Note: This analysis reflects concerns I have expressed in several of my past YouTube videos (see references) but also draws heavily on and complements the detailed work of Gutsick Gibbon on her YouTube channel, whose thorough examination of both the Yoo et al. (2025) Nature paper and Jeffrey Tomkins’ methodology has been invaluable. I encourage readers to watch her video “Okay How Similar are Humans and Chimps Genetically Now That We Have Full Genomes?” for further exploration of these data, including her correspondence with one of the paper’s authors, Dr. Smeds.

Introduction: The Claim That Keeps Getting Louder

In a recent interview on the Creation Ministries International YouTube channel, Dr. Rob Carter makes a dramatic claim: humans and chimpanzees are not 1% different in their DNA, as the public has long been told, but 10–15% different. From this, he concludes that evolutionary biology cannot account for these differences within the available timeframe, and therefore the Bible’s account of separate creation is vindicated.

The argument is emotionally compelling. It has the structure of a simple gotcha: scientists said 1%, the real number is 15%, therefore they lied and evolution fails. But as I will demonstrate in this article, the argument rests on a fundamental conflation of two entirely different measurements, a failure to provide comparative context, several serious misrepresentations of population genetics, and a convenient omission of the data that would undermine the entire rhetorical framework.

This is not a new strategy. Jeffrey Tomkins at the Institute for Creation Research has been making essentially the same claim for over a decade, and Carter himself published a paper in the Journal of Creation in 2024 arguing for an approximately 85% overall similarity. What is new is the 2025 Nature paper by Yoo et al., “Complete Sequencing of Ape Genomes,” which Carter and Tomkins are now claiming as vindication of their position. It is anything but.

Two Numbers, Two Measurements: The Core Deception

At the heart of Carter’s argument lies a bait-and-switch that, once you see it, is impossible to unsee. He presents his audience with two numbers and treats them as if they are the same kind of measurement. The first number is the traditional ~98.5–99% similarity figure, which refers to the percentage of nucleotide identity in aligned, orthologous sequences between human and chimpanzee genomes. This is the figure that appears in textbooks and museums. It measures how similar the two genomes are in the regions where they can be directly compared—gene for gene, base pair for base pair.

The second number, the ~85% figure Carter and Tomkins trumpet, is what we might call total genome identity, and it includes every base pair in both genomes, whether or not those base pairs can be aligned at all. This number drops substantially because it incorporates large structural differences: repetitive satellite DNA, centromeric sequences, copy number variations, large insertions and deletions, and other regions that are highly variable even within a single species.

Here is why this matters, and here is the point that Carter never makes for his audience: these same types of structural differences produce surprisingly large numbers even when comparing one human genome to another human genome.

The Elephant in the Room: Human-to-Human Variation

This is the critical piece of context that Carter and every other young-earth creationist commentator on this paper systematically omits, and it is the single most important point in this entire discussion.

When scientists completed the first true telomere-to-telomere (T2T) human genome in 2022, they could finally compare complete human genomes against each other without the gaps that had previously made such comparisons incomplete. What they found was startling to no one who understood genomics, but would be shocking to Carter’s audience if he told them about it: two complete human genomes can differ by 6–10% using the same total genome identity metric that produces the “85%” figure for human–chimpanzee comparisons.

The supplementary data of the Yoo et al. (2025) Nature paper itself reveals this. Supplementary Table III.19 shows the new T2T human genome (CHM13) aligning at only about 92–93% one-to-one identity with other human reference genomes. A 2023 paper on the T2T assembly of a Han Chinese individual (HG005) found approximately 330 megabases of sequence exclusive to that individual compared to CHM13. That is roughly 10% of the genome. As Gutsick Gibbon correctly noted in her video, two haplotypes within the same individual orangutan can differ at the megabase level in centromeric regions.

