quantification-of-circular-rnas-using-digital-droplet-pcr

Quantification of Circular RNAs Using Digital Droplet PCR

Digital droplet polymerase chain reaction (dd-PCR) is one of the most sensitive quantification methods; it fractionates the reaction into nearly 20,000 ...

Institute of Life Sciences

Gene expression in eukaryotic cells is tightly regulated at the transcriptional and posttranscriptional levels. Posttranscriptional processes, including pre-mRNA splicing, mRNA export, mRNA turnover, and mRNA translation, are controlled by RNA-binding proteins (RBPs) and noncoding (nc)RNAs. The vast family of ncRNAs comprises diverse regulatory RNAs, such as microRNAs and long noncoding (lnc)RNAs, but also the poorly explored class of circular (circ)RNAs. Although first discovered more than three decades ago by electron microscopy, only the advent of high-throughput RNA-sequencing (RNA-seq) and the development of innovative bioinformatic pipelines have begun to allow the systematic identification of circRNAs (Szabo and Salzman, 2016; Panda ., 2017b; Panda ., 2017c). However, the validation of true circRNAs identified by RNA sequencing requires other molecular biology techniques including reverse transcription (RT) followed by conventional or quantitative (q) polymerase chain reaction (PCR), and Northern blot analysis (Jeck and Sharpless, 2014). RT-qPCR analysis of circular RNAs using divergent primers has been widely used for the detection, validation, and sometimes quantification of circRNAs (Abdelmohsen ., 2015 and 2017; Panda ., 2017b). As detailed here, divergent primers designed to span the circRNA backsplice junction sequence can specifically amplify the circRNAs and not the counterpart linear RNA. In sum, RT-PCR analysis using divergent primers allows direct detection and quantification of circRNAs.

Detection and Analysis of Circular RNAs by RT-PCR.

Identifying intronic circRNAs: progress and challenges.

The coding potential of circRNAs.

Recent developments in high-throughput RNA sequencing methods coupled with innovative bioinformatic tools have uncovered thousands of circular (circ)RNAs. CircRNAs have emerged as a vast and novel class of regulatory RNAs with potential to modulate gene expression by acting as sponges for microRNAs (miRNAs) and RNA-binding proteins (RBPs). The biochemical enrichment of circRNAs by exoribonuclease treatment or by depletion of polyadenylated RNAs coupled with deep-sequencing is widely used for the systematic identification of circRNAs. Although these methods enrich circRNAs substantially, they do not eliminate efficiently non-polyadenylated and highly-structured RNAs. Here, we describe a method we termed RPAD, based on initial RNase R treatment followed by Polyadenylation and poly(A) RNA Depletion. These joint interventions drastically depleted linear RNAs leading to isolation of highly pure circRNAs from total RNA pools. By facilitating the isolation of highly pure circRNAs, RPAD enables the elucidation of circRNA biogenesis, sequence, and function.

RPAD (RNase R treatment, polyadenylation, and poly(A)+ RNA depletion) method to isolate highly pure circular RNA.

Skeletal muscles have an immense ability to regenerate from the muscle stem cells called satellite cells. The process of skeletal muscle regeneration is called myogenesis, which starts with activation of quiescent satellite cells immediately after muscle injury followed by proliferation and fusion of myoblasts into myotubes. Myogenesis is orchestrated through the expression of a specific set of genes which, at each step regulated by complex gene regulatory networks. Besides the well-established roles of transcription factors, increasing evidence demonstrated that circular (circ)RNAs modulate gene expression during myogenesis and are involved in muscle-related diseases. Here we review the recent findings of circRNAs involved in myogenesis.

Circular RNAs in myogenesis.

High-throughput RNA sequencing and novel bioinformatic pipelines have identified thousands of circular (circ)RNAs containing backsplice junction sequences. However, circRNAs generated from multiple exons may contain different combinations of exons and/or introns arising from alternative splicing, while the backsplice junction sequence is the same. To be able to identify circRNA splice variants, we developed a method termed circRNA-Rolling Circle Amplification (circRNA-RCA). This method detects full-length circRNA sequences by performing reverse transcription (RT) in the absence of RNase H activity, followed by polymerase chain reaction (PCR) amplification of full-length circRNAs using a forward primer spanning the backsplice junction sequence and a reverse primer exactly upstream of the forward primer. By sequencing the PCR products, circRNA splice variants bearing the same backsplice junctions, which were otherwise only predicted computationally, could be experimentally validated. The splice variants were further predicted to associate with different subsets of target RNA-binding proteins and microRNAs, supporting the notion that different circRNA splice variants can have different biological impacts. In sum, the circRNA-RCA method allows the accurate identification of full-length circRNA sequences, offering unique insight into their individual function.

