Beyond Relative Abundance: The Complete Guide to eDNA Absolute Quantification

Environmental DNA (eDNA) has revolutionized ecological monitoring. This non-invasive, highly sensitive technique allows researchers to detect the presence of species—from bacteria to blue whales—from simple samples of water, soil, or even air. It's a powerful tool for biodiversity monitoring, invasive species detection, ecosystem health assessment, and diet analysis.

But for all its power, standard eDNA metabarcoding has a hidden limitation that can mask the true ecological story. It primarily provides relative abundance.

This data tells you that 20% of your fish reads belong to Species A and 80% to Species B. But it doesn't tell you if that's 20 fish versus 80 fish, or 200,000 versus 800,000. It doesn't tell you if the total number of fish in the lake is increasing or decreasing.

For researchers who need to move from "what's there" to "how much is there," there is a solution. This is your complete guide to eDNA absolute quantification.

The Hidden Limitation of eDNA: Why "Relative Abundance" Isn't Enough

Relative abundance data is a powerful screening tool, but it's a percentage, not a census. This creates two fundamental problems for researchers.

1. The Comparison Problem

Imagine you are tracking an invasive carp species at two different locations in a river system.

• Site A: Your eDNA metabarcoding results show the invasive carp at 10% relative abundance.
• Site B: The results show the carp at 50% relative abundance.

The obvious conclusion is that Site B has a much worse invasion. But what if the total amount of fish eDNA at Site A is 100 times greater than at Site B due to a massive confluence of fish?

• Site A (10%) could be 10% of 10,000,000 eDNA copies/liter = 1,000,000 copies/liter
• Site B (50%) could be 50% of 100,000 eDNA copies/liter = 50,000 copies/liter

In this scenario, the "low abundance" site actually has 20 times more carp eDNA, indicating a far larger and more established population. Relative abundance data alone would have led you to the wrong conclusion.

2. The Longitudinal Problem

Consider a wetland restoration project. You collect eDNA samples every month to track the recovery of a key amphibian species.

• Month 1: The target species is at 2% relative abundance.
• Month 6: The target species is at 10% relative abundance.

This looks like a resounding success. But what if, during those six months, a massive algal or bacterial bloom occurred? This bloom would release an enormous amount of non-target eDNA, diluting your sample. The total eDNA pool (the denominator) increased, making your amphibian's "slice of the pie" (the numerator) look bigger, even if the amphibian population itself stayed the same... or even declined.

Without a fixed, absolute measure, you cannot confidently compare eDNA data across different samples, sites, or time points. Just as our 16S amplicon sequencing services moved to include absolute quantification for a truer picture of the microbiome, eDNA metabarcoding must do the same for a truer picture of the macro-environment.

Giving Data Real Meaning: What is eDNA Absolute Quantification?

eDNA absolute quantification solves this problem by converting your sequencing data from proportions into concentrations.

Instead of "20% of reads," you get a hard number: "1,500 eDNA copies per liter of water" or "50,0g00 eDNA copies per gram of soil."

This single shift changes everything.

• True Comparisons: You can now confidently compare Site A (1,000,000 copies/L) to Site B (50,000 copies/L) and know exactly which site has a greater biological footprint.
• Longitudinal Accuracy: You can track your amphibian population and know if its concentration is actually rising from 2,000 copies/L to 10,000 copies/L, regardless of what other species are doing.

This unlocks a higher level of ecological insight, allowing for accurate biomass estimation, reliable population density mapping, and defensible data for policy and management decisions.

qMiSeq-derived eDNA concentrations show significant positive relationships with captured individuals and biomass for multiple fish taxa across sites. (Tsuji S. et al. (2022) Scientific Reports).

To meet this critical research demand, CD Genomics offers a comprehensive eDNA Absolute Quantification Service. As part of our complete microbiome sequencing services, we help you design the best quantification strategy for your project, from sample to answer.

There are two primary methods for achieving this. Let's dive deep into how they work.

Method 1: The Spike-in Control Strategy - An Internal "Ruler" for Your Sample

The spike-in method is a clever solution that builds a conversion factor directly into each sample. It's like adding a 1-ounce measuring cup of red dye (the spike-in) to several opaque, differently-sized buckets of water (your samples). By seeing how diluted the red dye becomes in each bucket, you can accurately calculate the total volume of water.

The Core Principle: What is a Spike-in?

