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The Significance of Early Ct’s - Ask TaqMan #35

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  • The Significance of Early Ct’s - Ask TaqMan #35

    3:38

    Ask your question at

    Are you new to qPCR? Have you ever wondered what this whole ‘Ct’ thing means? Why is it important? And why is early Ct’s better?

    To answer these questions, we need to first understand what happens in a qPCR experiment. qPCR stands for quantitative Polymerase Chain Reaction. In a qPCR, DNA amplification is measured in real time by the fluorescent dye signals.

    Let’s take a look at our lab book.

    The increase in dye signal is in direct proportion to the number of PCR products. By collecting this fluorescent signal - during the exponential phase of the reaction - we are able to obtain quantitative information on the starting amount of the DNA target.

    Here’s how. Let’s examine this representative qPCR amplification plot. A threshold line is drawn through the plot in the exponential phase of the curve. Reagents are plentiful during this phase, and thus there is an exact doubling of the target. From this intersection, we can now drop down to the x-axis and assign a Ct value to this amplification reaction.

    Okay, so now we’ve got a Ct value, but what does it mean? And why is smaller better?

    The Ct value, or threshold cycle, is the cycle number at which the fluorescent signal of the reaction crosses the threshold. The Ct value is inversely related to the starting amount of our target DNA. For example, if I have two samples, one with 200 ng of cDNA and the other with 25 ng of cDNA, I will get an earlier, or smaller, Ct value with the first one. This is because it will take fewer PCR cycles for the fluorescent signal to rise above background for the first sample. The second sample, since it is starting from less template (only 1/8 as much!) will take more cycles to reach the same level of detectable fluorescence.

    So here’s the take home message: as the amount of DNA template decreases, the Ct value will increase. If the Ct value gets too high, say a Ct of 35 in a 96 well plate, it can be difficult to distinguish real signal from background. For this reason, many researchers will employ a Ct cutoff - and not use any data above that Ct value.

    Researchers who want to optimize their systems will often look to the raw Ct values to compare whether a reagent results in better performance or not. Let’s say for example, you ran the same samples and assay with 2 different master mixes. A mix that results in earlier Ct’s is therefore beneficial because you will not need to use as much sample for the same level of detection. This can be especially important when dealing with limited or precious samples.

    If you’ve got more qPCR or digital PCR questions, remember, just ask Taqman.

    Submit your question at thermofisher.com/ask and subscribe to our channel to see more videos like this.

    I’ll see you next time.

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  • Baselines in Real-Time PCR -- Ask TaqMan®: Ep. 5

    4:10

    Submit your Real-Time PCR questions and watch the rest of our videos at Life Technologies Sr. Field Application Specialist Doug Rains helps with the understanding of baselines in Real-Time PCR. We're looking at a fairly standard real-time amplification plot. We have some nice curves, each of which has the familiar geometric phase, linear phase, and plateau phase. So far, so good. But what's all this . . . junk in the early cycles? Well, friends, if you said junk, you were right. That's right, I said it -- junk, trash, waste, detritus, garbage, otherwise known as noise.
    It's the stuff we see before our actual signal from amplification gets high enough to overcome that noise. And, as the rather impolite adjectives I used a second ago would suggest, it's completely useless to us. This noise does have an effect on our curves. Our job is to minimize that effect by effectively subtracting out the noise. We do that by establishing what's known as a baseline -- a cycle-to-cycle range over which only noise can be seen, prior to the appearance of curves. Once established, the software will effectively subtract out the noise on a well-by-well basis, greatly improving the quality of our data.
    Let's switch the Y-axis to linear scale for a moment to illustrate the effect of baseline subtraction. Here's our data prior to baselining. Note how every sample begins from a slightly different spot on the Y-axis, causing our geometric phase data— this curvy part over here when we're in a linear scale— to look horrible. But once we subtract noise, every sample begins from the same point 0. And as a result, the data clean up nicely.
    The value we get after normalizing for background noise is something called delta-Rn. If you ever look closely at a log-scale amplification curve— the one we're used to seeing— you'll notice that delta-Rn is what's graphed on the Y-axis.
    But before you go, just note that there are two ways to set baselines in Applied Biosystems® real-time PCR software: manually, and automatically. If you do it the manual way, you set the baseline range under Analysis Settings. You either set it for a single assay, in which case all wells for that assay get the same subtraction . . . or you can go under Advanced Settings and set wells individually.
    Better yet, just use the default setting of Auto Baselining. With this selected, the software figures out how much noise needs to be subtracted from each well individually, and, as such, generally produces the best results.
    So why have a manual feature? Well, Auto does fail on occasion, especially with some SYBR® Assays and non-standard chemistries. You'll know auto has malfunctioned by the shapes of your curves. If they look more S-shaped than they should, it could be that auto has misapplied the baseline and set the End cycle too low. As a result, not enough noise is being subtracted, and the curves take on a strange shape. To fix the problem, switch over to manual mode for that assay and raise the End cycle until the curves take on a regular shape.

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  • Analyzing Quantitative PCR Data

    3:25

    Relative and absolute methods of qPCR analysis. Created for an assignment for BIOC3001: Molecular Biology at the University of Western Australia.
    ****SCRIPT**** [I know it's a bit fast]
    qPCR or quantitative real-time PCR…
    ….is simply classic PCR monitored using fluorescent dyes or probes.
    qPCR is accurate, reliable and extremely sensitive, it can even detect a SINGLE copy of a specific transcript.

    qPCR is commonly coupled to reverse transcription to measure gene expression.

    No wonder it is so important for molecular diagnostics, life sciences, agriculture, and medicine.

    Firstly, let's go over the NUTS and BOLTS of qPCR. For this you use a fluorescent dye which binds to the DNA. As qPCR progresses, the fluorescent signal increases.
    Ideally the signal should double with every cycle, which is then plotted.
    Because there are few template strands to start with, initially there’s a faint signal.

    Eventually, usually after 15 cycles, the signal rises above the background noise and can be detected. We call this the THRESHOLD CYCLE, Ct, the point from which all quantitative data analysis begins.

    But how do you analyse qPCR data?

    You can either use an absolute quantification method, with a standard curve, OR a relative method, using one or more reference genes to standardize and compare the differences in Ct values between two treatments.

    The absolute standard curve method determines ORIGINAL DNA concentration by comparing the Ct value of the sample of interest with a standard curve.
    To create the standard curve, you need to make DNA samples of different KNOWN concentrations.
    After doing PCR on these, you will see different PCR plots for each standard …..

    and unsurprisingly they have different Ct values. The GREATER the concentration of the original DNA sample, the SMALLER the Ct value.
    So if you plot ORIGINAL DNA concentration against the Ct values. You will have a standard curve like this…..

    Now let’s say the PCR plot of your unknown DNA sample is somewhere here…..
    ...which corresponds to this Ct value on the standard curve here….

    Using the standard curve you can figure out the log concentration of your DNA sample to be x.
    As this is in log scale, you can simply calculate your sample DNA concentration to be 10 to the power of x.
    Absolute analysis is suitable when you want to determine the ACTUAL transcript copy number, that is the level of gene expression.

    On the other hand, Relative quantification is used when you want to COMPARE the difference in gene expression BETWEEN two treatments, for example light or dark treated Arabadopsis thaliana.

    This is done using one or more reference genes, such as actin, which are expressed at the SAME level for both treatments.
    You then perform qPCR on both your samples and the reference genes, find out the DIFFERENCE between the two Cts values, delta Ct, in EACH treatment.
    Now the RATIO of the two delta Cts …[pause a bit] . tells you how much gene expression has changed.

    For instance, in the dark treatment, the Ct value of your reference gene is at THIS level, the Ct value of your target gene is THIS Level. So you have this delta Ct which is the difference in Cts in the first treatment.

    in the dark treatment, the Ct value of your reference gene is STILL at THIS level, but the Ct value of your target gene may become only this much.

    So the ratio of the two Ct values is..

    delta Ct(dark treatment) divided by delta Ct(light treament) equals one third

    ….showing the delta Ct has DECREASED by a factor of 3, which means that gene expression of the target gene is GREATER in the dark treated sample.

    This is how relative quantification using a reference gene helps detect change in the expression of your target gene.
    In conclusion, there are two ways to quantify transcripts using qPCR: absolute quantification using a standard curve, and relative quantification using a reference gene.

    The method used depends on whether you want to determine the ACTUAL number of transcripts or the RELATIVE change in gene expression.

