Copy number variation (CNV) is one of the most important, and often overlooked, measurements in molecular biology. In this Science Snapshot, we revisit expert conversations to explore how digital PCR enables precise copy number analysis across gene editing, cell therapy, transplant monitoring, chromosomal biology, and beyond.
In this Science Snapshot, we explore copy number variation (CNV) and why accurately measuring gene copies is critical for modern research.
Jordan Ruggieri and Lisa Crawford demonstrate how digital PCR has transformed DNA quantification using conversations with past Absolute Gene-ius guests including Dave Bauer, Dustin Rubinstein, Raquel Muñoz, Lee Ann Baxter-Lowe, Parker Wilson, Valeria Rangel, and Brian Bahder. They begin with the fundamentals of absolute quantification before exploring real-world applications in CRISPR genome editing, CAR-T cell expansion, transplant monitoring using donor-derived cell-free DNA, chromosomal mosaicism, leukemia research, and environmental genomics. Along the way, listeners learn why digital PCR provides advantages over traditional PCR approaches for measuring rare targets, validating edits, detecting low-abundance DNA, and producing confident quantitative results.
Whether you're new to CNV analysis or already using digital PCR in your research, this episode offers practical perspectives from scientists applying these technologies every day. It's a fast-paced overview of why accurate DNA measurement continues to shape discoveries across molecular biology.
Jordan Ruggieri00:00
That was funny because you said let's take a listen, and then I went to go a joke and say I don't hear Dave talking. But you said did anybody hear that? And so,
Lisa Crawford00:08
I ruined your joke.
Jordan Ruggieri00:10
You ruined my joke. It was great. Yours is better though. Wrestling cats always takes priority.
Jordan Ruggieri00:27
Welcome to another Science Snapshot episode of Absolute Gene-ius, a podcast series from Thermo Fisher Scientific. I'm Jordan Ruggeri.
Lisa Crawford00:35
And I'm Lisa Crawford. Today, we're diving into copy number variation, or CNV, one of the most important and sometimes overlooked measurements in molecular biology.
Jordan Ruggieri00:45
At its core, CNV is about counting DNA, understanding how many copies of a gene or genomic region are present. But as simple as that sounds, getting the number right isn't always straightforward.
Lisa Crawford00:57
Whether you're studying gene edits, tracking disease progression, or measuring rare DNA fragments, small inaccuracies in copy number can lead to very different biological conclusions.
Jordan Ruggieri01:07
So, before we explore how scientists are applying CNV analysis across different fields, it's worth asking a more fundamental question: What actually makes precise copy number measurement possible?
Lisa Crawford01:19
To answer that, we're going to start with Dr. Dave Bauer, who breaks down why digital PCR has become such a powerful and trusted tool for absolute quantification.
Jordan Ruggieri01:28
From precision to analytical sensitivity to eliminating the need for standard curves, Dave walks us through the core principles that make digital PCR uniquely situated for CNV analysis.
Lisa Crawford01:39
Let's take a listen.
Dave Bauer, PhD01:40
Yeah, so digital PCR, a lot of different applications, a lot of reasons to use it, and the Absolute Q checks a lot of those boxes for me, at least as a scientist. We know that with digital PCR you might have rare events, whether it's low abundance or it's rare because it's one of the few wild, a few mutants within the wild type population. In either case, you care about those rare positives, and the Absolute Q has a lot of features: the background subtraction, false positive rejection. So you have the confidence, so that you're detecting true signal on those rare events. That's always important. And then sometimes precision. Sometimes you're doing digital PCR for precision, and a lot of precision coming from Poisson statistics has to do with the number of microchambers you're using. And if your system has variable numbers of micro chambers or micro reactions run to run that impacts the precision and makes it more difficult to compare results across runs. Another critical benefit of digital PCR is the absolute quantification. So a lot of people doing real-time PCR might say, "Hey, I get quote-unquote absolute quantification", but that's always relative to a standard. There's always got to be a standard that you're comparing your Ct values from in that case. And there are a lot of potential issues dealing with standard curves. One of the biggest is what's your reference material, and if you're making it yourself, you obviously have a way to quantify it very accurately, so why are you using real-time PCR anyway? And if you're getting it from a vendor, you don't always know how they're quantifying it, how accurate their results are. And I can't tell you the number of times I've seen people switch digital PCR and say, "I'm getting different absolute quantifications from real time". And I say, "Run that standard. If it says it's 10,000 copies, put it in the digital PCR system and see what it says, and it isn't always what it says?”
Jordan Ruggieri03:25
Dave does a great job laying out the fundamentals. Digital PCR gives you precise, absolute quantification without relying on standard curves. But what does that actually look like in practice?
Lisa Crawford03:35
One of the clearest examples comes from genome editing. When you make a change to DNA, like inserting or deleting a sequence, you don't just want to know if the edit happened. You need to know exactly how many copies there are.
Jordan Ruggieri03:47
And that's where traditional PCR methods can fall short. You might see a band, but that doesn't tell you whether you have one copy, or many.
Lisa Crawford03:55
Dr. Dustin Rubenstein ran into this exact challenge while building CRISPR-based animal models. For his team, confirming copy number wasn't just helpful; it was essential for validating that their edits were correct.
Jordan Ruggieri04:06
Here's Dustin explaining how digital PCR became a critical tool for that kind of quality control.
Dustin Rubenstein, PhD 04:11
So, when you're doing genome editing, you make the change, and then obviously, it's really important to know what the change you just made is, right. That becomes the next big problem, what what's the change you just made? Almost everyone uses some sort of PCR-based method to read that out. The that you know PCR-based methods can sometimes like kind of add like a little fog. It can help you kind of maybe see what you want to see rather than what's actually there. So you might amplify, you might be trying to amplify a certain part of the genome, and you get your band, you get a PCR band, and you think, okay, great, this fragment exists in the genome just as I think it did. But one example might be that well, maybe that fragment exists in the genome, but only because maybe there are many, many copies of that insert, and that fragment exists as well as tons of other fragments that you can't see with PCR, right. And you. The thing is, sometimes you PCR something, and we might forget that we actually have like two chromosomes, and you're not just PCRing and getting a band from one. You'd want to make sure that you're interrogating both chromosomes. But when you do an endpoint PCR, you have no idea like which chromosome gave you that band, right. So using digital PCR kind of allows you to tease out some of those problems and address them. So we're finding that those are these are kind of really key things to do. And when you actually, it turns out when you actually like peel back like the layers, sometimes it's not as pretty as you, as you think it is.
Jordan Ruggieri05:36
Dustin's work highlights a core strength of CNV analysis: being able to confidently measure how many copies are present after a gene editing event, but in many cases that number isn't static.
Lisa Crawford05:48
In areas like cell and gene therapy, copy number can change over time as cells expand, contract, or respond to treatment. So now the question becomes not just how many copies there are, but how does that number evolve?
Jordan Ruggieri05:59
That's the challenge Dr. Raquel Munoz faced in her CAR-T cell research. Her team needed to track how engineered cells expanded in the body, essentially following copy number changes over time.
Lisa Crawford06:10
And she found that traditional qPCR methods struggle to give reliable answers, especially at low target levels.
Jordan Ruggieri06:17
Here's Raquel explaining how digital PCR enabled more accurate absolute quantification of those changes.
Raquel Munoz, PhD 06:23
We tried to measure the expansion of CAR-T cell. At first with a real time PCR, but we had a lot of problems because, as you know, with real time PCR, we need to amplify a reference target, and in the same reaction, we have all the reagents and the primers to amplify our target, but also the target reference, the reference target. Sorry. So, in cases of low frequency targets, as our case, there is a high probability of competition between the reagents, and maybe we could amplify only the reference target because there is a high proportion if we compare with our target. So this problem doesn't exist with digital PCR, because thanks to partition we have micro amplifications. So we do an absolute quantification. We don't need a reference. So we obtain an absolute quantification, and in our research, this is a great advantage. So we decide to use digital PCR.
Lisa Crawford07:49
Raquel's work shows how digital PCR can track changes in copy number over time, even in complex systems like CAR-T cell expansion. But sometimes the challenge isn't just tracking change, it's detecting DNA that's barely there at all.
Jordan Ruggieri08:02
In applications like transplant monitoring, researchers are often looking for tiny amounts of donor-derived DNA, sometimes less than 1% of the total DNA in a sample. At that level, even small measurement errors can completely change the interpretation.
Lisa Crawford08:19
Dr. Leanne Baxter-Lowe works in this exact space using donor-derived cell-free DNA as a marker for transplant health.
Jordan Ruggieri08:26
For her, precise copy number measurement at very low abundance isn't just important; it's essential.
Lisa Crawford08:32
Here's Dr. Baxter-Lowe explaining why digital PCR is uniquely suited for this kind of ultra-sensitive detection.
