Dataset Information

SbacHTS: spatial background noise correction for high-throughput RNAi screening.

ABSTRACT:

Motivation

High-throughput cell-based phenotypic screening has become an increasingly important technology for discovering new drug targets and assigning gene functions. Such experiments use hundreds of 96-well or 384-well plates, to cover whole-genome RNAi collections and/or chemical compound files, and often collect measurements that are sensitive to spatial background noise whose patterns can vary across individual plates. Correcting these position effects can substantially improve measurement accuracy and screening success.

Result

We developed SbacHTS (Spatial background noise correction for High-Throughput RNAi Screening) software for visualization, estimation and correction of spatial background noise in high-throughput RNAi screens. SbacHTS is supported on the Galaxy open-source framework with a user-friendly open access web interface. We find that SbacHTS software can effectively detect and correct spatial background noise, increase signal to noise ratio and enhance statistical detection power in high-throughput RNAi screening experiments.

Availability

http://www.galaxy.qbrc.org/

SUBMITTER: Zhong R

PROVIDER: S-EPMC3740628 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

SbacHTS: spatial background noise correction for high-throughput RNAi screening.

Zhong Rui R Kim Min Soo MS White Michael A MA Xie Yang Y Xiao Guanghua G

Bioinformatics (Oxford, England) 20130628 17

<h4>Motivation</h4>High-throughput cell-based phenotypic screening has become an increasingly important technology for discovering new drug targets and assigning gene functions. Such experiments use hundreds of 96-well or 384-well plates, to cover whole-genome RNAi collections and/or chemical compound files, and often collect measurements that are sensitive to spatial background noise whose patterns can vary across individual plates. Correcting these position effects can substantially improve me ...[more]

PMID: 23814141

Similar Datasets

Project description:BackgroundHost genetic backgrounds affect gene functions. The genetic backgrounds of genetically engineered organisms must be identified to confirm their genetic backgrounds identity with those of recipients. Marker-assisted backcrossing (MAB), transgenesis and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (CRISPR/Cas9) editing are three commonly used genetic engineering techniques. However, methods for genetic background screening between genetically engineered organisms and corresponding recipients suffer from low efficiency, low accuracy or high cost.ResultsHere, we improved our previously reported AmpSeq-SSR method, an amplicon sequencing-based simple sequence repeat (SSR) genotyping method, by selecting SSR loci with high polymorphism among varieties. Ultimately, a set of 396 SSRs was generated and applied to evaluate the genetic backgrounds identity between rice lines developed through MAB, transgenesis, and CRISPR/Cas9 editing and the respective recipient rice. We discovered that the percentage of different SSRs between the MAB-developed rice line and its recipient was as high as 23.5%. In contrast, only 0.8% of SSRs were different between the CRISPR/Cas9-system-mediated rice line and its recipient, while no SSRs showed different genotypes between the transgenic rice line and its recipient. Furthermore, most differential SSRs induced by MAB technology were located in non-coding regions (62.9%), followed by untranslated regions (21.0%) and coding regions (16.1%). Trinucleotide repeats were the most prevalent type of altered SSR. Most importantly, all altered SSRs located in coding regions were trinucleotide repeats.ConclusionsThis method is not only useful for the background evaluation of genetic resources but also expands our understanding of the unintended effects of different genetic engineering techniques. While the work we present focused on rice, this method can be readily extended to other organisms.

Project description:Major bottlenecks in development of therapeutic post transcriptional gene silencing (PTGS) agents (e.g. ribozymes, RNA interference, antisense) include the challenge of mapping rare accessible regions of the mRNA target that are open for annealing and cleavage, testing and optimization of agents in human cells to identify lead agents, testing for cellular toxicity, and preclinical evaluation in appropriate animal models of disease. Methods for rapid and reliable cellular testing of PTGS agents are needed to identify potent lead candidates for optimization. Our goal was to develop a means of rapid assessment of many RNA agents to identify a lead candidate for a given mRNA associated with a disease state. We developed a rapid human cell-based screening platform to test efficacy of hammerhead ribozyme (hhRz) or RNA interference (RNAi) constructs, using a model retinal degeneration target, human rod opsin (RHO) mRNA. The focus is on RNA Drug Discovery for diverse retinal degeneration targets. To validate the approach, candidate hhRzs were tested against NUH↓ cleavage sites (N = G,C,A,U; H = C,A,U) within the target mRNA of secreted alkaline phosphatase (SEAP), a model gene expression reporter, based upon in silico predictions of mRNA accessibility. HhRzs were embedded in a larger stable adenoviral VAI RNA scaffold for high cellular expression, cytoplasmic trafficking, and stability. Most hhRz expression plasmids exerted statistically significant knockdown of extracellular SEAP enzyme activity when readily assayed by a fluorescence enzyme assay intended for high throughput screening (HTS). Kinetics of PTGS knockdown of cellular targets is measureable in live cells with the SEAP reporter. The validated SEAP HTS platform was transposed to identify lead PTGS agents against a model hereditary retinal degeneration target, RHO mRNA. Two approaches were used to physically fuse the model retinal gene target mRNA to the SEAP reporter mRNA. The most expedient way to evaluate a large set of potential VAI-hhRz expression plasmids against diverse NUH↓ cleavage sites uses cultured human HEK293S cells stably expressing a dicistronic Target-IRES-SEAP target fusion mRNA. Broad utility of this rational RNA drug discovery approach is feasible for any ophthalmological disease-relevant mRNA targets and any disease mRNA targets in general. The approach will permit rank ordering of PTGS agents based on potency to identify a lead therapeutic compound for further optimization.

Dataset Information

SbacHTS: spatial background noise correction for high-throughput RNAi screening.

Motivation

Result

Availability

Publications

SbacHTS: spatial background noise correction for high-throughput RNAi screening.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets