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.

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)
<ol>
	<li>Retrieve the mature sequence from circRNA annotation data using BEDTools or from the UCSC genome browser by joining the exon/intron sequence present between the backsplice junction coordinates18,19.</li>
	<li>Prepare a PCR template sequence of 200 nucleotides in length by joining the last 100 nucleotides of the total circRNA sequence length to the first 100 nucleotides of the circRNA sequence10. 
	NOTE: If the circRNA length is less than 200 nucleotides, then divide it into two equal halves and join the nucleotides from the last half to the beginning of the first half.</li>
	<li>Use the above template sequence for primer design by using the Primer3 web tool and setting a PCR product length ranging from 120-180 nucleotides in length20.</li>
	<li>Use the default settings of Primer3 for other parameters such as Tm and primer length. The primer sequences for circBnc2 are listed in Table 1.</li>
	<li>Order the divergent primer sequences for synthesis from any oligo synthesizing company.</li>
</ol>
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.
<ol>
	<li>Take one 10 cm dish containing about 5 x 106 proliferating C2C12 myoblast cells and one 4-day differentiated C2C12 myotube for RNA isolation.</li>
	<li>Wash the cells with 10 mL of 1x PBS three times and discard the PBS using a pipette.</li>
	<li>Scrape the cells in 1 mL of 1x PBS using a cell scraper, centrifuge them at 4 &#730;C for 5 min at 750 x g, and discard the PBS using a pipette.</li>
	<li>Add 1 mL of RNA isolation reagent (RIR) and lyse the cells by vigorous pipetting21.</li>
	<li>Add 200 &#181;L (1/5 of the volume of RIR) of chloroform and vortex for 15 s. Centrifuge the tube at 4 &#730;C for 10 min at 12,000 x g.</li>
	<li>Take 400 &#181;L of the upper aqueous layer, load it on a silica column, and centrifuge for 1 min at 12,000 x g at room temperature. Take the flow-through to a new tube and add 600 &#181;L of 100% ethanol.</li>
	<li>Add 20 &#181;L of magnetic silica beads and place the tube on a thermomixer set at 25 &#730;C and 1,200 rpm for 5 min. 
	NOTE: The bead volume can be increased or decreased depending on the initial cell numbers taken for lysis. Magnetic silica beads can be procured from commercial vendors.</li>
	<li>Place the tube on a magnetic stand for 30 s or until the solution becomes clear. Discard the supernatant carefully using a pipette.</li>
	<li>Resuspend the magnetic silica beads in a 500 &#181;L of wash buffer containing 90% ethanol. Place the tube on the magnetic stand for 30 s. Rotate the tube twice on the magnetic stand to wash the beads. Let the beads settle toward the magnet and discard the buffer using a pipette.</li>
	<li>Repeat step 2.9 twice. After the wash, briefly spin the tube and place it back on the magnetic stand for 30 s. Discard the remaining wash buffer. Air-dry the tube at 50 &#730;C for 3 min on a thermomixer, keeping the lid open.</li>
	<li>Add 20 &#181;L of nuclease-free water and resuspend the beads. 
	NOTE: The RNA elution volume can be decreased down to 10 &#181;L to scale up the RNA concentration.</li>
	<li>Place the tubes for 2-3 min at room temperature. Place the tube back on the magnetic stand and let it sit for 30 s. Collect the dissolved RNA in a new tube for quantity and quality assessment using a spectrophotometer. 
	NOTE: RNA can be stored at &#8722;20 &#730;C or &#8722;80 &#730;C for long-term storage. To get an optimum result, it is recommended to proceed with the cDNA synthesis step the next day.</li>
</ol>
3. cDNA synthesis
<ol>
	<li>Measure the RNA concentration using a spectrophotometer and take 1 &#181;g of RNA for cDNA synthesis.</li>
	<li>Mix 1 &#181;g of total RNA with 1 &#181;L of dNTP mix (10 mM each of dATP, dTTP, dGTP, and dCTP), 4 &#181;L of 5x reverse transcriptase (RT) buffer, 2 &#181;L of 10x RT random primer, 0.25 &#181;L of reverse transcriptase enzyme (200 U/&#181;L), and 0.5 &#181;L of RNase inhibitor (40 U/&#181;L), and make up the volume up to 20 &#181;L using nuclease-free water. 
	NOTE: The reverse transcriptase enzyme volume can be altered depending on the initial RNA concentration taken for cDNA synthesis.</li>
	<li>Tap the tube to mix the reaction and spin briefly. Place the tube at 25 &#730;C for 10 min followed by at 50 &#730;C for 1 h.</li>
	<li>To inactivate the enzyme, place the tube at 85 &#730;C for 5 min.</li>
	<li>Ice chill the tube for 2 min and add 480 &#181;L of nuclease-free water to the tube to make the cDNA concentration to 2 ng/&#181;L. 
	NOTE: cDNA can be stored at -20 &#730;C or used immediately for dd-PCR analysis.</li>
</ol>
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.
<ol>
	<li>Preparation of the dd-PCR reaction.
	<ol>
		<li>Set up the PCR reaction of 22 &#181;L in 0.2 mL PCR tubes or strips along with a negative control tube and NTC (non-template control) tubes. 
