Articles tagged with Single Cell Sequencing
Researchers created a comprehensive single-cell map of the tumor immune microenvironment in multiple myeloma and its precursor conditions. The study identified five distinct subtypes, or 'ecotypes,' that capture meaningful insights into signaling pathways and genetic programs not fully explained by disease stage alone.
Researchers identified why some patients with rare blastic plasmacytoid dendritic cell neoplasm (BPDCN) leukemia don't respond to tagraxofusp. Severe TET2 gene mutations and low TXNRD1 enzyme levels contribute to resistance, suggesting these biomarkers could predict treatment outcomes.
Researchers used patient-derived xenograft (PDX) models to study deadly DNA loops in cancer cells. They found significant similarities between human tumor samples and PDX models, including consistent presence of extra copies of oncogenes. These findings suggest that ecDNA-positive tumor cells may drive tumor growth and recurrence.
Researchers from The University of Osaka discovered that only a small proportion of CD8 T cells undergo sustained clonal expansion in multiple myeloma immunotherapy, leading to the strongest anti-tumor response. Early immune activity could help predict which cells will become effective cancer fighters.
Researchers have developed a new single-cell technology called CIPHER-seq that captures the timing of cytokine activity with greater accuracy. This allows for a clearer view of immune cell behavior and strengthens the foundation for understanding cancer, inflammation, and treatment resistance.
Researchers developed an interpretable machine learning algorithm, scOMM, to classify cell types consistently across different single-cell methods. The integration strategies and scOMM establish a robust approach for cell atlas generation in complex tissues, leading to the discovery of previously undetected rare cell types.
Scientists have identified a new cell type and discovered that many normal-looking prostate cells harbor cancer-related changes. The study's findings could lead to new risk factors, earlier detection methods, and more targeted therapies for patients at high risk of aggressive disease.
Researchers at Earlham Institute isolated and sequenced genomes from seven uncultured Bodo spp. single cells, revealing three potentially novel species with unique genetic diversity. The study advances the field of single-cell sequencing in protists, shedding light on hidden biodiversity and symbiotic relationships.
Researchers have uncovered unusual clustering of endothelial cells around immune cells, signaling the start of excessive collagen production and scarring. This discovery could lead to new treatments for fibrosis, a common complication in Crohn's Disease affecting 10-20% of patients.
Researchers developed a capsule-based method to analyze individual cells through multiple experimental steps, overcoming a long-standing limitation in cell research. The technology, called semi-permeable capsule technology, allows scientists to keep cells' DNA intact and analyze hundreds of thousands of cells simultaneously.
Seq-Scope-eXpanded allows researchers to see even finer transcription detail, enabling discoveries that weren't possible with previous methods. The technology has been expanded to capture transcriptome from tissue with greater resolution.
A new study maps the impact of stressors during pregnancy on the developing fetal brain, revealing a cell atlas and identifying key immune pathways. The research sheds light on how maternal gut-immune disruptions can shape neurodevelopmental disorders in children.
A new study led by Northwestern University finds that tanning bed use increases melanoma risk by almost threefold, with DNA changes detected in areas protected from sun exposure. The study's findings support a broader field of DNA injury caused by tanning beds.
A new method developed by Penn State researchers improves the analysis of genetic data, identifying more genes associated with neurodegenerative diseases like Alzheimer's and ALS. The technique, BASIC, integrates both bulk tissue samples and single-cell data to uncover shared genetic effects across different cell types.
A study published in Chinese Medical Journal identified tumor-promoting keratinocytes linked to HPV infection and poor prognosis. These cells were found to interact with immune cells, promoting tumor proliferation and differentiation.
A new method enables scientists to read the genomes of individual cells and viral particles in the environment more quickly and efficiently. The approach, known as environmental microcompartment genomics, increases throughput by an order of magnitude and provides unique insights into the diverse world of marine viruses.
A new study published in Science finds CTE shares genetic similarities with Alzheimer's disease, including DNA damage and tau protein buildup in the brain. Researchers used single-cell genome sequencing to identify somatic mutations in neurons from patients with CTE, revealing abnormal patterns of damage similar to those seen in AD.
Researchers at Aarhus University used mini-organs to show that cervical epithelial cells actively detect and combat infections, with uninfected cells becoming immune-active. This discovery opens opportunities for mucosal vaccines and targeted treatments against STIs and infertility.
iRECODE reduces technical and batch noise in single-cell data, revealing cellular patterns hidden by noise. The method outperforms existing techniques with high accuracy and low computational cost, enabling researchers to detect rare cell types and subtle biological changes.