A "spike-in" is an exogenous (foreign) DNA sequence. It is a synthetic fragment of DNA with several key properties:

1. Known Sequence: It is 100% artificial and has no homology to any known organism, ensuring it won't be mistaken for a real species.
2. Known Concentration: This is the most critical part. You know exactly how many copies you are adding (e.g., 10,000 copies).
3. Amplifiable: It is designed to be amplified by PCR, either by its own specific primers or by the same "universal" primers used for your target group.

This known quantity is added to your extracted eDNA before the PCR amplification step.

Step-by-Step Workflow for the Spike-in Method

1. Sample Collection & Extraction: You collect your water, soil, or feces and extract the total DNA as usual.

2. Spiking: This is the key step. A precise, known copy number of the spike-in (e.g., 10,000 copies) is pipetted into each individual DNA extract.

3. PCR Amplification: The sample is amplified. The primers in the reaction amplify both your target eDNA (from fish, amphibians, etc.) and the spike-in DNA.

4. NGS Sequencing: The entire pool of amplicons is sequenced through a standard eDNA metabarcoding workflow.

5. Bioinformatics Analysis: This is where the calculation happens.

• The pipeline first counts the reads for all your species (OTUs) and for the spike-in.
• Let's say in Sample A, the spike-in received 50,000 reads.
• We know the input for that spike-in was 10,000 copies.
• We can now calculate a sample-specific conversion factor:

  

• Now, we look at your species of interest. Species X received 300,000 reads in the same sample.
• We calculate its absolute abundance:

  

6. Final Normalization: This number (60,000 copies) is then normalized back to your original sample volume (e.g., per liter of water), giving you the final, absolute concentration.

Advantages: Why Choose the Spike-in Method?

The single greatest advantage of the spike-in method is its ability to automatically correct for PCR inhibition.

Complex environmental samples (soil, sediment, feces, some water) are notoriously "dirty." They are filled with PCR inhibitors like humic acids, fulvic acids, and polysaccharides. These compounds bind to the DNA polymerase enzyme or to the DNA itself, stalling the PCR and reducing its efficiency.

This is a nightmare for quantification, as a "low" result could mean "low eDNA" or "high inhibition."

The spike-in solves this. Because the spike-in is in the same tube as the sample DNA, it is subjected to the exact same level of inhibition. If inhibitors in Sample A reduce the PCR efficiency by 50%, both the eDNA reads and the spike-in reads will be 50% lower.

Since the calculation is based on the ratio between them, the inhibitory effect is canceled out. This "internal calibration" is the most robust way to get accurate quantification from difficult samples.

Limitations and Considerations

1. Cost: The spike-in "competes" for sequencing reads. To ensure you detect both the spike-in and your rare species, you must sequence at a higher depth, which increases the cost of the project.
2. Pipetting Accuracy: The entire calculation hinges on the precision of the initial spike. An error in pipetting the 10,000-copy spike-in (e.g., only adding 9,000 copies) will create a 10% systematic error across every calculation for that sample.
3. Upstream Error: This method corrects for PCR inhibition but not for DNA extraction inefficiency. If your extraction protocol recovers 80% of fish DNA but only 50% of bacterial DNA, the spike-in (which is added after extraction) cannot correct for this.

Method 2: The eDNA Relative Abundance + qPCR Combination

The second major strategy is a "two-step" approach that decouples identification from quantification.

Think of it this way: You have a large, mixed bag of fruit.

• Step 1 (Sequencing): You pull out every piece of fruit, identify it, and find that 20% are apples and 80% are oranges.
• Step 2 (qPCR): You put all the fruit back and weigh the entire bag, finding it weighs 10 pounds.
• Calculation: You can now calculate the absolute amount: 2 pounds of apples (20% of 10) and 8 pounds of oranges (80% of 10).

The Core Principle: A "Two-Step" Calculation

This method uses two different lab techniques on the same DNA extract:

1. NGS (eDNA metabarcoding) is used to get the relative abundance (the 20%/80% split).
2. Quantitative PCR (qPCR) is used to get the total quantity of a target gene for the entire group (the 10-pound total weight).

Step-by-Step Workflow for the qPCR Method

1. Sample Collection & Extraction: Same as before.

2. Aliquot: The extracted DNA is split into (at least) two separate tubes.

3. Path A - Sequencing (The "Proportions"):

• Tube 1 is used for your standard eDNA metabarcoding library preparation, PCR, and NGS sequencing.
• Your bioinformatics analysis pipeline delivers the relative abundance data: e.g., Species A = 15%, Species B = 60%, Species C = 25%.

