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Found: 4 936
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Opposing gene regulatory programs governing myofiber development and maturation revealed at single nucleus resolution.
Skeletal muscle fibers express distinct gene programs during development and maturation, but the underlying gene regulatory networks that confer stage-specific myofiber properties remain unknown. To decipher these distinctive gene programs and how they respond to neural activity, we generated a combined multi-omic single-nucleus RNA-seq and ATAC-seq atlas of mouse skeletal muscle development at multiple stages of embryonic, fetal, and postnatal life. We found that Myogenin, Klf5, and Tead4 form a transcriptional complex that synergistically activates the expression of muscle genes in developing myofibers. During myofiber maturation, the transcription factor Maf acts as a transcriptional switch to activate the mature fast muscle gene program. In skeletal muscles of mutant mice lacking voltage-gated L-type Ca2+ channels (Cav1.1), Maf expression and myofiber maturation are impaired. These findings provide a transcriptional atlas of muscle development and reveal genetic links between myofiber formation, maturation, and contraction.
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A pilot multi-omics study reveals genetic mechanisms regulating milk component traits in dairy cattle.
Milk protein percentage (PP) and fat percentage (FP) are important indicators for measuring milk quality, but only a few causative genes such as DGAT1, GHR, and ABCG2, have been identified, indicating substantial potential for further exploration. Here, we integrated genotyping, RNA-seq, ATAC-seq, single-cell atlas and cis-QTLs datasets from the liver and mammary gland to investigate their genetic regulation. We identified cell type affecting milk composition, such as HPE2 and LumSec-HSPH1, and highlighted nine candidate genes (EFNA1, ERBB3, DUSP16, DEPTOR, TRIM46, HSTN, CIDEA, ACACA and SPP1) that are involved in the regulation of milk protein and fat synthesis through MAPK, AMPK, PI3K-Akt, and mTOR signalling pathways. Notably, EFNA1 was consistently identified across all omics analyses, showing increased promoter accessibility in the high PP group, potentially driven by CTCF and RXRA-mediated transcriptional activation. Overall, this study reveals potential cell types, candidate genes, and regulatory mechanisms influencing milk composition, offering insights to support milk quality improvement. The limited sample size represents the main constraint of this work, and future efforts will focus on population-scale genetic analyses and wet-lab validation.
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Single cell transcriptomic analysis of external genitalia reveals complex and sexually dimorphic cell populations in the early genital tubercle.
External genital organs are among the most recognizable sexually dimorphic characters. The penis and clitoris develop from the embryonic genital tubercle, an outgrowth at the anterior margin of the cloaca that undergoes an extensive period of development in male and female embryos prior to the onset of sexual differentiation. In mice, differentiation into the penis and clitoris begins around embryonic day (E)15.5. Current knowledge of cell types that comprise the genital tubercle is limited to a few studies that have fate mapped derivatives of endoderm, mesoderm, and ectoderm. Here we use single cell transcriptomics to characterize the cell populations in the genital tubercles of male and female mouse embryos at E14.5, approximately 24 h before the onset of sexual differentiation, and we present the first comprehensive atlas of single-cell gene expression during external genital development. Clustering analyses and annotation using marker genes shows 19 distinct cell populations in E14.5 genital tubercles. Mapping of cell clusters to anatomical locations using in situ gene expression patterns revealed granularity of cellular specializations and positional identities. Although E14.5 precedes sexually dimorphic morphogenesis of the genital tubercle, comparative analysis of males and females identified sexual dimorphisms at the single cell level, including male-specific cell clusters with transcriptional signatures of smooth muscle and bone progenitors, both of which are known to be sexually dimorphic in adult genitalia, as well as immune cells. These results provide a new resource for classification of external genital cell types based on gene expression profiles and reveal sex-specific cellular specializations in the early genital tubercle.
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Decoding the complexity of delayed wound healing following Enterococcus faecalis infection.
