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:Nano-GLADIATOR: real-time detection of copy number alterations from nanopore sequencing data.
| PRJEB27516 | ENA
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:PacBio HiFi and ONT UL FASTQ data
| PRJEB77558 | ENA
Project description:PacBio HiFi and ONT UL FASTQ data
| PRJEB75698 | ENA
Project description:PacBio HiFi and ONT UL FASTQ data
| PRJEB75739 | ENA
Project description:To identify genes with cell-lineage-specific expression not accessible by experimental micro-dissection, we developed a genome-scale iterative method, in-silico nano-dissection, which leverages high-throughput functional-genomics data from tissue homogenates using a machine-learning framework. This study applied nano-dissection to chronic kidney disease and identified transcripts specific to podocytes, key cells in the glomerular filter responsible for hereditary proteinuric syndromes and acquired CKD. In-silico prediction accuracy exceeded predictions derived from fluorescence-tagged-murine podocytes, identified genes recently implicated in hereditary glomerular disease and predicted genes significantly correlated with kidney function. The nano-dissection method is broadly applicable to define lineage specificity in many functional and disease contexts.
2013-08-06 | GSE47184 | GEO