The limits of chemical modification

The limits of chemical modification

In addition to potential reductions in on-target efficiency, chemically modifying siRNAs (to reduce off-target effects) may not work in many cases.  Rasmussen et al. show that chemically modified siRNAs can still show substantial seed effects:  

Deconvoluted Dharmacon pools are like a box of chocolates

Deconvoluted Dharmacon pools are like a box of chocolates

… you never know what you’re going to get! Falkenberg et al. (2014) performed a synthetic lethal  RNAi screen to identify genes which, when knocked down in combination with drug treatment, induced apoptosis in drug-resistant cells. The first screening pass covered over 18,000 protein-coding genes using Dharmacon’s siGENOME, probably the most widely used library for genome-wide RNAi screens. siGENOME is based on low-complexity pooling, with 4 siRNAs pooled per gene.  In the first pass, hits are identified based on the pooled siRNA…

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Intronic off-target effects with antisense oligos

Intronic off-target effects with antisense oligos

Undecided on whether to use silencing RNAs (siRNAs) or antisense oligos (ASOs) for your RNA interference experiments? Read on. ASOs are single-stranded DNA oligonucleotides which downregulate specific RNA by hybridizing with it, forming a heteroduplex recognizable by RNase H1. RNase H1 is found in the nucleus, hence ASOs are often used to target nuclear-localized RNAs such as non-coding RNA. A recent paper however highlighted that since RNase H1 is found in the nucleus, intronic sequences may also fall prey to ASO-mediated silencing,…

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Simplicity is the ultimate sophistication

Simplicity is the ultimate sophistication

The beauty of the siPOOL strategy is its simplicity. In this presentation from the  (relatively) early days of Apple, Steve Jobs says that his company’s goal is to serve the one-on-one relationship between a user and his/her computer.   Similarly, siPOOLs, are designed to serve the one-on-one relationship between a scientist and his/her RNAi results. By providing an interpretable result without the need for extensive follow-up work and off-target corrections, siPOOLs make it possible for a scientist to use a…

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Seed effects persist in hyperdimensional space

Seed effects persist in hyperdimensional space

Work from the Carpenter lab suggests that attempts to shake seed-based off-targets by going to  ‘phenotypic hyperspace’ will not work. They performed a high-content assay with 315 shRNAs covering 41 genes.  A 1301-dimensional profile was created for each well, and compressed to 205 principal components that captured  99% of the variance. The hope would be that by examining a wider phenotypic space, the gene-specific effects of RNAi reagents would become more prominent. However, the profiles between shRNAs targeting the same…

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Knocking out the phenotype

Knocking out the phenotype

Consistent with the work of Rossi et al. (discussed previously),  another recent paper shows a lack of phenotypic response when knocking out a gene that gives a phenotypic response when knocked down. Knocking out klf2a does not result in any discernible difference from wild-type (whereas knock-down has been shown to produce a range of cardiovascular phenotypes). The authors conclude: In summary, our work shows that even in the face of clear evidence of a potentially disruptive mutation induced in a gene…

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Genetic compensation

Genetic compensation

Recent work by Rossi et al. show that an unintended consequence of gene knockout may be genetic compensation that mitigates phenotypes. Knockdown in zebrafish of egfl7, an endothelial extracellular gene, causes severe vascular defects: However, following knockout of eglf7, there was no visible effect on vascular development, even after application of the knockdown reagent (demonstrating that the knockdown phenotype was not due to an off-target and that the knockout’s normal vascular development was not due some minor levels of egfl7): The authors found…

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Russian Roulette, RNAi style

Russian Roulette, RNAi style

Which bases should you choose for the seed region of a single siRNA? It’s like Russian Roulette on full-automatic, where a specific seed will result in dozens or hundreds of down-regulated genes. If you’re lucky, none of the off-targets results in a false-positive phenotype.   But odds are that you won’t be so lucky. A recent paper suggests that taking single siRNA drugs may be closer to real Russian Roulette than anyone would hope. The authors show that an siRNA designed to knock down…

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The beauty of the siPool

The beauty of the siPool

The siPool strategy is beautifully simple: By having many on-target siRNAs, each with a different seed sequence, you maintain on-target efficiency while diluting out off-target effects. One analogy is the beauty of composite faces. Which of these faces do you find most attractive? If you’re like most people, you will have chosen the last face, which is actually a composite of the other 5 faces (source). Each individual face has its flaw(s).  Spock ears, mildly everted lips, incongruous eyebrows, etc.  No…

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The nasty, ugly fact of off-target effects

The nasty, ugly fact of off-target effects

Once upon a time, it was imagined that siRNAs specifically knock down the intended target gene. Unfortunately, this turned out to be wrong. What, in theory, should have been the ultimate functional genomics tool has turned out to be, if not dead, then perhaps merely undead or delinquent. The failure of siRNA screening following the initial high hopes brings to mind T.H. Huxley‘s famous quote about a beautiful theory being killed by an ugly, nasty little fact. As pointed out by S.J….

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