Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Influence of RNA Labeling on Expression Profiling of MicroRNAs

ABSTRACT: Several technical parameters are now being optimized for microRNA expression profiling experiments, but the finite amount of total RNA available continues to bottleneck clinical investigations. We used microarrays to determine the influence of the labeling reagent on total RNA requirements and data quality.

ORGANISM(S): synthetic construct Homo sapiens

PROVIDER: GSE30045 | GEO | 2012/05/22

SECONDARY ACCESSION(S): PRJNA144079

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Influence of RNA Labeling on Expression Profiling of MicroRNAs

Project description:Several technical parameters are now being optimized for microRNA expression profiling experiments, but the finite amount of total RNA available continues to bottleneck clinical investigations. We used microarrays to determine the influence of the labeling reagent on total RNA requirements and data quality. Human brain/lung samples were each labeled in duplicate, at 1.0ug, 0.5ug, 0.2ug, and 0.1ug of total RNA, using two microRNA labeling kits (Genisphere Biotin and Biotin-HSR) that utilize the same labeling procedure but differ in the composition of the labeling reagent used to label the microRNA molecules in the samples. A total of 32 arrays were used for this experiment. Additionally, synthetic microRNA spike-in experiments were also performed to establish the signal dynamic range of the microarray using the Biotin-HSR labeling kit. Two-fold serial dilution samples were prepared that contained from 5000 to 4.88 attomoles of miRNA. A total of 12 arrays were used for this experiment, including a negative control sample.

2012-05-21 | E-GEOD-30045 | biostudies-arrayexpress

Influence of RNA Labeling on Expression Profiling of MicroRNAs

Project description:Influence of RNA Labeling on Expression Profiling of MicroRNAs

| PRJNA144079 | ENA

Off-the-shelf proximity labeling

Project description:Off-the-shelf proximity labeling

| PRJNA716256 | ENA

Application of endoscopic injection labeling in accurate treatment of advanced rectal cancer

Project description:Interventions: Carbon nanoparticle suspension labeling group:None;Ordinary enteroscopy group:None Primary outcome(s): Length of distal incisal margin;Excision length of intestine;Lymph node acquisition;Length of submucosal invasion Study Design: Cohort study

| 85121 | ecrin-mdr-crc

Sample multiplexed scRNA-seq using Nanocoding method for sample barcode labeling

Project description:Sample multiplexed scRNA-seq is a promising strategy to overcome current barriers in high cost and potential technical variations by multiple scRNA-seq tests. In this study, we developed a highly efficienct novel sample barcode labeling method using DNA-encoded Lipid Nanoparticles ('Nanocoding') that could label cells with minimal dependence on their type or sample conditions. This method provids a roubust and general protocol for sample barcoding and multiplexing in scRNA-seq. We demonstrated the performance of Nanocoding through three scRNA-seq studies, which include: 1. mouse spleen cells mix (one dataset including 6 mouse spleen tissues samples); 2. HeLa-mouse Stromal Vascular Fraction(SVF) cells mix (one dataset containing mixed HeLa cell and SVF cell); 3. Aged-Young SVF cells mix (one dataset containing two SVF samples) tests. These studies showcased the biomodal distribution of barcode counts in different models with high signal-to-background ratio, as well as pan-cell labeling activity for efficient and accurate sample-multiplexing. By using Nanocoding, we profiled obsity and age related change in lipid metabolism associated genes or inflammatory related features, in various cell types from spleen or adipose tissues.

2024-12-09 | GSE280262 | GEO

Homology mediated end joining enables efficient non-viral targeted integration of large DNA templates in primary human T cells

Project description:Adoptive cellular therapy using genetically engineered immune cells holds tremendous promise for the treatment of advanced cancers. While the number of available receptors targeting tumor specific antigens continues to grow, the current reliance on viral vectors for clinical production of engineered immune cells remains a substantial bottleneck limiting translation of promising new therapies. Here, we describe an optimized methodology for efficient CRISPR-Cas9 based, non-viral engineering of primary human T cells that overcomes key limitations of previous approaches. By synergizing temporal optimization of reagent delivery, reagent composition, and integration mechanism, we achieve targeted integration of large DNA cargo at efficiencies nearing those of viral vector platforms with minimal toxicity. CAR-T cells generated using our approach are highly functional and elicit potent anti-tumor cytotoxicity in vitro and in vivo. Importantly, our method is readily adaptable to current Good Manufacturing Practices (cGMP) and clinical scale-up, offering a near-term alternative to the use of viral vectors for production of genetically engineered T cells for cancer immunotherapy.

2024-11-04 | GSE246558 | GEO

BAP-seq proximity labeling of subcellular compartments

Project description:BAP-seq proximity labeling of subcellular compartments

| PRJNA954517 | ENA

isotope labeling groups in autotrophic anammox system

Project description:isotope labeling groups in autotrophic anammox system Genome sequencing

| PRJNA765193 | ENA

Tracking chromatin state changes using nanoscale protoproximity labeling

Project description:Tracking chromatin state changes using nanoscale protoproximity labeling

| PRJNA915358 | ENA

Analysis of RNA-TAG labeling in HeLa lysates

Project description:Analysis of RNA-TAG labeling in HeLa lysates