Rare genomic targets can carry important biological information, but finding and measuring them can be challenging when they are present at very low abundance or buried in complex samples. In this Science Snapshot episode, past Absolute Gene-ius guests explore how qPCR and digital PCR can help detect, quantify, and verify rare signals across virology, oncology, genomics, and cell and gene therapy research.
In this Science Snapshot episode of Absolute Gene-ius, Lisa Crawford and Jordan Ruggieri revisit conversations with researchers working at the limits of molecular detection. Dr. Nikhil Ram Mohan explains how digital PCR revealed viral RNA signals that were difficult to detect by qPCR and how absolute quantification helped expose subtle differences. Dr. Clarence Lee discusses finding known biomarkers and mutations in complex samples, including circulating tumor DNA and cell and gene therapy applications. Dr. Parker Wilson shares how digital PCR helped verify rare Y chromosome loss first observed by single-cell sequencing, while Dr. Jesus Mingorance describes using multiple PCR approaches to investigate difficult-to-measure HIV-2 viral load. Finally, Wendy Wang brings the concept of partitioning to life with a memorable analogy for understanding copy number and structural variation.
Together, these stories show that rare-target research is often about more than simply asking whether a signal is present. It is about choosing the right tools to detect it, measure it confidently, and decide what that small signal might mean.
Lisa Crawford 00:00
I'm going to have to make sure that I don't say rare tergets.
Jordan Ruggieri 00:03
Today we're talking about rare tarjays.
Lisa Crawford 00:06
And now we've ruined it for both of us.
Lisa Crawford 00:20
Welcome to another Science Snapshot episode of the Applied Biosystems Absolute Gene-ius podcast. I'm Lisa Crawford,
Jordan Ruggieri 00:27
And I'm Jordan Ruggeri. Today we're looking at one of the most persistent challenges in molecular biology. How do you find and measure something that is barely there?
Lisa Crawford 00:36
Rare genomic targets can be incredibly important, but they are often present at very low levels, hidden in complex samples, or difficult to distinguish from background signal.
Jordan Ruggieri 00:45
That challenge has come up again and again in our conversations with researchers across virology, oncology, immunology, pharmacogenetics, and genomics. Whether the target is viral RNA, circulating tumor DNA, a rare mutation, or a subtle chromosomal change, the central question is often the same: Is the target really absent? Or is it just hard to detect?
Lisa Crawford 01:08
And that's where technologies like qPCR and digital PCR can play such an important role. qPCR has long been a powerful tool for detection and quantification, while digital PCR can offer additional analytical sensitivity, precision, and absolute quantification when researchers are looking for especially rare or low abundance targets.
Jordan Ruggieri 01:27
In today's episode, we'll follow that story from detection to quantification through to biological insight. We'll hear how past guests have used PCR-based methods to find rare signals, measure subtle differences, and validate patterns that might otherwise be missed.
Lisa Crawford 01:42
We'll start with Dr. Nikhil Ram Mohan, who joined us in season one to discuss his work studying viral RNAnemia. In this clip, he explains how digital PCR changed what his team was able to see when qPCR showed only a very low positivity rate.
Jordan Ruggieri 01:57
It's a great example of why rare targets are not always absent. Sometimes they are simply below the detection limits of the method being used.
Nikhil Ram Mohan, PhD 02:06
When we were studying the viral RNAemia with qPCR, we were finding that half the subjects that we had tested, there was a very low positivity rate, but we didn't know if that was because of the lack of sensitivity in, sensitivity in the qPCR mechanism itself, or it was actually the case, right. So we started testing out the digital PCR, and we saw that, if I remember the numbers correctly, with qPCR, our positivity rate was about 1.4%. With digital PCR, we saw that they jumped up to about 24%, and we are getting absolute quantities, right. So there's no need for a standard curve or anything to get the viral load. So it just made more sense for us to go that route for that particular study. The challenge was that a lot of the samples that we had had really low viral loads to begin with. If we had relied on the one person from qPCR for us to go forward in that study, we'd needed a larger N for us to be able to do further analysis, right. But with a digital PCR that helped us out because the rate limiting step there was that we were only able to sample so many subjects coming in as well. The higher sensitivity with the digital PCR platform really helped us in being able to ascertain the patterns that were actually present.