  • The Purpose of ROX™ in Real-Time PCR -- Ask TaqMan®: Ep. 7

    3:30

    Submit your Real-Time PCR questions and watch the rest of our videos at Life Technologies Sr. Field Application Specialist Doug Rains helps with the understanding of ROX™ and its significance in Real-Time PCR. Much like FAM™, VIC®, and SYBR® Green, ROX™ is a fluorescent molecule that the real-time instrument can detect when it's present in the reactions. But unlike those other dyes, ROX™ is a passive dye—meaning, its fluorescent level doesn't change as a direct result of amplification. Within any real-time PCR system, there are several potential sources of well-to-well variability in the excitation of reporter molecule and the detection of signal from the reporter. These include ... uneven illumination, slight variations in the optics from well to well, and even differences in the amount of condensation. ROX™ normalizes for these and other sources of variability, and in the process, improves the precision of the data.
    Here's how it works. Say we're looking at two specific wells on my reaction plate. I pipet exactly the same amount of the same sample into each, then amplify in real-time. A short time later, we reach, oh, cycle 30. As at every cycle, the instrument will take a reading of my reporter dye. I expect those two readings to be identical, since I started with the same reaction components. Unfortunately, they're not, due to a system inconsistency between these two wells. Relatively speaking, these measurements are incorrect. Fortunately, we also have ROX™ in these same two wells, and, like the reporter, it's also being measured. And look— it's actually shadowing the reporter. In other words, the system inconsistency is affecting ROX™ to the same degree that it's affecting the reporter. Importantly, the instrument will collect these paired measurements in every well at every cycle, and then divide every reporter measurement by its corresponding ROX™ measurement at the end of the run. As a result, the precision of our data goes way up. By the way, the value that results is called Rn, which stands for normalized reporter.
    Two key points about ROX™: With a couple of specialized exceptions, the real-time master mixes from Life Technologies already contain optimized levels of ROX™ when they arrive at your door. So there's no need to add it. Second, the default in all Applied Biosystems® real-time PCR software is to look for and normalize to ROX™. This is important to know because if— for some reason— you decide to use a master mix that doesn't contain ROX™, you'll want to change the passive reference dye to None. Otherwise, the software will attempt to normalize to a dye that's not there.

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  • AriaMx: Analyzing a Quantitative PCR Experiment

    13:46

    The AriaMx Real-Time PCR System is a fully integrated quantitative PCR amplification, detection, and data analysis system. The system design combines a state-of-the-art thermal cycler, an advanced optical system with an LED excitation source, and complete data analysis software.

    Updated August 2016.

    More information at

  • Distiguishing Real Signal from Background Noise - Ask TaqMan #41

    3:41

    Are you stuck trying to distinguish real signal from background noise in your qPCR data?
    A common question about qPCR data is how to distinguish true signal from background noise. Today, we’re going to provide some useful tips on how to tell whether you are looking at real signal or background.
    Sometimes when you are running qPCR experiments, it can be difficult to distinguish real data from background signal, leaving you to wonder whether your data is real.
    Here are some parameters to check to determine whether you are looking at background or noise:
    First, make sure to run No Template controls to compare to your experimental samples. If your sample signal looks similar to your No Template Controls, it’s most likely background.
    Also, check your replicates. If the Ct value varies among the replicates (ex: 36,37,40), then it is likely not real signal.
    You can also do a reality check on your Ct values. In general, a single copy detection occurs by a Ct of 37 in a 20 uL qPCR reaction. Any signal seen later than this is not likely to be real amplification.
    Often, you can easily tell whether you are looking at true signal or noise by looking at your data in the instrument or cloud software. Here’s an example using the Thermo Fisher Cloud Design and Analysis Application. This well is questionable. If we change our plot to the linear view, we can see that this curve is actually flat, and no amplification is occurring. We can see this in the multicomponent view as well. This view shows the curves of each dye in the reaction at each cycle, and is very useful for troubleshooting. In this way, we can check the curves for exponential amplification, which indicates real signal, as opposed to a linear upward drift which can be probe degradation at the end of a run.
    We can even overlay the wells with our NTC samples, and see that there is not much difference. So we can be confident that those were wells do not represent real signal.
    Finally, you can also make sure the threshold is going through the exponential phase of the curve. For example, here you see that we have Ct values at 28 and 36, but the curve with the Ct value at 36 is from the plateau, not exponential phase of the curve, so this is not likely real signal.
    So, the next time you look at your qPCR data, try some of these useful tips to determine whether you are looking at true signal or background noise.
    If you have more questions on qPCR data analysis or any other qPCR questions, remember to Ask TaqMan and submit your questions on our website
    Thanks for watching!

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  • Endogenous Controls in qPCR - Ask TaqMan #24

    4:20

    Submit your question and we might make a video out of it:
    If you are studying gene expression by real-time PCR, then you are likely using relative quantitation or comparative Ct method. This method of analysis requires the use of an endogenous control, that is, a gene which does not change expression across different samples, treatments, or time points. This stable expression is required in order to provide a reliable basis for gene comparison. So, you may have asked yourself a question like the one we received from Wade Powell from Kenyon College, What's the best way to select a valid endogenous control for relative qPCR?

    To identify the best endogenous control, we need to find a gene that does not change expression across our different samples. Stable expression is defined as small variations, between 0-0.5 Cts, among the samples for the endogenous control gene.

    Keep in mind that a difference of one cycle equates to a twofold difference in initial template. Furthermore, a control with ∆CT values that vary over a two cycle range would have nearly a fourfold difference in expression levels! If we were to select a normalizer gene whose expression varied by two or four-fold between samples, then the final fold calculations would be in error by this same factor.

    Since there is no way to anticipate how a particular treatment or diseased state will affect gene expression, the only way to definitively identify the right control is to simply perform a qPCR run with your samples. You will need to choose some candidate genes and check their expression.

  • Understanding Reverse Transcriptase – Effects on Ct value

    2:38

    The reverse transcription step is one of the greatest sources of variation in RT-qPCR. With SuperScript IV reverse transcriptase, the Ct value can be reduced by as much as 8. This enzyme outperforms wild type reverse transcriptases with better sensitivity at lower target concentrations. And it shortens the reaction time to just 10 minutes.

  • Ct Values: How They Should be Assessed for SARS CoV 2

    6:14

    Professor Michael Mina, MD explains how the viral dynamics of SARS-CoV-2, the infectious window, and how Ct values (cycle threshold values) should be interpreted from PCR SARS CoV 2 testing. And how Ct values on a logarithmic scale can be misinterpreted.

    See the full interview with Professor Michael Mina, MD on rapid antigen testing for COVID 19 here:

    Michael Mina, MD, Ph.D. is an Assistant Professor of Epidemiology, Immunology, and Infectious Diseases at Harvard T. H. Chan School of Public Health. Dr. Mina is also a core member of the Center for Communicable Disease Dynamics (CCDD) and an Associate Medical Director in Clinical Microbiology (molecular diagnostics) in the Department of Pathology at Brigham and Women’s Hospital, Harvard Medical School
    Dr. Mina’s full bio:

    The volunteer-based rapid test advocacy website that Dr. Mina is the director of: (a great place to learn more about rapid antigen tests for COVID-19)

    Interviewer:

    Kyle Allred
    Physician Assistant
    MedCram.com Producer and Co-Founder
    Contact: customers@medcram.com



    THE MEDCRAM WEBSITE:

    MedCram is a leader in online medical education. Our videos are utilized by thousands of clinicians and medical schools, PA programs, NP, RN, RT, and other professional programs. We offer over 60 medical topics and 50 hours of category 1 CME / CEs for medical professionals. See new topics and more about ct value in COVID 19.

    Learn more:

    MedCram videos are for education and NOT intended to replace recommendations from your doctor.

    ----------------------
    In this video, Michael Mina, MD illustrates Ct Values (Cycle threshold values), Rapid antigen COVID tests (including the availability of an antigen test for COVID 19) vs. PCR tests for coronavirus.
    #COVID19 #SARSCoV2 #CtValues

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  • Fixing Software Setup Mistakes in Real-Time PCR -- Ask TaqMan®: Ep. 10

    3:40

    Submit your Real-Time PCR questions and watch the rest of our videos at Life Technologies Sr. Field Application Specialist Doug Rains offers advices for fixing common software set-up mistakes when performing Real-Time PCR. I'm showing you a completed run file. Let's say I made a lot more mistakes than you did while setting up my file: wrong sample names, wrong dyes, and, yes, even forgot to label some wells. As you can see, I'm in Analysis under the Experiment Menu. To fix things, I'm going to go up here and click Setup. In the Plate Setup window, you can see my list of targets and samples. If I originally entered information incorrectly, I can change it right here. Let's say it's something as simple as a sample name. I activate the offending box, type the new name, and hit Enter. I now go to my plate map, which I access by clicking this tab, and I find that the new sample name has been added to the appropriate wells automatically.
    Okay, let's go back to Define Targets and Samples. Now what if I assigned the wrong fluorescent label to one of my assays? This one says FAM, but it should say VIC. That mistake left unfixed will definitely cause some analysis issues. However, I can just use the Reporter pull-down menu and make the switch. When I now go back to Analysis and click the analyze button, my change gets applied. And of course, the data improve dramatically.
    How is this possible? It's possible because whenever the instrument takes readings, it does so through every filter set, regardless of your dye assignment. Thus, the raw data are always there in the file. Back to Setup, where we'll deal with the issue of missing well assignments. Row D is blank because somebody forgot to assign assays and samples. And so these wells yield no data. But if I simply make the assignments now like so then go back to Analysis and reanalyzed the data, curves for those wells will appear. So, what information can we change after the fact? Just about anything besides cycling conditions. That includes sample and Assay names, Tasks (such as which wells are standards), standard amounts, the passive reference dye, and plenty more. Not only that, every Life Technologies real-time PCR instrument gives you this leeway. So even if you're using an older instrument, that's okay. In fact, you can even change the experiment type on all of the newer Life Technologies platforms, So if you accidentally labeled your ddCt run as a standard curve experiment, you can change that.

