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* These authors contributed equally
This protocol describes the detailed method of digital droplet PCR (dd-PCR) for precise quantification of circular RNA (circRNA) levels in cells using divergent primers.
Digital droplet polymerase chain reaction (dd-PCR) is one of the most sensitive quantification methods; it fractionates the reaction into nearly 20,000 water-in-oil droplets, and the PCR occurs in the individual droplets. The dd-PCR has several advantages over conventional real-time qPCR, including increased accuracy in detecting low-abundance targets, omitting reference genes for quantification, eliminating technical replicates for samples, and showing high resilience to inhibitors in the samples. Recently, dd-PCR has become one of the most popular methods for accurately quantifying target DNA or RNA for gene expression analysis and diagnostics. Circular RNAs (circRNAs) are a large family of recently discovered covalently closed RNA molecules lacking 5' and 3' ends. They have been shown to regulate gene expression by acting as sponges for RNA-binding proteins and microRNAs. Furthermore, circRNAs are secreted into body fluids, and their resistance to exonucleases makes them serve as biomarkers for disease diagnosis. This article aims to show how to perform divergent primer design, RNA extraction, cDNA synthesis, and dd-PCR analysis to accurately quantify specific circular RNA (circRNA) levels in cells. In conclusion, we demonstrate the precise quantification of circRNAs using dd-PCR.
Recent advancements in RNA sequencing technologies and novel computational algorithms have discovered a new member of the growing family of non-coding RNAs, called circular RNA (circRNA)1. As the name suggests, circRNAs are a family of single-stranded RNA molecules with no free ends. They are formed by non-canonical head-to-tail splicing called back-splicing, where the upstream splice acceptor site joins covalently with the downstream splice donor site to form a stable RNA circle1,2. This process could be mediated by several factors, including inverted Alu repetitive elements present in the upstream and downstream of circularized exons, or can be mediated by some splicing factors or RNA binding proteins (RBPs)2,3. Circular RNAs generated exclusively from the exonic or intronic sequence are classified as exonic circRNA and circular intronic RNAs or ci-RNAs, whereas some exonic circRNAs retain the intron and are called exon-intron circRNAs (EIcircRNAs)3,4. The functions of circRNAs are multifaceted, including sponging miRNA and/or RBP, regulating transcription, and regulating cellular function by translating into peptides3,5,6,7. Several reports have highlighted the significance of circRNAs in various diseases and physiological processes8. Furthermore, tissue-specific expression patterns and resistance to exonuclease digestion make it a functional biomarker for disease diagnosis and it can also be used as a suitable therapeutic target8. Considering its importance in regulating health and diseases, the accurate quantification of circRNA expression is the need of the hour.
Several biochemical methods have been developed to quantify circRNAs in biological samples9. One of the most convenient and widely accepted methods for circRNA quantification is reverse transcription followed by quantitative polymerase chain reaction (RT-qPCR) using divergent primer pairs10. However, the majority of circRNAs are in low abundance compared to linear mRNAs, which makes it challenging to quantify them11. To overcome this issue, we sought to use digital droplet PCR (dd-PCR) to quantify the number of circRNAs in a given sample accurately. The dd-PCR is an advanced PCR technology that follows the microfluidics principle; it generates multiple aqueous droplets in oil, and the PCR occurs in each droplet as an individual reaction12. The reaction occurs in individual droplets and is analyzed using a droplet reader, which gives the number of positive or negative droplets for the gene of interest12. It is the most sensitive technique to accurately quantify a gene of interest, even if there is only a single copy in a given sample. Decreased sensitivity toward inhibitors, better precision, and omitting the reference gene for quantification make it more advantageous than conventional qPCR13,14,15. It has been widely used as a research and diagnostic tool for the absolute quantification of a gene of interest16,17. Here, we describe the detailed dd-PCR protocol for circRNA quantification in differentiating mouse C2C12 myotubes and proliferating mouse C2C12 myoblasts using divergent primers.