Lee Ann Baxter-Lowe, PhD 08:39
For us, we think it's perhaps the only useful platform to be able to test samples that have only one milliliter of blood and to isolate cell-free DNA from them. We're not going to have very much DNA to work with, and we're going to be measuring very small quantities. And when you have a very low copy number of something in a mixture, digital PCR is really the best approach. It helps you to get a much lower baseline. You know, for some of the probes we've been working with, if we just see one positive signal, we can be pretty confident that there's one copy there.
Jordan Ruggieri09:22
Leanne's work really highlights the power of digital PCR when you're working at the limits of detection, measuring just a handful of DNA molecules with confidence. But copy number variation doesn't just happen at low abundance; it can also happen at a much larger scale.
Lisa Crawford09:37
Some of the most important CNVs involve entire chromosomes or large chromosomal regions, especially in processes like somatic mosaicism. In these cases, you're not just asking how much DNA is there, you're asking how copy number varies across different cells within the same tissue.
Jordan Ruggieri09:53
That's exactly what Dr. Parker Wilson studies. His work focuses on chromosomal gains and losses, like changes in X and Y chromosome copy number, and how those variations show up in real biological systems.
Lisa Crawford10:05
Here, he explains how digital PCR allows his team to quantify those differences with high precision, even in mixed cell populations.
Parker Wilson, MD PhD 10:13
We ended up targeting a region near SRY, which is a gene on the Y chromosome, and this is important for determining male sex characteristics. It's in a region called the male-specific region of the Y chromosome. So once you find a region like this, you then need some other reference or target probes. We chose a region on the X chromosome, and just very simplistically, we were going to use a two-color assay where you have, say, for example green that targets the Y chromosome region, and then you have you know red that targets the X chromosome region, and then we did our digital PCR assay. We're using somewhere between 100 and 200 nanograms per sample. So you put your sample in there, and you put it in with your Y chromosome and your X chromosome probe, and then you do an endpoint PCR reaction. We're using, you know, 40 cycles. And then you count the number of positive wells that come up for X or Y. Maybe you're trying to achieve roughly 50% positivity for the number of wells. So if you get 10,000 positive wells, you're usually in pretty good shape, because then you can ask if you have say 10,000 wells that are positive for the Y chromosome, but you see 15,000 positive wells for the X chromosome you might think that there are more X chromosomes than Y chromosomes in the tissue from a male sample. And all the important assumptions here are that for the tissue that we're looking at, the vast majority of cells are going to have an equal number of X and Y chromosomes, which is certainly true for a non-tumor kidney sample. So that's the way we do it, and then we're kind of interested in how can you push this to the next level. You know, what are other things that we can incorporate? And I mentioned earlier, what about women? So this is a question that some of my reviewers ask. You know, you're interested in studying Y chromosome, but women don't have the Y chromosome, and they develop kidney disease and they have the same cell types or states that you see in the kidney. What are some of the other events that could be very closely related to loss of Y chromosome? And the one that we've thought of is loss of X chromosome. And loss of X chromosome has been described in the blood. It seems to happen at a much lower rate than Y chromosome loss, but not that many people have really looked at this. We're interested in developing an assay to develop loss of X chromosome in the kidney or the blood or other tissues and animal models. So, if we know that loss of X chromosome happens much less frequently than loss of Y chromosome, are we looking for samples that have 1% or less? Is it possible to find that by digital PCR is a is a question that we're interested in pursuing. We think we can see it by single cell sequencing, but we want to push the boundaries with the digital PCR because then you could use digital PCR as a quick, low cost, very effective assay to screen tissues or disease models, and then you could move on to a more expensive assay if you wanted to really dive deeper.
Lisa Crawford13:29
Parker's work shows just how complex genomic changes can be, especially when you're looking at entire chromosomes and mixed cell populations. But copy number variation is just one piece of a much broader picture.
Jordan Ruggieri13:41
In many biological systems, especially in cancer, you're not just dealing with changes in copy number. You're also seeing mutations, structural changes, and other forms of genomic instability happening at the same time.
Lisa Crawford13:53
And measuring those changes accurately is just as critical, especially when you're trying to validate gene edits or understand how cells respond.
Jordan Ruggieri14:01
Dr. Valeria Rangel works in this space, studying leukemia and using PCR-based approaches to detect and confirm genomic changes at very high sensitivity.
Lisa Crawford14:11
Here's Valeria describing how her team validates those edits and helps ensure their assays are capturing what's really happening at the DNA level.