  • Tips For Real-time PCR, Sequencing, and Digital PCR

    57

    Ask your question at

    Instead of watching cat videos and rap battles-- check out two video series from Thermo Fisher Scientific, AskTaqman for qPCR education and introducing, Seq It Out, covering all things sequencing.

    We’ll be covering things like: Which master mix do I use? Should I use Sanger or NGS for my sequencing needs? When should I use qPCR or digital PCR? What exactly is targeted sequencing? and more

    So join me, Mike, for Ask Taqman. And I’m Natalie, your host for Seq It Out

    We want to hear from you. If you have any sequencing questions or real time PCR just submit them at thermofisher.com/ask. And you never know, your question might be the next Ask Taqman or Seq It Out video.

  • Real-Time PCR Thresholds and Where to Place Them -- Ask TaqMan®: Ep. 6

    2:51

    Submit your Real-Time PCR questions and watch the rest of our videos at Life Technologies Sr. Field Application Specialist Doug Rains helps with the understanding of thresholds in Real-Time PCR. The threshold is a horizontal line in our amplification plot that can be moved up or down on the Y-axis. Its purpose? As we'll see in a minute, it tells the software where to take data. Of course, not all places on the Y-axis are equal. Some places we want to avoid. Specifically, we don't want to be too low, otherwise we get down into the noise. Conversely, if we go too high, we're in the linear or plateau phase of amplification, where data are less predictable. A happy spot? Some place where all of our curves are straight and parallel to one another.
    What we really want is to put the threshold wherever the precision of our replicates is highest. That's generally somewhere toward the middle of the geometric phase, or maybe slightly higher. In any case, with a really robust assay, hitting a bad spot is quite difficult. The default on all Applied Biosystems® real-time PCR software is Auto Threshold, meaning, the software sets thresholds for us the second we click Analyze. Notice that it sets a different threshold for each assay separately, which is good since not all assays have the same sweet spot. I could go switch any one or all of my thresholds to Manual mode, then move the line up or down with my mouse.
    Once the threshold is set and we click analyze, all the samples get their respective Ct values. Now, the attentive viewer might be tempted to ask: if the threshold can be moved up or down, doesn't that change the Cts? The answer is, Yes. But here's the thing: as long as we keep the threshold firmly within the geometric phase, the relative, or delta Ct between any two samples stays constant. This fact allows us to do things like calculate fold changes in expression from sample to sample, and to get quantity information from a standard curve.

  • How TaqMan Works -- Ask TaqMan® Ep. 13 by Life Technologies

    4:00

    Submit your real-time PCR questions at
    Just how does TaqMan work? Sr. Field Applications Specialist Doug Rains explores the specific mechanism by which TaqMan® achieves its unparalleled specificity and sensitivity. Around the world, researchers rely on TaqMan® for gene expression, SNP gentoyping , protein expression, pathogen detection and quantification, and more.
    For many years, TaqMan has been the gold-standard chemistry for real-time PCR. It's famed for its unparalleled specificity, sensitivity, and ease of use. So it's not surprising that users want to know what Shrikant at ICL College in India asked recently: namely, How does TaqMan work? I'm glad you asked.
    Just like any PCR, TaqMan-based reactions require a double-stranded template, as well as two fairly standard, target-specific primers. But unlike those used in regular PCR, TaqMan Assays require a third, sequence-specific oligo called a probe. TaqMan probes are quite different from the primers in two ways. First, they can't be extended by our friendly enzyme, Taq Polymerase, since they lack a free hydroxyl group.
    What's more, TaqMan probes are covalently joined to two other molecules. On the 5'-end, there's a fluorescent molecule known as the reporter -- called that because it reports signal to us as we generate more and more product. On the 3'-end is a molecule known as the quencher, which quenches the fluorescent signal from the reporter under certain circumstances. Let's see what those circumstances are.
    Here we're looking at an intact probe, with the reporter in green, the quencher in red. Normally, when we zap the probe with light, we expect the reporter to get excited and fluoresce. But because the quencher is in close proximity to the reporter, instead what happens is, the energy gets transferred from reporter to quencher. The transfer of energy is known as FRET, or Fluorescent Resonance Energy Transfer. The important thing to note here is that, as long as the probe remains intact, there is no permanent increase in fluorescent signal from the reporter.
    However, if the reporter and quencher are permanently separated during the reaction, and then light strikes the reaction, the Reporter does in fact fluoresce, producing signal the instrument can detect.
    The basic idea, then, is this: each time we create a new PCR amplicon, we want to permanently split the reporter and quencher. By doing so, florescence will always increase proportionally with product, allowing us to effectively monitor what's happening to our reactions throughout the run. Here it is in action.
    We begin our reactions (CLICK) by denaturing our template at a high temperature. As we lower the temperature, our probe and primers bind. Taq now comes in, finds the primers, and begins the extension phase of PCR by creating new complementary strands of DNA. But wait a second: there's a probe sitting in the way. It's a showdown in the making! What will the polymerase do? Stop in its tracks? Turn back in fear? Nay, friends, not Taq Polymerase. You see, our enzyme has what's referred to as exonuclease activity. Meaning? It pretty much eats DNA for lunch.
    So when Taq reaches the probe, it simply chews it to bits on its way to creating new amplicon. As a result, the reporter and quencher are physically separated, creating a permanent increase in fluorescence that, not coincidentally, perfectly accords with our doubling of product.
    And, of course, that our real-time instrument can monitor and record this increase in fluorescence after each cycle, generating an amplification plot that's more than a little useful for interpreting our data.

  • CT Value in RT-PCR: Lower Value - Higher Viral Load | Different from CT Score

    4:44

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    Short for cycle threshold, Ct is a value that emerges during RT-PCR tests, the gold standard for detection of the SARS-CoV-2 coronavirus. In an RT-PCR test, RNA is extracted from the swab collected from the patient. It is then converted into DNA, which is then amplified. Amplification refers to the process of creating multiple copies of the genetic material — in this case, DNA. This improves the ability of the test to detect the presence of virus. Amplification takes place through a series of cycles — one copy becomes two, two becomes four, and so on — and it is after multiple cycles that a detectable amount of virus is produced.

    Chapters:
    0:00 CT Value (Cycle Threshold) in RT-PCR
    1:21 Range for CT Value
    1:48 RT-PCR
    2:32 Cycle Threshold
    4:11 High and Low Viral Load
    #ctvalueinrtpcr #rangeforctvalue #rtpcr #cyclethreshold #highandlowviralload #examrace

  • How to Analyze Real-time PCR Data -- Ask TaqMan® Ep. 16 by Life Technologies

    3:52

    Submit your real-time PCR questions at
    In this video, Sr. Field Applications Specialist Doug Rains covers the various options that researchers have for performing final qPCR data calculations. Learn how to take advantage of Life Technologies' offerings of free external data analysis software, including DataAssist and ExpressionSuite.
    Welcome to AskTaqMan, where we answer your questions about real-time PCR. Here's an important question from Janaína at UFRGS in Brazil. She asks, How do I analyze my Real-Time PCR data? Well, there are in fact several options for analyzing data and generating final reports, depending on the particular application one is running. Let's address the most common qPCR experiment type: namely, gene expression.
    The first option is to have the instrument software perform calculations for you. In all of our most recent software versions, you have the option to set up new gene expression experiments by designating either comparative Ct or relative standard curve as your quantification method. You'll need to create at least 2 assay names -- one normalizer and one target -- and at least 2 sample names. You'll then assign these sample and assay names to the appropriate wells, making certain to identically label any wells representing pipetting replicates. If you're running the relative standard curve method, be sure to also label wells containing your dilution curve as standards, and to add standard amounts. There's a handy shortcut key that really helps set these up, by the way. Finally, tell the software which target on the plate is your normalizer gene and which sample you want to choose as the reference sample. - Most people choose the untreated sample, by the way.
    At the end of the run, simply go to either the Results or the Analysis tab, depending on your version, and to gene expression. If you labelled everything correctly, final fold change data will be generated for you at the end of the run and presented both in graphical and in tabular form. In the case of the latter, there's a column labelled RQ, or relative quantification, which is exactly the same as fold change.
    The instrument software has so many features for looking at your gene expression data that we just won't be able to go into too much detail in this video. So I suggest having a look at a copy of the Relative Quantification Getting Started Guide. It's available as a hard copy, as well as electronically online.
    And if you click on your software's Help menu, you'll even find a version right at your fingertips. But what about other options? In fact, Life Technologies offers two other exceptional tools for calculating gene expression data. Both are fre-standing packages that can be downloaded and used at no charge from the Life Technoligies website.
    Both DataAssist and Expression Suite offer intuitive workspaces and plenty of data crunching capabilities. Both can do multi-plate studies, calculate biological replicate fold change data, and present results in a variety of forms, including heat maps, volcano and scatter plots, and more.
    If you'd like to learn more about either of these packages, there are free video tutorials available on the web. Just go to learn.lifetechnologies.com, click on Gene Expression, and twirl down to the section on Web-Based training.

