Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Sub-genomewide shRNAs constructed using an optimized selection algorithm and microRNA backbone provide stronger evidence for follow-up studies

ABSTRACT: Sub-genomewide shRNA libraries were constructed using the current RNAi consortium constructs as well as using the DSIR (siRNA algoirthm) and a novel shRNA specific algorithm (shERWOOD). All libraries were placed into mir30 expression vectors. The shERWOOD libraries were also placed in a vector harboring an optimized mir cassette (ultramir). Each library was screened using the pancreatic cell line A385. A concensus set of essential genes identified as the set for which two shRNAs depleted in each of the libries. For these genes, a great percentage of shERWOOD seletected shRNA depleted. In addition the placement of shERWOOD selected constructs into ultramir scaffoled increased the rate of shRNA depletion for essential genes further.

ORGANISM(S): synthetic construct

PROVIDER: GSE62185 | GEO | 2014/11/24

SECONDARY ACCESSION(S): PRJNA263392

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Sub-genomewide shRNAs constructed using an optimized selection algorithm and microRNA backbone provide stronger evidence for follow-up studies

Project description:Sub-genomewide shRNA libraries were constructed using the current RNAi consortium constructs as well as using the DSIR (siRNA algoirthm) and a novel shRNA specific algorithm (shERWOOD). All libraries were placed into mir30 expression vectors. The shERWOOD libraries were also placed in a vector harboring an optimized mir cassette (ultramir). Each library was screened using the pancreatic cell line A385. A concensus set of essential genes identified as the set for which two shRNAs depleted in each of the libries. For these genes, a great percentage of shERWOOD seletected shRNA depleted. In addition the placement of shERWOOD selected constructs into ultramir scaffoled increased the rate of shRNA depletion for essential genes further. Purpose: shRNA screens were carried out using various library construction strategies to identify the strategy that provides the best shRNA screening results. Method: Libraries were constructed using the TRC shRNA set as well as shRNAs identified using the DSIR and shERWOOD algorithms. shRNA libraries were cloned into mir30 expression vectors. shERWOOD shRNAs were also cloned into an expression vector harboring an optimized microRNA scaffold termed ultramir. Each resultant library was screened using the pancreatic cell line A385. Each library was analyzed separately to identify a set of genes where at least two shRNAs depleted. These gene sets were intersected to develop a set of essential genes. Results: The shERWOOD shRNA libraries provided the highest number depleting shRNAs for each essential gene. Further these shRNAs depleted to a greater extent than did the shRNAs from the other libraries. When shERWOOD libraries were placed into the ultramir cassette a greater number of shRNAs per essential gene depleted.

2014-11-24 | E-GEOD-62185 | biostudies-arrayexpress

Transcriptome profiling of hnRNP A2/B1 and A1 depleted cells

Project description:We used NEBNext UltraÂ DirectionalÂ RNA Library Prep Kits to prepare RNA-seq libraries of total RNA from hnRNP A2/B1 and A1 depleted A549 cells. Pro-seq libraries were prepared from A549 cells using Illumina adapters hnRNP A2/B1 and A1 depleted A549 cells were generated by lentiviral infections of shRNA constructs. RNAs were isolated using Trizol.

2016-05-17 | E-GEOD-76151 | biostudies-arrayexpress

RNA-seq analysis of BAP1-depleted uveal melanoma cells

Project description:OCM-1A uveal melanoma cells were infected with lentivirus carrying shRNA expression constructs specific for BAP1 or GFP (control), and placed under selection for 6 days. RNA-seq was performed.

2018-10-15 | GSE110193 | GEO

Small-hairpin RNAs cause target-independent microRNA dysregulation in neurons and elicit global transcriptomic changes (RNA-seq)

Project description:Ribosomal-depleted total RNA was isolated from neuronal cultures transduced with different shRNA constructs direct against shNogoA with and without mismatches in the seed region

2020-12-31 | GSE156878 | GEO

Whole genome pooled shRNA screen to characterize Raptinal-induced apoptosis in the MIA PaCa-2 cell line

Project description:The goal of the study was to characterize the mechanism by which Raptinal induces apoptosis using a genome-wide pooled shRNA screen. Following drug treatment, the abundance of the shRNA constructs were determined and compared between DMSO and Raptinal-treated samples. Constructs depleted in Raptinal samples versus DMSO control, are expected to potentiate Raptinal-induced apoptosis by down regulating anti-apoptotic proteins. In contrast, shRNA constructs enriched upon Raptinal treatment are expected to target pro-apoptotic proteins, whose down regulation confers protection from Raptinal-induced apoptosis. Follow up experiments were performed on enriched shRNAs in order to validate potentially novel pro-apoptotic proteins.