		NOTE: Each different divergent primer pair for the detection of different circRNAs must have an NTC reaction along with test samples.</li>
		<li>Add 11 &#181;L of dd-PCR master-mix (e.g., EvaGreen Supermix) and 11 &#181;L of nuclease-free water to set up the negative control reaction tube. 
		NOTE: Thaw the dd-PCR master-mix at room temperature followed by a brief vortex to make a homogeneous mixture. Use the same nuclease-free water to set up the negative control reaction tube and NTC tubes that were used for diluting the cDNA.</li>
		<li>Add 11 &#181;L of dd-PCR master-mix, 5.5 &#181;L of circRNA specific forward and reverse primer mix of 1 &#181;M concentration, and 5.5 &#181;L of nuclease-free water to set up the NTC reaction tubes. 
		NOTE: Dilute the forward and reverse circular RNA-specific divergent primers of 100 &#181;M stock and mix to prepare a 1 &#181;M working concentration of forward and reverse circRNA primer mix; thus, the final primer concentration is 250 nM in the 22 &#181;L reaction.</li>
		<li>Add 11 &#181;L of dd-PCR master-mix, 5.5 &#181;L of circRNA specific forward and reverse primer mix of 1 &#181;M concentration, and 5.5 &#181;L of cDNA (2 ng/&#181;L) to set up the test reaction tubes.</li>
		<li>Vortex thoroughly followed by briefly centrifuging all the reaction tubes to get a homogeneous reaction mixture at the bottom of the tubes.</li>
	</ol>
	</li>
	<li>Droplet generation.
	<ol>
		<li>Transfer the 20 &#181;L of PCR mixture from 0.2 mL PCR tubes to the sample wells of the droplet generator cartridge.</li>
		<li>Add 70 &#181;L of droplet generation oil to the oil wells of the droplet generator cartridge carefully using a multi-channel pipette. 
		&#8203;NOTE: Incubate the droplet generation oil at room temperature for 15 min before use.</li>
		<li>Cover the droplet generator cartridge with the rubber gasket and place it in the droplet generator machine to get the sample-oil droplet mix, generated in the droplet wells of the cartridge.</li>
	</ol>
	</li>
	<li>PCR amplification.
	<ol>
		<li>Transfer 40 &#181;L of the sample-oil droplet mix from the droplet wells of the droplet generator cartridge to a 96-well PCR plate using a multi-channel pipette. 
		NOTE: Carefully transfer the sample-oil droplet mix while making an angle to the wells through the tips of the multi-channel pipette to avoid breaking the droplets while transferring them to the dd-PCR 96-well plate.</li>
		<li>Seal the 96-well PCR plate with the aluminum foil sealer, place it in the plate sealer machine block preheated at 80 &#730;C, and click seal for sealing the PCR plate.</li>
		<li>Now, place the plate in the dd-PCR thermal cycler and set the program as mentioned in Table 2 with the lid temperature set at 105 &#730;C and a ramp rate of 2 &#730;C/s.</li>
	</ol>
	</li>
	<li>Droplet counting.
	<ol>
		<li>Once PCR is over, place the plate on the dd-PCR droplet counter machine with the plate holder in the correct position for counting the droplets.</li>
		<li>Open the droplet analysis software and set up the run by giving input for the sample information.</li>
		<li>Click on the setup option. Then, click on the template option to open a new template.</li>
		<li>Define each well by putting the details of the experiment, such as sample name (cDNA used or negative control or NTC), target name (circRNA primer name) and type (unknown), and experiment type as ABS (absolute quantification) and Supermix (dd-PCR EvaGreen Supermix) used, etc.</li>
		<li>Finally, save the template and start the run by clicking on the run option and select counting by row or column-wise. Allow the machine to complete the droplet counting, which takes about 1 min/well.</li>
		<li>Click the Analyze button to analyze the data after the completion of the droplet reading.</li>
		<li>Click the 1D Amplitude button to see the positive and negative droplets</li>
		<li>To segregate the positive droplets from the negative droplets, put a common threshold line for all samples with the same target. 
		NOTE: The total droplets in each sample should be above 10,000 to be considered for absolute quantification. The NTC should not show positive droplet counts.&#160;The presence of positive droplets in the NTC indicates contamination of the reagents or amplification of the primer dimers. It is difficult to find out whether the positive droplets have primer dimers or non-specific products in NTC. It is advised to check the primers and avoid any contamination of the reagents as a general practice for any PCR including dd-PCR.</li>
		<li>Click the Export button to export the circRNA counts data as a .csv file. The exported data show the number of circRNAs present in each sample.</li>
		<li>Manually calculate the number of circRNAs in each sample per nanogram of RNA by considering the total amount of cDNA used in each reaction.</li>
	</ol>
	</li>
</ol>

