Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Short hairpin RNAs artifactually impair cell growth and suppress clustered microRNA expression [gene expression]

ABSTRACT: Short hairpin RNAs artifactually impair cell growth and suppress clustered microRNA expression [gene expression]

PROVIDER: PRJNA493266 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Short hairpin RNAs artifactually impair cell growth and suppress clustered microRNA expression

Project description:Short hairpin RNAs artifactually impair cell growth and suppress clustered microRNA expression

| PRJNA493260 | ENA

Short hairpin RNAs artifactually impair cell growth and suppress clustered microRNA expression [miRNA expression]

Project description:Short hairpin RNAs artifactually impair cell growth and suppress clustered microRNA expression [miRNA expression]

| PRJNA493265 | ENA

Short hairpin RNAs artifactually impair cell growth and suppress clustered microRNA expression [gene expression]

Project description:Gene disruption is a central tenet of cancer research, where novel drug targets are often identified and validated through cell-growth based knockdown studies or screens. Short hairpin RNA (shRNA) mediated mRNA knockdown is widely used in both academic and pharmaceutical cancer research settings. However, off-target effects of shRNAs as well as interference with endogenous small RNA processing have both been reported. We show here that both gene-specific and control shRNA expression impair in vitro cell growth and preferentially decrease clustered microRNA levels, significantly reducing oncogenic microRNA cluster expression. In addition, exogenous shRNAs induce a depressed cell-cycle-gene expression signature that is shRNA-sequence independent and present across several studies. The collective impact of these observations is important to cancer research, given the widespread historical use of shRNAs in the field and the common goal of interrogating genes that regulate proliferation. We therefore recommend that for future shRNA use, care be taken to titrate lentiviral dose, use hairpin-expressing controls, perform gene-of-interest rescue experiments and/or validate shRNA-derived results by small interfering RNA (siRNA) knockdown or CRISPR/Cas9-mediated genetic knockout.

2025-09-01 | GSE120525 | GEO

Short hairpin RNAs artifactually impair cell growth and suppress clustered microRNA expression [miRNA expression]

2025-09-01 | GSE120526 | GEO

Short hairpin RNAs artifactually impair cell growth and suppress clustered microRNA expression

Project description:This SuperSeries is composed of the SubSeries listed below.

2025-09-01 | GSE120528 | GEO

Design of antiviral AGO2-dependent short hairpin RNAs

Project description:Design of antiviral AGO2-dependent short hairpin RNAs

| PRJNA1086185 | ENA

Expression data from short hairpin RNA mediated CTCF knockdown in human prostate epithelial cells

Project description:Transcriptional profiling of immortalized human prostate epithelial cells after CTCF knockdown by short hairpin RNA. Knockdown by shRNA targeting CTCF was conducted for 5 days by addition of doxycycline to induce shRNA expression. RNA was purified from triplicate biological replicates of induced and uninduced shRNA samples. Gene expression was quantified by hybridization to Affymetrix Human Transciptome 2.0 arrays.

2019-02-20 | GSE93363 | GEO

Design of antiviral AGO2-dependent short hairpin RNAs

Project description:The increasing emergence and re-emergence of RNA virus outbreaks underlines the urgent need to develop effective antivirals. RNA interference (RNAi) is a sequence-specific gene silencing mechanism that is triggered by small interference RNAs (siRNAs) or short hairpin RNAs (shRNAs), which exhibit significant promise for antiviral therapy. AGO2-dependent shRNA (agshRNA) generates a single-stranded guide RNA effector and presents significant advantages over traditional siRNA and shRNA. In this study, we applied a logistic regression algorithm to a previously published chemically siRNA efficacy dataset and built a machine learning-based algorithm with high predictive power. Using this algorithm, we designed siRNA sequences targeting diverse RNA viruses, including human enterovirus A71 (EV71), Zika virus (ZIKV), dengue virus 2 (DENV2), mouse hepatitis virus (MHV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and developed them into agshRNAs according to the rule of agshRNA design. These agshRNAs inhibited viral replication in infected cells and their efficiencies of antiviral effects displayed a consistent trend with the score ranking of siRNA sequences predicted by the algorithm. Using the agshRNA targeting EV71 as an example, we showed that the anti-EV71 effect of agshRNA was more potent compared with the corresponding siRNA and shRNA. Moreover, the antiviral effect of agshRNA is dependent on AGO2-processed guide RNA, which can load into the RISC. We also confirmed the antiviral effect of agshRNA in vivo. Together, this work develop a novel approach that combines machine learning-based algorithm and agshRNA design to custom design antiviral agshRNAs with high efficiency.

2024-09-18 | GSE261262 | GEO

Tumor PD-L1 engages myeloid PD-1 to suppress type I interferon to impair cytotoxic T lymphocyte recruitment

Project description:Tumor PD-L1 engages myeloid PD-1 to suppress type I interferon to impair cytotoxic T lymphocyte recruitment

| PRJNA633487 | ENA

Transcription Analysis of Clustered Essential Genes

Project description:Transcription Analysis of Clustered Essential Genes

| PRJNA612782 | ENA