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At least 307 records · Page 17Linked to original sources
PubMed2026

Identification of ultrasound-associated gene candidates in myeloid cells and construction of a prognostic risk model for acute myeloid leukemia.

BACKGROUND: Incorporating ultrasound (US) treatment sensitivity analysis may improve the treatment of acute myeloid leukemia (AML). METHODS: This study integrated single-cell and bulk datasets for analysis. Differential expression analysis between US-treated and control samples was performed using limma package. The AUCell package was used to calculate US-associated scores in the single-cell dataset. Differentially expressed genes (DEGs) between the specific groups were identified, followed by intersection analysis with previously identified DEGs. Univariate regression, Least Absolute Shrinkage and Selection Operator (LASSO) analysis (using the glmnet package), and stepwise multivariate regression (using the MASS package) were used to refine the candidate genes and to construct a risk model. The model genes were validated using in vitro experiments. Enrichment analysis was conducted using gene set enrichment analysis (GSEA), and immune infiltration was evaluate by single-sample GSEA (ssGSEA) and ESTIMATE algorithms. The correlations between RiskScores and drug sensitivity were analyzed by oncoPredict package. Finally, tumor mutational burden (TMB) and genomic mutations were compared between the risk groups. RESULTS: Nine prognostic signatures (SPINK2, HNRNPAB, SH3BGRL3, CLEC11A, ITGA4, RPL39L, MX1, HEXIM1, and MAP4K4) were identified. Particularly, low expression of SPINK2 attenuated the activity and invasion of AML cells. High-risk group had higher immune cell infiltration. Eight drugs were predicted to be correlated with the RiskScore model. DNMT3A and RUNX1 showed higher mutation frequencies in the high-risk group, whereas KIT and MUC16 showed higher mutation frequencies in the low-risk group. CONCLUSION: The RiskScore model established in this study provides a theoretical basis for clinically screening responsive populations and optimizing treatment strategies.

Humans↗
PubMed1997

Molecular single cell studies of normal and transformed lymphocytes.

The polymerase chain reaction allows the characterization of RNA and DNA sequences from single cells. Methods were established to analyse single cells isolated from suspension or by multicolour flow cytometry. We established a method to isolate single immunostained cells from frozen tissue sections and to analyse those cells for immunoglobulin gene rearrangements. This method was first used to study B cell differentiation within human germinal centres. In another series of experiments, Hodgkin and Reed-Sternberg (HRS) cells from a total of 14 cases of HD were analysed for B lineage derivation and clonality. In 13 of the 14 cases, clonal V gene rearrangements were identified. This shows that HRS cells generally represent the outgrowth of a clonal population of B cells. The detection of somatic mutations in all VH gene rearrangements amplified from HRS cells and the nature of those mutations identifies a GC B cell as the HRS precursor.

Gene Rearrangement↗
PubMed2026

Single-cell multiomics reveals exosome-mediated reprogramming and clonotypic remodeling of T cells in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive and immunogenic subtype lacking targeted therapies. While tumor-derived exosomes are known to modulate immune function, their direct impact on human T cell plasticity and antigen specificity remains poorly defined. Here, we conducted a comprehensive single-cell multiomic analysis of primary human T cells exposed to exosomes derived from 17 genomically diverse TNBC cell lines and 35 patient samples. Integrating single-cell RNA-seq, V(D)J sequencing, non-coding RNA profiling, bulk and single-cell cytokine analyses, we uncovered conserved and subtype-specific immunomodulatory programs induced by TNBC exosomes. Exosome-treated T cells displayed skewing toward regulatory and dysfunctional phenotypes, including Th17-like, Treg, and PD-1⁺/PD-L1⁺ Tfh cells. Functional profiling revealed suppression of early activation markers and cytokine responses, alongside selective preservation of cytotoxic features in γδ T and NKT subsets. Transcriptomic and miRNA network analyses demonstrated widespread downregulation of immune effector genes (e.g., HBEGF and TNFSF9) mediated by exosome-delivered regulatory miRNAs (has-miR-98-5p). Notably, exosome-stimulated T cells displayed distinct clonotypic expansions, characterized by the emergence of five tumor-specific γδ TCR clonotypes and 30 unique αβ TCR CDR3 sequences that were absent in mock-treated controls, underscoring the role of exosomes in shaping TCR repertoire dynamics.

Humans↗
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↗
PubMed2002

Complexities in ETS-domain transcription factor function and regulation: lessons from the TCF (ternary complex factor) subfamily. The Colworth Medal Lecture.