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<li>Hindson, B. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((High-throughput+droplet+digital+PCR+system+for+absolute+quantitation+of+DNA+copy+number%5BTitle%5D)+AND+%22Analytical+Chemistry%22%5BJournal%5D)">High-throughput droplet digital PCR system for absolute quantitation of DNA copy number.</a> Analytical Chemistry. 83 (22), 8604-8610 (2011).</li>
<li>Ishak, A., AlRawashdeh, M. M., Esagian, S. M., Nikas, I. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Diagnostic%2C+prognostic%2C+and+therapeutic+value+of+droplet+digital+PCR+%28ddPCR%29+in+COVID-19+patients%3A+A+systematic+review%5BTitle%5D)+AND+%22Journal+of+Clinical+Medicine%22%5BJournal%5D)">Diagnostic, prognostic, and therapeutic value of droplet digital PCR (ddPCR) in COVID-19 patients: A systematic review.</a> Journal of Clinical Medicine. 10 (23), 5712(2021).</li>
<li>Li, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Application+of+droplet+digital+PCR+to+detect+the+pathogens+of+infectious+diseases%5BTitle%5D)+AND+%22Bioscience+Reports%22%5BJournal%5D)">Application of droplet digital PCR to detect the pathogens of infectious diseases.</a> Bioscience Reports. 38 (6), (2018).</li>
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The authors declare no conflicts of interest.

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 differentiates it from the parental mRNA9. RT-PCR using divergent primers has been the gold standard technique to validate circRNA since its discovery9,10. Although several molecular methods have been developed for circRNA quantification, it is challenging to measure circRNA expressions accurately because of their low abundance. Since dd-PCR can amplify very low-abundant&#160;RNA/DNA molecules from a given sample14, it is one of the best methods for the accurate quantification of circRNAs.
The dd-PCR is an end-point assay that gives absolute quantification of the target gene15. Unlike conventional qPCR, it is time-consuming, tedious, and expensive, making it less accepted compared to real-time PCR even a decade after its discovery15. However, it offers several advantages over the widely used qPCR to study gene expression changes13,23. First, dd-PCR can provide the exact number of copies of DNA present in a given sample. Second, a change in housekeeping gene expression alters the calculation of the target gene population in a given sample. This can be avoided in dd-PCR, which does not depend on standard curves or housekeeping genes for quantifying target DNA15. Third, as the PCR reaction occurs in small compartments, it provides higher flexibility toward the presence of non-specific inhibitors or background DNA, making it a more accurate method for quantifying target genes23,24.
We used the dd-PCR technology to quantify circBnc2 expression in proliferating C2C12 myoblasts and differentiated myotubes using divergent primers. However, specific circRNA amplification with divergent primer pairs without primer-dimers must be checked in regular PCR before performing dd-PCR. Also, the dd-PCR protocol must be followed carefully for the accurate measurement of circRNA expression. The workflow presented here can be easily adapted for the quantification of any circRNA of interest. Recent studies have highlighted the diagnostic values of circRNAs present in tissue and body fluids for the detection of diseases8. Together, this method will be an essential tool in the research and diagnostics industry and will accelerate circRNA research.

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.

