Drosophila development: RNA interference ab ovo

A novel protein required for RNA interference in Drosophila, Armitage, was identified in a screen for genes involved in embryonic axis formation. In armitage mutants, oocyte polarity and the regulation of oskar mRNA translation are impaired, suggesting that RNA silencing regulates the first steps of Drosophila development.     

Target validation and biomarker identification in oncology : the example of aurora kinases

The strong link between gene expression of mitotic Aurora kinases and cancer has stimulated a very high interest in developing Aurora kinase inhibitors for cancer therapy. Validation of Aurora kinases as targets, and development of pharmacodynamic biomarkers for inhibitors of Aurora kinases, provides an example of how target validation can help the drug discovery process, and also of how to interpret results depending on the technology used. In this review, we outline the principal tools, concepts, and strategies of target and biomarker validation for Aurora kinases, with emphasis on validation results derived from RNA-interference experiments. These data were essential for the decision to enter the next steps in drug development and for the selection of the appropriate biomarkers for clinical trials.     

Large-scale, high-throughput validation of short hairpin RNA sequences for RNA interference

A method for high-throughput cloning and analysis of short hairpin RNAs (shRNAs) is described. Using this approach, 464 shRNAs against 116 different genes were screened for knockdown efficacy, enabling rapid identification of effective shRNAs against 74 genes. Statistical analysis of the effects of various criteria on the activity of the shRNAs confirmed that some of the rules thought to govern small interfering RNA (siRNA) activity also apply to shRNAs. These include moderate GC content, absence of internal hairpins, and asymmetric thermal stability. However, the authors did not find strong support for position specific rules. In addition, analysis of the data suggests that not all genes are equally susceptible to RNA interference (RNAi).     

Induction of RNA interference genes by double-stranded RNA; implications for susceptibility to RNA interference

Gene silencing by RNA interference (RNAi) can be a useful reverse genetics tool in eukaryotes. However, some species appear refractory to RNAi. To study the role of the differential expression of RNAi proteins in RNAi, we isolated partial dicer-2, argonaute-2 translin, vasa intronic gene (VIG) and tudor staphylococcus/micrococcal nuclease (TSN) genes from the tobacco hornworm, Manduca sexta, a well-studied insect model which we have found to be variably sensitive to RNAi. We found that the RNAi gene, translin, was expressed at minimal levels in M. sexta tissue and that there is a specific, dose-dependent upregulation of dicer-2 and argonaute-2 expression in response to injection with dsRNA, but no upregulation of the other genes tested. Upregulation of gene expression was rapid and transient. In order to prolong the upregulation we introduced multiple doses of dsRNA, resulting in multiple peaks of dicer-2 gene expression. Our results have implications for the design of RNAi experiments and may help to explain differences in the sensitivity of eukaryotic organisms to RNAi.     

The phenomenon of RNA interference and development of organism

RNA interference consists in specific mRNA degradation in response to introduction of a double-stranded RNA, homologous in nucleotide sequence. RNA interference was found in eukaryotes and is used in genomics as a powerful method to determine the functions of genes with known nucleotide sequences. RNA interference is considered as a tool of protection against viruses and harmful consequences of mobile elements' transposals. The involvement of the components of RNA interference is considered in spermatogenesis of Drosophila melanogaster and regulation of the expression of genes in Caenorhabditis elegans responsible for temporal patterns of development. The role of RNQA interference in stem cell formation and functioning is also considered.     

Technique review: how to use RNA interference.

RNA interference (RNAi) has been rapidly adopted as a general method for inhibiting gene expression in most laboratory organisms. This paper discusses how libraries of RNAi reagents are being used to perform genome-wide reverse genetic screens in both model organisms and mammalian cells. Guidelines for designing effective small interfering RNAs and appropriate controls for mammalian RNAi experiments will also be discussed.     

RNA interference: listening to the sound of silence

The term RNA interference (RNAi) describes the use of double-stranded RNA to target specific mRNAs for degradation, thereby silencing their expression. RNAi is one manifestation of a broad class of RNA silencing phenomena that are found in plants, animals and fungi. The discovery of RNAi has changed our understanding of how cells guard their genomes, led to the development of new strategies for blocking gene function, and may yet yield RNA-based drugs to treat human disease.     