The ETS-domain transcription factor family can be divided into a series of subfamilies. Elk-1 represents the founding member of the ternary complex factor (TCF) subfamily. By focusing on the TCF subfamily, we can demonstrate the complexities that exist in the function and regulation of ETS-domain transcription factors. This article focuses on Elk-1 in detail and summarizes the functions of other TCFs. The key themes covered include the domain structure of the TCFs, the mechanisms of complex formation with serum response factor, regulation of TCFs by mitogen-activated protein kinase cascades, and transcriptional regulatory properties of the TCFs. Finally, the emerging role of the TCFs in vivo is discussed. A picture is developing indicating that, while these proteins exhibit significant sequence and functional conservation, key differences in their structure and regulation are being identified which may relate to unique functions of these proteins in vivo.

Amino Acid Sequence↗
PubMed2026

CHCHD10 Mitigates Alzheimer's Disease-Related Phenotypes in Association With Epigenetic Remodeling in Directly Reprogrammed Neurons.

Mitochondrial dysfunction and chromatin dysregulation are interconnected contributors to neuronal vulnerability in Alzheimer's disease (AD), yet the molecular mechanisms linking these processes remain poorly understood. CHCHD10, a mitochondrial intermembrane space protein, has been implicated in neurodegenerative disorders, but its role in AD has not been defined. Here, we identify CHCHD10 as a previously unrecognized modulator of neuronal epigenomic stability in AD. Using direct fibroblast-to-neuron reprogramming, which preserves patient-specific epigenetic signatures, we show that AD neurons recapitulate genome-wide hypomethylation patterns observed in postmortem AD cortex. CHCHD10 expression is significantly reduced in AD neurons and across multiple human brain datasets, including single-cell and bulk RNA sequencing, proteomics, and human cortical tissue analyses. Restoration of CHCHD10 in AD neurons reduces amyloid-β and insoluble tau accumulation while reversing AD-associated differentially methylated regions across CpG islands, promoters, and regulatory elements. CHCHD10-responsive methylation changes overlap with those observed in human AD brain regions and colocalize with significant AD loci and cortex-specific eQTL loci, including MAPT and ABCA7. Finally, we identify KATNAL2 as a CHCHD10-responsive effector whose loss enhances tau phosphorylation and seeding, whereas its restoration mitigates tau pathology. Together, these findings support a CHCHD10-associated neuroprotective pathway linking mitochondrial dysfunction, epigenomic instability, and tau pathology in AD.

Humans↗
PubMed2026

Cell-of-origin Discovery in Infant Leukemia through Integration of 3D Models and Patient Transcriptomic Data.

Pediatric hematological malignancies remain challenging to investigate and model due to the age group-specificity of certain genetic abnormalities. In utero origin has been demonstrated for a subset of pediatric leukemias, placing their respective cell of origin (CoO) during embryonic development. We recently reported a 3D hemogenic gastruloid (haemGx) model of embryonic blood formation derived from mouse embryonic stem cells, resolving the spatio-temporal complexity of developmental hematopoiesis. Importantly, it allows genetic engineering to introduce disease-relevant mutations. Using haemGx, we modeled the most common acute myeloid leukemia exclusive to infants (infAML), subtype t(7;12)(q36;p13), which arises in utero and is characterized by MNX1 overexpression. Here, we detail a method to define susceptibility to specific mutations that integrate phenotypic and transcriptional changes in the haemGx system and compares them with patient data. By proxy of our MNX1-overexpression haemGx, we show a pipeline from cell engineering to downstream analyses of leukemogenic potential. In particular, we focus on the clinical relevance of the model by integrating single-cell and/or bulk RNA sequencing from the haemGx platform with patient data to extract cellular composition and temporal placement of the putative CoO. This method is adaptable to the introduction of other oncogenic mutations, chromosomal rearrangements, or epigenetic modifications, as well as to chemical perturbations, including drug vulnerability and growth factor dependence. This flexibility allows for broad application across diverse disease contexts, enabling mechanistic dissection of how specific alterations disrupt early developmental trajectories with clinical relevance.

Humans↗
PubMed2026

A scalable, low-cost, sample hashing workflow for multiomic single-cell analysis using the Seq-Well S3 platform.

In-depth analyses of clinical samples have the potential to provide unparalleled insights into the cellular mechanisms that underlie both health and disease, as well as therapeutic and prophylactic responses. However, these specimens are often paucicellular, necessitating the use of workflows that maximize the amount of information that can be learned. Here we provide a detailed protocol for generating and analyzing single-cell multiomic data from low-input samples with the Seq-Well S3 platform. We further describe a matched pipeline for sample hashing that reduces costs and sources of technical variation in the resulting data while also enhancing throughput. In brief, our streamlined and efficient methodology involves: (1) optionally staining single-cell suspensions with antibody-oligonucleotide conjugates for cell surface protein quantification and/or sample multiplexing; (2) generating Seq-Well S3 sequencing libraries; (3) optionally producing bulk-RNA sequencing libraries via SMART-seq2 to support genetic demultiplexing; and (4) computationally analyzing the resulting data. Each step herein has been designed to leverage readily available reagents and standard laboratory equipment, substantially lowering barriers to entry for researchers. The overall Protocol can yield high-quality multiomic insights from samples in under a week.