<table><tbody><tr><td>1.5 ml microcentifuge tube</td><td>Tarson</td><td>500010</td><td></td></tr><tr><td>0.2 ml tube strips with cap</td><td>Tarson</td><td>610020, 510073</td><td></td></tr><tr><td>Filter Tips</td><td>Tarson</td><td>528104</td><td></td></tr><tr><td>DNase/RNase-Free Distilled Water</td><td>Thermo Fisher Scientific</td><td>10977023</td><td></td></tr><tr><td>Phosphate-buffered saline (PBS)</td><td>Sigma</td><td>P4417</td><td></td></tr><tr><td>Cell scrapper</td><td>HiMedia</td><td>TCP223</td><td></td></tr><tr><td>Chloroform</td><td>SRL</td><td>96764</td><td></td></tr><tr><td>DNA diluent</td><td>HiMedia</td><td>MB228</td><td></td></tr><tr><td>Random primers</td><td>Thermo Fisher Scientific</td><td>48190011</td><td></td></tr><tr><td>dNTP set</td><td>Thermo Fisher Scientific</td><td>R0181</td><td></td></tr><tr><td>Murine RNase inhibitor</td><td>NEB</td><td>M0314S</td><td></td></tr><tr><td>Maxima reverse transcriptase</td><td>Thermo Fisher Scientific</td><td>EP0743</td><td></td></tr><tr><td>QX200 dd-PCR Evagreen Supermix</td><td>Bio-Rad</td><td>1864033</td><td></td></tr><tr><td>Droplet generation oil for Evagreen</td><td>Bio-Rad</td><td>1864006</td><td></td></tr><tr><td>PCR Plate Heat Seal, foil, pierceable</td><td>Bio-Rad</td><td>1814040</td><td></td></tr><tr><td>DG8 Cartridges and Gaskets</td><td>Bio-Rad</td><td>1864007</td><td></td></tr><tr><td>DG8 Cartridge holder</td><td>Bio-Rad</td><td>1863051</td><td></td></tr><tr><td>QX200 Droplet Generator</td><td>Bio-Rad</td><td>1864002</td><td></td></tr><tr><td>ddPCR 96-Well Plates</td><td>Bio-Rad</td><td>12001925</td><td></td></tr><tr><td>PX1 PCR Plate Sealer</td><td>Bio-Rad</td><td>1814000</td><td></td></tr><tr><td>C1000 Touch Thermal Cycler with 96&amp;ndash;Deep Well Reaction Module</td><td>Bio-Rad</td><td>1851197</td><td></td></tr><tr><td>QX200 Droplet Reader</td><td>Bio-Rad</td><td>1864003</td><td></td></tr><tr><td>Quantasoft Software</td><td>Bio-Rad</td><td>1864011</td><td></td></tr><tr><td>Silica column</td><td>Umbrella Life Science</td><td>38220090</td><td></td></tr><tr><td>UCSC Genome Browser</td><td></td><td>https://genome.ucsc.edu/</td><td></td></tr><tr><td>Primer 3</td><td></td><td>https://primer3.ut.ee/</td><td></td></tr></tbody></table>

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 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.