Let me put this plainly: by the accounting method that Carter uses to arrive at his 85% figure, you and I might be only 90–94% “similar.” Does this mean we are different species? Does this mean we don’t share a common ancestor? Of course not. It means that the raw alignment metric is capturing enormous amounts of variation in non-functional repetitive DNA that accumulates rapidly and tells us relatively little about organismal differences.

Carter never mentions any of this. Not once in a 35-minute interview does he offer his audience a single comparative data point. He never tells them what total genome identity looks like for two humans, for two chimpanzees, for chimp versus bonobo, or for Bornean versus Sumatran orangutans. Without that context, the “85%” figure is meaningless—or rather, it is meaningful only as a rhetorical weapon. This is not an oversight. It is a pattern.

The Pairwise Comparison Matrix Carter Won’t Show You

If Carter were being honest with his audience, he would present the data as a comparative matrix. This is what I have called the “apples-to-apples” comparison. Here is what such a matrix would look like, using approximate values from the published literature and the Yoo et al. supplementary data:

Method 1: Aligned sequence identity (SNPs in orthologous regions)

Human vs. Human: ~99.5–99.9%

Human vs. Neanderthal: ~99.5%

Chimp vs. Chimp: ~99.3–99.8%

Chimp vs. Bonobo: ~99.4–99.6%

Human vs. Chimp: ~98.5–99%

Human vs. Gorilla: ~97%

Any two great apes: ~95%+

Method 2: Total genome identity (including all unalignable regions)

Human vs. Human (T2T): ~90–94%

Chimp vs. Bonobo: ~87–88%

Human vs. Chimp: ~85–88%

Human vs. Gorilla: ~84–86%

Bornean vs. Sumatran Orangutan: ~90%

Notice the pattern. By Method 2, the human–chimp comparison (~85–88%) is only modestly lower than the human–human comparison (~90–94%) and is quite close to the chimp–bonobo comparison (~87–88%). The relative ordering is exactly what evolutionary theory predicts: organisms that diverged more recently are more similar, regardless of which method you use. By both methods, humans are always closer to chimps than to gorillas, chimps are always closer to bonobos than to humans, and the phylogenetic tree is unchanged.

Carter’s rhetoric depends entirely on his audience never seeing this matrix. If they did, the shock value of “85%” evaporates immediately.

Carter’s Misrepresentation of the Nature Paper

Carter implies that the authors of the Yoo et al. paper “buried” their results in supplementary material because the findings were embarrassing to evolutionary biology. This is a conspiratorial framing that misunderstands how major genomics papers work. The Yoo et al. paper is a comprehensive resource paper characterizing newly completed ape genomes across dozens of dimensions: centromeric structure, segmental duplications, transposable elements, gene families, immune loci, and much more. It runs 17 pages in the main text with 173 pages of supplementary material. Detailed alignment statistics belong in supplementary tables because that is standard practice for a resource paper of this scope.

More importantly, the authors explicitly discuss the gap divergence in the main text. They write that “12.5–27.3% of an ape genome failed to align or was inconsistent with a simple one-to-one alignment.” They note that gap divergence showed “a five-fold to 15-fold difference in the number of affected megabases when compared to single nucleotide variants,” attributing this to “rapidly evolving and structurally varied regions of the genome as well as technical limitations of alignment in repetitive regions.” None of this was hidden. It was discussed, contextualized, and placed within the broader framework of ape genome evolution.

Critically, the paper also provides data showing that these large structural differences are not unique to the human–chimpanzee comparison. Gorillas show the greatest amount of structurally divergent regions of any species examined. Orangutans show enormous variation in segmental duplications. Bonobos have dramatically miniaturized centromeres compared to chimpanzees despite having diverged only about 1.6 million years ago. The paper is a celebration of the dynamic, rapidly evolving regions of ape genomes—not an embarrassed admission of evolutionary failure.

Population Genetics: Where Carter’s Math Falls Apart

Carter makes a series of claims about population genetics that range from oversimplified to simply wrong. Let me address them in order.