Single-Cell Analysis↗
PubMed1995

Analysis of immunoglobulin gene rearrangements in single B cells.

The polymerase chain reaction allows the characterization of RNA and DNA sequences in samples as small as a single cell. The recent development of amplification systems designed to isolate rearranged immunoglobulin genes from single B lineage cells has provided a powerful tool to investigate various aspects of B-cell development.

Animals↗
PubMed2026

Multiancestry genome-wide association and multiomics analyses elucidate spatiocellular features of multiple sclerosis genetics.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by demyelination disseminated in space and time. Here we performed a genome-wide association study (GWAS) using 688 MS cases and 205,199 controls from the Japanese population and identified significant associations in the major histocompatibility complex region and a population-specific risk variant in 11q24. Through cross-population GWAS meta-analyses using a total of 29,374 cases and 1,843,563 controls from 4 ancestral populations, we identified 22 novel susceptibility loci. Integration of GWAS and single-cell and single-nucleus RNA sequencing of peripheral blood mononuclear cells and subcortical lesions from patients with MS revealed enrichment of genetic risk factors for MS in CD4+ T helper cell lineage and regulatory T cells, as well as in endothelial cells. Furthermore, spatial transcriptomics of subcortical lesions demonstrated spatial and temporal heterogeneity in associations with MS genetic risk. Our study demonstrates the value of investigation of spatiocellular features of disease genetics across diverse populations and omics modalities.

Humans↗
PubMed1979

Expression of single copy DNA sequences in nuclear RNA from undifferentiated mouse embryonal carcinoma and differentiated muscle cell line.

Nuclear RNA from an undifferentiated mouse embryonal carcionma (EC) cell line and a differentiated muscle (Mt) cell line from similar origin has been analysed with respect to base sequence complexity and frequency distribution with different probes. With the single copy component of mouse genomic DNA it is shown that total EC nuclear RNA and Mt nuclear RNA have respectively base sequence complexities of 100 Kb and 140 Kb corresponding to 6% and 8% of one strand of DNA. It is shown by hybridization with a purified DNA component complementary to total nuclear RNA that nuclear poly A+RNA in both cell types has only one fifth of total nuclear RNA complexity (as has polysomal RNA), but still contains all poly A+RNA present in polysomal poly A+RNA. Polysomal poly A+ sequences in total and poly A+ nuclear RNA are present in a restricted range of frequency distribution in contrast to the situation observed at the polysomal level. The implication of these results in terms of transcriptional and post-transcriptional control is discussed.

Animals↗
PubMed1990

[In situ hybridization: principles, methods and applications].

In situ hybridization is used to localize DNA or RNA sequences in tissue sections, single cells or chromosome preparations. The preparation and labeling of probes and the main steps of the technique are described and discussed together with its main applications.

Base Sequence↗
PubMed2025

Deciphering Cell Fate and Clonal Dynamics via Integrative Single-Cell Lineage Modeling.

Through natural or synthetic lineage barcodes, single-cell technologies now enable the joint measurement of molecular states and clonal identities, providing an unprecedented opportunity to study cell fate and dynamics. Yet, most computational methods for inferring cell development and differentiation rely exclusively on transcriptional similarity, overlooking the lineage information encoded by lineage barcodes. This limitation is exemplified by T cells, where subtle transcriptional differences mark divergent fates with distinct biological activity. Single-cell RNA and matched TCR sequencing is now ubiquitous in the analysis of clinical samples, where the TCR sequence provides an endogenous clonal barcode and could reveal clonal T cell responses. We present Clonotrace, a computational framework that jointly models gene expression and clonotype information to infer cell state transitions and fate biases with higher fidelity. While motivated by challenges in analyzing T cell populations, especially in the tumor microenvironment and immunotherapy settings, Clonotrace is broadly applicable to any lineage-barcoded single-cell dataset. Across diverse systems including T cells, hematopoietic differentiation, and cancer therapy resistance models, Clonotrace reveals differentiation hierarchies, distinguishes unipotent from multipotent states, and identifies candidate fate-determining genes driving lineage commitment.

Journal Article↗
PubMed2025

Deciphering Cell Fate and Clonal Dynamics via Integrative Single-Cell Lineage Modeling.