  • Troubleshooting qPCR - What are my amplification curves telling me?

    1:1:10

    Quantitative PCR (qPCR) is the method of choice for accurate estimation of gene expression. Part of its appeal for researchers comes from having a protocol that is easy to execute. However when your reactions do not result in ideal amplification, troubleshooting why can be challenging. Factors including sample quality, template quantity, master mix differences, assay design, and incorrect primer or probe resuspension can all influence efficient amplification. When troubleshooting, analysis of the appearance of your amplification curve can give you clues towards improving your results. This webinar will present a variety of problematic qPCR issues and how they are manifested in the amplification curve.

  • How to Measure PCR Efficiency of an Assay -- Ask TaqMan®: Ep. 4

    3:23

    Submit your Real-Time PCR questions and watch the rest of our videos at Life Technologies Sr. Field Application Specialist Doug Rains helps with the understanding of PCR efficiency and how to properly measure it in your assays. To check the efficiency of an assay, you need to run a template dilution curve in real-time, and then look at the resulting slope of that curve.
    That slope value -- assuming you prepare the curve properly -- tells you the efficiency. If the slope is a -3.3, then the assay is amplifying at or very near 100% -- exactly what we want in real-time PCR. But if that value is more negative -- say, -3.7 -- then the efficiency will be less than 100%. There's actually a formula into which you can plug this slope and get your numerical efficiency.
    Happily, with all newer AB instrument software, the efficiency calculation is actually done for you. Just go to Results  Standard Curve, and there it is. Now, here's the thing: I see a lot of cases where people make mistakes preparing their dilution curves, and as a result, calculate incorrect efficiencies. So what I want to do is give you TEN . . . suggestions on how to improve the accuracy of your dilution curves.
    #10: Use well-calibrated pipettemen
    #9: Serially dilute standard material
    #8: For AQ, always use an appropriate standard material
    #7: Mix standards thoroughly after each dilution
    #6: Pipette higher volumes for better precision
    #5: Run ≥ triplicates of each dilution point in real-time
    #4: Use minimum of 5 dilution points, 10-fold dilutions
    #3: After run, check R2 / look for outliers; omit.
    #2: If curve has more than 1 or 2 outliers, or if the spacing between points is irregular, repeat curve
    #1: Have more than one person run a curve the first time to check validity
    One good thing to note is that all the TaqMan® Assays Life Technologies sells are designed to work at or near 100% efficiency. In fact, we tested thousands of these and published the results in an application note entitled Amplification Efficiency of TaqMan® Gene Expression Assays. That document is available for download on the Life Technologies website.

  • CFX Manager™ Software Part 4: Doing Data Analysis

    4:55

    For more information, visit
    This brief tutorial walks through the various data analysis options in CFX Manager 3.1.

    Bio-Rad’s CFX Manager™ Software provides intuitive qPCR setup and rich data visualization tools to reduce confusion and anxiety while performing real-time PCR experiments.

    CFX Manager Software is included with al Bio-Rad CFX Real-Time PCR Detection Systems:
    • CFX96 Touch™ System
    • CFX96 Touch™ Deep Well System
    • CFX384 Touch™ System
    • CFX Connect™ System

    Features and Benefits:
    • One-click experimental setup and data analysis with the Startup Wizard
    • Easily customized data analysis and export preferences
    • Application-specific data analysis for gene expression and SNP genotyping studies
    • Graphical data representation helps you quickly interpret and understand your data



    We Are Bio-Rad.

    Our mission: To provide useful, high-quality products and services that advance scientific discovery and improve healthcare. At Bio-Rad, we are united behind this effort. These two objectives are the driving force behind every decision we make, from developing innovative ideas to building global solutions that help solve our customers' greatest challenges.

    Connect with Bio-Rad Online:
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  • Getting Reliable Data in qPCR - Ask TaqMan #22

    3:57

    Submit your question:
    At the end of the day you want to be able to write up your results and know the changes you see are real -- and not the result of handling or pipeting error. This prompted our next question from Anessh Chandran from the Rajiv Gandhi center for biotechnology, who asked What is the best method to ensure reliable and reproducible data?

    Let's begin with our experimental plan. For instance, how many replicates do we really need to do? No one wants to use up any more reagents than necessary. To keep reagents at a minimum, while still being able to catch any errors in pipeting, we recommend running triplicates. Let's look at an example to show why.

    Here is a set of replicates for our target. The Ct values are 20, 19, and 37. Hmm...looks like maybe I forgot to add sample to this well. But that is not a problem. With triplicates, we can clearly say that the Ct value of 37 is an outlier and should be removed. I simply click to omit, update my data by clicking Analyze again, and viola! I can move on and still use this data point for the sample. But let's look at another example, what if I only ran duplicates? Now I have two samples with Cts of 22 and 31. Hmm..that's a lot of variation in a replicate. I don't really want to average them, but I don't have any justification to use one over the other either. Now I am forced to omit the entire sample from my data

    So, now we've seen why triplicates are a good practice, but do note that there are cases in which replicates would not be required -- such as large screening projects. In these studies, many targets are tested at once to find significant hits, and those targets are later validated with more scrutiny... and more replicates!

    So how do we ensure that our triplicates are tight? Ideally the deviation among replicates is less than 0.5 Ct. Let's go through some recommendations on the best practices for tight replicates:.

  • What is RT PCR COVID Test | CT Value in RT PCR Technique | Pulse Oximeter Working | COVID Recovery?

    28:16

    What is RT PCR COVID Test | What is CT Value in RT PCR Technique | How To Use Pulse Oximeter and Pulse Oximeter Working | COVID Recovery? | How To Recover From Corona

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  • x
  • Real Time PCR Analysis qPCR Terms

    9:26




    Real Time PCR differs from the conventional PCR/ End point PCR is that in real time PCR both amplification and quantification of the target DNA molecule is possible.

    In real time PCR the amplified DNA is detected in real time, where as in convention PCR detection is possible only at the end of PCR by performing agarose gel electrophoresis for the PCR product.



    Related Videos:
    --------------------------------------------------------------------------------------
    Plotting Bacterial Growth Curve:
    Colony Forming Units:
    Serial Dilution Methods:
    Copy Number Calculation for qPCR:
    How to analyze Primer Sequence or Oligonucleotide sequence designed for PCR / qPCR:
    How to generate qPCR standard curve in excel and calculate PCR efficiency:
    Real Time qPCR optimization, Calculating PCR Efficiency:
    Taqman Assay Vs SYBR Green Assay:
    Resolving poor PCR efficiency:

  • 3) Polymerase Chain Reaction

    8:24

    What is Quantitative PCR (qPCR)?
    ➜ Real-Time PCR or quantitative PCR (qPCR) is a PCR-based technique that is able to simultaneously amplify and detect changes in the amplicon concentration. Real-time PCR collects data during PCR amplification by utilizing fluorescence signals emitted by either special probes or DNA binding dyes.

    For more information on qPCR and for a list of the sources used, please visit:
    ➜ Knowledge Base:

    **Please note that the labels of 5’ and 3’ are flipped at 4:35 – 5:22. Usually R (reporter) is at the 5' end and Q (quencher) is at the 3' end, and thus the top strand bound by the Taqman Probe should be labelled as 3’ on the left, and 5’ on the right. Vice versa for the bottom strand: this should be labelled as 5’ on the left, and 3’ on the right. Please refer to Figure 3 of our knowledge base: We apologize for the confusion and thank our youtube community for pointing out the error.

    Thank you to all of the amazing community contributions towards translating this video into other languages including:
    ➜ Indonesian
    (To view the translations, toggle the CC button and then go to Settings ➜ Subtitles/CC to select a language.)

    Check out our other video series:
    ➜ Polymerase Chain Reaction (PCR) - An Introduction:
    ➜ CRISPR Cas9:
    ➜ Adeno Associated Virus:
    ➜ Cell Culture:

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  • Dr Steve Hawkins Clinic episode One: limit of detection in qPCR

    1:59

    Hint's Tips & Tricks

    In this two-minute episode, Dr Hawkins delivers a few hints, tips and tricks for limit of detection in qPCR.

    The easiest way of determining sensitivity is to determine the LOD aka LOQ.

    Basic principle: When you run a qPCR and you get a curve this would mean you have 10-fold less DNA, the curve moves to the right and you get a lower Ct value. You do this again and it goes further to the right. The distance between the curves with a 10-fold dilution should be 3.32 Cts.

    Steve explains in more detail throughout this video.


    Subscribe and lookout for more episodes from Dr Hawkins clinic for more hints, tips and tricks.

    Bioline Reagents

  • Real Time PCR Controls

    5:33




    Real Time PCR differs from the conventional PCR/ End point PCR is that in real time PCR both amplification and quantification of the target DNA molecule is possible.

    In real time PCR the amplified DNA is detected in real time, where as in convention PCR detection is possible only at the end of PCR by performing agarose gel electrophoresis for the PCR product.