Lisa Crawford 03:30
That's a great first example. Going from about 1% positivity with qPCR to nearly 25% of samples with digital PCR changes more than just the numbers. It's got to change what researchers can conclude from the study.
Jordan Ruggieri 03:43
Exactly. When rare targets are present at very low levels, analytical sensitivity can determine whether a biological pattern is visible at all. But detecting the target is only the first step.
Lisa Crawford 03:54
Once you can see that rare signal, the next logical question is whether you can measure it precisely enough to understand what it means.
Jordan Ruggieri 04:00
Nikhil also talked about how absolute quantification helped his team interpret subtle differences that might not have stood out from the Ct values alone.
Nikhil Ram Mohan, PhD 04:09
Just the absolute numbers help, right. It it's not unlike that the qPCR data has never been used before because all you have to do is make sure that you're lab log transforming the data. But with absolute numbers, it's easier to see the minute differences as well. A Ct value from 23 to 24 might not seem as big, but you might still see a lot of differences in the absolute quantity itself. So, to be able to parse those out, having the absolute quantities from the digital PCR definitely helped out.
Lisa Crawford 04:45
That's an important distinction. Ct values are incredibly useful, but when the differences are small, absolute quantities can make those changes easier to see and interpret.
Jordan Ruggieri 04:54
And that's important because rare target work often depends on confidence. It's not just can I detect something; it's can I trust that signal, reproduce it, and compare it across samples or even across labs.
Lisa Crawford 05:07
That idea came up in our conversation with Clarence Lee. Clarence talked about the value of digital PCR when the researchers already know the rare biomarker, mutation, or contaminant that they want to find.
Jordan Ruggieri 05:18
In those cases, digital PCR can help simplify the work by removing the need for standard curve preparation and reducing one source of variability.
Clarence Lee, PhD 05:26
When you know what you're looking for, then yes, it's definitely something that helps out. You don't need to waste time and real estate, let's say, to prepare a set of standards, where okay, I'm going to build a set of standards so I know what that needle looks like and how much it should be. And instead, I'm just going to, “Nope, I'm going to see. I'm going to do my analysis and look for those, that biomarker that I know I'm interested in, or a potential contaminant.” In that sense, you're also trying to show, yeah, I do literally have a needle in the haystack. Of course, people are always concerned about the reproducibility of your results as you go from user to user. And here you're kind of taking away one variable. A very important variable when you think about it. Okay, how do I, how does that person interpret what that standard should be, and where like how I should do it. And that could be within the lab or in between labs and stuff like that, and now it's like, well, we have a method where, oh, everyone knows how, like, is there a signal or not? Yes or no. That's it. And so now there's a common agreement, and you see the value of what digital PCR can bring.
Lisa Crawford 06:51
That's a helpful way to think about digital PCR. When the target is known, the question becomes much more direct. Is that rare signal there, and how much of it is present?
Jordan Ruggieri 07:00
And that can be especially powerful in complex research areas where the target may be biologically meaningful but present at very low abundance.
Lisa Crawford 07:09
Clarence also talked about how that rare target challenge shows up in liquid biopsy research, where scientists may be looking for circulating tumor DNA mutations across a large background of other DNA.
Jordan Ruggieri 07:19
He also connected that same need for precise quantification to cell and gene therapy research, where teams may be measuring critical molecular targets as they build and evaluate new therapeutic approaches. A
Clarence Lee, PhD 07:31
A lot of our assay efforts have been very focused within the cell and gene therapeutic space, as well as, of course, with liquid biopsy. So, built out a menu of liquid biopsy assays as an example to really take into account the circulating tumor DNA and the size of that, and looking for that needle in a haystack of the mutations that we want to see with across the cancers for treatment monitoring or just MRD and all of that stuff of minimal residual disease for people familiar with that term. And then the side of things within the cell and gene therapy spaces, we just see a lot of activities and interests in terms of using the Absolute Q and digital PCR system to quantify things without the need for a standard curve as they start building out these therapeutics.