Claim: “Mutation rate equals the rate of change.” This is a garbled version of a real principle in population genetics, but Carter applies it incorrectly. The principle he is gesturing toward is that for neutral mutations in a population at equilibrium, the rate of substitution (fixation of new mutations) equals the mutation rate, independent of population size. This is a foundational result from Kimura’s neutral theory. But Carter uses this to argue that ~100 mutations per generation over ~200,000–300,000 generations can only account for about a 1% change—and therefore anything more than 1% difference is unexplainable.

This calculation contains multiple errors. First, human and chimpanzee lineages have been diverging independently since their last common ancestor. Mutations accumulate on both lineages, so the total divergence is the sum of changes on both branches, not just one. Second, the effective mutation rate per generation in primates is estimated at roughly 70–100 new mutations, spread across a genome of ~3 billion base pairs. Over ~200,000 generations on each lineage (400,000 total generational events), with ~70–100 mutations per generation, the arithmetic actually works out to approximately 28–40 million single nucleotide changes—which is remarkably close to the ~35 million SNPs reported in the 2005 chimpanzee genome paper. The math works fine.

Claim: “99.999% of new mutations are lost.” Carter presents this as if it means evolution needs astronomically more mutations than actually occurred. While it is true that any individual new neutral mutation has a very low probability of eventual fixation (approximately 1/2N for a diploid population, where N is the effective population size), the total number of mutations entering the population each generation is enormous. With an effective population size of even 10,000 and ~80 new mutations per individual per generation, the number of new mutations entering the population every generation is on the order of millions. The vast majority are indeed lost, but a predictable fraction fix. This is not a problem for evolutionary theory. It is a solved mathematical framework that has been producing accurate predictions for decades.

Claim: “Evolution needs mutations to appear, spread to everyone, and the original version to be lost.” Carter here conflates two different things: the number of fixed differences between species and the total number of differences. Many of the differences between human and chimpanzee genomes are not fixed differences at all. They include polymorphisms segregating in one or both species, copy number variants, structural rearrangements that arise through mechanisms other than point mutation, and transposable element insertions that can copy themselves throughout the genome in a single generation. The structural differences that inflate the total genome identity number to ~15% are overwhelmingly of this latter type. They are not SNPs that require individual fixation events.

The Tomkins Problem: A History of Methodological Failures

Carter aligns himself with Jeffrey Tomkins of the Institute for Creation Research, who has been claiming an 85% human–chimpanzee similarity for over a decade. But the history of Tomkins’ work is a cautionary tale about what happens when ideological conclusions precede data analysis.

In his early studies, Tomkins reported human–chimp similarities as low as 70%. This was eventually traced to a bug in the BLASTN algorithm he was using, which had been documented by the software developers themselves. After correcting for this, his numbers rose to the mid-80s. But even his corrected methodology has been criticized on multiple grounds. As Carter himself acknowledged in his 2024 Journal of Creation paper, Tomkins’ 2018 study produced a bimodal distribution of similarity scores with peaks in the high-60s and high-90s, with almost no matches in the 84% range he reported as his average. Taking the mean of a bimodal distribution is statistically meaningless—it describes a number that essentially no data points actually occupy.

More damaging is what Tomkins has never done. As I and Gutsick Gibbon have both emphasized repeatedly: Tomkins has never applied his methodology to a control comparison. He has never run chimp versus bonobo. He has never run human versus human. He has never run human versus Neanderthal. If he did, his methodology would almost certainly produce numbers that are similarly “shocking” for those comparisons—and that would reveal that his approach systematically underestimates similarity for all species comparisons, not just human–chimp. The absence of control comparisons is the single biggest methodological red flag in Tomkins’ entire body of work.

What the Data Actually Show About Human Uniqueness

None of this is to deny that humans and chimpanzees are genuinely different organisms. They obviously are. But the differences between us are concentrated in specific, identifiable categories:

First, the protein-coding regions of our genomes remain over 99% similar, and 99–99.6% of human protein-coding genes are represented in the other ape genomes. This is a number that actually went up with the new T2T assemblies. Second, the key differences between humans and chimpanzees appear to lie primarily in gene regulation: where, when, and how much specific genes are expressed, particularly in the brain. This has been the prevailing hypothesis since King and Wilson proposed it in 1975, and the new genome data continue to support it. Third, a small number of human-specific genes have been identified, including SRGAP2C and NOTCH2NL, which are associated with frontal cortex development. These are precisely the kinds of specific, testable findings that advance our understanding of human uniqueness.

By contrast, the ~15% total genome difference is driven overwhelmingly by repetitive, non-functional DNA: satellite repeats, centromeric sequences, transposable element expansions, and large structural variants in regions that are not under selective constraint. As Gutsick Gibbon emphasized, these regions accumulate differences so rapidly that even two haplotypes within a single individual orangutan can differ by megabases in centromeric regions. Counting every one of these base pairs as an “individual difference” between species is a bit like comparing two editions of an encyclopedia and counting every difference in the blank margins, page numbers, and printing artifacts alongside the actual text. You get a bigger number, but it tells you surprisingly little about how different the books actually are.

The Unfalsifiable Framework

There is a telling moment in Carter’s interview that deserves attention. He says: “In the biblical model, we don’t make a prediction. God could have made us as similar to chimpanzees as He chose. We could be 1% different or we could be a lot more. It doesn’t matter.”

This is an extraordinary admission. Carter is telling us, up front, that no genetic data of any kind could possibly count against his model. If humans and chimps were 99.9% similar, that would be fine—God chose to make them similar. If they were 50% similar, that would also be fine—God chose to make them different. The biblical model, as Carter frames it, makes no predictions and can accommodate any result. This is the textbook definition of an unfalsifiable hypothesis.

By contrast, the evolutionary model makes specific, testable predictions. It predicts that humans and chimpanzees should be more similar to each other than either is to gorillas. It predicts that the degree of difference should be proportional to divergence time. It predicts that protein-coding regions should be more conserved than non-functional regions. It predicts that the phylogenetic tree derived from genetic data should match the tree derived from anatomy and the fossil record. Every single one of these predictions is confirmed by the Yoo et al. data.

Carter then pivots to arguing that evolutionary theory can’t explain the differences. But notice the rhetorical move: when the data appear to support evolution, it doesn’t matter for his model; when the data appear (in his misreading) to challenge evolution, it matters enormously. This is not how honest scientific reasoning works. You do not get to be immune to evidence against your position while simultaneously claiming evidence against your opponent’s position.

Why This Matters for Christians

I write this critique as a Christian who takes Scripture seriously. I am not arguing against the uniqueness of humanity, the reality of the image of God, or the truth of the gospel. I am arguing against the misinformation that organizations like Creation Ministries International and the Institute for Creation Research disseminate to well-meaning Christians who trust them to be honest with the data.

Carter’s argument depends on his audience not understanding comparative genomics. It depends on them never seeing the human–to–human comparison data. It depends on them never asking, “What do these same numbers look like for chimps and bonobos?” When those questions are asked and answered honestly, the rhetoric collapses.

The doctrine that God works providentially through natural processes—what Reformed theology calls the doctrine of secondary causes—provides a far more robust theological framework than the gap-dependent arguments Carter offers. Arguments built on “science can’t explain X” are fragile. They depend on current scientific limitations remaining permanent, and the history of science shows us that gaps close. When your faith depends on a gap in scientific knowledge, you are building on sand.

Christians deserve better than to be told that the latest Nature paper confirms their faith when in reality that paper’s authors see nothing in their data that challenges the standard evolutionary framework, and when the data actually strengthen the evidence for common ancestry by providing a more complete picture of genomic evolution across the ape lineage.