Valeria Rangel14:19
We did use CRISPR-Cas9 methods to validate the assay. It was our sort of proof-of-concept experiment to be able to show to our readers and our audience that you know we've tested this out with single guide RNAs and we can you know create a mutation at a specific site and show that the assay is actually sensitive enough to pick up those mutations. So what we did is we designed several different single guide RNAs that would create a Cas9 break at either the one or several of the CPG binding sites. But we introduced a single guide RNA. In the paper, you can see these results as well. We're able to detect amplicons where only our non-CPG hex control probe binded, but not the TAMRA probe. So those would be amplicons where some sort of mutation inhibited the TAMRA probe combining.
Jordan Ruggieri15:08
Valeria's work highlights how critical it is to accurately detect genomic changes, especially in complex biological systems where multiple types of variation are happening at once.
Lisa Crawford15:19
And it also underscores an important point: the method you choose really depends on the question you're trying to answer.
Jordan Ruggieri15:25
That's something our next guest, Dr. Brian Bader, deals with every day, but in a completely different context.
Lisa Crawford15:32
Working in environmental and ecological systems, Brian uses both qPCR and digital PCR, depending on the level of analytical sensitivity and specificity required.
Jordan Ruggieri15:42
While this isn't a copy number variation application, it's a great example of how researchers think about choosing the right tool for the job.
Lisa Crawford15:50
Here's Brian explaining how he balances those approaches in real-world samples.
Brian Bahder, PhD 15:55
We still run qPCR on our assays because it's cheaper, and people have to pay for the service. And for the samples, you don't, they always send in palm samples where it's symptomatic, and when the palm's symptomatic, the phytoplasma is fully systemic. So you don't need that level of sensitivity that you get with the digital PCR. So it's not cost effective to use it. So we stick with qPCR for that. But from a research perspective, there is a very specific niche that I use qPCR for, and that's with HRM analysis. If you're looking at a single SNP within a region or a few, you can't design assays that are specific for those and use it on the digital PCR to be exclusive. It's just not, not possible with every scenario. So that's a case where, like the insect species I work with that transmits the pathogen, we did a population genetic study in Florida and found four distinct haplotypes that differ by one to two nucleotides. Like really, really being stringent, you might be able to get it to where the probe doesn't work or one of the primers doesn't, but it's, you just can't get that specificity with some things that are so closely related. So with HRM, with the qPCR, basically we have that app that gives you really high resolution. So, you know, we run the qPCR, we amplify the CO1 gene for these bugs, and then eventually we want to use HRM to be a cost-effective way to screen these genetic variants that only differ by one nucleotide.
Lisa Crawford17:40
Brian's work is a great reminder that there's no one-size-fits-all approach. Different biological questions require different tools, and understanding those trade-offs is key.
Jordan Ruggieri17:50
But across all of these examples, from environmental DNA to human disease, we keep coming back to the same core challenge: How do you make accurate, confident measurements of DNA?
Lisa Crawford18:01
And when that question becomes how many copies are there, that's where copy number variation comes into focus. And with that, we've reached the end of our exploration of copy number variation.
Jordan Ruggieri18:12
From gene editing and cell therapy to transplant monitoring and chromosomal biology, one theme keeps coming up: CNV is ultimately about measurement.
Lisa Crawford18:22
It's about knowing not just what's there, but how much there is, and being confident in that answer, even when the biology gets complex.
Jordan Ruggieri18:29
And as we've heard from our guests, that confidence becomes especially important when you're dealing with low abundance targets, mixed cell populations, or dynamic systems that change over time.
Lisa Crawford18:40
Digital PCR plays a key role here, offering the precision, analytical sensitivity, and absolute quantification needed to make those measurements meaningful.
Jordan Ruggieri18:48
But across all of these examples, from environmental DNA to human disease, we keep coming back to the same core challenge: How do you make accurate, confident measurements of DNA? And when that question becomes how many copies are there, that's where copy number variation comes into focus.
Lisa Crawford19:07
Thanks for joining us for another Science Snapshot. We hope these insights help you think differently about how and why you measure DNA.
Jordan Ruggieri19:14
Stay tuned for more upcoming episodes, and don't forget to subscribe to Absolute Gene-ius wherever you get your podcasts.
Lisa Crawford19:21
This episode was produced by Sarah Briganti, Matt Ferris, and Matthew Stock.
Jordan Ruggieri19:26
Products mentioned in this episode are for research use only, not for use in diagnostic procedures.
Lisa Crawford19:31
I wanted to make some sort of band joke, but I wasn't fast. All right, I might see a band. I love seeing bands. Man, what's the last band you saw? Rhymes with schmoling schmoens.