Wound infections are highly prevalent and can lead to delayed or failed healing, causing significant morbidity and adverse economic impacts. These infections occur in various contexts, including diabetic foot ulcers, burns, and surgical sites. Enterococcus faecalis is often found in persistent non-healing wounds, but its contribution to chronic wounds remains understudied. To address this, we employed single-cell RNA sequencing (scRNA-seq) on infected wounds in comparison to uninfected wounds in a mouse model. Examining over 23,000 cells, we created a comprehensive single-cell atlas that captures the cellular and transcriptomic landscape of these wounds. Our analysis revealed unique transcriptional and metabolic alterations in infected wounds, elucidating the distinct molecular changes associated with bacterial infection compared to the normal wound healing process. We identified dysregulated keratinocyte and fibroblast transcriptomes in response to infection, jointly contributing to an anti-inflammatory environment. Notably, E. faecalis infection prompted a premature, incomplete epithelial-mesenchymal transition in keratinocytes. Additionally, E. faecalis infection modulated M2-like macrophage polarization by inhibiting pro-inflammatory resolution in vitro, in vivo, and in our scRNA-seq atlas. Furthermore, we discovered macrophage crosstalk with neutrophils, which regulates chemokine signaling pathways, while promoting anti-inflammatory interactions with endothelial cells. Overall, our findings offer new insights into the immunosuppressive role of E. faecalis in wound infections.
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Single-cell analysis reveals insights into epithelial abnormalities in ovarian endometriosis.
Ovarian endometriosis is characterized by the growth of endometrial tissue within the ovary, causing infertility and chronic pain. However, its pathophysiology remains unclear. Utilizing high-precision single-cell RNA sequencing, we profile the normal, eutopic, and ectopic endometrium from 34 individuals across proliferative and secretory phases. We observe an increased proportion of ciliated cells in both eutopic and ectopic endometrium, characterized by a diminished expression of estrogen sulfotransferase, which likely confers apoptosis resistance. After translocating to ectopic lesions, endometrial epithelium upregulates nicotinamide N-methyltransferase expression that inhibits apoptosis by promoting deacetylation and subsequent nuclear exclusion of transcription factor forkhead box protein O1, thereby leading to the downregulation of the apoptotic gene BIM. Moreover, epithelial cells in ectopic lesions elevate HLA class II complex expression, which stimulates CD4+ T cells and consequently contributes to chronic inflammation. Altogether, our study provides a comprehensive atlas of ovarian endometriosis and highlights potential therapeutic targets for modulating apoptosis and inflammation.
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Transcriptome-wide characterization of genetic perturbations.
Single cell CRISPR screens such as Perturb-seq enable transcriptomic profiling of genetic perturbations at scale. However, the data produced by these screens are often noisy due to cost and technical constraints, limiting power to detect true effects with conventional differential expression analyses. Here, we introduce TRanscriptome-wide Analysis of Differential Expression (TRADE), a statistical framework which estimates the transcriptome-wide distribution of true differential expression effects from noisy gene-level measurements. Within TRADE, we derive multiple novel, interpretable statistical metrics, including the "transcriptome-wide impact", an estimator of the overall transcriptional effect of a perturbation which is stable across sampling depths. We analyze new and published large-scale Perturb-seq datasets to show that many true transcriptional effects are not statistically significant, but detectable in aggregate with TRADE. In a genome-scale Perturb-seq screen, we find that a typical gene perturbation affects an estimated 45 genes, whereas a typical essential gene perturbation affects over 500 genes. An advantage of our approach is its ability to compare the transcriptomic effects of genetic perturbations across contexts and dosages despite differences in power. We use this ability to identify perturbations with cell-type dependent effects and to find examples of perturbations where transcriptional responses are not only larger in magnitude, but also qualitatively different, as a function of dosage. Lastly, we expand our analysis to case/control comparison of gene expression for neuropsychiatric conditions, finding that transcriptomic effect correlations are greater than genetic correlations for these diagnoses. TRADE lays an analytic foundation for the systematic comparison of genetic perturbation atlases, as well as differential expression experiments more broadly.
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Identification of sex- and inflammation-associated heterogeneity in the mouse omentum.
The omentum is a critical intraperitoneal organ essential for peritoneal homeostasis, yet detailed characterization of its cellular composition remains limited by the lack of validated markers. Here, we employed single-cell RNA sequencing to systematically define cellular heterogeneity in naive and activated mouse omentum from both sexes. Our analysis identified previously uncharacterized immune and stromal cell subsets, including three macrophage subtypes with activation-dependent gene expression patterns, implying specialized roles in inflammation and immune regulation. Comparative analysis revealed marked transcriptional differences between omental and peritoneal macrophages, underscoring tissue-specific microenvironments. Additionally, sexually dimorphic gene expression in omental stromal cells correlated with peritoneal macrophage polarization, indicating sex-specific regulatory mechanisms. Critically, macrophages from omentum of female mice with ovarian cancer metastases showed unique gene signatures associated with tumor migration and invasion. Collectively, we provide the first comprehensive atlas of omental cell populations stratified by sex and activation state, offering novel insights into peritoneal immunity and identifying potential therapeutic targets for inflammatory and metastatic diseases.