Through natural or synthetic lineage barcodes, single-cell technologies now enable the joint measurement of molecular states and clonal identities, providing an unprecedented opportunity to study cell fate and dynamics. Yet, most computational methods for inferring cell development and differentiation rely exclusively on transcriptional similarity, overlooking the lineage information encoded by lineage barcodes. This limitation is exemplified by T cells, where subtle transcriptional differences mark divergent fates with distinct biological activity. Single-cell RNA and matched TCR sequencing is now ubiquitous in the analysis of clinical samples, where the TCR sequence provides an endogenous clonal barcode and could reveal clonal T cell responses. We present Clonotrace, a computational framework that jointly models gene expression and clonotype information to infer cell state transitions and fate biases with higher fidelity. While motivated by challenges in analyzing T cell populations, especially in the tumor microenvironment and immunotherapy settings, Clonotrace is broadly applicable to any lineage-barcoded single-cell dataset. Across diverse systems including T cells, hematopoietic differentiation, and cancer therapy resistance models, Clonotrace reveals differentiation hierarchies, distinguishes unipotent from multipotent states, and identifies candidate fate-determining genes driving lineage commitment.

Journal Article↗
PubMed2025

Cell-type-specific response to silicon treatment in soybean leaves revealed by single-nucleus RNA sequencing and targeted gene editing.

Mineral nutrient uptake and deposition profoundly influence plant development, stress resilience, and productivity. Silicon (Si), though classified as a non-essential element, significantly influences a plant's physiology, particularly in fortifying defense responses and mitigating stress. While the genetic and molecular mechanisms of Si uptake and transport are well studied in monocots, particularly rice, their role in dicot species, such as soybean, remains unclear at the cellular and molecular levels. In this study, we utilized single-nucleus RNA sequencing (snRNA-seq) to dissect cellular responses to Si accumulation in soybean leaves. We identified distinct cellular populations, including a unique Si-induced or Si-associated cell cluster within vascular cells, suggesting a specialized mechanism of Si distribution. Si treatment notably induced the expression of defense-related genes, with a pronounced enrichment in vascular cells, underscoring their pivotal role in activating plant defense mechanisms. Moreover, Si modulated the expression of genes involved in phytoalexin biosynthesis, salicylic acid, and immune receptor signaling, suggesting transcriptional priming of genes involved in defense responses. Further investigation of Si transporters revealed precise expression of an Si efflux gene in epidermal cells in response to Si treatment. We also validated the role of efflux Si transporters using a Xenopus oocyte assay and CRISPR/Cas9 genome editing of composite soybean plant roots. This study provides critical insights into the biotic stress regulatory networks influenced by Si treatment in soybean leaves at the single-cell level, thus laying the foundation for enhancing stress tolerance through optimized mineral nutrient uptake.

Glycine max↗
PubMed2025

Single-cell analysis of dup15q syndrome reveals developmental and postnatal molecular changes in autism.

Duplication 15q (dup15q) syndrome is a leading genetic cause of autism spectrum disorder, offering a key model for studying autism-related mechanisms. Using single-cell and single-nucleus RNA sequencing of cortical organoids from dup15q patient-derived iPSCs and post-mortem brain samples, we identify increased glycolysis, disrupted layer-specific marker expression, and aberrant morphology in deep-layer neurons during fetal-stage organoid development. In adolescent-adult postmortem brains, upper-layer neurons exhibit heightened transcriptional burden related to synaptic signaling, a pattern shared with idiopathic autism. Using spatial transcriptomics, we confirm these cell-type-specific disruptions in brain tissue. By gene co-expression network analysis, we reveal disease-associated modules that are well preserved between postmortem and organoid samples, suggesting metabolic dysregulation that may lead to altered neuron projection, synaptic dysfunction, and neuron hyperexcitability in dup15q syndrome.

Humans↗
PubMed2025

Cell-type-specific dysregulation of gene expression due to Chd8 haploinsufficiency during mouse cortical development.

Disruptive variants in the chromodomain helicase CHD8 are associated with risk for autism spectrum disorder (ASD). CHD8 haploinsufficiency is hypothesized to contribute to ASD by perturbing neurodevelopmental gene expression. However, insight into cell-type-specific transcriptional effects of CHD8 haploinsufficiency remains limited. We used single-cell and single-nucleus RNA sequencing to identify dysregulated genes in the embryonic and juvenile Chd8+/- mouse cortex. Chd8 and other ASD risk-associated genes showed a convergent expression trajectory conserved between mouse and human developing cortex, increasing from progenitor zones to the cortical plate. Genes associated with neurodevelopmental disorders or involved in chromatin remodeling and neuron projection development were dysregulated in Chd8+/- embryonic radial glia. Genes implicated in synaptic activity and organization were dysregulated in Chd8+/- postnatal excitatory cortical neurons, suggesting impaired synaptogenesis. Our findings reveal complex patterns of transcriptional dysregulation due to Chd8 haploinsufficiency, potentially with distinct impacts on progenitors and maturing neurons in the excitatory neuronal lineage.

Animals↗