Oncogene-induced senescence (OIS), provoked in response to oncogenic activation, is considered an important tumor suppressor mechanism. Long non-coding RNAs (lncRNAs) are transcripts longer than 200 nt without a protein-coding capacity. Functional studies showed that deregulated lncRNA expression promote tumorigenesis and metastasis and that lncRNAs may exhibit tumor-suppressive and oncogenic function. Here, we first identified lncRNAs that were differentially expressed between senescent and non-senescent human fibroblast cells. Using RNA interference, we performed a loss-function screen targeting the differentially expressed lncRNAs, and identified lncRNA-OIS1 (lncRNA#32, AC008063.3 or ENSG00000233397) as a lncRNA required for OIS. Knockdown of lncRNA-OIS1 triggered bypass of senescence, higher proliferation rate, lower abundance of the cell-cycle inhibitor CDKN1A and high expression of cell-cycle-associated genes. Subcellular inspection of lncRNA-OIS1 indicated nuclear and cytosolic localization in both normal culture conditions as well as following oncogene induction. Interestingly, silencing lncRNA-OIS1 diminished the senescent-associated induction of a nearby gene (Dipeptidyl Peptidase 4, DPP4) with established role in tumor suppression. Intriguingly, similar to lncRNA-OIS1, silencing DPP4 caused senescence bypass, and ectopic expression of DPP4 in lncRNA-OIS1 knockdown cells restored the senescent phenotype. Thus, our data indicate that lncRNA-OIS1 links oncogenic induction and senescence with the activation of the tumor suppressor DPP4.
BackgroundFunctional characterization of non-coding elements in the human genome is a major genomic challenge and the maturation of genome-editing technologies is revolutionizing our ability to achieve this task. Oncogene-induced senescence, a cellular state of irreversible proliferation arrest that is enforced following excessive oncogenic activity, is a major barrier against cancer transformation; therefore, bypassing oncogene-induced senescence is a critical step in tumorigenesis. Here, we aim at further identification of enhancer elements that are required for the establishment of this state.ResultsWe first apply genome-wide profiling of enhancer-RNAs (eRNAs) to systematically identify enhancers that are activated upon oncogenic stress. DNA motif analysis of these enhancers indicates AP-1 as a major regulator of the transcriptional program induced by oncogene-induced senescence. We thus constructed a CRISPR-Cas9 sgRNA library designed to target senescence-induced enhancers that are putatively regulated by AP-1 and used it in a functional screen. We identify a critical enhancer that we name EnhAP1-OIS1 and validate that mutating the AP-1 binding site within this element results in oncogene-induced senescence bypass. Furthermore, we identify FOXF1 as the gene regulated by this enhancer and demonstrate that FOXF1 mediates EnhAP1-OIS1 effect on the senescence phenotype.ConclusionsOur study elucidates a novel cascade mediated by AP-1 and FOXF1 that regulates oncogene-induced senescence and further demonstrates the power of CRISPR-based functional genomic screens in deciphering the function of non-coding regulatory elements in the genome.Electronic supplementary materialThe online version of this article (10.1186/s13059-018-1494-1) contains supplementary material, which is available to authorized users.
Motivation Ribosome Profiling (Ribo-seq) has revolutionized the study of RNA translation by providing information on ribosome positions across all translated RNAs with nucleotide-resolution. Yet several technical limitations restrict the sequencing depth of such experiments, the most common of which is the overabundance of rRNA fragments. Various strategies can be employed to tackle this issue, including the use of commercial rRNA depletion kits. However, as they are designed for more standardized RNAseq experiments, they may perform suboptimally in Ribo-seq. In order to overcome this, it is possible to use custom biotinylated oligos complementary to the most abundant rRNA fragments, however currently no computational framework exists to aid the design of optimal oligos. Results Here, we first show that a major confounding issue is that the rRNA fragments generated via Ribo-seq vary significantly with differing experimental conditions, suggesting that a “one-size-fits-all” approach may be inefficient. Therefore we developed Ribo-ODDR, an oligo design pipeline integrated with a user-friendly interface that assists in oligo selection for efficient experiment-specific rRNA depletion. Ribo-ODDR uses preliminary data to identify the most abundant rRNA fragments, and calculates the rRNA depletion efficiency of potential oligos. We experimentally show that Ribo-ODDR designed oligos outperform commercially available kits and lead to a significant increase in rRNA depletion in Ribo-seq. Availability Ribo-ODDR is freely accessible at https://github.com/fallerlab/Ribo-ODDR Supplementary information Supplementary data are available at Bioinformatics online.
Ribosome profiling (Ribo-seq) has revolutionized the study of RNA translation. The technique provides information on ribosome positions across all translated RNAs with nucleotide-resolution. However, several technical limitations restrict the sequencing depth of such experiments, the most common of which is the overabundance of ribosomal RNA (rRNA) fragments. Various strategies have been employed to tackle this issue, including the use of commercial rRNA depletion kits, however these may perform suboptimally. Here we show that the rRNA fragments generated via Riboseq vary significantly with differing experimental conditions, suggesting that a "one-size-fits-all" approach may result in inefficient rRNA depletion. In order to overcome this it is possible to use custom-designed biotinylated oligos complementary to the most abundant rRNA fragments, however currently no computational framework exists to aid the design of optimal oligos. We have developed Ribo-ODDR, an oligo design pipeline integrated with a user-friendly interface that assists in oligo selection for efficient experiment-specific rRNA depletion. Ribo-ODDR uses preliminary data to identify the most abundant rRNA fragments, and calculates the rRNA depletion efficiency of potential oligos. We show that Ribo-ODDR designed oligos lead to a significant increase in rRNA depletion, and increased sequencing depth as a result. Ribo-ODDR is freely accessible at https://github.com/fallerlab/Ribo-ODDR
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