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 simultaneously using the same reagents and procedure. To perform the absolute quantification of circRNAs using the dd-PCR reaction, an equal amount of initial total RNA should be used for cDNA synthesis to calculate the exact number of target RNA molecules per nanogram of total RNA. For example, 1 &#181;g of total RNA was used for cDNA synthesis and diluted to 500 &#181;L using nuclease-free water to get a final concentration of 2 ng/&#181;L before performing the dd-PCR assay (Figure 1).
As shown in Figure 2A, cDNA from 10 ng of RNA from proliferating C2C12 myoblasts cells (MB) and a 4-day differentiated myotube (MT) was used to check the difference in expression of circBnc2 in these two conditions. The samples were processed to generate the droplet and perform PCR, followed by counting the positive and negative droplets using the droplet analysis software as per the manufacturer&#39;s instructions (Figure 2B). Since primers can amplify non-specific products and form primer dimers, NTC should be used for all primer sets. Ideally, NTC should have no positive droplet counts.
As shown in Figure 3A, all samples except MT1 showed more than 12,000 droplet counts. Since the total droplet count was low in MT1, this sample was not considered for final data analysis. The low total droplet count could be due to an error in droplet generation, rupture of the droplets during transfer to the PCR plate, or pipetting issues. Interestingly, there was a clear difference in the expression pattern of circBnc2 in the 4-day differentiated myotube condition compared to the myoblast cells. The analysis of circBnc2 abundance in terms of copy number indicated that the three replicates of C2C12 myoblasts had 76.8, 67, and 46 copies/ng of RNA, while the two myotube samples had 558 and 610 copies/ng of RNA (Figure 3B). Since one myotube sample did not work well, it is better to have a greater number of biological replicates to study the statistical differences in their expression patterns in the two conditions.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64464/64464fig01.jpg" /> 
Figure 1: Schematic representation of the divergent primer design for the PCR amplification of circBnc2. <a href="https://www.jove.com/files/ftp_upload/64464/64464fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/64464/64464fig02.jpg" /> 
Figure 2: The dd-PCR workflow for circRNA quantification. The complete dd-PCR workflow includes many steps: (A) RNA isolation and cDNA preparation from C2C12 myoblast and 4-day differentiated myotube cells, PCR mixture preparation, (B) droplet generation, PCR amplification, droplet counting, and data analysis. <a href="https://www.jove.com/files/ftp_upload/64464/64464fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/64464/64464fig03.jpg" /> 
Figure 3: Data analysis using QuantaSoft software. (A) Data analysis includes the identification of positive and negative droplets using the quantitation software. (B) Calculating the number of circRNAs/ng of RNA in C2C12 myoblasts (MB) and myotubes (MT). The data in the panel B bar graph represent the mean &#177; STDEV of two to three biological replicates. <a href="https://www.jove.com/files/ftp_upload/64464/64464fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Primer Name</td>
			<td>Sequence</td>
		</tr>
		<tr>
			<td>circBnc2 Forward primer</td>
			<td>AAAGAGATGCACGTCTGCAC</td>
		</tr>
		<tr>
			<td>circBnc2 Reverse primer</td>
			<td>AACCGCAGAAACTGCTGAAG</td>
		</tr>
	</tbody>
</table>
Table 1: Divergent primer sequences used for the amplification of circBnc2.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Step</td>
			<td>Temperature (&#730;C)</td>
			<td>Time</td>
			<td>No of cycles</td>
			<td>Ramp rate</td>
		</tr>
		<tr>
			<td>Enzyme activation</td>
			<td>95</td>
			<td>10 min</td>
			<td>1</td>
			<td>~ 2 &#730;C/s</td>
		</tr>
		<tr>
			<td>Denaturation</td>
			<td>94</td>
			<td>30 s</td>
			<td>40</td>
			<td>~ 2 &#730;C/s</td>
		</tr>
		<tr>
			<td>Annealing/Extension</td>
			<td>60</td>
			<td>1 min</td>
			<td>40</td>
			<td>~ 2 &#730;C/s</td>
		</tr>
		<tr>
			<td>Signal stabilisation</td>
			<td>4</td>
			<td>5 min</td>
			<td>1</td>
			<td>~ 2 &#730;C/s</td>
		</tr>
		<tr>
			<td>Signal stabilisation</td>
			<td>90</td>
			<td>5 min</td>
			<td>1</td>
			<td>~ 2 &#730;C/s</td>
		</tr>
	</tbody>
</table>
Table 2: Conditions for PCR amplification of circBnc2 on a thermal cycler.

Watch this Scientific Journal Video about Quantification of Circular RNAs Using Digital Droplet PCR at JoVE.com

Quantification of Circular RNAs Using Digital Droplet PCR

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 ...

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

Nanyang Technological University

Research

JoVE Journal

Biology

3.4K Views.  Institute of Life Sciences. 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. 

Video: Quantification of Circular RNAs Using Digital Droplet PCR

Detection of a CDH1 Rare Transcript Variant in Fresh-frozen Gastric Cancer Tissues by Chip-based Digital PCR

CDH1a, a non-canonical transcript of the CDH1 gene, has been found to be expressed in some gastric cancer (GC) cell lines, whereas it is absent in normal gastric mucosa. Recently, we detected CDH1a transcript variant in fresh-frozen tumor tissues obtained from patients with GC. The expression of this variant in tissue samples was investigated by the chip-based digital PCR (dPCR) approach presented here. dPCR offers the potential for an accurate, robust, and highly sensitive measurement of nucleic acids and is increasingly utilized for many applications in different fields. dPCR is capable of detecting rare targets; in addition, dPCR offers the possibility for absolute and precise quantification of nucleic acids without the need for calibrators and standard curves. In fact, the reaction partitioning enriches the target from the background, which improves amplification efficiency and tolerance to inhibitors. Such characteristics make dPCR an optimal tool for the detection of the CDH1a rare transcript.

Detection of a CDH1 Rare Transcript Variant in Fresh-frozen Gastric Cancer Tissues by Chip-based Digital PCR

The manuscript describes a chip-based digital PCR assay to detect a rare CDH1 transcript variant (CDH1a) in fresh-frozen normal and tumor tissues obtained from patients with gastric cancer.

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Cancer Research

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids

Complications associated with upfront and repeat surgical tissue sampling present the need for minimally invasive platforms capable of molecular sub-classification and temporal monitoring of tumor response to therapy. Here, we describe our dPCR-based method for the detection of tumor somatic mutations in cell free DNA (cfDNA), readily available in&#160;patient biofluids. Although limited in the number of mutations that can be tested for in each assay, this method provides a high level of sensitivity and specificity. Monitoring of mutation abundance, as calculated by MAF, allows for the evaluation of tumor response to therapy, thereby providing a much-needed supplement to radiographic imaging.

