The miR-17-5p microRNA is a key regulator of the G1/S phase cell cycle transition.

BACKGROUND: MicroRNAs are modifiers of gene expression, acting to reduce translation through either translational repression or mRNA cleavage. Recently, it has been shown that some microRNAs can act to promote or suppress cell transformation, with miR-17-92 described as the first oncogenic microRNA. The association of miR-17-92 encoded microRNAs with a surprisingly broad range of cancers not only underlines the clinical significance of this locus, but also suggests that miR-17-92 may regulate fundamental biological processes, and for these reasons miR-17-92 has been considered as a therapeutic target. RESULTS: In this study, we show that miR-17-92 is a cell cycle regulated locus, and ectopic expression of a single microRNA (miR-17-5p) is sufficient to drive a proliferative signal in HEK293T cells. For the first time, we reveal the mechanism behind this response - miR-17-5p acts specifically at the G1/S-phase cell cycle boundary, by targeting more than 20 genes involved in the transition between these phases. While both pro- and anti-proliferative genes are targeted by miR-17-5p, pro-proliferative mRNAs are specifically up-regulated by secondary and/or tertiary effects in HEK293T cells. CONCLUSION: The miR-17-5p microRNA is able to act as both an oncogene and a tumor suppressor in different cellular contexts; our model of competing positive and negative signals can explain both of these activities. The coordinated suppression of proliferation-inhibitors allows miR-17-5p to efficiently de-couple negative regulators of the MAPK (mitogen activated protein kinase) signaling cascade, promoting growth in HEK293T cells. Additionally, we have demonstrated the utility of a systems biology approach as a unique and rapid approach to uncover microRNA function.

Stem cell transcriptome profiling via massive-scale mRNA sequencing.

We developed a massive-scale RNA sequencing protocol, short quantitative random RNA libraries or SQRL, to survey the complexity, dynamics and sequence content of transcriptomes in a near-complete fashion. This method generates directional, random-primed, linear cDNA libraries that are optimized for next-generation short-tag sequencing. We surveyed the poly(A)(+) transcriptomes of undifferentiated mouse embryonic stem cells (ESCs) and embryoid bodies (EBs) at an unprecedented depth (10 Gb), using the Applied Biosystems SOLiD technology. These libraries capture the genomic landscape of expression, state-specific expression, single-nucleotide polymorphisms (SNPs), the transcriptional activity of repeat elements, and both known and new alternative splicing events. We investigated the impact of transcriptional complexity on current models of key signaling pathways controlling ESC pluripotency and differentiation, highlighting how SQRL can be used to characterize transcriptome content and dynamics in a quantitative and reproducible manner, and suggesting that our understanding of transcriptional complexity is far from complete.