Proteins are built by using the information contained in molecules of messenger RNA (mRNA). Cells have several ways of controlling the amounts of different proteins they make. For example, a so-called ‘microRNA’ molecule can bind to an mRNA molecule to cause it to be more rapidly degraded and less efficiently used, thereby reducing the amount of protein built from that mRNA. Indeed, microRNAs are thought to help control the amount of protein made from most human genes, and biologists are working to predict the amount of control imparted by each microRNA on each of its mRNA targets. All RNA molecules are made up of a sequence of bases, each commonly known by a single letter—‘A’, ‘U’, ‘C’ or ‘G’. These bases can each pair up with one specific other base—‘A’ pairs with ‘U’, and ‘C’ pairs with ‘G’. To direct the repression of an mRNA molecule, a region of the microRNA known as a ‘seed’ binds to a complementary sequence in the target mRNA. ‘Canonical sites’ are regions in the mRNA that contain the exact sequence of partner bases for the bases in the microRNA seed. Some canonical sites are more effective at mRNA control than others. ‘Non-canonical sites’ also exist in which the pairing between the microRNA seed and mRNA does not completely match. Previous work has suggested that many non-canonical sites can also control mRNA degradation and usage. Agarwal et al. first used large experimental datasets from many sources to investigate microRNA activity in more detail. As expected, when mRNAs had canonical sites that matched the microRNA, mRNA levels and usage tended to drop. However, no effect was observed when the mRNAs only had recently identified non-canonical sites. This suggests that microRNAs primarily bind to canonical sites to control protein production. Based on these results, Agarwal et al. further developed a statistical model that predicts the effects of microRNAs binding to canonical sites. The updated model considers 14 different features of the microRNA, microRNA site, or mRNA—including the mRNA sequence around the site—to predict which sites within mRNAs are most effectively targeted by microRNAs. Tests showed that Agarwal et al.'s model was as good as experimental approaches at identifying the effective target sites, and was better than existing computational models. The model has been used to power the latest version of a freely available resource called TargetScan, and so could prove a valuable resource for researchers investigating the many important roles of microRNAs in controlling protein production.

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Predicting effective microRNA target sites in mammalian mRNAs

MicroRNAs constitute a large family of small, approximately 21-nucleotide-long, non-coding RNAs that have emerged as key post-transcriptional regulators of gene expression in metazoans and plants. In mammals, microRNAs are predicted to control the activity of approximately 30% of all protein-coding genes, and have been shown to participate in the regulation of almost every cellular process investigated so far. By base pairing to mRNAs, microRNAs mediate translational repression or mRNA degradation. This Review summarizes the current understanding of the mechanistic aspects of microRNA-induced repression of translation and discusses some of the controversies regarding different modes of microRNA function.

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Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight?

The simplicity of programming the CRISPR (clustered regularly interspaced short palindromic repeats)–associated nuclease Cas9 to modify specific genomic loci suggests a new way to interrogate gene function on a genome-wide scale. We show that lentiviral delivery of a genome-scale CRISPR-Cas9 knockout (GeCKO) library targeting 18,080 genes with 64,751 unique guide sequences enables both negative and positive selection screening in human cells. First, we used the GeCKO library to identify genes essential for cell viability in cancer and pluripotent stem cells. Next, in a melanoma model, we screened for genes whose loss is involved in resistance to vemurafenib, a therapeutic RAF inhibitor. Our highest-ranking candidates include previously validated genes NF1 and MED12 , as well as novel hits NF2 , CUL3 , TADA2B , and TADA1. We observe a high level of consistency between independent guide RNAs targeting the same gene and a high rate of hit confirmation, demonstrating the promise of genome-scale screening with Cas9.

/pdf/genome-scale-crispr-cas9-knockout-screening-in-human-cells-52hijutmcc.pdf

Genome-Scale CRISPR-Cas9 Knockout Screening in Human Cells

A mammalian microRNA expression atlas based on small RNA library sequencing.

In the 10 years that have passed since the Nobel prize-winning discovery of RNA interference (RNAi), billions of dollars have been invested in the therapeutic application of gene silencing in humans. Today, there are promising data from ongoing clinical trials for the treatment of age-related macular degeneration and respiratory syncytial virus. Despite these early successes, however, the widespread use of RNAi therapeutics for disease prevention and treatment requires the development of clinically suitable, safe and effective drug delivery vehicles. Here, we provide an update on the progress of RNAi therapeutics and highlight novel synthetic materials for the encapsulation and intracellular delivery of nucleic acids.

Knocking down barriers: advances in siRNA delivery

Transfected siRNAs and miRNAs regulate numerous transcripts that have only limited complementarity to the active strand of the RNA duplex. This process reflects natural target regulation by miRNAs, but is an unintended ("off-target") consequence of siRNA-mediated silencing. Here we demonstrate that this unintended off-target silencing is widespread, and occurs in a manner reminiscent of target silencing by miRNAs. A high proportion of unintended transcripts silenced by siRNAs showed 3' UTR sequence complementarity to the seed region of the siRNA. Base mismatches within the siRNA seed region reduced the set of original off-target transcripts but generated new sets of silenced transcripts with sequence complementarity to the mismatched seed sequence. An inducible shRNA silenced a subset of transcripts that were silenced by an siRNA of the same sequence, demonstrating that unintended silencing is sequence mediated and is independent of delivery method. In all cases, off-target transcript silencing was accompanied by loss of the corresponding protein and occurred with dependence on siRNA concentration similar to that of silencing of the target transcript. Thus, short stretches of sequence complementarity to the siRNA or shRNA seed region are key to the silencing of unintended transcripts.