Here, we present a protocol to detect tumor somatic mutations in circulating DNA present in patient biological fluids (biofluids). Our droplet digital polymerase chain reaction (dPCR)-based method enables quantification of the tumor mutation allelic frequency (MAF), facilitating a minimally invasive complement to diagnosis and temporal monitoring of tumor response.

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Identification of Circular RNAs using RNA Sequencing

Circular RNAs (circRNAs) are a class of non-coding RNAs involved in functions including micro-RNA (miRNA) regulation, mediation of protein-protein interactions, and regulation of parental gene transcription. In classical next generation RNA sequencing (RNA-seq), circRNAs are typically overlooked as a result of poly-A selection during construction of mRNA libraries, or are found at very low abundance, and are therefore difficult to isolate and detect. Here, a circRNA library construction protocol was optimized by comparing library preparation kits, pre-treatment options and various total RNA input amounts. Two commercially available whole transcriptome library preparation kits, with and without RNase R pre-treatment, and using variable amounts of total RNA input (1 to 4 &#181;g), were tested. Lastly, multiple tissue types; including liver, lung, lymph node, and pancreas; as well as multiple brain regions; including the cerebellum, inferior parietal lobe, middle temporal gyrus, occipital cortex, and superior frontal gyrus; were compared to evaluate circRNA abundance across tissue types. Analysis of the generated RNA-seq data using six different circRNA detection tools (find_circ, CIRI, Mapsplice, KNIFE, DCC, and CIRCexplorer) revealed that a stranded total RNA library preparation kit with RNase R pre-treatment and 4 &#181;g RNA input is the optimal method for identifying the highest relative number of circRNAs. Consistent with previous findings, the highest enrichment of circRNAs was observed in brain tissues compared to other tissue types.

Circular RNAs (circRNAs) are non-coding RNAs that may have roles in transcriptional regulation and mediating interactions between proteins. Following assessment of different parameters for construction of circRNA sequencing libraries, a protocol was compiled utilizing stranded total RNA library preparation with RNase R pre-treatment and is presented here.

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Genetics

Detecting Off-Target CRISPR-Cas9 Cleavage Events with CIRCLE-Seq

CIRCLE-Seq for Interrogation of Off-Target Gene Editing

Circularization for In Vitro Reporting of Cleavage Effects by Sequencing (CIRCLE-seq) is a novel technique developed for the impartial identification of unintended cleavage sites of CRISPR-Cas9 through targeted sequencing of CRISPR-Cas9 cleaved DNA. The protocol involves circularizing genomic DNA (gDNA), which is subsequently treated with the Cas9 protein and a guide RNA (gRNA) of interest. Following treatment, the cleaved DNA is purified and prepared as a library for Illumina sequencing. The sequencing process generates paired-end reads, offering comprehensive data on each cleavage site. CIRCLE-seq provides several advantages over other in vitro methods, including minimal sequencing depth requirements, low background, and high enrichment for Cas9-cleaved gDNA. These advantages enhance sensitivity in identifying both intended and unintended cleavage events. This study provides a comprehensive, step-by-step procedure for examining the off-target activity of CRISPR-Cas9 using CIRCLE-seq. As an example, this protocol is validated by mapping genome-wide unintended cleavage sites of CRISPR-Cas9 during the modification of the AAVS1 locus. The entire CIRCLE-seq process can be completed in two weeks, allowing sufficient time for cell growth, DNA purification, library preparation, and Illumina sequencing. The input of sequencing data into the CIRCLE-seq pipeline facilitates streamlined interpretation and analysis of cleavage sites.

A significant barrier to technologies like CRISPR is the off-target events that can disrupt vital genes. 'Circularization for In Vitro Reporting of Cleavage Effects by Sequencing' (CIRCLE-seq) is a technique designed to identify unintended cleavage sites. This method maps the genome-wide activity of CRISPR-Cas9 with high sensitivity and without bias.

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Circulating MicroRNA Quantification Using DNA-binding Dye Chemistry and Droplet Digital PCR

Circulating (of cell-free) microRNAs (miRNAs) are released from cells into the blood stream. The amount of specific microRNAs in the circulation has been linked to a disease state and has the potential to be used as disease biomarker. A sensitive and accurate method for circulating microRNA quantification using a dye-based chemistry and droplet digital PCR technology has been recently developed. Specifically, using Locked Nucleic Acid (LNA)-based miRNA-specific primers with a green fluorescent DNA-binding dye in a compatible droplet digital PCR system it is possible to obtain the absolute quantification of specific miRNAs. Here, we describe how performing this technique to assess miRNA amount in biological fluids, such as plasma and serum, is both feasible and effective.

