exploration of genetic interactions' roles in drug response and immunotherapy. CONCLUSIONS: Collectively, this study provides a comprehensive atlas and a novel computational framework, DISCERN, for interpreting drug responses in the context of genetic interactions at single-cell resolution. The publicly available CellGIdb ( https://biodata.hrbmu.edu.cn/CellGIdb/index.html ) resource will support further exploration of cell-type-specific vulnerabilities in cancer therapy.
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A single-nucleus transcriptome atlas of soybean anthers.
Anther development is crucial for plant sexual reproduction. However, a high-resolution, cell-type-specific transcriptomic atlas of this process is lacking for the legume crop soybean (Glycine max). Here, we construct a comprehensive transcriptional atlas of developing soybean anthers using single-nucleus RNA sequencing (snRNA-seq). We identify and characterize nine distinct cell types spanning both somatic and reproductive lineages. Our analysis reveals robust transcriptional continuity across anther developmental stages and dynamic reprogramming during key transitions. Notably, the shift from diploid meiocytes to haploid unicellular microspores is marked by the induction of previously inactive genes, despite an overall reduction in transcript abundance. Subsequently, within bicellular microspores, generative and vegetative cell lineages exhibit sharply divergent transcriptional programs: generative cells specialize in mRNA export and turnover, whereas vegetative cells up-regulate translational machinery. Evolutionary analysis further indicates that generative-cell-specific genes are subject to more relaxed purifying selection compared to those specific to vegetative cells. Functional validation using mutants generated by CRISPR/Cas9-mediated genome editing and EMS mutagenesis reveals the essential roles of OSD1A and PKSA in pollen development and fertility. This high-resolution atlas provides fundamental insights into the transcriptional regulation of soybean anther development and serves as a valuable resource for manipulating male fertility to advance hybrid breeding programs. The data are available at https://databases.genedenovo.com/pollen.
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Integrated Spatial and Single-Cell Transcriptomics Reveals Poor Prognostic Ligand-Receptor Pairs in Glioblastoma.
Glioblastoma (GBM) is an aggressive and lethal malignant brain tumor. Cell-cell interactions (CCIs) in the tumor microenvironment, mediated by ligand-receptor (LR) pairs, are known to contribute to its poor prognosis. However, the prognostic influence of CCIs on patients with GBM and the spatial expression profiles of such LR pairs within tumor tissues remain incompletely understood. This study aimed to identify prognostic LR pairs in GBM and their intratumoral localization via multitranscriptomic analysis. The CCIs among GBM cells as well as between GBM and niche cells were comprehensively evaluated using 40,958 cells in single-cell RNA sequencing datasets. They were found to form intercellular networks in GBM by specific LR pairs, which were mainly implicated in extracellular matrix (ECM)-related biological processes. Survival analysis revealed that 13 LR pairs related to ECM biological processes contributed to poor prognosis (p < 0.05, and 95% confidence intervals > 1). Notably, our spatial transcriptomic analysis using three independent GBM cohorts revealed that the identified poor prognostic LR pairs were localized in specific regions within GBM tissues. Although the clinical importance of these LR pairs requires further investigation, our findings suggest potential therapeutic targets for GBM.
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Single-cell transcriptomic atlas-guided NRG3-ERBB4 axis enhances the efficacy of chemo-immunotherapy during induction phase in high-risk neuroblastoma.
Chemo-immunotherapy (CI) administered during the induction phase markedly ameliorates immune responses and improves clinical efficacy in patients with high-risk neuroblastoma (NB), yet the underlying translational mechanisms remain poorly defined. Single-cell transcriptomic analysis revealed selective activation of the NRG3-ERBB4 axis in pretreatment tumor specimens from high-risk NB patients, accompanied by augmented cytotoxic programs in CD8+ T cells and natural killer cells. During induction therapy, chemotherapy alone suppressed NRG3 and ERBB4 expression, whereas their levels were significantly upregulated upon the addition of naxitamab and positively correlated with NB-reactive immune responses. Functional assays further confirmed that NB cells exposed to CI activated NRG3-ERBB4 signaling, which in turn induced the upregulation of GZMB and GNLY in effector lymphocytes. Integrated analysis of bulk RNA sequencing and lipidomics further demonstrated that the NRG3-ERBB4 rewired ganglioside metabolism to limit its intratumoral accumulation, thereby restoring tumor-reactive immune surveillance. Collectively, these findings delineate an NRG3-ERBB4 axis-centered tumor-immune crosstalk that operates across pretreatment, chemotherapy, and CI, uncovering a previously unrecognized mechanism underlying naxitamab-mediated immune activation. Our results also support ERBB4 as a promising predictive biomarker and therapeutic target to optimize CI strategies for high-risk NB.
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Single-cell atlas of the equine placenta reveals cellular heterogeneity and gestational-stage-associated programs.
INTRODUCTION: The placenta mediates critical interactions between mother and offspring that guide development and impact long-term health. Despite its importance, the cellular organization of the equine (Equus caballus) placenta remains poorly defined. The equine epitheliochorial placenta, characterized by the absence of trophoblast invasion and prominent endocrine activity, provides a unique comparative model for studying placental cellular composition and development. METHODS: We applied single-cell RNA sequencing to chorioallantois tissue collected from first-trimester (n = 1) and term (n = 2) equine placentas to generate a comprehensive cellular atlas across gestation. RESULTS: We identified four major fetal cell lineages: trophoblast, stromal, endothelial, and Hofbauer-like cells. Subclustering revealed ten transcriptionally distinct cell populations, highlighting previously unrecognized heterogeneity within trophoblast, stromal, and Hofbauer-like cells. Comparative analyses between first-trimester and term placentas demonstrated marked gestational-stage-associated differences in cellular composition and gene expression programs. The early-stage placenta was dominated by shared transcriptional signatures associated with growth, extracellular matrix organization, and cell cycle activity, whereas term placentas exhibited increased immune-related and tissue remodeling pathways and greater cell type-specific specialization. DISCUSSION: Together, this study provides the first high-resolution single-cell transcriptomic atlas of the equine placenta, offering fundamental insights into placental cellular diversity and developmental dynamics. This resource establishes a foundation for comparative placental biology and for investigating equine gestational disorders.