    Related Videos:
    --------------------------------------------------------------------------------------
    Plotting Bacterial Growth Curve:
    Colony Forming Units:
    Serial Dilution Methods:
    Copy Number Calculation for qPCR:
    How to analyze Primer Sequence or Oligonucleotide sequence designed for PCR / qPCR:
    How to generate qPCR standard curve in excel and calculate PCR efficiency:
    Real Time qPCR optimization, Calculating PCR Efficiency:
    Taqman Assay Vs SYBR Green Assay:
    Resolving poor PCR efficiency:

  • Ct value in RT-PCR

    6:10

    RT-PCR ????????
    Dr Mohanapriya Michael uploads dental lectures which would be help for dental students all over the world and also does MCQ Discussions, textbook discussion for people appearing for competitive dental examinations ????????????

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  • Troubleshooting qPCR

    45:48

    What are my amplification curves telling me? This presentation was given by Dr Aurita Menezes, qPCR Product Manager at IDT, on April 15th, 2014 at the qPCR Workshop at the University of Iowa BioVentures Center.

  • Phases of Real-Time PCR and Why Theyre Important – Ask TaqMan® Ep. 9

    3:34

    Submit your Real-Time PCR questions and watch the rest of our videos at Life Technologies Sr. Field Application Specialist Doug Rains helps with the understanding of the different phases Real-Time PCR and why they're important. PCR does in fact have phases. But it's normally difficult to see PCR's phases in action. That said, once we do real-time PCR, we can easily visualize its phases. Fortunately, real-time is where PCR phases really matter. When we first start our reactions, there's a molar excess of all the reagents needed for amplification. As a result, we typically get a nice doubling of product with each cycle. In an amplification plot set to log scale, we see that exponential increase in product manifests itself as a straight line. This phase is known variously as the geometric, log, or exponential phase. Unfortunately, this doubling doesn't go on forever. At some point, the reagents in the tube— primers, dNTPs, and so on— start to run low. As a result, the reaction slows down. We call this the linear phase.
    Finally, after some point, assuming the plate is run for enough cycles, the reactions run out of some critical ingredient. As a result, the reactions come to a halt. We call this the plateau phase. So why do we care? Because only one phase yields high-quality quantitative data: namely? You guessed it— the geometric phase. To see why, let's look at an example file.
    In this run, I took a highly concentrated sample and serially diluted in 10-fold increments over 7 logs. I also ran eight technical replicates for each dilution point. What I want you to notice is this: in the geometric phase, which is approximately the area inside the box, all of my dilutions are very evenly spaced, exactly as I would expect. Also, my pipetting replicates are very tight, meaning I have excellent precision. But as we move into the later cycles—the so-called linear phase— that predictability starts to go away. My nice, straight lines begin to curve, messing up my even spacing. And my precision drops off considerably. Finally, in the later or plateau cycles, my data all merge together. The point is we always want to look at our data in the geometric phase, since this is where we'll get the best results, especially for a quantitative reaction. How do we do that? By making sure that's where the threshold is set.

  • What does CT-value signify?

    3:40

    The cycle thresholds (CT values) in the (corona) PCR Test are confusing.
    An entertaining comparison will show you what actually happens during the test.
    With this knowledge you can finally relax and smile :-)

    Download the film file to post and share it yourself:

    Nevertheless, keep your own immune system in good condition at all times. I will show you how on: (in German only)

    Original Film in German:
    Link for download:

    The link on the last picture: goes to

  • LlaveDeAbrirCanecas

    1:06

  • Over 100% Assay Efficiency in qPCR? Not so fast. -- Ask TaqMan #21

    5:59

    Submit your question:
    In another Ask TaqMan video, we discussed assay efficiency and how to calculate it. But how does efficiency really impact our experiments, or as Julie Kase at George Washington University asks, why is it important? Does the efficiency for all of my targets have to be the same? The aim for all assays is to be 100% efficient, which means there is an exact doubling of your template every cycle.

    We previously found that this can be calculated thru a dilution series and the following equation. In order to use the ΔΔCT method for relative quantitation, the efficiency of the target and endogenous control must be approximately equal -- meaning that the assay efficiency should be within 10% of each other, so 100% +/- 10%. If the range is greater than 10%, then you need to be aware that when you evaluate fold changes, the unequal PCR efficiencies will correlate to a decrease in the accuracy of the calculated fold change.

    Keep in mind that Life Technologies has well over one million pre-developed Assays, which have been in-silico validated to be up to 100% efficient, so the efficiency calculation is not necessary. However, If you do check, and find the efficiency is outside of the acceptable range, then there is likely something from the sample or setup that is throwing things off.

    So what happens if my efficiency is say, 150%? Your first thought might be, Wow, my assay rocks! That's good, right? Well, actually no. It is not possible to be over 100% efficient, so something else is going on here. Let's review some causes of high or low efficiency, and how to fix them.

    First, let's take a look at what's going on with efficiency over 100%. The most common cause of efficiencies greater than 100% are inhibitors. This can be carryover from the sample itself such as heparin or humic acids. Or another source could be contaminants from the RNA or DNA isolation such as SDS or phenol.

  • Ask TaqMan ®: Ep. 2 Real-Time PCR Assay 디자인을 위한 팁

    3:28

    Real-Time PCR에 대한 사용자 여러분의 질문을 등록하시면 라이프 테크놀로지스의Sr. Field Application Specialist인 Doug Rains이 도와드립니다.

    [Script]
    안녕하세요. 라이프테크놀로지스의 더그입니다. 이번 'TaqMan에게 물어봐'에서는 분석 설계에 대해 말씀 드리겠습니다.
    겔 기반 PCR을 수 년간 사용하고 수 백 개의 프라이머 세트를 만들어봤지만 실시간 PCR은 사용해 보지 않은 사람들이 많이 하는 질문입니다. 여러분도 스스로에게 물어봤을 수 있습니다. 뭔가 특별한 게 필요한가?
    우선 실시간 PCR에서는 앰플리콘의 크기가 매우 중요합니다. 산물의 크기가 너무 크면 PCR 의 효율이 떨어질 수 있습니다. 염기 길이를 50bp에서 150bp 사이로 유지해야 합니다.
    둘째, 정량 분석에서 중요한 사항인데 올리고를 미스매치나 다형 부위에 디자인하지 마십시오. PCR 주기를 몇 번 지나지 않아 결합 효율이 떨어지고 Ct가 오른쪽으로 치우치게 됩니다. 대신 항상 시퀀스가 올바른지 확인해야 합니다.
    셋째, 고유하지 않은 시퀀스에 디자인할 때는 신중해야 합니다. 특히 거의 비슷한 동족체에 주의하세요. 일부라도 같은 영역이 있으면 잘못된 신호가 나타나게 됩니다. 적어도 하나의 올리고를 고유한 영역에 설계하여 원치않는 신호가 나오지 않게 합니다.
    마지막으로 게놈이나 전사체에서 전혀 고유하지 않은 반복 영역을 포함해 복잡성이 낮은 시퀀스에 올리고를 디자인하지 마십시오.
    지금 말씀드린 모든 기준에 부합하는 분석을 할 수 있는 방법은 많습니다. 그 중 하나는 물론 컨텍스트 시퀀스에서 모든 바이오인포매틱스 작업을 하고 Primer Express Software 같은 프로그램을 사용해 분석을 디자인하는 것입니다. 또 개별 올리고를 주문해야지요. Primer Express Software의 장점 중 하나는 보편적인 사이클링 조건에서 사용할 수 있는 올리고 세트를 디자인한다는 것입니다. 즉 실시간 PCR 조건을 최적화할 필요가 없습니다. 매우 편리하지요. 편리한 걸 원한다면 우수한 품질의TaqMan® Assay을 편리하게 구할 수 있는 두 가지 방법이 있습니다. 라이프테크놀로지스의 맞춤형 서비스를 이용해서 원하는 디자인을 구하거나 디자인되어 있는 Assay를 구입하는 것이지요. 어느 쪽이든 바이오인포매틱스 작업에 문제 없이 어떤 조건에서도 작업을 할 수 있으며 효율을 100% 높일 수 있습니다. 좋은 것 뿐이지요? 이미 개발되어있는 TaqMan Assay를 유전자 발현에 이용하고자 한다면 정말 많은 종에 적용할 수 있는 제품이 있습니다.
    시청해 주셔서 감사합니다. 실시간 PCR에 대해 질문이 있으시면 트위터, 페이스북,라이프테크놀로지스 홈페이지LifeTechnologies.com/askTaqMan으로 TaqMan에게 물어보세요.

  • COVID-19 Laboratory Test.

    1:56

  • qPCR Assay Design Prep - Ask TaqMan #36

    3:36

    Ask your question at

    It’s easy to design a custom TaqMan single nucleotide polymorphism or SNP Assay using the tools online, but we often get users asking us, “Do we need to do anything to our target sequence before submitting it into the Custom TaqMan Assay Design Tool?”

    Great question! Let’s find out.
    You can definitely analyze and mask your target sequence to improve the likelihood of obtaining a highly-specific and well performing assay design. We call this “preparing your target sequence.” You should always prepare your target before entering it into the Custom TaqMan Assay Design Tool, which is the tool that designs the SNP assay itself.

    Let’s take a look at our lab book.