A sensitive and accurate method for cell-free microRNAs quantification using a dye-based chemistry and droplet digital PCR technology is described.

Circulating (of cell-free) microRNAs (miRNAs) are released from cells into the blood stream. The amount of specific microRNAs in the circulation has been ...

Bioengineering

Digital PCR for Quantifying Circulating MicroRNAs in Acute Myocardial Infarction and Cardiovascular Disease

Circulating serum microRNAs (miRNAs) have shown promise as biomarkers for the cardiovascular disease and acute myocardial infarction (AMI), being released from the cardiovascular cells into the circulation. Circulating miRNAs are highly stable and can be quantified. The quantitative expression of specific miRNAs can be linked to the pathology, and some miRNAs show high tissue and disease specificity. Finding novel biomarkers for cardiovascular diseases is of importance for medical research. Quite recently, digital polymerase chain reaction (dPCR) has been invented. dPCR, combined with fluorescent hydrolysis probes, enables specific direct absolute quantification. dPCR exhibits superior technical qualities, including a low variability, high linearity, and high sensitivity compared to the quantitative polymerase chain reaction (qPCR). Thus, dPCR is a more accurate and reproducible method for directly quantifying miRNAs, particularly for the use in large multi-center cardiovascular clinical trials. In this publication, we describe how to effectively perform digital PCR in order to assess the absolute copy number in serum samples.

Circulating microRNAs have shown promise as biomarkers for cardiovascular diseases and acute myocardial infarctions. In this study, we describe a protocol for miRNA extraction, reverse transcription, and digital PCR for the absolute quantification of miRNAs in the serum of patients with cardiovascular disease.

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Medicine

Standardized Protocol for Viral Genome Quantification Using Digital Droplet PCR

Quantification of Adeno-Associated Viral Genomes in Purified Vector Samples by Digital Droplet Polymerase Chain Reaction

Adeno-associated virus (AAV) is a non-pathogenic virus used as a delivery vehicle to transfer therapeutic genes into patients. Accurate quantification of AAV genome copy number in vector preparations is essential for bioprocess optimization and dosage calculation in both preclinical and clinical studies of AAV-based gene therapy products. Currently, a consensus protocol for AAV viral genome titration is lacking. Here, we present a digital droplet PCR (dd_PCR) protocol for the quantification of viral genomes in purified vector samples. Samples are treated with DNase I to eliminate unpackaged contaminant DNA. DNase-treated samples are then mixed with an appropriate primer-probe set (designed according to the target AAV genome) and PCR reagents, and then loaded into a droplet generator. The prepared droplets are transferred into a PCR plate, where PCR amplification is performed and analyzed. The viral genome titer is calculated based on the concentration (copies/&#181;L), accounting for sample dilutions. A successful measurement shows a clear separation of the positive and negative droplet clouds, has at least 10,000 accepted droplets, shows a value between 10 copies/&#181;L and 10,000 copies/&#181;L, and has a coefficient of variation (CV) between repeats lower than 20%. Reliable viral genome titration will aid in the development of safe and effective AAV-based gene therapy products.

Author Spotlight: Optimizing Digital Droplet PCR Method for Accurate Adeno-Associated Viral Genome Quantification

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The mammalian mitochondrial (mt)DNA is a small, circular, double-stranded, intra-mitochondrial DNA molecule, encoding 13 subunits of the electron transport chain. Unlike the diploid nuclear genome, most cells contain many more copies of mtDNA, ranging from less than 100 to over 200,000 copies depending on cell type. MtDNA copy number is increasingly used as a biomarker for a number of age-related degenerative conditions and diseases, and thus, accurate measurement of the mtDNA copy number is becoming a key tool in both research and diagnostic settings. Mutations in the mtDNA, often occurring as single nucleotide polymorphisms (SNPs) or deletions, can either exist in all copies of the mtDNA within the cell (termed homoplasmy) or as a mixture of mutated and WT mtDNA copies (termed heteroplasmy). Heteroplasmic mtDNA mutations are a major cause of clinical mitochondrial pathology, either in rare diseases or in a growing number of common late-onset diseases such as Parkinson's disease. Determining the level of heteroplasmy present in cells is a critical step in the diagnosis of rare mitochondrial diseases and in research aimed at understanding common late-onset disorders where mitochondria may play a role. MtDNA copy number and heteroplasmy have traditionally been measured by quantitative (q)PCR-based assays or deep sequencing. However, the recent introduction of ddPCR technology has provided an alternative method for measuring both parameters. It offers several advantages over existing methods, including the ability to measure absolute mtDNA copy number and sufficient sensitivity to make accurate measurements from single cells even at low copy numbers. Presented here is a detailed protocol describing the measurement of mtDNA copy number in single cells using ddPCR, referred to as droplet generation PCR henceforth, with the option for simultaneous measurement of heteroplasmy in cells with mtDNA deletions. The possibility of expanding this method to measure heteroplasmy in cells with mtDNA SNPs is also discussed.