/pdf/widespread-sirna-off-target-transcript-silencing-mediated-by-1wg060e494.pdf

Widespread siRNA "off-target" transcript silencing mediated by seed region sequence complementarity.

Transfected siRNAs regulate numerous transcripts sharing limited complementarity to the RNA duplex. This unintended (‘‘offtarget’’) silencing can hinder the use of RNAi to define gene function. Here we describe position-specific, sequence-independent chemical modifications that reduced silencing of partially complementary transcripts by all siRNAs tested. Silencing of perfectly matched targets was unaffected by these modifications. The chemical modification also reduced off-target phenotypes in growth inhibition studies. Key to the modification was 29-O-methyl ribosyl substitution at position 2 in the guide strand, which reduced silencing of most off-target transcripts with complementarity to the seed region of the siRNA guide strand. The sharp position dependence of 29-O-methyl ribosyl modification contrasts with the broader position dependence of base-pair substitutions within the seed region, suggesting a role for position 2 of the guide strand distinct from its effects on pairing to target transcripts.

/pdf/position-specific-chemical-modification-of-sirnas-reduces-1dxrujzqfw.pdf

Position-specific chemical modification of siRNAs reduces “off-target” transcript silencing

Background: MicroRNAs (miRNAs) are endogenous, small noncoding RNAs. Because of their size, abundance, tissue specificity, and relative stability in plasma, miRNAs hold promise as unique accessible biomarkers to monitor tissue injury. Methods: We investigated the use of liver-, muscle- and brain-specific miRNAs as circulating biomarkers of tissue injury. We used a highly sensitive quantitative PCR assay to measure specific miRNAs (miR-122, miR-133a, and miR-124) in plasma samples from rats treated with liver or muscle toxicants and from a rat surgical model of stroke. Results: We observed increases in plasma concentrations of miR-122, miR-133a, and miR-124 corresponding to injuries in liver, muscle, and brain, respectively. miR-122 and miR-133a illustrated specificity for liver and muscle toxicity, respectively, because they were not detectable in the plasma of animals with toxicity to the other organ. This result contrasted with the results for alanine aminotransferase (ALT) and aspartate aminotransferase, which were both increased with either organ toxicity. Furthermore, miR-122 exhibited a diagnostic sensitivity superior to that of ALT when the results were correlated to the liver histopathologic results. The miR-124 concentration increased in the plasma of rats 8 h after surgery to produce brain injury and peaked at 24 h, while the miR-122 and miR-133a concentrations remained at baseline values. Conclusions: These results demonstrate that tissue-specific miRNAs may serve as diagnostically sensitive plasma biomarkers of tissue injury.

/pdf/plasma-micrornas-as-sensitive-and-specific-biomarkers-of-50zcyy76so.pdf

Plasma MicroRNAs as Sensitive and Specific Biomarkers of Tissue Injury

microRNAs (miRNAs) are abundant, approximately 21-nucleotide, noncoding regulatory RNAs. Each miRNA may regulate hundreds of mRNA targets, but the identities of these targets and the processes they regulate are poorly understood. Here we have explored the use of microarray profiling and functional screening to identify targets and biological processes triggered by the transfection of human cells with miRNAs. We demonstrate that a family of miRNAs sharing sequence identity with miRNA-16 (miR-16) negatively regulates cellular growth and cell cycle progression. miR-16-down-regulated transcripts were enriched with genes whose silencing by small interfering RNAs causes an accumulation of cells in G(0)/G(1). Simultaneous silencing of these genes was more effective at blocking cell cycle progression than disruption of the individual genes. Thus, miR-16 coordinately regulates targets that may act in concert to control cell cycle progression.

Transcripts targeted by the microRNA-16 family cooperatively regulate cell cycle progression

microRNAs in the miR-106b family are overexpressed in multiple tumor types and are correlated with the expression of genes that regulate the cell cycle. Consistent with these observations, miR-106b family gain of function promotes cell cycle progression, whereas loss of function reverses this phenotype. Microarray profiling uncovers multiple targets of the family, including the cyclin-dependent kinase inhibitor p21/CDKN1A. We show that p21 is a direct target of miR-106b and that its silencing plays a key role in miR-106b-induced cell cycle phenotypes. We also show that miR-106b overrides a doxorubicin-induced DNA damage checkpoint. Thus, miR-106b family members contribute to tumor cell proliferation in part by regulating cell cycle progression and by modulating checkpoint functions.

Lee Lim

Papers

Widespread siRNA "off-target" transcript silencing mediated by seed region sequence complementarity.

Position-specific chemical modification of siRNAs reduces “off-target” transcript silencing

Plasma MicroRNAs as Sensitive and Specific Biomarkers of Tissue Injury

Transcripts targeted by the microRNA-16 family cooperatively regulate cell cycle progression

MicroRNAs in the miR-106b Family Regulate p21/CDKN1A and Promote Cell Cycle Progression