Dataset Information

Accurate transcriptome-wide prediction of microRNA targets and small interfering RNA off-targets with MIRZA-G.

ABSTRACT: Small interfering RNA (siRNA)-mediated knock-down is a widely used experimental approach to characterizing gene function. Although siRNAs are designed to guide the cleavage of perfectly complementary mRNA targets, acting similarly to microRNAs (miRNAs), siRNAs down-regulate the expression of hundreds of genes to which they have only partial complementarity. Prediction of these siRNA 'off-targets' remains difficult, due to the incomplete understanding of siRNA/miRNA-target interactions. Combining a biophysical model of miRNA-target interaction with structure and sequence features of putative target sites we developed a suite of algorithms, MIRZA-G, for the prediction of miRNA targets and siRNA off-targets on a genome-wide scale. The MIRZA-G variant that uses evolutionary conservation performs better than currently available methods in predicting canonical miRNA target sites and in addition, it predicts non-canonical miRNA target sites with similarly high accuracy. Furthermore, MIRZA-G variants predict siRNA off-target sites with an accuracy unmatched by currently available programs. Thus, MIRZA-G may prove instrumental in the analysis of data resulting from large-scale siRNA screens.

SUBMITTER: Gumienny R

PROVIDER: S-EPMC4330396 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Accurate transcriptome-wide prediction of microRNA targets and small interfering RNA off-targets with MIRZA-G.

Gumienny Rafal R Zavolan Mihaela M

Nucleic acids research 20150127 3

Small interfering RNA (siRNA)-mediated knock-down is a widely used experimental approach to characterizing gene function. Although siRNAs are designed to guide the cleavage of perfectly complementary mRNA targets, acting similarly to microRNAs (miRNAs), siRNAs down-regulate the expression of hundreds of genes to which they have only partial complementarity. Prediction of these siRNA 'off-targets' remains difficult, due to the incomplete understanding of siRNA/miRNA-target interactions. Combining ...[more]

PMID: 25628353

Similar Datasets

Project description:Currently, there is a serious absence of pharmaceutically attractive small molecules that mitigate the lethal effects of an accidental or intentional public exposure to toxic doses of ionizing radiation. Moreover, cellular systems that emulate the radiobiologically relevant cell populations and that are suitable for high-throughput screening have not been established. Therefore, we examined two human pluripotent embryonal carcinoma cell lines for use in an unbiased phenotypic small interfering RNA (siRNA) assay to identify proteins with the potential of being drug targets for the protection of human cell populations against clinically relevant ionizing radiation doses that cause acute radiation syndrome. Of the two human cell lines tested, NCCIT cells had optimal growth characteristics in a 384 well format, exhibited radiation sensitivity (D(0) = 1.3 ± 0.1 Gy and ñ = 2.0 ± 0.6) comparable to the radiosensitivity of stem cell populations associated with human death within 30 days after total-body irradiation. Moreover, they internalized siRNA after 4 Gy irradiation enabling siRNA library screening. Therefore, we used the human NCCIT cell line for the radiation mitigation study with a siRNA library that silenced 5,520 genes known or hypothesized to be potential therapeutic targets. Exploiting computational methodologies, we identified 113 siRNAs with potential radiomitigative properties, which were further refined to 29 siRNAs with phosphoinositide-3-kinase regulatory subunit 1 (p85?) being among the highest confidence candidate gene products. Colony formation assays revealed radiation mitigation when the phosphoinositide-3-kinase inhibitor LY294002 was given after irradiation of 32D cl 3 cells (D(0) = 1.3 ± 0.1 Gy and ñ = 2.3 ± 0.3 for the vehicle control treated cells compared to D(0) = 1.2 ± 0.1 Gy and ñ = 6.0 ± 0.8 for the LY294002 treated cells, P = 0.0004). LY294002 and two other PI3K inhibitors, PI 828 and GSK 1059615, also mitigated radiation-induced apoptosis in NCCIT cells. Treatment of mice with a single intraperitoneal LY294002 dose of 30 mg/kg at 10 min, 4, or 24 h after LD(50/30) whole-body dose of irradiation (9.25 Gy) enhanced survival. This study documents that an unbiased siRNA assay can identify new genes, signaling pathways, and chemotypes as radiation mitigators and implicate the PI3K pathway in the human radiation response.

Project description:BACKGROUND: MicroRNA are a class of small RNAs that regulate gene expression by inhibiting translation of protein encoding transcripts through targeting of a microRNA-protein complex by base-pairing of the microRNA sequence to cognate recognition sequences in the 3' untranslated region (UTR) of the mRNA. Target identification for a given microRNA sequence is generally accomplished by informatics analysis of predicted mRNA sequences present in the genome or in databases of transcript sequence for the tissue of interest. However, gene models for porcine skeletal muscle transcripts in current databases, specifically complete sequence of the 3' UTR, are inadequate for this exercise. METHODOLOGY/PRINCIPAL FINDINGS: To provide data necessary to identify gene targets for microRNA in porcine skeletal muscle, normalized cDNA libraries were sequenced using Roche 454 GS-FLX pyrosequencing and de novo assembly of transcripts enriched in the 3' UTR was performed using the MIRA sequence assembly program. Over 725 million bases of sequence were generated, which assembled into 18,202 contigs. Sequence reads were mapped to a 3' UTR database containing porcine sequences. The 3' UTR that mapped to the database were examined to predict targets for previously identified microRNA that had been separately sequenced from the same porcine muscle sample used to generate the cDNA libraries. For genes with microRNA-targeted 3' UTR, KEGG pathways were computationally determined in order to identify potential functional effects of these microRNA-targeted transcripts. CONCLUSIONS: Through next-generation sequencing of transcripts expressed in skeletal muscle, mapping reads to a 3' UTR database, and prediction of microRNA target sites in the 3' UTR, our results identified genes expressed in porcine skeletal muscle and predicted the microRNA that target these genes. Additionally, identification of pathways regulated by these microRNA-targeted genes provides us with a set of genes that can be further evaluated for their potential role in skeletal muscle development and growth.

Dataset Information

Accurate transcriptome-wide prediction of microRNA targets and small interfering RNA off-targets with MIRZA-G.

Publications

Accurate transcriptome-wide prediction of microRNA targets and small interfering RNA off-targets with MIRZA-G.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets