Discovery of a dicer-independent, cell-type dependent alternate targeting sequence generator: implications in gene silencing & pooled RNAi screens.

Abstract

There is an acceptance that plasmid-based delivery of interfering RNA always generates the intended targeting sequences in cells, making it as specific as its synthetic counterpart. However, recent studies have reported on cellular inefficiencies of the former, especially in light of emerging gene discordance at inter-screen level and across formats. Focusing primarily on the TRC plasmid-based shRNA hairpins, we reasoned that alleged specificities were perhaps compromised due to altered processing; resulting in a multitude of random interfering sequences. For this purpose, we opted to study the processing of hairpin TRCN#40273 targeting CTTN; which showed activity in a miRNA-21 gain-of-function shRNA screen, but inactive when used as an siRNA duplex. Using a previously described walk-through method, we identified 36 theoretical cleavage variants resulting in 78 potential siRNA duplexes targeting 53 genes. We synthesized and tested all of them. Surprisingly, six duplexes targeting ASH1L, DROSHA, GNG7, PRKCH, THEM4, and WDR92 scored as active. QRT-PCR analysis on hairpin transduced reporter cells confirmed knockdown of all six genes, besides CTTN; revealing a surprising 7 gene-signature perturbation by this one single hairpin. We expanded our qRT-PCR studies to 26 additional cell lines and observed unique knockdown profiles associated with each cell line tested; even for those lacking functional DICER1 gene suggesting no obvious dependence on dicer for shRNA hairpin processing; contrary to published models. Taken together, we report on a novel dicer independent, cell-type dependent mechanism for non-specific RNAi gene silencing we coin Alternate Targeting Sequence Generator (ATSG). In summary, ATSG adds another dimension to the already complex interpretation of RNAi screening data, and provides for the first time strong evidence in support of arrayed screening, and questions the scientific merits of performing pooled RNAi screens, where deconvolution of up to genome-scale pools is indispensable for target identification.