Nano-MDBG
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB88618 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Spatial transcriptomics workflows using barcoded capture arrays are commonly used for resolving gene expression in tissues. However, existing techniques are either limited by capture array density or are cost prohibitive for large scale atlasing. We present Nova-ST, a dense nano-patterned spatial transcriptomics technique derived from randomly barcoded Illumina sequencing flow cells. Nova-ST enables customized, low cost, flexible, and high-resolution spatial profiling of large tissue sections. Benchmarking on mouse brain sections demonstrates significantly higher sensitivity compared to existing methods, at reduced cost.
2024-02-22 | GSE256319 | GEO
Project description:Spatial transcriptomics workflows using barcoded capture arrays are commonly used for resolving gene expression in tissues. However, existing techniques are either limited by capture array density or are cost prohibitive for large scale atlasing. We present Nova-ST, a dense nano-patterned spatial transcriptomics technique derived from randomly barcoded Illumina sequencing flow cells. Nova-ST enables customized, low cost, flexible, and high-resolution spatial profiling of large tissue sections. Benchmarking on mouse brain sections demonstrates significantly higher sensitivity compared to existing methods, at reduced cost.
2024-02-22 | GSE256318 | GEO
Project description:To deeply investigate the details of the nano-SiO2 effects, we examined the gene expression profile alterations after nano-SiO2 treatment in BMMCs. The difference analysis between the groups showed that 285 genes were significantly expressed after treatment with nano-SiO2. Compared with the blank group, both nano-SiO2 exposure and DNP-HSA stimulation increased the expression of genes related to the MAPK signaling pathway in mast cells to varying degrees.
2022-07-05 | GSE206630 | GEO
Project description:During maturation, eukaryotic precursor RNAs undergo processing events including intron splicing, 3’-end cleavage, and polyadenylation. Here, we describe nanopore analysis of CO-transcriptional Processing (nano-COP), a method for probing the timing and patterns of RNA processing. An extension of native elongating transcript sequencing (NET-seq), which quantifies transcription genome-wide through short-read sequencing of nascent RNA 3’ ends, nano-COP uses long-read nascent RNA sequencing to observe global patterns of RNA processing. First, nascent RNA is stringently purified through a combination of 4-thiouridine metabolic labeling and cellular fractionation. In contrast to cDNA or short-read–based approaches relying on reverse transcription or amplification, the sample is sequenced directly through nanopores to reveal the native context of nascent RNA. nano-COP identifies both active transcription sites and splice isoforms of single RNA molecules during synthesis, providing insight into patterns of intron removal and the physical coupling between transcription and splicing. The nano-COP protocol yields data within 3 days.
2021-01-06 | GSE154079 | GEO
Project description:Long-read RNA sequencing technologies offer unparalleled in- sights into transcriptomes by enabling full-length sequencing of RNA molecules, uncovering novel isoforms and alternative splicing events. While long-read sequencing platforms, such as Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), have historically been associated with higher error rates, recent advancements in both platforms have significantly en- hanced read accuracy, broadening their applicability for tran- scriptomic studies. With the rapid evolution of sequencing protocols and bioin- formatics tools, the trade-offs between sequencing throughput, read length, accuracy, and cost present significant challenges in selecting the optimal approach. Systematic benchmarking studies that compare these options are crucial to inform fu- ture research directions. However, many existing benchmark- ing datasets with matched data across multiple platforms have limitations, including: 1) a lack of realistic biological replicates, which may restrict the generalisability of differential analysis results to real-world scenarios, and 2) the use of earlier sequenc- ing kits, which may not reflect the latest advancements in se- quencing technology, limiting their relevance for future studies that typically use newer sequencing protocols. Here we present LongBench, a comprehensive benchmarking dataset designed to fill these critical gaps. Derived from eight lung cancer cell lines with synthetic RNA spike-ins, LongBench includes bulk, single-cell, and single-nucleus RNA-seq data from three state-of-the-art long-read sequencing platforms — ONT PCR-cDNA, ONT direct RNA, PacBio Kinnex — alongside Il- lumina short-read data for robust cross-platform comparisons. The LongBench dataset is a valuable resource for benchmarking and improving sequencing protocols and bioinformatics tools. With the LongBench dataset we present a systematic evaluation of transcript capture, quantification, and differential expression analyses, examining the strengths and limitations of each se- quencing platform in various biological contexts, enabling re- searchers to make more informed decisions on platform and method selection.
2025-09-01 | GSE303762 | GEO
Project description:Eukaryotic genes often generate a variety of RNA isoforms that can lead to functionally distinct protein variants. The synthesis and stability of RNA isoforms is however poorly characterized. The reason for this is that current methods to quantify RNA metabolism use short-read sequencing that cannot detect RNA isoforms. Here we present nanopore sequencing-based Isoform Dynamics (nano-ID), a method that detects newly synthesized RNA isoforms and monitors isoform metabolism. nano-ID combines metabolic RNA labeling, long-read nanopore sequencing of native RNA molecules and machine learning. nano-ID derived RNA stability estimates enable a distinctive evaluation of stability determining factors such as sequence, poly(A)-tail length, RNA secondary structure, translation efficiency and RNA binding proteins. Application of nano-ID to the heat shock response in human cells reveals that many RNA isoforms change their stability. nano-ID also shows that the metabolism of individual RNA isoforms differs strongly from that estimated for the combined RNA signal at a specific gene locus. nano-ID enables studies of RNA metabolism on the level of single RNA molecules and isoforms in different cell states and conditions.
2020-05-06 | GSE127890 | GEO
Project description:Nano-GLADIATOR: real-time detection of copy number alterations from nanopore sequencing data.
| PRJEB27516 | ENA
Project description:Response of Nano-N (nano-urea) and Nano-Zn fertilizers to soil microbial community in response to Mustard-Pearl millet ecosystem Metagenome
| PRJNA993396 | ENA
Project description:We observe that the siIRF5 nano-immunotherapeutics were efficiently taken up by lesional macrophages, particularly Cd11c+ and Trem2hi macrophages, and enhanced their phagocytic clearance of apoptotic cells by efficiently silencing IRF5 expression within these macrophage subsets in atherosclerotic plaques. This resulted in remarkable therapeutic efficacy, as evidence by reduction of necrotic core area and enhancement of plaque stability in two independent ApoE-/- murine models of atherosclerosis. Mechanistically, single-cell RNA sequencing analysis revealed that siIRF5 nano-immunotherapeutics increased the pro-efferocytic receptors while decreasing the expression of pro-inflammatory genes associated with cytokine and chemokine pathways in lesional macrophages.
2025-08-14 | GSE301529 | GEO