Articles tagged with Rna Sequencing
Researchers developed a novel model to identify specific genes and genetic alterations in multiple myeloma, stratifying the cancer's severity via DNA and RNA sequencing. This model revealed diverse subtypes and high-risk patients beyond current classifications.
Using next-generation sequencing, researchers identified four major regulatory pathways and specific molecular effectors behind COVID-19 symptoms. The study may pave the way for a more personalized approach to diagnosis and treatment.
Researchers at MIT and Harvard University have developed a way to selectively turn on gene therapies in target cells by detecting specific messenger RNA sequences. This technology can fine-tune gene therapies for applications ranging from regenerative medicine to cancer treatment, potentially reducing side effects and increasing efficacy.
A research group at Osaka University has developed a new tool for sequencing various types of RNA base modifications, including microRNA modifications. They successfully detected two types of chemical base modifications simultaneously using a single-molecule quantum sequencer.
Researchers found large numbers of B cells and their immature progenitors in the outer layer of the meninges, a surprising discovery that suggests these cells play a special immune system function there. The study used single-cell RNA sequencing to analyze the genes active in each individual cell and confirmed the finding in human tissue.
A study published in Cell Reports Medicine reveals the molecular and cellular changes in testicular tissue of infertile men, identifying alterations in spermatogonial stem cell compartment. The research provides new insights into male infertility and prepares ground for better diagnosis.
A new software, ModTect, identifies RNA modifications using pre-existing sequencing data, revealing associations with cancer survival outcomes. The study found dysregulation of the epitranscriptome in patients across multiple cancer types, associated with cancer progression and survival.
Researchers at Tampere University identified a specific population of treatment-resistant cells that persists in prostate cancer tissue. This finding suggests that the presence of these cells can predict patient responses to treatment and may help tailor treatment for different subgroups of patients.
Researchers discovered that noncoding RNA derived from pericentromeric repetitive sequences upregulates SASP-like inflammatory gene expression by disturbing chromatin interactions. hSATII RNA is highly detectable in cancer cells and supports tumor development via small EVs, highlighting a new role in age-related pathologies.
A new study by Ivan Zanoni at Boston Children's Hospital reveals a complex picture of interferon production in mild versus severe COVID-19. The researchers found that different types of interferons have opposite roles in the upper and lower respiratory tract, and that specific interferons determine disease severity.
Researchers studied electrical conduction through membranes during Controlled Breakdown, a technique to fabricate single nanopores. They found that redox reactions occur at the membrane-electrolyte interface, allowing localization of pore formation using metal microelectrodes.
A new study uses long-read sequencing to reveal diverse splicing events and unique exons in circular RNAs, which may play a role in neuronal disease. The research identifies microexons, previously linked to autism, as preferential findings in circRNAs.
Researchers developed a new model, MultiRM, that can predict the 12 most desirable RNA modifications for large-scale prediction. The approach integrates multiple tasks into a single prediction task, providing a more comprehensive view of epitranscriptomes and discovering underlying mechanisms.
Researchers from CeMM Research Center have developed a new method called scifi-RNA-seq that enables efficient RNA sequencing for millions of individual cells. This method marks the RNA of many cells with specific barcodes, allowing for analysis of complex tissues and organs.
Researchers developed a new method to test AI algorithms' decision-making processes by presenting them with carefully designed synthetic data. The technique, called Global Importance Analysis, revealed that AI models consider more factors beyond just sequence length, such as RNA folding and motif proximity.
Scientists at Cold Spring Harbor Laboratory have created a new tool called BARseq2 that uses genetic tags to label brain cells and trace thousands of brain circuits simultaneously. This allows researchers to examine the complex interactions between neurons, enabling a better understanding of brain function and behavior.
Researchers at Penn State develop a new framework for meta-assembly, allowing for accurate reconstruction of full-length mRNA sequences from short fragments. This enables better understanding of cell machinery and potential biomarkers for diagnosis.
Researchers at MIT have devised a way to label and sequence individual RNA molecules within a tissue sample, allowing for a unique snapshot of which genes are being expressed in different parts of a cell. This technique offers new insights into how gene expression is influenced by a cell's location or its interactions with nearby cells.
Researchers have discovered that coinfection with cytomegalovirus and Aspergillus fumigatus triggers synergistic interactions between the two pathogens and human cells, leading to increased risk of complications.
A new study from Baylor College of Medicine found that starting genetic analysis with RNA sequencing can increase diagnostic yield by up to 17% in rare genetic diseases. This approach allows for a more comprehensive understanding of the effects of noncoding changes and enhances confidence in diagnoses.
A new study provides an in-depth look at how CD4+ T cells respond to SARS-CoV-2, revealing a novel T cell subset that may contribute to severe COVID-19 cases. The research also found that dysfunctional TFH cells can lead to reduced antibody production and worsen disease severity.
A unified classification of diverse cell types in the cerebral cortex has been proposed by a Columbia-led team, which could shed light on how our brains work and potentially lead to treatments for diseases. The new system uses single-cell RNA sequencing and can be updated regularly using algorithms.
Researchers at ETH Zurich have developed a method to determine how tightly ribosomes bind to hundreds of thousands of RNA sequences in a single experiment, using machine learning and deep sequencing technology. This approach enables precise control over protein production in bacteria, with potential applications in genetic diseases.
A $2 million NSF award will support research on identifying and functionalizing dozens of different types of RNA modifications in diverse model and crop species. The project aims to develop resources that make it easier for plant scientists to utilize and expand upon the discoveries.
Researchers have identified many genome locations that code for RNA molecules influencing gene expression, using techniques like eCLIP and RNA Bind-N-Seq. The study reveals the functions of these RNA sequences and their interactions with RNA-binding proteins.
Scientists have developed an alternative approach to traditional immunohistochemistry, leveraging RNA sequencing to analyze tumor samples. The new method reveals correlations between specific biomarker genes and cancer diagnosis outcomes.
A genetic study reveals that COVID-19 and SARS viruses have stable RNA fragments with stem-and-loop structures, which may enhance virus survival. Researchers used a new technique called Fate-seq to analyze the stability of these sequences in human cells.
A new computational method, Souporcell, can accurately separate single-cell RNA sequencing data from multiple individuals without prior genome information. This enables researchers to study the effects of genetic variants on gene expression during infection or response to drugs.
Researchers at IBS South Korea successfully dissected SARS-CoV-2 RNA genome, mapping subgenomic RNAs to viral proteins. The study reveals dozens of unknown RNAs with potential roles in immune evasion.
Researchers developed an online tool to refine results from RNA sequencing obtained from clinically-accessible tissues. The study found that 40.2% of non-clinically-available tissues have inadequate splicing representation in at least one clinically-available tissue.
The Centre for Genomic Regulation has launched a new database to analyze COVID-19 data and compare different variations of the virus. Researchers can use this publicly available resource to study how SARS-CoV-2 grows, mutates, and replicates.
Researchers have developed a new technique to detect point mutations relevant to human health, providing accurate early diagnosis and guiding therapy. The method, called SNIPRs, can be applied in living cells and offers a rapid, highly accurate, and inexpensive means of identifying mutations.
A new study provides the first in-depth look at the human sperm microbiome using RNA sequencing. The researchers found that non-targeted sequencing of human sperm RNA can identify micro-organisms such as bacteria and viruses, offering a potential diagnostic tool for microbial status and fertility assessment.
Researchers in a new study employ RNA sequencing techniques to classify brain cells in crabs, finding that single-method approaches yield inaccurate results. By combining multiple modalities of data, they reveal more accurate cell identities.
A Tel Aviv University study found a technical bias in RNA-seq data that often leads to false results. Researchers were able to identify and remove this bias, preserving biologically relevant findings.
Researchers validated a popular method using RNA sequencing to identify unknown human brain neurons by comparing it with crab nervous system data. The study could contribute to future breakthroughs in understanding the brain and neurological diseases.
Researchers identified a potential new therapy for lymphatic filariasis, a disabling parasitic disease, using innovative RNA sequencing techniques. The experimental cancer drug JQ1 effectively kills adult worms in laboratory settings and may be more effective than standard treatments.
Researchers at Carnegie Mellon University have developed an algorithm to identify and correct mistakes in gene expression data, a major breakthrough in biological research. The CMU algorithm has detected 88 previously unknown anomalies in widely used RNA-seq libraries, opening up new avenues for investigation.
A technique identified T cells that react to peanut allergens by analyzing their RNA expression. The study could help guide researchers in developing new treatments for food allergies.
Researchers found a technical bias in RNA-seq data, leading to false results and misinterpretation of biological functions. The study highlights the importance of proper statistical handling to filter out false calls and preserve genuine findings.
A team of researchers used single-cell RNA sequencing to understand herpes simplex virus type 1 (HSV-1) infections. They found that the NRF2 transcription factor slows infection progression and identified a drug, bardoxolone methyl, that inhibits HSV-1 by activating this factor.
Researchers developed SILVER-seq to detect extracellular RNA in 5-7-microliter droplets of blood serum. The assay distinguishes between biopsies from patients with breast cancer and control samples, suggesting its potential use in diagnostic trials.
Researchers have developed a new technology that uses DNA for information processing and storage in living cells. The DOMINO system enables the deep interrogation of biology and can execute cascades of DNA writing events in response to biological signals.
A study published in PLOS Biology analyzed RNA transcripts from a 14,300-year-old canid preserved in Siberian permafrost, providing evidence that RNA from ancient animals may be well-preserved. The analysis revealed tissue-specific transcriptomes in the ancient wolf, with many liver-specific transcripts matching modern samples.
A new study published in Nature reveals the full spectrum of cells involved in congenital heart defect formation, identifying key cell types and their functions. The research uses single-cell RNA sequencing to uncover the molecular drivers of different cell types, shedding light on genetic mutations and disease mechanisms.
A comprehensive RNA sequence analysis reveals that normal cell populations contain lineages of mutational mosaics, with sun-exposed skin and throat tissues developing more mutations. The study's findings suggest a link between age, cell proliferation rate, and environmental exposure to cancer risk.
BRB-seq, a novel approach to RNA sequencing, preserves strand-specificity and detects the same number of genes as gold standard methods. The technique is 25 times less expensive than commercial RNA sequencing technologies, enabling bulk RNA sequencing of large sets of samples.
Researchers have developed a new analytical tool that uses deep learning to analyze RNA splicing patterns from modestly covered RNA sequencing data sets. This tool, DARTS, enables scientists to discover disease biomarkers and therapeutic targets more efficiently.
Single-cell RNA-seq technology reveals which genes are active in early embryo cells, offering a snapshot of cellular behavior. Researchers use molecular trackers to monitor individual cells' fate during development, shedding light on organ formation and tissue regeneration.
Astronauts may have access to fresh salads in space, but the microgravity environment affects plant growth. Researchers compared two transcriptomic approaches to understand how plants adapt, finding that RNA-Seq and microarray chips have relative advantages.
Researchers from the University of Chicago have developed a high-throughput RNA sequencing strategy to study the activity of the gut microbiome. The new tools analyze transfer RNA, allowing scientists to understand the activity of naturally occurring microbiomes and study their responses to environmental changes.
A team of scientists has developed a new method for detecting specific strains of E. coli using molecular electronics, which could lead to rapid and straightforward detection of pathogens and antimicrobial resistant bacterial strains.
Researchers have developed a more sensitive single-cell RNA sequencing method, mcSCRB-seq, to analyze the functional state of individual cells. This technique provides a molecular fingerprint of each cell's mRNA population, revealing its protein-making capacity and gene regulation.
A team of researchers has identified 40 new subtypes of retinal ganglion cells, shedding light on the molecular differences that distinguish them. The study, published in Nature Communications, provides a detailed census of RGCs and demonstrates the importance of single-cell RNA sequencing in understanding cell type identity.
Researchers have developed a simpler and faster CRISPR method that allows for off-the-shelf genome engineering, reducing the barrier to entry for this powerful technology. The approach targets universal sequences found in gene knockout collections, enabling rapid single nucleotide editing and generating chromosomal mutant collections.
A team of clinical neurologists, molecular biologists, and computer scientists have uncovered the earliest events in motor neuron disease using stem cell technology and RNA sequencing data. They discovered that a protein called SFPQ is lost from the nucleus in diseased motor neurons, leading to their death.
The new software, called Scallop, can reconstruct complete RNA transcripts from fragments of RNA sequences with improved accuracy. This advancement will help scientists better understand the regulation of gene expression.
Researchers Shenglong Zhang and Wenjia Li are developing novel direct RNA sequencing methods to explore potential environmental and biological factors in serious diseases like cancer and diabetes. Their new tool can analyze RNA modifications in human, animal, and bacterial cells.
A new technique called CITE-seq enables simultaneous measurement of transcriptomes and proteins on thousands of single cells, offering a major breakthrough in cell typing and disease research. The tool has the potential to characterize tumor heterogeneity and develop new immunotherapeutic approaches.
Researchers created a new tool that analyzes RNA sequencing data using topology, providing insights into cellular differentiation and development. The approach identifies connections between cellular states and genes active during development, offering potential discoveries in understanding cell identity and guiding cellular development.