Project description: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.
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:Transcriptional regulation by microRNAs (miRNAs) involves complementary base-pairing at target sites on mRNAs, yielding complex secondary structures. Here we introduce an efficient computational approach and software (FASTH) for genome-scale prediction of miRNA target sites based on minimizing the free energy of duplex structure. We apply our approach to identify miRNA target sites in the human and mouse transcriptomes. Our results show that short sequence motifs in the 5' end of miRNAs frequently match mRNAs perfectly, not only at validated target sites but additionally at many other, energetically favourable sites. High-quality matching regions are abundant and occur at similar frequencies in all mRNA regions, not only the 3'UTR. About one-third of potential miRNA target sites are reassigned to different mRNA regions, or gained or lost altogether, among different transcript isoforms from the same gene. Many potential miRNA target sites predicted in human are not found in mouse, and vice-versa, but among those that do occur in orthologous human and mouse mRNAs most are situated in corresponding mRNA regions, i.e. these sites are themselves orthologous. Using a luciferase assay in HEK293 cells, we validate four of six predicted miRNA-mRNA interactions, with the mRNA level reduced by an average of 73%. We demonstrate that a thermodynamically based computational approach to prediction of miRNA binding sites on mRNAs can be scaled to analyse complete mammalian transcriptome datasets. These results confirm and extend the scope of miRNA-mediated species- and transcript-specific regulation in different cell types, tissues and developmental conditions.
Project description:MicroRNAs (miRNAs) are an abundant class of small non-coding RNAs that regulate gene expression at the post-transcriptional level. They are suggested to be involved in most biological processes of the cell primarily by targeting messenger RNAs (mRNAs) for cleavage or translational repression. Their binding to their target sites is mediated by the Argonaute (AGO) family of proteins. Thus, miRNA target prediction is pivotal for research and clinical applications. Moreover, transfer-RNA-derived fragments (tRFs) and other types of small RNAs have been found to be potent regulators of Ago-mediated gene expression. Their role in mRNA regulation is still to be fully elucidated, and advancements in the computational prediction of their targets are in their infancy. To shed light on these complex RNA-RNA interactions, the availability of good quality high-throughput data and reliable computational methods is of utmost importance. Even though the arsenal of computational approaches in the field has been enriched in the last decade, there is still a degree of discrepancy between the results they yield. This review offers an overview of the relevant advancements in the field of bioinformatics and machine learning and summarizes the key strategies utilized for small RNA target prediction. Furthermore, we report the recent development of high-throughput sequencing technologies, and explore the role of non-miRNA AGO driver sequences.
Project description:UnlabelledViruses are dependent on their host cells for replication and thus have evolved in intimate association with them. The identification of host factors required for viral infection has led to advances in both viral and cellular biology. Vesicular stomatitis virus (VSV), a negative-sense RNA virus, replicates in all eukaryotic cells in culture, suggesting that the host requirements for its replication are ubiquitous. In this study, we performed a genome-wide small interfering RNA screen of human cells in culture and identified multiple cellular genes that influence the entry and replication of VSV. From a list of >300 genes, we selected the most promising candidates to perform further analysis to assign their functions to either the entry or intracellular replication step of infection. We implicate 3 new factors in VSV entry and 20 new factors in viral gene expression. These proteins have diverse cellular roles, including S-adenosylmethionine synthesis, respiration, and host translation machinery, underscoring the intimate relationship between VSV and the host cell. Together, these results provide a curated list of genes required for VSV replication.ImportanceReplication of vesicular stomatitis virus (VSV) has long served as a model for understanding host-virus interactions and neuropathogenesis. We performed a genome-wide analysis of host factors and revealed genes critical for viral replication, including some involved in vesicular trafficking, cell cycling, and protein modification. Our results provide an enriched list of host factors that are required for specific stages of VSV entry and gene expression. This study may also potentially expand the repertoire of targets for antiviral therapy against negative-strand RNA viruses.
Project description:During early vertebrate development, a large number of noncoding RNAs are maternally inherited or expressed upon activation of zygotic transcription. The exact identity, expression levels, and function for most of these noncoding RNAs remain largely unknown. miRNAs (microRNAs) and piRNAs (piwi-interacting RNAs) are two classes of small noncoding RNAs that play important roles in gene regulation during early embryonic development. Here, we utilized next-generation sequencing technology to determine temporal expression patterns for both miRNAs and piRNAs during four distinct stages of early vertebrate development using zebrafish as a model system. For miRNAs, the expression patterns for 198 known miRNAs within 122 different miRNA families and eight novel miRNAs were determined. Significant sequence variation was observed at the 5' and 3'ends of miRNAs, with most extra nucleotides added at the 3' end in a nontemplate directed manner. For the miR-430 family, the addition of adenosine and uracil residues is developmentally regulated and may play a role in miRNA stability during the maternal zygotic transition. Similar modification at the 3' ends of a large number of miRNAs suggests widespread regulation of stability during early development. Beside miRNAs, we also identified a large and unexpectedly diverse set of piRNAs expressed during early development.
Project description:During early vertebrate development, a large number of noncoding RNAs are maternally inherited or expressed upon activation of zygotic transcription. The exact identity, expression levels, and function for most of these noncoding RNAs remain largely unknown. miRNAs (microRNAs) and piRNAs (piwi-interacting RNAs) are two classes of small noncoding RNAs that play important roles in gene regulation during early embryonic development. Here, we utilized next-generation sequencing technology to determine temporal expression patterns for both miRNAs and piRNAs during four distinct stages of early vertebrate development using zebrafish as a model system. For miRNAs, the expression patterns for 198 known miRNAs within 122 different miRNA families and eight novel miRNAs were determined. Significant sequence variation was observed at the 5' and 3'ends of miRNAs, with most extra nucleotides added at the 3' end in a nontemplate directed manner. For the miR-430 family, the addition of adenosine and uracil residues is developmentally regulated and may play a role in miRNA stability during the maternal zygotic transition. Similar modification at the 3' ends of a large number of miRNAs suggests widespread regulation of stability during early development. Beside miRNAs, we also identified a large and unexpectedly diverse set of piRNAs expressed during early development.
Project description:Alternative polyadenylation (APA) enables a gene to generate multiple transcripts with different 3' ends, which is dynamic across different cell types or conditions. Many computational methods have been developed to characterize sample-specific APA using the corresponding RNA-seq data, but suffered from high error rate on both polyadenylation site (PAS) identification and quantification of PAS usage (PAU), and bias toward 3' untranslated regions. Here we developed a tool for APA identification and quantification (APAIQ) from RNA-seq data, which can accurately identify PAS and quantify PAU in a transcriptome-wide manner. Using 3' end-seq data as the benchmark, we showed that APAIQ outperforms current methods on PAS identification and PAU quantification, including DaPars2, Aptardi, mountainClimber, SANPolyA, and QAPA. Finally, applying APAIQ on 421 RNA-seq samples from liver cancer patients, we identified >540 tumor-associated APA events and experimentally validated two intronic polyadenylation candidates, demonstrating its capacity to unveil cancer-related APA with a large-scale RNA-seq data set.
Project description:RNA interference (RNAi) has become a gold standard for validating gene function in basic life science research and provides a promising therapeutic modality for cancer and other diseases. This mini-review focuses on the potential of small interfering RNAs (siRNAs) in anticancer treatment, including the establishment and screening of cancer-associated siRNA libraries and their applications in anticancer drug target discovery and cancer therapy. This article also describes the current delivery approaches of siRNAs using lipids, polymers, and, in particular, gold nanoparticles to induce significant gene silencing and tumor growth regression.