Lisa Crawford 08:23
Clarence's examples highlight how good dPCR instrumentation and assays can help researchers measure rare targets in complex areas like liquid biopsy and cell and gene therapy research.
Jordan Ruggieri 08:34
And that brings us to another important role for digital PCR. Sometimes it's not the first technology that reveals a possible rare event. Instead, it helps researchers confirm whether a pattern seen with another method is real.
Lisa Crawford 08:49
That was the case for Dr. Parker Wilson, who joined in season two to talk about rare mosaic chromosomal alterations. His team first saw evidence of possible Y chromosome loss using single cell sequencing.
Jordan Ruggieri 09:01
But single cell sequencing data can be sparse, and some genomic regions are especially difficult to analyze. That's where Parker's team turned to digital PCR to help validate and quantify the pattern in the same samples.
Parker Wilson, MD PhD 09:14
I came into this in the reverse fashion. We started off with single cell sequencing, and what we noticed was that some cells, by single cell sequencing, whether you're measuring RNA or ATAC, which is sort of a form of DNA sequencing, a proportion of cells is missing transcripts or DNA fragments that map to the Y chromosome, and single cell sequencing is really sparse. So you don't know, maybe did we not sequence deep enough? Are we you know looking at the wrong thing or thinking the wrong way about this? But we saw these patterns, and we saw that some cells have a much higher proportion of loss of Y chromosome. So, if you're only looking at gene expression, maybe that's due to downregulation of Y chromosome. But we were using a technology called multiome sequencing, where we can look at both RNA and ATAC simultaneously in the same cell, and we saw a pattern that was consistent between the two modalities. We looked at this in a variety of other data sets, but we thought, how do we validate this? Is anybody going to believe us if we try and publish single-cell sequencing data alone? I think you could always argue that it's too sparse, and maybe your reads are not mapping very well to the Y chromosome. The Y chromosome has a lot of heterochromatin. It's highly repetitive. It's very hard to map to. People tend to ignore it in GWAS for this reason. And we looked to digital PCR to develop an assay to do this. And we took the same samples that we did single cell sequencing, and then we looked at them by digital PCR to quantify a ratio between the X and the Y chromosome, and we saw the same patterns. There was a positive correlation between the single cell estimate for loss of Y and a bulk estimate, which is what we're doing here by digital PCR of loss of Y. It is convenient that the cell type we're interested in or that gets injured happens to be the majority of the kidney, but you could conceivably sort cells. We have done this in cell culture assays, and we've also developed similar models or similar assays for digital PCR in animal models of kidney disease.
Jordan Ruggieri 11:30
Parker's example shows how digital PCR can help researchers validate a rare genomic pattern first seen with another technology.
Lisa Crawford 11:37
And that's an important point. The story is not always about one method replacing another. Often, it's about choosing the right combination of tools for the question in front of you.
Jordan Ruggieri 11:46
That idea came through clearly in our conversation with Dr. Jesus Mingorance, whose team was studying HIV-2 viral load. In this case, the subject was already known to have HIV-2, but one assay was not detecting a clear signal. So his team explored additional PCR-based approaches, including qPCR and digital PCR, to better understand whether the virus could be detected and quantified.
Lisa Crawford 12:10
Here is Jesus describing how a difficult single subject question became a broader evaluation of different methods.
Dr. Jesus Mingorance 12:17
In this particular case, this was the subject was already diagnosed, so we knew that he had HIV-2, and I think he was not responding correctly to the drugs. But when my colleagues at the microbiology department did the NASBA assay, they couldn't find any signal. They couldn't detect the virus. So they send some samples to a laboratory in France, and in France they could detect it. And even they could sequence it. So they were curious what was happening. They thought that maybe this this virus was highly mutated and probably was not being detected by the NASBA assay because of this, so they ask us to test something different. At that time, we had the machine, the dPCR Absolute Q machine. We were testing for other reasons, so we contact Thermo and ask them for a master mix for RT, reverse transcription PCR, and they send us a beta. So we tried with a TaqMan assay, HIV-2 TaqMan assay to detect and it was great because we could detect and quantify the virus, so the, our colleagues say, okay, so we have some samples in the freezer. We could try if we you can detect also with this system, because there was no other system at that time to quantify HIV-2. While we were doing this this work. Altona commercialized PCR, qPCR assay, so at that time we could test both in parallel the Altona qPCR, the Thermo dPCR, and in parallel with the classical NASBA assay, and those were the results. We were initially trying to identify the viral load in a single subject, but then it became an evaluation.