Researchers at Cold Spring Harbor Laboratory have mapped two known stem cell regulators across thousands of maize and Arabidopsis shoot cells. This discovery reveals new stem cell regulators in both species and links some to size variations in maize.
A team of scientists has estimated that an average cell line acquires and retains roughly 13 percent of its genes every million years through lateral gene transfer. This process enables microbes to adapt to new environments and access essential nutrients. The study provides the first quantitative analysis of gene transfer rates across ...
This study reveals that GPNMB modifies the tumor microenvironment by repurposing macrophages into immunosuppressive tumor-associated macrophages. The interaction between GPNMB and Siglec-9 enables this reprogramming, leading to increased cancer cell motility and invasiveness.
A randomized, placebo-controlled study shows that acupuncture can safely reduce methadone requirements and counteract opioid-induced immune and gut disturbances. Acupuncture was found to lower methadone doses by 20% in 84% of patients, while boosting antiviral gene activity and restoring bile acid balance.
A head-to-head comparison of five scRNA-seq CNV inference methods identified CaSpER and CopyKAT as top performers, excelling in tumor subpopulation identification and rare cell detection. The study provides a roadmap for researchers to select accurate CNV tools tailored to specific platforms and research goals.
The study reveals three new subsets of follicular T cells that increase in follicular lymphoma, each with distinct gene expression and spatial distribution patterns. These T-cell subsets serve as a strong predictor of patient prognosis, enhancing treatment approaches for the disease.
Researchers mapped the bone marrow T-cell atlas in CML patients, identifying a CML-specific T-cell population and its interaction with the bone marrow microenvironment. The study found that CD8 TE cells play a key role in regulating the CML immune microenvironment.
Scientists have developed a new tool named scICE to tackle the stability problem in single-cell RNA sequencing data. The tool provides a way to validate clustering outcomes mathematically, ensuring higher confidence in conclusions drawn from single-cell data.
A new technology, Toti-N-Seq, harnesses the presence of N-glycans to tag cells and nuclei, achieving precise sample multiplexing without cell-type or species restrictions. This enables accurate single-cell profiling, preserving rare cell populations and reducing doublet rates.
Dr. Eric Sun's groundbreaking work uses spatial aging clocks to measure biological age at the individual cell level, identifying specific cell types that drive brain aging in neighboring tissues. His machine learning models reveal complex intercellular communication networks that determine aging rates.
A new machine learning algorithm, SAVANA, has been developed to accurately detect structural variations in cancer genomes using long-read sequencing data. The algorithm was tested on 99 human tumour samples and showed high consistency with current clinical standards.
A new computational tool, CellWalker2, integrates different forms of biological data to reveal relationships between cell types. The tool identifies precise cell types and assigns broader labels based on hierarchical relationships, enabling scientists to compare cell types across experiments and species.
A new study reveals the spatial organization and tumor microenvironment of primary testicular diffuse large B-cell lymphomas. The research identifies exhausted CD8+ T cells and B1 cells as playing a role in tumor progression, while E2F and CREB inhibition shows promise as novel therapeutic targets.
Researchers analyzed DNA from four generations of a large family to understand genetic mutations and their transmission. They found that the rate of de novo mutations varied by over twenty-fold depending on genome location.
A novel AI-based method called scNET combines gene expression data with networks of possible gene interactions to identify biological patterns in response to drug treatments. The system reveals complex mechanisms underlying cellular behavior, providing insights for new therapeutic approaches.
Researchers identified four distinct cell populations in PDAC, including MMP1+ and S100A2+ tumor cells, CCL2+ macrophages, and OMD+ fibroblasts. These cell subsets contribute to a pro-tumor microenvironment, predicting unfavorable prognosis.
A new method has been developed to link individual microbes to their genetic code, providing insights into the activity of microorganisms in coastal sediments. The study reveals a diverse microbial community thriving in environments subject to frequent disruptions from rapid temperature changes and tides.
Researchers use generative AI to predict chromatin structures in single cells, overcoming limitations of existing experimental methods. The technique can generate thousands of structure predictions in minutes, enabling faster study of how 3D genome organization affects gene expression.