    First, we recommend masking non-target SNPs in the sequence that you are submitting. Masking is the process of substituting an “N” for an existing base. The custom SNP assay design pipeline will not design a primer or probe that spans a masked base. The pipeline will move upstream or downstream to another area of the sequence for assay design. Why is it important to avoid designing an assay over a SNP that is not your intended target? Assays that have probes or primers overlapping a SNP will have inefficient hybridization when the polymorphism is present, potentially producing an inaccurate genotyping call. We definitely want to avoid that!
    The other important thing to mask in your target sequence is repeats. Repeats are patterns of DNA sequence that occur in multiple copies throughout the genome. Why do we want to avoid designing to non-unique regions of the genome? Assays that are designed in regions that contain repeats are likely to produce non-specific amplification. Remember, we want our assay to detect our SNP in our unique region of the genome- not bind to other areas of the genome!
    The last step in preparing your genome is checking whether your target sequence is unique in your organism of study. We call this “genome QC”. Using public databases and tools, such as UCSC BLAT or NCBI BLAST, you can check whether there are any regions of your target sequence that are similar to sequences in the reference database for that particular organism. If you find any sequences that are similar, you should mask those regions with Ns. This will ensure that your assay is only detecting your target region containing your SNP of interest. You do not want to detect other regions in the genome.


    Thanks for asking TaqMan about target sequence preparation! By properly preparing your target sequence, you can enhance the quality of your custom TaqMan SNP assay performance.
    If you’ve got more qPCR or digital PCR questions, remember, just ask Taqman.
    Submit your question at and subscribe to our channel to see more videos like this.

    I’ll see you next time.

  • Do TaqMan® Assays Comply with MIQE Guidelines? -- Ask TaqMan® Ep. 19 by Life Technologies

    3:44

    Submit your real-time PCR questions at
    After introducing MIQE guidelines, a set of standards for producing and publishing qPCR data, Sr. Field Applications Specialist Doug Rains explains how Life Technologies' large and diverse collection of TaqMan® assays comply with these guidelines. Learn about Life Technologies' TaqMan assays guarantee program and the rigorous bioinformatics process through which each TaqMan® assays is designed.
    Welcome to Ask TaqMan, where we answer your questions about real-time PCR. A concern among some researchers in the qPCR community is ensuring that experimental designs and data reporting practices meet the standards set out by MIQE Guidelines. Specifically, users often wonder whether or not Life Technologies' pre-developed TaqMan Assays comply with MIQE's set of recommendations. I'm here today to tell you that they do, and to explain how Life Technologies qPCR assays can help you to achieve the highest level of confidence in your data.
    MIQE, which stands for Minimum Information for Publication of Quantitative Real-Time PCR Experiments, is a set of guidelines originally published in 2009, then revised slightly in 2011. The authors behind MIQE propose guidelines for all aspects of qPCR experimental design and analysis, as well as standards for sharing this information with colleagues.
    So how do Life Tech's pre-developed qPCR Assays help labs fulfill MIQE recommendations with respect to design and information sharing? I'm glad you ask.
    As explained both in the Life Technologies TaqMan Assays Guarantee Program white paper, all of Life Tech's million-plus qPCR assays are designed using an advanced bioinformatics pipeline that ensures maximum amplification efficiency, standardized running conditions requiring no optimization, and -- perhaps most importantly -- target specificity. During the design process, high-quality RefSeq context sequences are subjected to rigorous bioinformatic scrutiny using long-established design algorithms. This process produces gene-centric assays that won't amplify pseudogenes and homologues, while simultaneously avoiding known polymorphic sites and low-complexity sequences. What's more, Life technologies performs regular remapping based on revisions to the NCBI databases, helping ensure that assays and their associated information remain current.
    When researchers search for an assay on our website, they can peruse a host of helpful information, including the NCBI gene ID, the gene symbol, a list of RefSeq IDs that are interrogated by that assay, and RNA accession numbers. And while we don't share the specific oligo sequences, we provide the context sequence, the probe location, and -- if appropriate -- the exon-exon boundary that the assay crosses. Finally, users can consult an a map showing how all assays for a given gene line up with all know transcripts.
    In short, Life Technologies provides all information necessary for choosing just the right assay to meet experimental needs, and for meeting the requirements set out by MIQE. And best of all, TaqMan Assays have been offered for many years now, with well over 5000 publications citing their use.
    If you'd like to learn more about searching for and selecting a TaqMan Assay that will suit your needs, please have a look at the Ask TaqMan video on this very topic.

  • Dr Christie Massen Lab FAQs - CT values

    2:18

    You had questions about cycle threshold (CT) values when it comes to the processing COVID-19 tests... and Dr. Christie Massen, NDDoH Chief Laboratory Officer, has answers in the first edition of COVID-19 Lab Testing FAQs!

  • Ct value in your COVID-19 test? Why so important? What is it? Severe COVID-19? Isolation,Second wave

    3:31

    Many doctors are now telling patients that their Covid-19 test reports should mention the cycle threshold (Ct) value, and not just the positive or negative outcome.

    Ct value indicates the number of cycles needed in the RT-PCR test to amplify viral RNA, so it can reach a detectable level. A lower Ct value, 20 or below, is a sign of high viral load. Apart from ascertaining the severity of symptoms, doctors are also using Ct value to suggest home isolation or hospital admission to patients.


    This video will explain everything you must know about Ct value and how one must address it.

    #covid19 #vaccine #moderna #pfizer
    #sputnik #astrazeneca #mRNA #corona

    00:42 - What is Ct value in your COVID-19
    test report

    00:52 - How is Ct values measured

    01:54 - Understanding with an example

    02:11 - COVID-19 Report analysis

    02:26 - Why you shouldn't panic with your Ct scores

    02:45 - Avoiding false sense of security

    03:03 - How can Ct values turn significant

    || THANK YOU ||

    My Instagram handle:

  • Taqman PCR

    9:26

    For more information, log on to-

    Download the study materials here-

    The polymerase chain reaction (PCR) is a biochemical technology in molecular biology to amplify a single or a few copies of a piece of DNA across several orders of magnitude, generating thousands to millions of copies of a particular DNA sequence.

    Developed in 1983 by Kary Mullis,[1][2] PCR is now a common and often indispensable technique used in medical and biological research labs for a variety of applications.[3][4] These include DNA cloning for sequencing, DNA-based phylogeny, or functional analysis of genes; the diagnosis of hereditary diseases; the identification of genetic fingerprints (used in forensic sciences and paternity testing); and the detection and diagnosis of infectious diseases. In 1993, Mullis was awarded the Nobel Prize in Chemistry along with Michael Smith for his work on PCR.[5]

    The method relies on thermal cycling, consisting of cycles of repeated heating and cooling of the reaction for DNA melting and enzymatic replication of the DNA. Primers (short DNA fragments) containing sequences complementary to the target region along with a DNA polymerase (after which the method is named) are key components to enable selective and repeated amplification. As PCR progresses, the DNA generated is itself used as a template for replication, setting in motion a chain reaction in which the DNA template is exponentially amplified. PCR can be extensively modified to perform a wide array of genetic manipulations.

    Almost all PCR applications employ a heat-stable DNA polymerase, such as Taq polymerase, an enzyme originally isolated from the bacterium Thermus aquaticus. This DNA polymerase enzymatically assembles a new DNA strand from DNA building-blocks, the nucleotides, by using single-stranded DNA as a template and DNA oligonucleotides (also called DNA primers), which are required for initiation of DNA synthesis. The vast majority of PCR methods use thermal cycling, i.e., alternately heating and cooling the PCR sample through a defined series of temperature steps. In the first step, the two strands of the DNA double helix are physically separated at a high temperature in a process called DNA melting. In the second step, the temperature is lowered and the two DNA strands become templates for DNA polymerase to selectively amplify the target DNA. The selectivity of PCR results from the use of primers that are complementary to the DNA region targeted for amplification under specific thermal cycling conditions. Source of the article published in description is Wikipedia. I am sharing their material. © by original content developers of Wikipedia.
    Link- Animation source: University of Nebraska. Copyright 2000. All the credit goes to the original content developer.
    Link:

  • RT PCR test for Covid 19| what is ct value?

    6:14

    This Video lecture of BiologyExplained talks in detail about what is ct value in Covid Test.
    To understand what is ct value one has to perform RT PCR, which in case of Covid means Real Time Reverse Transcription Polymerase
    Chain reaction. Polymerase chain reaction is a process of amplification of small amount of DNA to a large amount. And it is done
    with the help of an enzyme DNA polymerase. Reverse Transcription is the process by which cDNA is made from RNA.
    And real time means we are observing the values instantly as the reaction is going. Ct value in case of RT PCR means
    cycle threshold value that is at what cycle the DNA amount becomes detectable. If the Viral DNA (Sars-CoV2 Virus has RNA which is
    converted to DNA by reverse transcription) is detectable before cycle 35 that is if ct value is below 35 then one is Covid positive.
    Lesser the ct value more is the viral load. That means if a person have ct value of 17 he/she is positive. Again if a person has
    ct value of 25, then also he/she is positive. But the person with lower ct value has higher viral load.
    However please remember ct value indicates infectivity of the disease and not severity.
    LINK for English version:
    LINK for Bangla version:

    Time strap: English
    00:00 Introduction
    00:33 What is RT PCR
    03:30 What is ct value
    04:49 ct value and Covid 19

    #ctValue #RTPCR #COVID #BiologyExpalained

  • Presence/Absence Ct Threshold for Thermo Fisher Cloud

    1:38

    This video explains the new Ct threshold functionality for Presence/Absence detection in the PA application module on Thermo Fisher Cloud.