RNA interference to target lipid disorders

PURPOSE OF REVIEW: This review focuses on proof-of-principle experiments providing validation of new targets for the development of RNA interference-based therapeutics for dyslipidemia. RECENT FINDINGS: Over the past few years, RNA interference has become an accepted approach to manipulate gene expression in mammalian systems. Advantage has been taken of the relative tissue specificity of adenovirus for liver, and the genetic specificity of short hairpin RNA-mediated RNA interference to create liver-specific downregulation of different genes. A different approach to target liver has been through the administration of chemically modified short interfering RNAs. For example, apolipoprotein B messenger RNA has been silenced in liver and jejunum resulting in decreased plasma levels of apolipoprotein B and total cholesterol. SUMMARY: RNA interference has aroused great interest as a powerful experimental tool and a potential therapeutic strategy. Successful animal studies indicate that RNA interference might be useful for the treatment of various human diseases. Clinical studies will soon begin to assess the use of this new class of therapeutics to treat dyslipidemia.     

Tissue microarrays: emerging standard for biomarker validation

With the widespread use of DNA microarrays, hundreds of biomarkers are in need of validation in cohorts of well-annotated clinical samples. Tissue microarrays are emerging as the tool par excellence to rapidly perform DNA, RNA, and especially protein expression analyses on large numbers of clinical samples. Although still somewhat limited by the subjectivity of scoring methods and tissue sample representativeness, TMAs represent an increasingly validated means of understanding the clinical impact of diagnostic-related, prognostic-related, and therapy-related markers. Automated methods are being developed for TMA analysis and cell microarrays and frozen tissue TMAs have been better optimized. More and more biomarker studies are availing themselves of the high-throughput nature of TMAs, recognizing that they are becoming indispensable for rapid translation of laboratory data to the clinic.     

RNA interference: it's a small RNA world

Short RNAs regulate gene expression in many species. Some are generated from any double-stranded RNA and degrade complementary RNAs; others are encoded by genes and repress specific mRNAs. Both, it turns out, are processed and handled by similar proteins. These pathways offer a glimpse into a world of small RNAs.     

PEDF,a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation

Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multicollinearity in our serum cytokines, chemokines, and high-throughput platform datasets used to phenotype WTC-disease. To address this concern, we used automated, machine-learning, high-dimensional data pruning, and validated identified biomarkers. The parent cohort consisted of male, never-smoking firefighters with WTC-LI (FEV_{1, %Pred}< lower limit of normal (LLN); n = 100) and controls (n = 127) and had their biomarkers assessed. Cases and controls (n = 15/group) underwent untargeted metabolomics, then feature selection performed on metabolites, cytokines, chemokines, and clinical data. Cytokines, chemokines, and clinical biomarkers were validated in the non-overlapping parent-cohort via binary logistic regression with 5-fold cross validation. Random forests of metabolites (n = 580), clinical biomarkers (n = 5), and previously assayed cytokines, chemokines (n = 106) identified that the top 5% of biomarkers important to class separation included pigment epithelium-derived factor (PEDF), macrophage derived chemokine (MDC), systolic blood pressure, macrophage inflammatory protein-4 (MIP-4), growth-regulated oncogene protein (GRO), monocyte chemoattractant protein-1 (MCP-1), apolipoprotein-AII (Apo-AII), cell membrane metabolites (sphingolipids, phospholipids), and branched-chain amino acids. Validated models via confounder-adjusted (age on 9/11, BMI, exposure, and pre-9/11 FEV_{1, %Pred}) binary logistic regression had AUC_ROC [0.90(0.84–0.96)]. Decreased PEDF and MIP-4, and increased Apo-AII were associated with increased odds of WTC-LI. Increased GRO, MCP-1, and simultaneously decreased MDC were associated with decreased odds of WTC-LI. In conclusion, automated data pruning identified novel WTC-LI biomarkers; performance was validated in an independent cohort. One biomarker—PEDF, an antiangiogenic agent—is a novel, predictive biomarker of particulate-matter-related lung disease. Other biomarkers—GRO, MCP-1, MDC, MIP-4—reveal immune cell involvement in WTC-LI pathogenesis. Findings of our automated biomarker identification warrant further investigation into these potential pharmacotherapy targets.     

RNA interference: potential therapeutic targets

One of the most exciting findings in recent years has been the discovery of RNA interference (RNAi). RNAi methodologies hold the promise to selectively inhibit gene expression in mammals. RNAi is an innate cellular process activated when a double-stranded RNA (dsRNA) molecule of greater than 19 duplex nucleotides enters the cell, causing the degradation of not only the invading dsRNA molecule, but also single-stranded (ssRNAs) RNAs of identical sequences, including endogenous mRNAs. The use of RNAi for genetic-based therapies has been widely studied, especially in viral infections, cancers, and inherited genetic disorders. As such, RNAi technology is a potentially useful method to develop highly specific dsRNA-based gene-silencing therapeutics.