4. Path B - Quantification (The "Total"):

• Tube 2 is used for a qPCR experiment.
• Crucially, this qPCR uses universal primers for the entire group of interest (e.g., "MiFish" primers for all fish, "18S" for all eukaryotes).
• The qPCR machine runs this sample against a standard curve (a series of DNA samples with known copy numbers) to determine the total number of gene copies for that group.
• The result is a hard number, e.g., "5,000,000 total fish 12S gene copies per mL of extract."

5. The Calculation:

• The two results are multiplied together.
• Total Fish Copies = 5,000,000 copies/mL
• Relative Abundance of Species A = 15%
• Absolute Abundance of Species A = 5,000,000 * 0.15 = 750,000 copies/mL

6. Final Normalization: This value is then converted back to your original sample units (per liter of water, etc.).

Advantages: Why Choose the qPCR Combination?

The killer feature of this method is flexibility.

Let's say you have five years of eDNA metabarcoding data sitting in your freezer. You can't go back in time and add a spike-in. But you can pull those old DNA extracts, run a new qPCR experiment (Path B) on them, and retroactively "upgrade" your entire historical dataset from relative to absolute quantification.

This is an incredibly powerful and cost-effective way to get new life from old data. It's also useful if you only care about the absolute abundance of one specific species, as you can run a species-specific qPCR and skip the expensive universal quantification.

Limitations and Considerations

1. The PCR Inhibitor Problem: This is the method's Achilles' heel. The qPCR reaction (Path B) is highly vulnerable to PCR inhibitors. If humic acids in Sample A reduce its qPCR efficiency, the "Total Copies" number will be systematically underestimated. This error then cascades to every single species calculated for that sample.
2. Primer Bias: The "universal" primers used for the qPCR step are never truly universal. They always have biases, amplifying some species more efficiently than others. This "primer bias" can skew the "Total Copies" number, introducing another layer of error.
3. Standard Curve Accuracy: The qPCR result is only as good as the standard curve it's measured against. This standard (usually a plasmid) must be perfectly quantified and handled, as any error here becomes an error in every sample.

Decision Guide: Spike-in vs. qPCR? How to Choose the Best Method for Your Study

Which method is right for you? It depends entirely on your samples and your research question.

The core trade-off is this: The Spike-in method offers superior accuracy in the face of PCR inhibition but is more expensive and must be planned from the start. The qPCR method offers incredible flexibility and is cost-effective for upgrading old data, but it is highly vulnerable to PCR inhibition and primer bias.

Pro-Tip: For the highest level of accuracy, many researchers now use digital PCR (dPCR) instead of qPCR for Path B. dPCR partitions the sample into thousands of tiny droplets, making it a "counting" method that is far less sensitive to PCR inhibitors. At CD Genomics, our team can help you navigate these advanced custom sequencing solutions.

Case Study: How eDNA Absolute Quantification Aided the Detection of the Yangtze Finless Porpoise

This isn't just a theoretical exercise. Absolute quantification provides critical insights that change scientific conclusions.

Publication: Environment International (Impact Factor: 9.1)

DOI: 10.1016/j.envint.2024.108706

The Research Question: Researchers needed to know the most effective eDNA collection method for monitoring aquatic life, including the endangered Yangtze finless porpoise. They compared a traditional, labor-intensive "active filtration" method with a new, simple "passive eDNA sampler" (PEDS).

The Relative Abundance (Metabarcoding) Results:

At first glance, the methods looked comparable. The metabarcoding data showed that both active filtration and the new PEDS captured similar species richness and similar community structure. If the study had stopped here, the conclusion would have been weak: "Both methods are fine."

The Absolute Quantification (qPCR) Results:

This is where the story changed completely. The researchers used species-specific qPCR to get the absolute concentration of porpoise eDNA.

1. Detection Rate: The PEDS method detected the endangered porpoise at 7 sampling sites, while the traditional filtration method only detected it at 2.
2. Concentration: Even more importantly, the absolute concentration of porpoise eDNA captured by PEDS was significantly higher than the concentration captured by filtration.

qPCR results for yangtze finless porpoise edna recovered by water filtration and peds. (Chen, Xiaoyu, et al., Environment International, 2024)

The "Aha!" Moment (The Conclusion):

Without absolute quantification, the researchers could only say "the porpoise was present or absent." They would have completely missed the true story: that the PEDS method was quantifiably better at capturing and concentrating the eDNA from this rare, high-priority species.