  • Testing for COVID-19 Infectivity

    34:58

    How can we determine whether someone who has COVID-19 can transmit the virus to other people? Tests in routine clinical use, such as reverse-transcription polymerase chain reaction and antigen tests, are designed to determine whether SARS-CoV-2 is present or not, but many people have proposed that these tests be used to determine whether a patient is infectious. Furthermore, tests for SARS-CoV-2 that are not routinely used in clinical laboratories, such as viral culture and detection of sub-genomic viral RNAs, have also been discussed as indicators of infectivity. But how accurate are any of these tests for determining whether someone is infectious?

    Guest:

    Dr. Matthew Binnicker, Director of Clinical Virology and Professor of Laboratory Medicine and Pathology at Mayo Clinic. Twitter: @DrMattBinnicker

    Links:
    Can Testing Predict SARS-CoV-2 Infectivity? The Potential for Certain Methods to be a Surrogate for Replication-Competent Virus

    Visit to read articles and/or submit a manuscript.

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  • cDNA 농도를 노멀라이즈 하는 방법 - Ask TaqMan #15

    3:16

    상대적 유전자 발현연구는 실시간 기기에 수행하는 가장 흔한 어플리케이션 중 하나입니다. 그래서 펜실베이나 주립대학의 Shan에게 이런 질문을 받았을 때에도 놀라지 않았지요. 질문은 모든 cDNA에 관심 유전자와 내부 대조를 모두 검사해야 한다면 각 cDNA의 농도가 동일해야 합니까?입니다. 좋은 질문이지요. 잠깐 검토로 시작 해보죠.
    유전자 발현 실험을 할 때마다 적어도 두 개의 유전자별 분석이 필요합니다. 하나는 관심 유전자용이고 다른 하나는 내부 대조 유전자용이지요. 이는 정상화 유전자, 하우스키핑(housekeeping )유전자, 내재 대조 유전자라고도 합니다. 말은 다르지만 똑같은 의미입니다.
    그러면 두 번째 유전자인 정규화 유전자는 우리를 위해 무슨 일을 할까요? 물론 말 그대로 제일 중요한 역할은 넣는 템플릿의 양을 정규화하여 최종 데이터를 만드는 것입니다. 제가 설명하죠.
    관심 유전자 발현을 샘플 두 개 (약물 처리 세포주와 비처리세포주)를 비교한다고 합시다. 리얼타임 결과를 보면 두 샘플에서 Ct값 1이 차이가 나는군요. 이 결과는 두 샘플 간 표적 발현에 2배 차이가 있다는 것을 말해줍니다. 하지만 어떻게 실제로 두배 차이란것을 알 수 있을까요?
    결국 미처리 cDNA와 처리 cDNA 농도가 다른 것이 아닐까요? 농도차이가 Ct값 1차이를 만든것 아닐까요? 확실히 가능성이 있습니다. 그렇기 때문에 각 샘플에 정규화 (Normalizer, internal control)유전자를 넣어야 하는 것입니다.
    좋은 정규화 유전자는 여러 샘플 유형에서 발현이 안정적이어서 양이 일정하다고 가정할 수 있는 유전자 입니다. 이 두 번째 유전자를 이용한 분석에서 얻은 데이터 덕분에 샘플마다 주입량이 달라도 cDNA 주입량을 효과적으로 모니터링할 수 있습니다. 그러면 실험 마지막에 정규화 유전자에서 얻은 Ct값을 사용해 cDNA 주입량이 다른 것에 대해 최종 발현값을 보정할 수 있습니다. 그러면 실험에서 항상 샘플간 동일한 양의 템플릿이 있어야 하는것이 아니지요.
    하지만 정규화 유전자가 제역활을 하려면 샘플 세트 전반에서 발현량이 안정적이어야 합니다. 그렇지 않다면 이 정규화 유전자에서 나온 데이터가 오히려 최종 발현값의 덜 정확하게 만들수 있죠. 그러면 어떻게 좋은 정규화유전자를 선택할 수 있을까요?
    이 문제에 대해서는 라이프테크놀로지 웹페이지를 방문하셔서 상대적 유전자 발현 작업흐름 문서 사본을 다운받아보실 것을 강력히 추천합니다. 이 PDF 파일에는 추측이 아닌 확실한 실험 데이터를 근거로 가장 적합한 정상화 유전자를 선택할 수 있는 방법에 대한 항이 있습니다.
    실시간 PCR에 대해 질문이 있으세요? TaqMan®에게 물어보세요. #askTaqman으로 트위터하거나 페이스북으로 찾아보세요. 아니면 웹사이트로 오셔도 됩니다.

  • Ask TaqMan ®: Ep. 8 SYBR® Green을 사용한 융해 곡선에서 여러 개의 피크 발견

    3:29

    Real-Time PCR에 대한 사용자 여러분의 질문을 등록하시면 라이프 테크놀로지스의Sr. Field Application Specialist인 Doug Rains이 도와드립니다.

    [Script]
    실시간 분석에 SYBR® Green chemistry를 이용하는데 융해 곡선에서 피크가 여러 개 나옵니까? 이게 제대로 된 건지 궁금하세요?
    배경 정보부터 시작합시다. SYBR® Green은 유리 부유 염료로 시험관에서 자유롭게 떠다니고 있을 때에는 실시간 PCR 기기에서 광원을 적용할 때도 형광을 많이 발하지 않습니다. 하지만 SYBR® Green 염료는 이중 가닥 DNA에 확실히 결합해 빛을 쪼이면 여기하여 형광을 발합니다. 이론적으로 그 기본 개념은 이렇습니다; PCR에서는 많은 산물들이 생성되기 때문에 SYBR® Green 염료의 신호가 이에 비례해서 커져야 하지만, 실제로 항상 그렇게 되는 것은 아닙니다. SYBR® Green 염료가 이중 가닥 DNA라면 어디에든 결합하기 때문입니다. 즉 시험관 안의 모든 이중 가닥분자가 SYBR® Green 염료에 결합하여 형광 신호를 추가시킵니다.
    이런 문제 때문에 사용자는 각 실험 후 융해 곡선을 실행합니다. 이는 차단 온도를 섭씨 약 60도에서 95도로 천천히 올리며 형광을 모니터링 합니다. 보시다시피 신호가 점점 낮아지다가 어떤 지점이 되면 갑자기 0으로 뚝 떨어집니다. 이 강하부분의 중간을 PCR 산물의 융해 온도로 추정합니다. 미적분 기능이 있는 소프트웨어에서는 '편차 보기'를 할 수 있습니다. 이는 Drop-off를 피크로 전환시키기 때문에 보기가 편합니다. 분명한 피크 하나를 보고자 하시겠죠? 이는 단일 산물이 깨끗하게 증폭되었다고 제시합니다. 입증이 아닌 제시입니다.
    증폭 곡선이 하나 이상 산물로 이루어 졌다고 제시하는 여러 개의 피크는 보고싶지 않으시겠지요. 상관없는 피크는 왜 생길까요? 이는 비특이적 증폭이나 프라이머 이합체 형성 등 상황에 따라 다를 수 있습니다. 비특이적 증폭 때문이라면 프라이머를 특이성 높은 시퀀스로 다시 디자인해야 합니다. 프라이머 이합체 형성의 경우에는 프라이머 농도를 낮추어 이합체 형성을 막아야 합니다. 프라이머 재설계가 필요할 수도 있습니다. 하지만 여러 개의 개별 피크만 문제가 되는 것은 아닙니다. 비대칭 피크, 숄더, 비정상적으로 뭉친 피크 등 기타 이상 형태가 데이터 의 타당성을 저해하게 됩니다. 문제는 무엇이 어떤 이상 형태를 야기하는지 정확하게 알기 어려워 여러 가지 새로운 조건이나 새로운 여러 프라임으로 실험을 계속 반복하며 시간을 보내야 한다는 데 있습니다. 재미도 없고 비용도 드는 일이지요. 하지만 제대로 작업이 된다면 SYBR® chemistry는 qPCR에 확실히 유효합니다. 단지 TaqMan® chemistry를 사용할 때보다 실험 설계에 좀 더 신경을 쓰고 데이터를 평가할 때 품질 관리 단계를 추가해야 할 뿐입니다.
    페이스북, 트위터, 홈페이지 lifetechnologies.com/asktaqman로 여러분의 질문을 보내주세요.

