Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “ScRNA-seq”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

131 records · Page 8Linked to original sources
PubMed2026

Single-nucleus profiling of postmortem diffuse midline gliomas identifies mitochondrial biogenesis as a resistance mechanism to imipridone therapy.

BACKGROUND: Imipridone ONC201 is the first FDA-approved therapy for H3K27-altered diffuse midline glioma; however, clinical responses remain limited. Defining tumor-intrinsic determinants and microenvironmental, extrinsic factors that shape sensitivity or resistance to imipridones will identify actionable therapeutic opportunities and inform improved clinical strategies. METHODS: To identify mechanisms of imipridone resistance, we obtained postmortem brain tissue from DMG patients who had received imipridones and/or standard care. Single-nucleus RNA and open-chromatin sequencing were performed on N = 22 cases. Immunofluorescence-based myeloid phenotyping was performed on N = 46 cases. Mitochondrial copy-number analysis was performed on N = 19 cases. Validation of imipridone sensitivity, its effect on mitochondrial density, and its synergy with inhibition of mitochondrial biogenesis were assessed in DMG primary cells. RESULTS: We established a single-cell RNA/open-chromatin atlas from postmortem DMG cases and found imipridone treatment resulting in regressed mesenchymal transition, reduced myeloid-derived suppressive cells, and reversed aberrant H3K27-altered enhancer activity. Resistant tumors showed increased mitochondrial density, turnover, and membrane potential. Mitochondrial biogenesis and PPARGC1A emerged as resistance biomarkers and actionable targets. CONCLUSIONS: These studies implicate mitochondrial biogenesis as a biomarker of imipridone resistance and a focus for the development of combinatorial strategies to provide effective therapeutic options for a challenging pediatric brain tumor.

Humans↗
PubMed2025

Ovarian development is driven by early spatiotemporal priming of the coelomic epithelium.

Ovarian organogenesis requires the coordinated specification of supporting and steroidogenic cell lineages from multipotent coelomic epithelium (CE) progenitors. A longstanding question is whether the CE contains transcriptionally distinct, spatially organized progenitor subpopulations with predetermined lineage biases, or whether specification into supporting and steroidogenic lineages occurs only after delamination and integration into the bipotential gonad. The developmental origins of granulosa cells and the emergence of ovarian steroidogenic/stromal progenitors (SPs) also remain poorly defined. Here, we show that CE cells covering the fetal mouse ovary are transcriptionally heterogeneous and spatially organized into subdomains already primed toward supporting or steroidogenic fates. CE priming is dynamic, with transient coexistence of supporting- and steroidogenic-biased CE progenitors before resolving into a predominantly supporting-biased CE. Local delamination of these primed cells seeds intragonadal niches where pre-granulosa cells and SPs mirror the spatio-temporal arrangements of CE-primed progenitors. We further demonstrate a dual origin for the supporting lineage, with granulosa cells deriving from both the CE and supporting-like cells (SLCs). In parallel, we show that SPs arise from steroidogenic-primed CE cells, expand to represent 52% of ovarian somatic cells at birth, persist into adulthood and contribute to both theca and steroidogenic stromal cells. Together, these findings reveal transcriptionally and spatially distinct CE subpopulations that shape somatic lineage emergence with important implications for ovarian pathophysiology.

Ovarian development↗
PubMed2025

Cellular imbalance in proximal and distal lung of CFTR-/- sheep in utero and at birth.

BACKGROUND: The Lung is the major focus of therapeutic approaches for the inherited disorder cystic fibrosis (CF) as without treatment lung disease is life-limiting. However, the initiating events that predispose the CF lung to cycles of infection, inflammation and resultant tissue damage are still unclear. Inflammation may occur in the CF lung prior to birth in human and several large animal models suggesting an in utero origin for the disease and encouraging further studies prior to birth. METHODS: Here we used the sheep model of CF (CFTR-/-) and age-matched wild-type (WT) sheep of the same breed to investigate the single cell transcriptomes of proximal and distal lung tissue at 80 days and 120 days of gestation and at term (147 days). Single cell RNA-seq was performed on tissues from 4 to 7 animals of each genotype (WT and CFTR-/-) at each time point. RESULTS: At term, FOXJ1-expressing ciliated cells are overrepresented in both lung regions from CFTR-/- lambs, while secretory epithelial and basal cells are underrepresented in proximal lung, as are T cells and monocytes in distal lung. The imbalance in ciliated and basal cells was confirmed by immunohistochemistry. At 120 days of gestation, lymphoid cells are slightly more abundant in proximal and distal lung from CFTR-/- animals compared to WT, consistent with the transient CF-associated inflammatory response in utero. At 80 days of gestation, T and B cells are underrepresented in both lung regions. CONCLUSIONS: The differences in epithelial cell abundance observed in the CFTR-/- lambs at term may reflect sequelae from the loss of CFTR on lung development and differentiation in utero. These findings provide novel insights into the cellular mechanisms of pathology and may be relevant to the design of new therapeutic approaches for CF lung disease.

Animals↗
PubMed2024

Single cell RNA sequencing provides novel cellular transcriptional profiles and underlying pathogenesis of presbycusis.

Age-related hearing loss (ARHL) or presbycusis is associated with irreversible progressive damage in the inner ear, where the sound is transduced into electrical signal; but the detailed mechanism remains unclear. Here, we sought to determine the potential molecular mechanism involved in the pathogeneses of ARHL with bioinformatics methods. A single-cell transcriptome sequencing study was performed on the cochlear samples from young and aged mice. Detection of identified cell type marker allowed us to screen 18 transcriptional clusters, including myeloid cells, epithelial cells, B cells, endothelial cells, fibroblasts, T cells, inner pillar cells, neurons, inner phalangeal cells, and red blood cells. Cell-cell communications were analyzed between young and aged cochlear tissue samples by using the latest integration algorithms Cellchat. A total of 56 differentially expressed genes were screened between the two groups. Functional enrichment analysis showed these genes were mainly involved in immune, oxidative stress, apoptosis, and metabolic processes. The expression levels of crucial genes in cochlear tissues were further verified by immunohistochemistry. Overall, this study provides new theoretical support for the development of clinical therapeutic drugs.

Animals↗
PubMed2026

Benchmarking computational decontamination of ambient RNA.

Gene expression profiling of single cells using single-cell and single-nucleus RNA sequencing (sxRNA-seq) enables researchers to characterize cellular heterogeneity and unraveling complex biological processes at unprecedented resolution. However, sxRNA-seq faces challenges due to the presence of ambient RNA, extraneous RNA molecules not originating from the cells of interest. Sample preparation is a major source of ambient RNA, where harsh conditions can lead to cell lysis and the release of intracellular RNA. This inescapable inclusion of ambient RNA can cause erroneous results and hinder downstream analyses. To address this issue, various methodologies have been developed to identify, quantify, and remove ambient RNA. Here, we rigorously evaluate 7 state-of-the-art methodologies for ambient RNA removal using simulated datasets, species-mixing experiments of varying complexities, and genotype-mixing experiments. We find that no single method performs the best across all datasets and metrics, but CellBender, DecontX and SoupX generally perform well.

ambient RNA↗