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Cell type-specific gene expression dynamics during human brain maturation.
The human brain undergoes protracted post-natal maturation, guided by dynamic changes in gene expression. Most studies exploring these processes have used bulk tissue analyses, which mask cell type-specific gene expression dynamics. Here, using single nucleus (sn)RNA-seq on temporal lobe tissue, including samples of African ancestry, we build a joint paediatric and adult atlas of 75 cell subtypes, which we verify with spatial transcriptomics. We explore the differences between paediatric and adult cell types, revealing the genes and pathways that change during brain maturation. Our results highlight excitatory neuron subtypes, including the LTK and FREM subtypes, that show elevated expression of genes associated with cognition and synaptic plasticity in paediatric tissue. The new resources we present here improve our understanding of the brain during its development and contribute to global efforts to build an inclusive brain cell map.
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Single-cell atlas of early chick development reveals gradual segregation of neural crest lineage from the neural plate border during neurulation.
The epiblast of vertebrate embryos is comprised of neural and non-neural ectoderm, with the border territory at their intersection harboring neural crest and cranial placode progenitors. Here, we a generate single-cell atlas of the developing chick epiblast from late gastrulation through early neurulation stages to define transcriptional changes in the emerging 'neural plate border' as well as other regions of the epiblast. Focusing on the border territory, the results reveal gradual establishment of heterogeneous neural plate border signatures, including novel genes that we validate by fluorescent in situ hybridization. Developmental trajectory analysis infers that segregation of neural plate border lineages only commences at early neurulation, rather than at gastrulation as previously predicted. We find that cells expressing the prospective neural crest marker Pax7 contribute to multiple lineages, and a subset of premigratory neural crest cells shares a transcriptional signature with their border precursors. Together, our results suggest that cells at the neural plate border remain heterogeneous until early neurulation, at which time progenitors become progressively allocated toward defined neural crest and placode lineages. The data also can be mined to reveal changes throughout the developing epiblast.
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CSRP1 expression is associated with a mesenchymal, stroma-rich tumor profile and poor prognosis in colon cancer.
BACKGROUND/AIM: Cysteine and glycine-rich protein 1 (CSRP1) is involved in the cysteine-rich protein family and is a marker of smooth muscle lineages. In colon cancer, the expression of this gene is associated with poor prognosis. In this study, the aim was to reevaluate its prognostic relationship in independent cohorts and explore potential underlying biological processes that are linked to aggressive behavior in tumors with high CSRP1 expression, such as epithelial-to-mesenchymal transition (EMT), stromal fractions in the tumor microenvironment, and consensus molecular subtypes (CMSs). MATERIALS AND METHODS: RNA sequencing (RNAseq)-, microarray-, and single-cell RNAseq (scRNAseq)-based transcriptomic data were obtained from public databases. The EMT score was calculated based on the expression of E-cadherin and vimentin genes using a previously published method. The stromal score generated by the ESTIMATE method was utilized for the analysis of correlation with the CSRP1 expression. The scRNAseq data were analyzed via the Seurat R package. The immunohistochemistry-based protein level expression of CSRP1 was evaluated using the Human Protein Atlas database. RESULTS: Lower CSRP1 expression was noted in colon tumors compared to normal colon tissue. Patients with a high CSRP1 expression had shorter recurrence-free, overall, and disease-specific survivals in the GSE39582 and GSE17536 datasets (p < 0.05). The methylation level of the CSRP1 gene was negatively correlated (r = -0.57, p < 0.0001) with CSRP1 expression in The Cancer Genome Atlas colon adenocarcinoma dataset. CSRP1 expression was positively correlated with the expression of mesenchymal markers, EMT score, and stromal score obtained via the ESTIMATE method. CMS4 colon tumors had a significantly higher CSRP1 expression compared to other CMSs. Analysis of the scRNAseq data revealed that CSRP1 was expressed by epithelial cells and cancer-associated fibroblasts in the colorectal tumor microenvironment, which was also confirmed by the protein expression data from the Human Protein Atlas database. CONCLUSION: CSRP1 expression is associated with CMS4, a more mesenchymal stroma-rich molecular profile, and poor prognosis in colon cancer.