Optimized RNA-targeting CRISPR/Cas13d technology outperforms shRNA in identifying functional circRNAs

Zhang, Yang; Nguyen, Tuan M.; Zhang, Xiao‐Ou; Wang, Limei; Phan, Tin; Clohessy, John G.; Pandolfi, Pier Paolo

doi:10.1186/s13059-021-02263-9

Cited by 101 publications

(95 citation statements)

References 35 publications

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“…circRNAs have been implicated in human physiology and diseases, although their functions are largely unclear due to a lack of adequate methods to study them ( 39 ). Recently, CRISPR-Cas13d has been successfully applied to study the functions of circRNAs in a screening manner ( 40, 41 ), providing a novel yet efficient approach to systematically investigate circRNA functions.…”

Section: Resultsmentioning

confidence: 99%

“…We first applied DeepCas13 to one circRNA screening dataset ( 40 ) where >□2500 human hepatocellular carcinoma-related circRNAs were screened. DeepCas13 successfully distinguished efficient sgRNAs from inefficient sgRNAs (Figure 3A, AUC score is 0.7492), although the area under the precision-recall curve (AUPR) was quite low for all the guides (Figure 3B).…”

Section: Resultsmentioning

confidence: 99%

“…For dataset from circRNA screening study ( 40 ), we performed 5-fold cross validation to get Deep Scores for these limited training sgRNAs. Any sgRNAs with LFC <= -0.5 were set as positive samples and other sgRNAs were set as negative samples.…”

Section: Methodsmentioning

confidence: 99%

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Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches

Cheng

Shan

et al. 2021

Preprint

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A major challenge in the application of the CRISPR-Cas13d (RfxCas13d, or CasRx) RNA editing system is to accurately predict its guide RNA (gRNA) dependent on-target and off-target effect. Here, we performed CRISPR-Cas13d proliferation screens that target protein-coding genes and long non-coding RNAs (lncRNAs), followed by a systematic modeling of Cas13d on-target efficiency and off-target viability effect. We first designed a deep learning model, named DeepCas13, to predict the on-target activity of a gRNA with high accuracy from its sequence and secondary structure. DeepCas13 outperforms existing methods and accurately predicts the efficiency of guides targeting both protein-coding and non-coding RNAs (e.g., circRNAs and lncRNAs). Next, we systematically studied guides targeting non-essential genes, and found that the off-target viability effect, defined as the unintended effect of guides on cell viability, is closely related to their on-target RNA cleavage efficiency. This finding suggests that these gRNAs should be used as negative controls in proliferation screens to reduce false positives, possibly coming from the unwanted off-target viability effect of efficient guides. Finally, we applied these models to our screens that included guides targeting 234 lncRNAs, and identified lncRNAs that affect cell viability and proliferation in multiple cell lines. DeepCas13 is freely accessible via http://deepcas13.weililab.org.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches

Cheng

Shan

et al. 2021

Preprint

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“…A guide RNA expression cassette driven by the U6 promoter was also inserted, thereby allowing both the Cas13 effector protein (Supplementary Figure S1A) and its associated guide RNA (Supplementary Figure S1B, C) to be expressed from a single plasmid. We then took advantage of simple co-transfection assays using fluorescent protein reporter genes to characterize the on-and off-target effects of each Cas13 effector, starting with RxCas13d (from Ruminococcus flavefaciens) because it is among the smallest and most commonly used Cas13 effectors (8,29,33,34,36,(45)(46)(47)(48). As diagrammed in Figure 1A, Drosophila DL1 cells were transiently transfected with the RxCas13d/guide RNA (24-nucleotide spacer length) expression plasmid along with reporter gene plasmids that express eGFP and mCherry from the copper-inducible Metallothionein A (MtnA) promoter.…”

Section: Strong Off-target Effects Can Be Observed When Rxcas13d Is Used To Deplete An Rna Of Interest In Drosophila Cellsmentioning

confidence: 99%

CRISPR/Cas13 effectors have differing extents of off-target effects that limit their utility in eukaryotic cells

Liang

Wilusz

2021

Preprint

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CRISPR/Cas13 effectors have garnered increasing attention as easily customizable tools for detecting and depleting RNAs of interest. Near perfect complementarity between a target RNA and the Cas13-associated guide RNA is required for activation of Cas13 ribonuclease activity. Nonetheless, the specificity of Cas13 effectors in eukaryotic cells has been debated as the Cas13 nuclease domains can be exposed on the enzyme surface, providing the potential for promiscuous cleavage of nearby RNAs (so-called collateral damage). Here, using co-transfection assays in Drosophila and human cells, we found that the off-target effects of RxCas13d, a commonly used Cas13 effector, can be as strong as the level of on-target RNA knockdown. The extent of off-target effects is positively correlated with target RNA expression levels, and collateral damage can be observed even after reducing RxCas13d/guide RNA levels. The PspCas13b effector showed improved specificity and, unlike RxCas13d, can be used to deplete a Drosophila circular RNA without affecting the expression of the associated linear RNA. PspCas13b nonetheless still can have off-target effects and we notably found that the extent of off-target effects for Cas13 effectors differs depending on the cell type and target RNA examined. In total, these results highlight the need for caution when designing and interpreting Cas13-based knockdown experiments.

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“…Previous studies have reported that the majority of miRNAs and lncRNAs have regulatory functions, including regulation of the evolution of stem cells, cardiomyocytes and epithelial cells, and regulation of the translation, stabilization and degradation of mRNA (15)(16)(17)(18)(19). With the development of several state-of-the-art technologies, such as the next generation of high-throughput sequencing techniques, gene silencing and gene editing, emerging evidence has demonstrated that, not only miRNAs and lncRNAs, but also circRNAs, have regulatory functions, and are associated with a variety of diseases (20)(21)(22)(23)(24). circRNAs can interact with protein complexes, RNA molecules and DNA molecules to exert their effects, and regulate a wide variety of physiological and pathological processes (25)(26)(27).…”

Section: Introductionmentioning

confidence: 99%

Circular RNA: A novel type of biomarker for glioma (Review)

et al. 2021

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With the rapid development of sequencing technologies, the characteristics and functions of circular RNAs (circRNAs) in different tissues, and their underlying pathophysiological mechanisms, have been identified. circRNAs are significantly enriched in the brain and are continually expressed from the embryonic stage to the adult stage in rats. Previous studies have reported that certain circRNAs are differentially expressed in glioma and regulate a number of biological processes, such as cell proliferation, metastasis and oncogenesis of glioma. Furthermore, certain circRNAs have been associated with tumor size, World Health Organization tumor grade and poor prognosis in patients with glioma. It has been hypothesized that circRNAs may be involved in the onset and progression of glioma through transcriptional regulation, protein translation and binding to microRNAs. These properties and functions suggest the potential of circRNAs as prognostic biomarkers and therapeutic targets for glioma. For the present review, published studies were examined from PubMed, Embase, Cochrane Central and the reference lists of the retrieved articles. The aim of the present review was to summarize the progress of circRNA research in glioma, discuss the potential diagnostic and prognostic values, and the roles of circRNAs in glioma, and provide a novel theoretical basis and research concepts for the prediction, diagnosis and treatment of glioma.

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Optimized RNA-targeting CRISPR/Cas13d technology outperforms shRNA in identifying functional circRNAs

Cited by 101 publications

References 35 publications

Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches

Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches

CRISPR/Cas13 effectors have differing extents of off-target effects that limit their utility in eukaryotic cells

Circular RNA: A novel type of biomarker for glioma (Review)

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