Lisa Crawford 14:43
Jesus's story is a great reminder that rare target detection is often a problem-solving exercise. The target may be known. The biology may be important, but the signal can still be difficult to capture with confidence.
Jordan Ruggieri 14:55
And across all of these examples, digital PCR helps by dividing a sample into 1000s of individual reactions to help make rare signals easier to detect, quantify, and interpret.
Lisa Crawford 15:06
Our final clip brings that concept to life in a very memorable way.
Jordan Ruggieri 15:10
In season three, Wendy Wang joined us to talk about identifying structural variants. She explained why digital PCR can be useful for copy number and structural variation analysis, especially when subtle deviations from expected results may point to something biologically meaningful.
Lisa Crawford 15:26
And she used an analogy that may be one of our favorites from the entire series.
Wendy Wang 15:31
When we have changes in the PCR efficiency, the micro reactions when they don't go to endpoint, that means there's something in that recipe, something in that compartment that is like running out or hindering the reaction for it to reach that final amplitude, I like to think of it as like a soup. And imagine your big soup, your big stew of all your PCR reactions, right. You've got like peas and carrots, and you've got like noodles, and you take your ladle. Like each one of those ladlefuls is like your micro reaction, right. So with dPCR, the goal is to have everything homogenized. Like you would hope that every single one of those micro reactions has similar amounts of everything in them. So by statistical chance, sometimes you're going to get like no peas in one scoop and more carrots in the other, and like this noodle is the only thing in this reaction, and like that's just going to like happen normally. It's like the change of what's already there when it's parsed out in these ladlefuls of soup is where you get these deviations from what you expect. And that can either mean yes we have a copy number, or maybe yes there's a copy number and it looks weird and there's something else under there, or like this is supposed to be normal, but it looks very strange. You know, it's just really the preciseness of being able to ladle out all of those reactions and the aggregate of that information tells you so much.
Jordan Ruggieri 17:03
Lisa, I think that conversation with Wendy may have changed the way I look at a bowl of soup.
Lisa Crawford 17:09
And it made me hungry. But really, it is a helpful analogy. When a sample is divided into many individual reactions, rare signals and subtle differences can become easier to identify and interpret.
Jordan Ruggieri 17:20
And that connects all of today's clips. Whether our guests were studying viral RNA, circulating tumor DNA, chromosomal mosaicism, HIV-2 viral load, or structural variation, they were all working with targets that were difficult to see clearly.
Lisa Crawford 17:36
In some cases, digital PCR helped reveal signals that might otherwise have been missed. In others, it helped researchers quantify subtle differences, validate patterns found by other technologies, or compare methods when the answer was not obvious.
Jordan Ruggieri 17:50
And that's really the larger story. Rare targets are not just difficult measurements; they can be important clues. With the right tools, researchers can move from asking "Is anything there?" to asking, "How much is there?" and "What does it mean?"
Lisa Crawford 18:03
qPCR and digital PCR each have important roles to play in that process. And when the target is rare, the sample is complex, or small differences matter, digital PCR can help provide the analytical sensitivity, precision, and confidence needed to turn rare targets into meaningful insight.
Jordan Ruggieri 18:19
And that's a wrap on another Absolute Gene-ius Science Snapshot. Stay tuned for more upcoming episodes and be sure to subscribe to Absolute Gene-ius to get the latest episodes as they are available. Until then, stay curious.
Lisa Crawford 18:31
This episode was produced by Sarah Briganti, Matt Ferris, and Matthew Stock. All products mentioned in this episode are for research use only. Not for use in diagnostic procedures.