Rolling Circle cDNA Synthesis Uncovers Circular RNA Splice Variants.

By interacting with proteins and nucleic acids, the vast family of mammalian circRNAs is proposed to influence many biological processes. Here, RNA sequencing analysis of circRNAs differentially expressed during myogenesis revealed that circSamd4 expression increased robustly in mouse C2C12 myoblasts differentiating into myotubes. Moreover, silencing circSamd4, which is conserved between human and mouse, delayed myogenesis and lowered the expression of myogenic markers in cultured myoblasts from both species. Affinity pulldown followed by mass spectrometry revealed that circSamd4 associated with PURA and PURB, two repressors of myogenesis that inhibit transcription of the myosin heavy chain (MHC) protein family. Supporting the hypothesis that circSamd4 might complex with PUR proteins and thereby prevent their interaction with DNA, silencing circSamd4 enhanced the association of PUR proteins with the Mhc promoter, while overexpressing circSamd4 interfered with the binding of PUR proteins to the Mhc promoter. These effects were abrogated when using a mutant circSamd4 lacking the PUR binding site. Our results indicate that the association of PUR proteins with circSamd4 enhances myogenesis by contributing to the derepression of MHC transcription.

circSamd4 represses myogenic transcriptional activity of PUR proteins.

Circular RNAs (circRNAs) are a large family of noncoding RNAs that have emerged as novel regulators of gene expression. However, little is known about the function of circRNAs in pancreatic β-cells. Here, transcriptomic analysis of mice pancreatic islet RNA-sequencing data identified 77 differentially expressed circRNAs between mice fed with a normal diet and a high-fat diet. Surprisingly, multiple circRNAs were derived from the intron 2 of the preproinsulin 2 () gene and are termed as circular intronic (). The expression of  transcripts in mouse pancreatic islets, and βTC6 cells were confirmed by reverse transcription PCR, DNA sequencing, and RNase R treatment experiments. The level of  was altered in βTC6 cells upon exposure to elevated levels of palmitate and glucose. Computational analysis predicted the interaction of several RNA-binding proteins with  and their flanking region, suggesting their role in the  function or biogenesis. Additionally, bioinformatics analysis predicted the association of several microRNAs with . Gene ontology and pathway analysis of genes targeted by miRNAs associated with  suggested the regulation of several key biological processes. Together, our findings indicate that differential expression of circRNAs, especially  transcripts, may regulate β-cell function and may play a critical role in the development of diabetes.

Identification and Characterization of Circular Intronic RNAs Derived from Insulin Gene.

Recent advances in sequencing technologies and the discovery of non-coding RNAs (ncRNAs) have provided new insights in the molecular pathogenesis of cancers. Several studies have implicated the role of ncRNAs, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and recently discovered circular RNAs (circRNAs) in tumorigenesis and metastasis. Unlike linear RNAs, circRNAs are highly stable and closed-loop RNA molecules. It has been established that circRNAs regulate gene expression by controlling the functions of miRNAs and RNA-binding protein (RBP) or by translating into proteins. The circRNA-miRNA-mRNA regulatory axis is associated with human diseases, such as cancers, Alzheimer's disease, and diabetes. In this study, we explored the interaction among circRNAs, miRNAs, and their target genes in various cancers using state-of-the-art bioinformatics tools. We identified differentially expressed circRNAs, miRNAs, and mRNAs on multiple cancers from publicly available data. Furthermore, we identified many crucial drivers and tumor suppressor genes in the circRNA-miRNA-mRNA regulatory axis in various cancers. Together, this study data provide a deeper understanding of the circRNA-miRNA-mRNA regulatory mechanisms in cancers.

Cancer-Associated circRNA-miRNA-mRNA Regulatory Networks: A Meta-Analysis.