  • 리얼타임 PCR 반응의 민감도를 개선하는 방법 - Ask TaqMan #12

    3:29

    간질환이나 시상하부를 연구하는 연구자들은 행운이라고 생각해야 합니다. RNA양이 적거나 발현양이 적거나 하지않기 때문이죠. 하지만 micro dissection된 마우스 종양 샘플, 심지어 단일세포로 연구를 하는 사람은 어떨까요? 또 제한된 세포 분리 분획에서 연구를 하는 사람은요? 바레토스 암병원(Barretos Cancer Hospital)의 Andre같은 사람은 이렇게 말합니다. 매우 적은사람 세포에서 전사된 특정 유전자에서 돌연변이를 연구하고 있습니다. 리얼타임 PCR assay 민감도를 높이려면 어떻게 해야 하나요? Andre, 제가 답변해드릴 수 있겠네요.
    가능한 솔루션을 말하기 전 방금 언급한 두 가지 문제를 시나리오와 함께 이야기 해보겠습니다. 첫번째는 적은 세포양으로 시작할 때에는 RNA 손실의 우려 입니다. 컬럼 정제나 핵산 침전이 포함된 일반적인 분리와 클린업 방법을 사용을 원한다면 샘플이 손실되는 위험이 있습니다. tRNA같은 캐리어 (carrier)를 추가할 수 있겠지만 이것도 회수율을 보장할 수 없습니다.
    그럼 어떤 방법이 있을까요? 네, 좋은 방법 하나는 배양된 세포나 미세해부된 샘플의 경우에는 직접 용해를 적용 하는거죠.
    세포를 5분간 용해하여 용액에 RNA를 방출하고 2분간 반응을 정지시킨 후 용해액을 직접 역전사반응에 넣는 것이지요. 이러면 RNA 가 소실되지 않습니다. 마지막으로 이렇게 나온 cDNA 유전자를 리얼타임 반응을 시킵니다.
    하지만 이렇게RNA 전부를 살려도 시작량이 제한적이거나 표적 유전자 발현이 미미한 경우에 우수한 리얼타임 신호를 얻지못하는 경우는 어떻게 할까요? 이 경우에는 전처리증폭 단계가 매우 유용할 수 있습니다. 바로 RT 단계 후 다운스트림에서 조사할 표적 특정 프라이머를 사용해 관심 표적을 전처리증폭할 수 있습니다.
    최대 100쌍의 프라이머 풀과 특수 리얼타임PCR 마스터믹스을 사용하여 전처리 증폭을 하게되며 대략 10-14cycle정도 입니다.
    제한된 clycle로서 여러 표적cDNA의 화학양론을 유지할 수 있으며 유전자 정량 정보가 필요한 연구자에게 매우 중요합니다. 동시에, 희석에 충분한 cDNA를 얻을수 있고 수많은 리얼타임PCR 반응을 수행할 수 있습니다. 라이프 테크놀로지스는 물론 이 프로세스의 모든 단계에 필요한 분리 키트, 증폭 시약 그리고 전사별 분석 모두를 제공합니다. 더 많은 정보를 원하신다면 lifetechnologies.com에서 cells-to-ct를 검색해보세요. 사전 증폭용과 아닌 것, mRNA용이나 microRNA용 등 TaqMan과 SYBR 화학 키트를 비롯하여 수많은 키트 옵션이 있습니다.
    실시간 PCR에 대해 질문이 있으세요? TaqMan®에게 물어보세요. #askTaqman으로 트위터하거나 페이스북으로 찾아보세요. 아니면 웹사이트로 오셔도 됩니다.

  • Ask a Scientist: What is a Genome Equivalent?

    4:20

    What is a genome equivalent, and why does it matter when planning next-generation sequencing (NGS) experiments? This video describes the relationship between the number of genome equivalents in an NGS sample and the theoretical maximum coverage depth achievable for that sample. It also explains how understanding genome equivalents can help with experiment planning and increase the quality of NGS data, especially in hybrid-capture target enrichment workflows.

    Presented by Teri Rambo Mueller, Field Applications Consultant at Roche Sequencing and Life Science.

    MC-US-07905

  • How to Normalize cDNA Concentrations -- Ask TaqMan® Ep. 15 by Life Technologies

    3:16

    Submit your real-time PCR questions at
    In this video, Sr. Field Applications Specialist Doug Rains examines why the choice of an appropriate normalizer gene is so critical for the accuracy of final real-time PCR data. In addition to discussing this gene's importance, Doug provides a helpful reference document which explains in detail how researchers can quantitatively validate their choice of a control gene.
    Relative gene expression is one of the most common applications that researchers perform on their real-time instruments. So it's never a surprise when I receive a question like the one I got recently from Shan at Pennsylvania State University, who asks the following:, Since every cDNA is run with both the gene of interest and internal control, do I have to be sure that the concentration of each cDNA is the same? Excellent question. Let's start with a little bit of review.
    Whenever we do a gene expression experiment, we need at least two gene-specific assays one for our gene of interest, and one for an internal control gene, also sometimes referred to as a normalizer, housekeeping gene, or endogenous control. Different terms, same idea.
    So what does this second gene -- the normalizer -- do for us? Essentially, its number one job is to normalize our final data for differing input amounts of template. Here's what I mean.
    Say I'm comparing the expression of my gene of interest in two samples: an untreated and a treated cell line. When I examine the real-time results, I find that my two samples differ by a single Ct. This result suggests that there's a two-fold difference in my target's expression between the two samples. But how do I know that two-field difference is real?
    After all, isn't it possible that my untreated and treated cDNAs had different concentrations, and that's the reason we're seeing a one-Ct difference? Definitely a possibility. Precisely why I also have to run a normalizer gene on each sample.
    A good normalizer gene is one whose expression is stable across my various sample types, assuming equal starting amounts. Thanks to the data I collect from this second gene assay, I can effectively monitor input amounts of cDNA, even when they differ from sample to sample. Then, at the end of the run, I can use Ct data from the normalizer gene to correct final expression values for differing input amounts of cDNA. I can thereby avoid having to always add equal amounts of template when running my experiments.
    But clearly, for the normalizer to do its job correctly, its expression has to be stable across our sample set. If it's not, the data from the normalizer can actually make our final expression values less accurate. So how does one choose a good normalizer?
    To find out, I strongly recommend our kind viewers visit the Life Technologies web page, where you can download a copy of the Relative Gene Expression Workflow document. This PDF has an entire section on choosing the most appropriate normalizer, based not on guesswork, but on good, hard empirical data.

  • Absolute Quantification of mRNAs - Ask TaqMan #26

    4:54

    Submit your question:
    Relative quantitation is the most common application with real-time PCR, but sometimes fold change data is just not enough. For instance, let's say I'm looking at samples infected with HIV and I need to know exactly how many copies of virus are present in the sample. What other options are there, when you need more concrete answers? That brings us to this great question from Jamsai Duangporn at Monash University who asks Can TaqMan assays to be used to determine the absolute quantity of the mRNAs?
    TaqMan assays can be used for a technique called Absolute Quantitation, sometimes also known as Standard Curve analysis. ABSOLUTE QUANTIFICATION involves the precise molecular measure of a target concentration. In an ABSOLUTE QUANTIFICATION experiment, samples of a known quantity are serially diluted and then amplified to generate a standard curve. The unknown samples can then be extrapolated into quantities based on the slope of this curve.
    The main hurdle in an ABSOLUTE QUANTIFICATION experiment is the generation of this standard curve. Although it seems simple in principle, there are a lot of things to consider! Your standard needs to meet the following criteria:
    First, the quantity of a sample must be known by some independent means. For this step, the concentration can be measured by with a spectrophotometer and converted to number of copies using the molecular weight of the DNA or RNA. You can also refer to our handy guide called Creating Standard Curves for more details on how to do this.
    Second, the standard should closely resemble the target from a biological standpoint, and it is very important that the DNA or RNA be a single, pure species. For example, when measuring gene expression of RNA transcripts, you would want to use in vitro transcribed RNA. Take care here because purity will be an important factor in the accuracy of your measurement.
    Third and finally, don't forget that your excellent pipetting skills can be put to good use here! One of the major pitfalls for scientists setting up standard curves is that they do not pay enough attention accuracy of pipetting of technical replicates. For the best results from your standard curve, ensure that your pipets have been recently calibrated. Be very careful when making dilutions and pipetting into the plate, and ideally make use of low retention tips.
    Now that we have our standards, let's setup a dilution curve in our plate. We recommend to run in triplicate, with 10 fold dilutions and at least 5 points.
    When set up correctly, all ABI Real-Time PCR instrument software will generate a standard curve for you from these points. The equation of the linear regression line through those points is then used to automatically calculate the quantities of any unknowns on the plate, in the same units.
    For example, in this curve I have 5 points, starting with 20,000 copies of my target as the highest concentration going down to 1250 copies. The standard curve plot is showing the input on the x-axis as [log X] and the Ct values on the y-axis. Quantities are then determined from this equation: We'll remove any outlying replicates or points when necessary.
    Solving for X using the Ct values of our unknown samples will give us the missing quantities. Notice that they will be in the same units as our standards; copies for copies, ng for ng, and so on. So now we have determined the absolute quantities of our unknown samples!

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    Limits of detection are a complex part of qPCR analysis and there is still much debate in the literature about the true LOD of qPCR. But as a general rule of thumb anything after a Cq of 32 in a SYBR Green assay or after 35 in a probe assay is on the limit of detection. This means that any amplification after that should be treated with caution

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