An Arrayed RNA Interference Genome-Wide Screen Identifies Candidate Genes Involved in the MicroRNA 21 Biogenesis Pathway

Abstract

MicroRNAs (miRNAs) are evolutionary conserved noncoding molecules that regulate gene expression. They influence a number of diverse biological functions, such as development and differentiation. However, their dysregulation has been shown to be associated with disease states, such as cancer. Genes and pathways regulating their biogenesis remain unknown and are highly sought after. For this purpose, we have validated a multiplexed high-content assay strategy to screen for such modulators. Here, we describe its implementation that makes use of a cell-based gain-of-function reporter assay monitoring enhanced green fluorescent protein expression under the control of miRNA 21 (miR-21); combined with measures of both cell metabolic activities through the use of Alamar Blue and cell death through imaged Hoechst-stained nuclei. The strategy was validated using a panel of known genes and enabled us to successfully progress to and complete an arrayed genomewide short interfering RNA (siRNA) screen against the Ambion Silencer Select v4.0 library containing 64,755 siRNA duplexes covering 21,565 genes. We applied a high-stringency hit analysis method, referred to as the Bhinder-Djaballah analysis method, leading to the nomination of 1,273 genes as candidate inhibitors of the miR-21 biogenesis pathway; after several iterations eliminating those genes with only one active duplex and those enriched in seed sequence mediated off-target effects. Biological classifications revealed four major control junctions among them vesicular transport via clathrin-mediated endocytosis. Altogether, our screen has uncovered a number of novel candidate regulators that are potentially good druggable targets allowing for the discovery and development of small molecules for regulating miRNA function.

Comparative Analysis of RNAi Screening Technologies at Genome-Scale Reveals an Inherent Processing Inefficiency of the Plasmid-Based shRNA Hairpin

“…Among them were five regulators of transcription from RNA polymerase II including the transcription initiation factor GTF2A2 . However, we were not able to identify the key functional classes of exosome and epigenetic control as previously identified in the siRNA screen [16], as an example only one member of the exosome complex DIS3 was found in common.…”

“…We have reported on the execution of an siRNA screen to identify modulators of the miRNA biogenesis pathway and nominated 1,273 gene candidates with a putative role in the process [16]. Using a consistent approach mimicking a controlled experimental environment, we subsequently performed an additional shRNA screen against the TRC1 library and leading to the identification of 497 gene candidates [17].…”

“…The assays for both screens were developed and optimized according to the technology employed (Fig 1A). For siRNA screening, we used a reverse transfection protocol to introduce siRNA duplexes into the cells and measured EGFP signal, NUCL count, and Alamar Blue readout after seven days [16]. Whereas for shRNA screening, we introduced shRNA hairpins through a transduction process using lentiviral particles and measured EGFP signal and NUCL count post cell fixing and imaging after ten days [7]; shRNA technology uses lentiviral particles for delivery and a puromycin selection step which inherently prolongs the length of the assay (Fig 1A).…”

“…We implemented a cell based assay system which measured gain in EGFP expression, under the control of miR-21, upon knockdown of critical components of miRNA biogenesis pathway, as assessed by automated microscopy [31]. We first executed on a siRNA genome-wide screen against the Ambion Silencer Select V4.0 library covering 21,565 genes and leading to the nomination of a hit list of 1,273 candidates [16]; followed by an shRNA genome-wide screen against the TRC1 library covering 16,039 genes and leading to the nomination of a hit list of 497 candidates [17]. At the first stage of gene-level comparison, we observed a marginal overlap of only 29 gene candidates between the two hit lists (Table 1); a surprising result considering the fact that 15,068 genes are commonly covered in both AMB and TRC1.…”

“…For this reason, we postulated that the best comparative analysis, perhaps, would be the one where the same experimental logistics and personnel were to be used to perform controlled RNAi screens across the two popular technologies (siRNA and shRNA), and allows for the best possible unbiased scenario for addressing the hit discordance issues and concerns at inter-screen level; and ultimately shed some light and provide some guidelines as to the reported discrepancies. Since we have reported on the execution of an siRNA screen against the AMB library covering 21,565 genes to score for those which modulate miR-21 biogenesis, and leading to the nomination of 1,274 gene candidates [16]; we reasoned that by performing an additional genome-wide screen against the TRC1 library, an shRNA plasmid based RNAi technology, covering 16,039 genes would allow us in principle to compare and contrast the performances of the siRNA duplex and shRNA hairpin technologies in arrayed formats. As such, we have recently completed the execution of an arrayed genome-scale shRNA screen against the TRC1 library containing 80,598 hairpins and covering 16,039 genes with an average of 5 shRNA hairpins per gene [17].…”