Circular RNAs (circRNAs) are a large family of noncoding RNA molecules that have emerged as novel regulators of gene expression by sequestering microRNAs (miRNAs) and RNA-binding proteins (RBPs). Several computational tools have been developed to predict circRNA interaction with target miRNAs and RBPs with a view to studying their potential effect on downstream target genes and cellular physiology. Biochemical assays, including reporter assays, AGO2 pulldown, ribonucleoprotein pulldown, and biotin-labeled RNA pulldown, are used to capture the association of miRNAs and RBPs with circRNAs. Only a few studies have used circRNA pulldown assays to capture the associated miRNAs and RBPs under physiological conditions. In this detailed protocol, the circRNA of interest () was captured using a biotin-labeled antisense oligo (ASO) targeting the  backsplice junction sequence followed by pulldown with streptavidin-conjugated magnetic beads. The specific enrichment of circRNA was analyzed using reverse transcription quantitative PCR (RT-qPCR). Furthermore, the ASO pulldown assay can be coupled to miRNA RT-qPCR and western blotting analysis to confirm the association of miRNAs and RBPs predicted to interact with the target circRNA. In summary, the specific pulldown of circRNA using this quick and easy method makes it a useful tool for identifying and validating circRNA interaction with specific miRNAs and RBPs.

Antisense Oligo Pulldown of Circular RNA for Downstream Analysis.

High-throughput RNA-sequencing (RNA-seq) technologies combined with novel bioinformatic algorithms discovered a large class of covalently closed single-stranded RNA molecules called circular RNAs (circRNAs ). Although RNA-seq has identified more than a million circRNAs, only a handful of them is validated with other techniques, including northern blotting, gel-trap electrophoresis, exonuclease treatment assays, and polymerase chain reaction (PCR). Reverse transcription (RT) of total RNA followed by PCR amplification is the most widely used technique for validating circRNAs identified in RNA-seq. RT-PCR is a highly reproducible, sensitive, and quantitative method for the detection and quantitation of circRNAs. This chapter details the basic guidelines for designing suitable primers for PCR amplification and validation of circRNAs .

Validation of Circular RNAs by PCR.

Editorial: Structural and Functional Characterization of Circular RNAs.

Circular RNAs (circRNAs) are a newly discovered family of regulatory RNAs generated through backsplicing. Genome-wide profiling of circRNAs found that circRNAs are ubiquitously expressed and regulate gene expression by acting as a sponge for RNA-binding proteins (RBPs) and microRNAs (miRNAs). To identify circRNAs expressed in mouse skeletal muscle, we performed high-throughput RNA-sequencing of circRNA-enriched gastrocnemius muscle RNA samples, which identified more than 1,200 circRNAs. In addition, we have identified more than 14,000 and 15,000 circRNAs in aging human skeletal muscle tissue and satellite cells, respectively. A subset of abundant circRNAs was analyzed by RT-PCR, Sanger sequencing, and RNase R digestion assays to validate their expression in mouse skeletal muscle tissues. Analysis of the circRNA-miRNA-mRNA regulatory network revealed that conserved  might associate with miR-204-5p, a suppressor of myocyte enhancer factor 2c () expression. To support the hypothesis that  might regulate myogenesis by controlling  expression, silencing  moderately reduced  mRNA expression and inhibited C2C12 differentiation. We propose that  promotes  expression during muscle cell differentiation in part by acting as a sponge for miR-204-5p.

Identification of Potential circRNA-microRNA-mRNA Regulatory Network in Skeletal Muscle.

The last decade has seen a robust increase in various types of novel RNA molecules and their complexity in gene regulation. RNA molecules play a critical role in cellular events by interacting with other biomolecules, including protein, DNA, and RNA. It has been established that RNA-RNA interactions play a critical role in several biological processes by regulating the biogenesis and function of RNA molecules. Interestingly, RNA-RNA interactions regulate the biogenesis of diverse RNA molecules, including mRNAs, microRNAs, tRNAs, and circRNAs, through splicing or backsplicing. Structured RNAs like rRNA, tRNA, and snRNAs achieve their functional conformation by intramolecular RNA-RNA interactions. In addition, functional consequences of many intermolecular RNA-RNA interactions have been extensively studied in the regulation of gene expression. Hence, it is essential to understand the mechanism and functions of RNA-RNA interactions in eukaryotes. Conventionally, RNA-RNA interactions have been identified through diverse biochemical methods for decades. The advent of high-throughput RNA-sequencing technologies has revolutionized the identification of global RNA-RNA interactome in cells and their importance in RNA structure and function in gene expression regulation. Although these technologies revealed tens of thousands of intramolecular and intermolecular RNA-RNA interactions, we further look forward to future unbiased and quantitative high-throughput technologies for detecting transcriptome-wide RNA-RNA interactions. With the ability to detect RNA-RNA interactome, we expect that future studies will reveal the higher-order structures of RNA molecules and multi-RNA hybrids impacting human health and diseases. This article is categorized under: RNA Methods > RNA Analyses In Vitro and In Silico RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.

Amaresh C. Panda

Institute of Life Sciences

Quantification of Circular RNAs Using Digital Droplet PCR