Scientists from Gladstone Institutes developed a new method called RASAM, which made a surprising discovery that large sections of newly formed DNA are hyperaccessible for many hours. This finding holds important implications for basic understanding of biology and the development of new medicines.
A zebrafish protein, Hmga1, has been found to unlock dormant genes for heart repair in mice. The discovery could lead to regenerative therapies to prevent heart failure in humans.
Researchers at Sanford Burnham Prebys used two sequencing methods to reveal new mRNAs associated with Alzheimer's disease, dementia with Lewy bodies, and Parkinson's disease. The study found vast mRNA isoform diversity in genes related to neurodegenerative diseases.
Researchers at the Hubrecht Institute have mapped the activity of DNA repair proteins in individual human cells, discovering unique and sometimes rare ways to repair DNA damage. These proteins organize into 'hubs' where multiple damaged DNA regions come together, making the process more efficient.
The Human Cell Atlas has made significant progress in mapping individual adult tissues, developing gut cell types for ulcerative colitis research, and creating comprehensive reference maps of all human cells. The initiative aims to capture all aspects of human diversity, including genetic, geographic, age, and sex, to advance diagnosti...
Researchers have created the world's largest freely-available resource of human gut cells, mapping 1.6 million cells to identify new ways to treat disease. The study highlights a specific gut cell type involved in inflammation, potentially leading to new targets for IBD treatment and bowel cancer prevention.
A team of researchers has developed strategies to identify regulators of intestinal hormone secretion, which could lead to new treatments for metabolic and gut motility disorders. They used human organoids to study the function of 'nutrient sensors' on hormone-producing cells in the gut.
A research team at IIT has identified a molecular signature in triple-negative breast cancer cells that can predict the formation of metastases and chemotherapy resistance. The study used single-cell sequencing to track the evolution of cancer cells over time, revealing key epigenetic features involved in tumor development.
The BICAN Rapid Release Inventory provides early access to single-cell transcriptomic and epigenomic profiles from humans and other mammalian species. This open data release aims to accelerate discoveries in neuroscience by facilitating collaboration and data reuse among researchers.
Scientists have mapped the global repertoire of genes that determine the male or female sexual fates in Plasmodium falciparum malaria parasites. This study reveals key regulators of gene expression during development and identifies novel candidate 'driver' genes, shedding light on the complex biology of malaria transmission.
Researchers at HIRI and THWS develop a desktop application to visualize scRNA-seq data, enabling interactive 3D exploration of gene expression in single cells. The tool allows users to focus on specific cell populations or genes of interest, facilitating better understanding of bacterial defenses against antibiotics.
Researchers discovered that dexamethasone works in patients with severe COVID-19 by influencing impaired inflammatory response through specific immune cells. A predictive tool using single-cell analysis can identify early responders to treatment, offering hope for targeted therapy development.
Researchers used single-cell sequencing technology to study immune responses in healthy adult volunteers exposed to SARS-CoV-2. They discovered unique immune responses associated with resisting sustained viral infection and disease, including activation of specialized mucosal immune cells and a reduction in inflammatory white blood cells.
Scientists at Gladstone Institutes developed two new tools for single-molecule analysis, slashing the amount of DNA needed by 90 to 95 percent. The SMRT-Tag tool allows researchers to study DNA at single-molecule resolution using as few as 10,000 cells, enabling the analysis of tumor biopsies and other clinically relevant samples.
Researchers have mapped the critical developmental stages of malaria parasite Plasmodium falciparum using single-cell RNA sequencing. This high-resolution approach reveals new insights into the life stages of the parasite, including its transformation from an asexual to sexual state.
Researchers at Karolinska Institutet developed a Single Cell Atlas (SCA) platform to profile human biology through multi-omics technologies. The extensive collection of data provides unique insights into individual cell properties and tissue interactions.
The study provides a detailed understanding of the progression of sarcopenia and frailty in older adults. Researchers identified key elements that predict susceptibility to sarcopenia, including changes in type 2 muscle fibers and cell metabolism.
Researchers developed a new method to link genetics and function of individual microbes living without oxygen deep below Earth's surface. The approach enabled discovery of the most active organism in a Death Valley groundwater aquifer, expanding its application to low biomass environments.
A team of Rice University researchers has developed a platform for integrating DNA and RNA data from single-cell sequencing with greater speed and precision. The method, MaCroDNA, relies on a classical algorithm to identify matching pairs of data and outperformed state-of-the-art technologies in accuracy measurements.