This case proves that the importance of eDNA absolute quantification for biodiversity studies cannot be overstated. It's essential for validating new methods, comparing sampling efficiencies, and making accurate ecological assessments.

The Time to Act is Now: The Era of eDNA Absolute Quantification

The field of eDNA research is moving past simple "presence/absence" checklists. To unlock true ecological insights, we need to speak the language of "how much." Absolute quantification provides the robust, defensible data needed for:

• True ecological comparisons between sites.
• Accurate monitoring of restoration efforts or population decline.
• Reliable density mapping of invasive species.
• Defensible data for conservation policy and management.

From Experimental Design to Advanced Bioinformatics Analysis

Making the right choice (Spike-in vs. qPCR vs. dPCR) is the most critical first step. It depends entirely on your sample type (high-inhibition soil vs. clean water), your research goals (comparing two sites vs. tracking one species), and your budget.

Don't leave your data's full potential untapped. The PhD-level scientific team at CD Genomics can support your entire workflow. We provide custom sequencing solutions tailored to your project, from initial experimental design to our robust bioinformatics analysis pipeline that translates your raw reads into actionable, absolute data.

[Contact Us for a Free Project Consultation]

Frequently Asked Questions (FAQ) about eDNA Absolute Quantification

1. What is the main difference between relative and absolute eDNA quantification?

Relative quantification from standard metabarcoding expresses the proportion of a species among all reads in that sample (e.g., "Species A is 10% of the reads"), whereas absolute quantification reports the concentration of that species relative to the original sample volume or mass (e.g., "Species A is at 1,000 copies per liter of water"). The latter enables valid comparisons across samples and through time.

2. How do I deal with PCR inhibitors in my eDNA samples?

PCR inhibitors (like humic acids in soil) can cause your quantification to be artificially low. The Spike-in Control Method is the best solution for this, as its internal "ruler" is affected by inhibitors in the same way as your sample, allowing it to automatically correct the final calculation. Alternatively, using dPCR instead of qPCR can also overcome most inhibition.

3. Is dPCR (digital PCR) better than qPCR for absolute quantification?

In many cases, yes. dPCR (digital PCR) is an "endpoint" method that counts individual DNA molecules in thousands of droplets. It is generally more precise and far less sensitive to PCR inhibitors than qPCR, which relies on a standard curve. dPCR is considered a next-generation standard for quantification, though it can be more expensive.

4. Can I convert my old eDNA metabarcoding data to absolute abundance?

Yes! This is the primary advantage of the Relative Abundance + qPCR Method. If you have saved your extracted DNA samples (even in a freezer), you can perform a new qPCR or dPCR experiment on them to determine the "total" copy number. You can then use the relative abundance data from your original sequencing run to calculate the absolute abundance for every species.

5. How accurate is eDNA absolute quantification?

Accuracy depends on the method and error control: in the spike-in approach it hinges on precise pipetting of the spike-in, while in the qPCR approach it depends on the quality of the standard curve and the absence of inhibitors. When executed correctly, either method yields a far more accurate ecological picture than relative abundance alone.

References

1. Chen, Xiaoyu, et al. "Passive eDNA sampling facilitates biodiversity monitoring and rare species detection." Environment International 187 (2024): 108706.
2. Ding, L., Fan, X., Li, J. et al. Passive eDNA sampling characterizes fish community assembly in the Lancang River of Yunnan, China. Biology 14, 1080 (2025).
3. Li, X., Wang, Y., Li, J. et al. qPCRtools: An R package for qPCR data processing and visualization. Frontiers in Genetics 13, 1002704 (2022).
4. Tsuji, S., Inui, R., Nakao, R. et al. Quantitative environmental DNA metabarcoding shows high potential as a novel approach to quantitatively assess fish community. Scientific Reports 12, 21524 (2022).
5. Ushio, S. et al. Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2, e23297 (2018).
6. Miya, M., Sato, Y., Fukunaga, T. et al. MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: detection of more than 230 subtropical marine species. Royal Society Open Science 2, 150088 (2015).
7. Hindson, B.J., Ness, K.D., Masquelier, D.A. et al. High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Analytical Chemistry 83, 8604–8610 (2011).