Conclusion

Dr. Rob Carter’s interview presents a misleadingly simple narrative: the old number was 1%, the new number is 15%, evolution can’t explain 15%, therefore the Bible wins. Every step in this chain is either wrong or misleading.

The “old number” of ~1% and the “new number” of ~15% are not the same measurement. They are apples and oranges. When you use the same method consistently, human–chimp similarity has not dramatically changed. Protein-coding similarity has actually increased slightly with the new T2T assemblies. The total genome identity metric produces large numbers for all species comparisons, including comparisons between individual humans. The phylogenetic relationships are unchanged regardless of which metric you use. The population genetics arguments Carter offers are either garbled or wrong. And Tomkins’ “vindication” is no such thing—his methodology remains untested against basic controls.

The 2025 Yoo et al. paper is a genuinely remarkable scientific achievement. It gives us the most complete picture of ape genome evolution ever assembled. It deserves to be discussed accurately and in context, not strip-mined for rhetorical ammunition by people who have predetermined their conclusions. I encourage anyone who watched Carter’s interview to read the actual paper, to watch Gutsick Gibbon’s thorough video analysis, and to ask the hard question: am I being given the whole picture, or only the parts that serve a particular narrative?

Blessings,

Joel Duff

References

1. Yoo, D., Rhie, A., Hebbar, P., et al. (2025). Complete sequencing of ape genomes. Nature, 641, 401–418.

2. Chimpanzee Sequencing and Analysis Consortium. (2005). Initial sequence of the chimpanzee genome and comparison with the human genome. Nature, 437, 69–87.

3. King, M.C. & Wilson, A.C. (1975). Evolution at two levels in humans and chimpanzees. Science, 188(4184), 107–116.

4. Nurk, S., Koren, S., Rhie, A., et al. (2022). The complete sequence of a human genome. Science, 376(6588), 44–53.

5. Liao, W.W., Asri, M., Ebler, J., et al. (2023). A draft human pangenome reference. Nature, 617, 312–324.

6. Du, Z., Ma, L., Qu, S., et al. (2023). T2T-assembled diploid reference genome for Han Chinese. Science Bulletin, 69(2), 183–186.

7. Seaman, J. & Buggs, R.J.A. (2020). FlexiMAP: A regression-based method for discovering differential sequence conservation in multiple alignments. Bioinformatics, 36(5), 1414–1420.

8. Tomkins, J.P. (2018). Comparison of 18,000 de novo assembled chimpanzee contigs to the human genome yields average BLASTN alignment identities of 84%. Answers Research Journal, 11, 205–209.

9. Tomkins, J.P. (2016). Analysis of 101 chimpanzee trace read data sets: Assessment of their overall similarity to human and possible contamination with human DNA. Answers Research Journal, 9, 294–298.

10. Carter, R.W. (2024). Reassessing human–chimpanzee genetic similarity. Journal of Creation, 38(1), 93–103.

11. Britten, R.J. (2002). Divergence between samples of chimpanzee and human DNA sequences is 5%, counting indels. Proceedings of the National Academy of Sciences, 99(21), 13633–13635.

12. Kimura, M. (1968). Evolutionary rate at the molecular level. Nature, 217, 624–626.

13. Gutsick Gibbon (Erika). (2025). “Okay How Similar are Humans and Chimps Genetically Now That We Have Full Genomes?” YouTube video. https://youtu.be/kHsPj1Mo9pA?si=o2pOyGg_qUSmrOsH

14. Duff, J. (2025). “Chimpanzee and Human DNA: Misused Statistics and Creationist Confusion.” YouTube video: https://youtu.be/hf4WgEON84o?si=0ncLys4gQ-m4sBPM

15. Duff, J. (2025). “Chimp Genome Sequencing Results: What Ken Ham Won’t Tell You.” YouTube video: https://youtu.be/gV2VutD0kZo?si=79gDCIRIKPOtevHV