Here we present a protocol for measuring absolute mitochondrial (mt)DNA copy number and mtDNA deletion heteroplasmy levels in single cells.

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Absolute Quantification of Plasma MicroRNA Levels in Cynomolgus Monkeys, Using Quantitative Real-time Reverse Transcription PCR

RT-qPCR is one of the most common methods to assess individual target miRNAs. MiRNAs levels are generally measured relative to a reference sample. This approach is appropriate for examining physiological changes in target gene expression levels. However, absolute quantification using better statistical analysis is preferable for a comprehensive assessment of gene expression levels. Absolute quantification is still not in common use. This report describes a protocol for measuring the absolute levels of plasma miRNA, using RT-qPCR with or without pre-amplification.
A fixed volume (200 &#181;L) of EDTA-plasma was prepared from the blood collected from the femoral vein of conscious cynomolgus monkeys (n = 50). Total RNA was extracted using commercially available system. Plasma miRNAs were quantified by probe-based RT-qPCR assays which contains miRNA-specific forward/reverse PCR primer and probe. Standard curves for absolute quantification were generated using commercially available synthetic RNA oligonucleotides. A synthetic cel-miR-238 was used as an external control for normalization and quality assessment. The miRNAs that showed quantification cycle (Cq) values above 35 were pre-amplified prior to the qPCR step.
Among the 8 miRNAs examined, miR-122, miR-133a, and miR-192 were detectable without pre-amplification, whereas miR-1, miR-206, and miR-499a required pre-amplification because of their low expression levels. MiR-208a and miR-208b were not detectable even after pre-amplification. Sample processing efficiency was evaluated by the Cq values of the spiked cel-miR-238. In this assay method, technical variation was estimated to be less than 3-fold and the lower limit of quantification (LLOQ) was 102 copy/&#181;L, for most of the examined miRNAs.
This protocol provides a better estimate of the quantity of plasma miRNAs, and allows quality assessment of corresponding data from different studies. Considering the low number of miRNAs in body fluids, pre-amplification is useful to enhance detection of poorly expressed miRNAs.

This report describes a protocol for measuring the absolute levels of plasma miRNA, using quantitative real-time reverse transcription PCR with or without pre-amplification. This protocol affords better understanding of the quantity of plasma miRNAs and allows qualitative assessment of corresponding data from different studies or laboratories.

RT-qPCR is one of the most common methods to assess individual target miRNAs. MiRNAs levels are generally measured relative to a reference sample. This ...

In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions

Circular RNAs (circRNAs) are a class of non-coding RNAs that are formed via back-splicing. These circRNAs are predominantly studied for their roles as regulators of various biological processes. Notably, emerging evidence demonstrates that host circRNAs can be differentially expressed (DE) upon infection with&#160;pathogens (e.g., influenza and coronaviruses), suggesting a role for circRNAs in regulating host innate immune responses. However, investigations on the role of circRNAs during pathogenic infections are limited by the knowledge and skills required to carry out the necessary bioinformatic analysis to identify DE circRNAs from RNA sequencing (RNA-seq) data. Bioinformatics prediction and identification of circRNAs is crucial before any verification, and functional studies using costly and time-consuming wet-lab techniques. To solve this issue, a step-by-step protocol of in silico prediction and characterization of circRNAs using RNA-seq data is provided in this manuscript. The protocol can be divided into four steps: 1) Prediction and quantification of DE circRNAs via the CIRIquant pipeline; 2) Annotation via circBase and characterization of DE circRNAs; 3) CircRNA-miRNA interaction prediction through Circr pipeline; 4) functional enrichment analysis of circRNA parental genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). This pipeline will be useful in driving future in vitro and in vivo research to further unravel the role of circRNAs in host-pathogen interactions.

In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions

The protocol submitted here explains the complete in silico pipeline needed to predict and functionally characterize circRNAs from RNA-sequencing transcriptome data studying host-pathogen interactions.

Circular RNAs (circRNAs) are a class of non-coding RNAs that are formed via back-splicing. These circRNAs are predominantly studied for their roles as ...

Quantification of Circular RNAs Using Digital Droplet PCR

Summary

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