Classic Papers Series: Lin et al. show RNAi screen dominated by seed effects
Over the coming months, we will highlight a number of seminal papers in the RNAi field.
The first such paper is from 2005 by Lin et al. of Abbott Laboratories, who showed that the top hits from their RNAi screen were due to seed-based off-target effects, rather than the intended (and at that time, rather expected) on-target effect.
The authors screened 507 human kinases with 1 siRNA per gene, using a HIF-1 reporter assay to identify genes regulating hypoxia-induced HIF-1 response.
In the validation phase of their screen, they tested new siRNAs for hit genes, but found that they failed to reproduce the observed effect, even when using siRNAs that had a better on-target knock down than the pass 1 siRNAs.
Figure 1A. Left panel shows on-target knock down of pass 1 siRNA for GRK4 (O) and the new design (N). Centre panel shows Western blot of protein levels Right panel shows HIF-1 reporter activity for positive control (HIF1A) and the original (O) and new (N) siRNAs.
The on-target knock down is much-improved for the new design, yet its reporter activity is indistinguishable from negative control. Yet the pass 1 siRNA with poor knock down gives almost as strong a result as HIF1A (positive control).
By qPCR, they then showed that GRK4(O) and another one of the top 3 siRNAs silence HIF1A (the positive control gene). Using a number of different target constructs they also nicely show that it was due to seed-based targeting in the 3′ UTR.
Although the authors screened at a high initial concentration (100 nM), the observed off-targets persisted at 5 nM, suggesting that just screening at lower concentrations would not have improved their results.
The authors conclude:
In addition, due to the large percentage of the off- target hits generated in the screening, using a redundant library without pooling in the primary screen could significantly reduce the efforts required to eliminate off-target false positives and therefore, will be a more efficient design than using a pooled library.
This is true for low-complexity pools, but high-complexity pools can overcome this problem by providing a single reliable result for each screened gene.
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