An arrayed RNA interference genome-wide screen identifies candidate genes involved in the MicroRNA 21 biogenesis pathway

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

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.

Modulators of the microRNA biogenesis pathway via arrayed lentiviral enabled RNAi screening for drug and biomarker discovery

MicroRNAs (miRNAs) are small endogenous and conserved non-coding RNA molecules that regulate gene expression. Although the first miRNA was discovered well over sixteen years ago, little is known about their biogenesis and it is only recently that we have begun to understand their scope and diversity. For this purpose, we performed an RNAi screen aimed at identifying genes involved in their biogenesis pathway with a potential use as biomarkers. Using a previously developed miRNA 21 (miR-21) EGFP-based biosensor cell based assay monitoring green fluorescence enhancements, we performed an arrayed short hairpin RNA (shRNA) screen against a lentiviral particle ready TRC1 library covering 16,039 genes in 384-well plate format, and interrogating the genome one gene at a time building a panoramic view of endogenous miRNA activity. Using the BDA method for RNAi data analysis, we nominate 497 gene candidates the knockdown of which increased the EGFP fluorescence and yielding an initial hit rate of 3.09%; of which only 22, with reported validated clones, are deemed high-confidence gene candidates. An unexpected and surprising result was that only DROSHA was identified as a hit out of the seven core essential miRNA biogenesis genes; suggesting that perhaps intracellular shRNA processing into the correct duplex may be cell dependent and with differential outcome. Biological classification revealed several major control junctions among them genes involved in transport and vesicular trafficking. In summary, we report on 22 high confidence gene candidate regulators of miRNA biogenesis with potential use in drug and biomarker discovery.

Chemical & RNAi screening at MSKCC: a collaborative platform to discover & repurpose drugs to fight disease

Memorial Sloan Kettering Cancer Center (MSKCC) has implemented the creation of a full service state-of-the-art High-throughput Screening Core Facility (HTSCF) equipped with modern robotics and custom-built screening data management resources to rapidly store and query chemical and RNAi screening data outputs. The mission of the facility is to provide oncology clinicians and researchers alike with access to cost-effective HTS solutions for both chemical and RNAi screening, with an ultimate goal of novel target identification and drug discovery. HTSCF was established in 2003 to support the institution's commitment to growth in molecular pharmacology and in the realm of therapeutic agents to fight chronic diseases such as cancer. This endeavor required broad range of expertise in technology development to establish robust and innovative assays, large collections of diverse chemical and RNAi duplexes to probe specific cellular events, sophisticated compound and data handling capabilities, and a profound knowledge in assay development, hit validation, and characterization. Our goal has been to strive for constant innovation, and we strongly believe in shifting the paradigm from traditional drug discovery towards translational research now, making allowance for unmet clinical needs in patients. Our efforts towards repurposing FDA-approved drugs fructified when digoxin, identified through primary HTS, was administered in the clinic for treatment of stage Vb retinoblastoma. In summary, the overall aim of our facility is to identify novel chemical probes, to study cellular processes relevant to investigator's research interest in chemical biology and functional genomics, and to be instrumental in accelerating the process of drug discovery in academia.

Systematic analysis of RNAi reports identifies dismal commonality at gene-level and reveals an unprecedented enrichment in pooled shRNA screens

RNA interference (RNAi) has opened promising avenues to better understand gene function. Though many RNAi screens report on the identification of genes, very few, if any, have been further studied and validated. Data discrepancy is emerging as one of RNAi main pitfalls. We reasoned that a systematic analysis of lethality-based screens, since they score for cell death, would examine the extent of hit discordance at inter-screen level. To this end, we developed a methodology for literature mining and overlap analysis of several screens using both siRNA and shRNA flavors, and obtained 64 gene lists censoring an initial list of 7,430 nominated genes. We further performed a comparative analysis first at a global level followed by hit re-assessment under much more stringent conditions. To our surprise, none of the hits overlapped across the board even for PLK1, which emerged as a strong candidate in siRNA screens; but only marginally in the shRNA ones. Furthermore, EIF5B emerges as the most common hit only in the shRNA screens. A highly unusual and unprecedented result was the observation that 5,269 out of 6,664 nominated genes (~80%) in the shRNA screens were exclusive to the pooled format, raising concerns as to the merits of pooled screens which qualify hits based on relative depletions, possibly due to multiple integrations per cell, data deconvolution or inaccuracies in intracellular processing causing off-target effects. Without golden standards in place, we would encourage the community to pay more attention to RNAi screening data analysis practices, bearing in mind that it is combinatorial in nature and one active siRNA duplex or shRNA hairpin per gene does not suffice credible hit nomination. Finally, we also would like to caution interpretation of pooled shRNA screening outcomes.