2018-02-27 | GSE66423 | GEO

Gene expression data of human chord blood hematopoietic progenitor cells subjected to myeloid differentiation and transduced with shRNAs against LINC00173

Project description:Long non-coding RNAs (lncRNAs) and miRNAs have emerged as crucial regulators of gene expression and cell fate decisions. We predicted LINC00173 as a novel non-coding regulator of granulopoiesis. We knocked down LINC00173 using two independent shRNA constructs, which resulted in diminished granulocytic in vitro differentiation, myeloid colony-formation and function. In addition, both shRNA and CRISPR-KRAB mediated knock-down of LINC00173 showed reduced cell proliferation in stem cells and NB4 cells (2-3-fold, p≤0.01). Here we assess early effects of LINC00173 knockdown in human HSPC subjected to myeloid differentiation conditions.

2017-05-31 | GSE98829 | GEO

Prediction of potent shRNAs with a sequential classification algorithm.

Project description:We present SplashRNA, a sequential classifier to predict potent microRNA-based short hairpin RNAs (shRNAs). Trained on published and novel data sets, SplashRNA outperforms previous algorithms and reliably predicts the most efficient shRNAs for a given gene. Combined with an optimized miR-E backbone, >90% of high-scoring SplashRNA predictions trigger >85% protein knockdown when expressed from a single genomic integration. SplashRNA can significantly improve the accuracy of loss-of-function genetics studies and facilitates the generation of compact shRNA libraries.

| S-EPMC5416823 | biostudies-literature

shRNA Sensor Analysis of 5' U converted shRNAs reveals 3' target bias exists in addition to 5' guide bias

Project description:shRNAs selected with the shERWOOD algorithm were converted to have a U at the 5' end of their guide. When endogenous 1U shRNAs were compared to artificial shRNA via the sensor algorithm, the endogenous shRNAs were found to be more efficacious. Purpose: Structural studies have hinted that the 5' end of shRNA guides is engulfed in the RISC complex. It has also been reported that shRNAs with a 5' U are more efficacious than those with other 5' caps. We wished to determine whether replacement of shRNA guide 5' nucleotides with a U, regardless of the corresponding target base, would increase their efficacy. Method: For each gene in the "druggable genome" 10 shRNAs were selected with the shERWOOD algorithm. In each case the score was assessed as if the guide had a 5' U. Sensor constructs were designed pairing 1U-guide shRNAs with their endogenous target. shRNAs were assessed for efficacy via the shRNA sensor assay (Fellmann et al. Mol Cell 2011). Results: shRNAs with artificial 5' Us were found to be less efficacious than those with an endogenous 5' U,

2014-11-24 | E-GEOD-62186 | biostudies-arrayexpress

Gene expression analysis of untreated and NT-shRNA transduced kidney proximal tubular epithelial cells (PTECs) at day 6 and day 16 after transduction, as well as SETD2-shRNA transduced PTECs at day 25 after transduction.

Project description:Primary kidney PTECs gradually became senescesince day 16, but SETD2 depletion prevented PTECs from senescence and maintained their proliferation beyond their limited dividing capacity. Transcriptional profiling of human PTECs, with comparing of non-senescent PTECs (PTECs-day 6), senescent PTECs (PTECs-day16), and SETD2 depleted PTECs at day 25 (SETD2 KD-PTECs-day 25). Three PTECs of different origins were transduced with shRNA constructs against SETD2 (sh1 or sh2), or with a non-targeting sequence. Untreated and NT-shRNA transduced samples were harvest at day 6 and day 16 respectively, SETD2-KD shRNA transduced PTECs were harvest at day 25.

2016-01-09 | E-GEOD-72792 | biostudies-arrayexpress

EWS-Fli and LNC regulated genes in comparison to GFP samples

Project description:RNA from A673 cells with shRNA-mediated knockdown of GFP (4 libraries), EWS-FLI1 (4 libraries), or lnc277 (7 libraries) was isolated with TRIzol (Invitrogen). Each sample was DNase treated and further purified on an RNeasy Mini column (Qiagen) before quality analysis on an Agilent 2100 Bioanalyzer. For each sample, 100-150ng of RNA was synthesized into cDNA, sheared on a Covaris ultrasonicator, and amplified using the NuGen Encore Complete kit (NuGen) to produce strand-specific and rRNA-depleted libraries. Samples were multiplexed (4/lane) for 2x100bp paired-end sequencing on an Illumina HiSeq 2000 RNA from A673 cells with shRNA-mediated knockdown of GFP (4 libraries), EWS-FLI1 (4 libraries), or lnc277 (7 libraries) was isolated with TRIzol (Invitrogen).

2014-11-01 | E-GEOD-60949 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data