RNA is sensitive to RNases; therefore, all reagents, instruments, and workspaces should be RNase-free and handled with care.
1. Divergent primer design for circRNA (see Figure 1)
2. RNA isolation
NOTE: Isolate total RNA from the mouse C2C12 cells using any commercially available kits or in-house RNA isolation method. The in-house RNA isolation method used here has been described previously21. The magnetic silica beads are prepared in the lab using the previously published protocol22. These magnetic beads can also be procured from various vendors.
3. cDNA synthesis
4. Digital droplet PCR (dd-PCR) workflow
NOTE: The workflow of dd-PCR involves multiple steps, starting from sample preparation, followed by droplet generation, PCR amplification, droplet counting, and data analysis. Each step is crucial for accurate data generation as dd-PCR involves the absolute quantification of products and does not need any standard curve. Hence, each of the different steps of dd-PCR has been described below.
The absolute number of circRNAs in each sample can be derived from the exported dd-PCR data. Real-time quantitative PCR analysis suggested differential expression of circBnc2 in the differentiated C2C12 myotubes (data not shown). Here, we wanted to check the absolute copy number of circBnc2 in proliferating C2C12 myoblasts and myotubes. Since the expression of circBnc2 is compared in two conditions, it is really important to process all samples for RNA isolation, cDNA synthesis, and PCR simulta...
CircRNA research has grown in the last decade with the discovery of high-throughput sequencing technologies. As a result, it has been considered a potential molecule for future RNA therapeutics. In addition, it is known to act as a biomarker in several diseases, including cancer and cardiovascular diseases4,8. However, the identification of circRNA is tricky because of its low abundance and it having only one specific backsplice junction sequence that differentia...
The authors declare no conflicts of interest.
This work was supported by intramural funding from the Institute of Life Sciences, the DBT research grant (BT/PR27622/MED/30/1961/2018), and the Wellcome Trust/DBT India Alliance Fellowship [IA/I/18/2/504017] awarded to Amaresh C. Panda. We thank other lab members for proofreading the article.
Name | Company | Catalog Number | Comments |
1.5 ml microcentifuge tube | Tarson | 500010 | |
0.2 ml tube strips with cap | Tarson | 610020, 510073 | |
Filter Tips | Tarson | 528104 | |
DNase/RNase-Free Distilled Water | Thermo Fisher Scientific | 10977023 | |
Phosphate-buffered saline (PBS) | Sigma | P4417 | |
Cell scrapper | HiMedia | TCP223 | |
Chloroform | SRL | 96764 | |
DNA diluent | HiMedia | MB228 | |
Random primers | Thermo Fisher Scientific | 48190011 | |
dNTP set | Thermo Fisher Scientific | R0181 | |
Murine RNase inhibitor | NEB | M0314S | |
Maxima reverse transcriptase | Thermo Fisher Scientific | EP0743 | |
QX200 dd-PCR Evagreen Supermix | Bio-Rad | 1864033 | |
Droplet generation oil for Evagreen | Bio-Rad | 1864006 | |
PCR Plate Heat Seal, foil, pierceable | Bio-Rad | 1814040 | |
DG8 Cartridges and Gaskets | Bio-Rad | 1864007 | |
DG8 Cartridge holder | Bio-Rad | 1863051 | |
QX200 Droplet Generator | Bio-Rad | 1864002 | |
ddPCR 96-Well Plates | Bio-Rad | 12001925 | |
PX1 PCR Plate Sealer | Bio-Rad | 1814000 | |
C1000 Touch Thermal Cycler with 96–Deep Well Reaction Module | Bio-Rad | 1851197 | |
QX200 Droplet Reader | Bio-Rad | 1864003 | |
Quantasoft Software | Bio-Rad | 1864011 | |
Silica column | Umbrella Life Science | 38220090 | |
UCSC Genome Browser | https://genome.ucsc.edu/ | ||
Primer 3 | https://primer3.ut.ee/ |
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