In September 2015 young earth creationist Dr Nathaniel Jeanson published a study attempting to show that molecular clocks and the mutation rate support the young earth creation narrative. This was followed up by another study in April 2016.
The molecular clock uses the mutation rate of DNA to deduce the time that has passed since different life forms diverged. It operates under the assumption that mutations to some parts of the genome happen like clockwork. This presents a particular problem for young earth creationists because there is a lot of genetic diversity present within modern species. This diversity, in the absence of hyper-mutation, must have taken hundreds of thousands of years to evolve.
The molecular clock works by counting up the number differences between two individuals. If we know the rate of change it becomes possible to work out how many generations it took for these differences to accumulate. Then we can also infer how long since these two lineages stemmed from a common origin. This has been used to investigate a number of important issues such as the date of divergence between modern humans and Neanderthals.
To give an illustration of how this works, let’s say you were to meet a stranger and compare your Y-Chromosomes. You find that there are 12 differences that separate you. This would imply that on average each of your patrilineal lineages have undergone 6 changes since the time that you last shared a common patrilineal ancestor. You could now look up the mutation rate for the human Y-Chromosome (about 1.8 new mutations each generation) and you would find that you are probably second cousins. You share a common patrilineal ancestor going back 3 generations.
This technique can also be done using female ancestors and mitochondrial DNA. The mutation rate will be different but the principal is the same. If we were to find the two most different humans alive today and count up the differences in mitochondrial DNA between them, we should be able to calculate the amount of time that has passed since they last shared a common matrilineal ancestor – commonly called mitochondrial eve.
The creationist mutation rate
This is what Jeanson attempted to do in his most recent study. He referenced a paper from 2013 which looked at 7098 mitochondrial genomes. The authors of this paper found that the two most different people in their dataset – who were both of African descent – had 123 differences between them. The next closest pair consisted of an African and a European individual who had 122 differences between them.
Jeanson then took this maximum genetic distance (123) and a mitochondrial mutation rate which he had manufactured in his previous 2015 study. Based on this he concluded that these individuals could only be separated by a few thousand years at most. A figure conveniently conforming to AIG’s belief that women were created from a rib in 4004 BC.
The problem lay with his mutation rate. It was wrong – horribly wrong.
The mutation rate he used was 0.197 mutations per generation. Assuming a generation time of 20 years and given that the mitochondrial genome is 16,569 nucleotides in length, this works out to a mutation rate of 5.94 x 10-7 mutations per nucleotide per year. Or to put it another way, a new mitochondrial mutation every 100 years.
So how does this compare with the widely accepted mutation rate for the mitochondrial genome in humans?
This was estimated fairly accurately back in 2009 by Soares et al. They found the mutation rate for the entire human mitochondrial genome to be 1.665 × 10−8 substitutions per nucleotide per year. In other words, a new mutation every 3624 years. This was found to agree well with archaeological including:
- Corroborating archaeological dating for the settlement of the Canary Islands and Remote Oceania
- Yielding an age of modern human expansion in the Americas at ∼15 kya, consistent with the archaeology.
- Accurately predicting the timing of the first modern human settlement of Europe and resettlement after the Last Glacial Maximum.
Not only did it agree well with the archaeological evidence, but when they compared their mutation rate to a rate based on looking at just synonymous mutations, they found it to be accurate.
Yet Jeanson was using a mutation rate which was 35 times greater than this observed value! How did he come up with a mutation rate so wildly different from the measured results published in scientific literature?
The manufacture of his mutation rate goes back to the original study, Jeanson 2015b, where he calculated it.
He consulted 3 studies which looked at differences in mitochondrial DNA between mothers and children. By grouping all of this data together, if he could divide the total number of changes that had been detected in one generation by the total number of mother and child pairs he could come up with a figure for the average number of mutation that happen in each generation.
Two of the studies he referenced were small and found no differences. Nevertheless Jeanson added these to his overall result which had the effect of diminishing his mutation rate. By adding null results from small studies like this he could effectively fine tune his mutation rate. Add a study with no detected changes and you can reduce your mutation rate or simply remove a study with no detected changes to increase it again.
The third study (Ding et al 2015) did purport to find differences (63 differences between mother and child for 333 pedigrees) and so this is the study we will need to look at. It becomes necessary at this point to briefly explain the difference between homoplasmic and heteroplasmic mutations.
Homoplasmic vs. Heteroplasmic mutations
Each cell within our body contains a single nuclear genome (the genome that lies within our nucleus) at the same time, each cell within our bodies contains many hundreds of mitochondria and so it is possible for a cell to have many hundreds of copies of its mitochondrial genome – not only that but if you have a mutation in your mitochondrial genome it is possible for that mutation to be in some of your mitochondria but not in others. This is known as a heteroplasmy. The opposite of this: where all of your mitochondria agree on the DNA letter at a given position is known as a homoplasmy.
Note that as well as talking about entire cells as being either hetero- or homo-, we can also talk about single nucleotide positions within the mitochondrial genome as being either hetero- or homo-
For example if 100% of the bases at position 10,564 are the letter C then that base is homoplasmic. If 60% of the bases at that position are the letter C and 40% are the letter A then that base is heteroplasmic.
The Ding study looked at mitochondria from somatic cells (lymphocytes). Typically somatic cells undergo many more divisions than germ cells and so are more likely to contain a heteroplasmy as the chance for a new mutation increases with each division of a mitochondrion. It is possible for somatic cells like lymphocytes to have heteroplasmies even though these were not inherited from the mother and will not be passed on to future generations.
Children on the other hand are more likely to inherit a homoplasy from their mothers due to a mitochondrial bottleneck in the germ-line even if mothers are heteroplasmic.
Jeanson used the Ding study and then picked the table shown below to provide him with data to create his mutation rate.
If you look at the table carefully you will see that it uses data from 333 children along with their 333 mothers. The study compared sequences from these individuals with a reference genome called rCRS (The Revised Cambridge reference sequence) The rCRS belongs to a European of haplogroup H2a2a1. A variant here is any nucleotide position which varies from the reference genome. As you can tell from the table, a variant can be a homoplasmy or a heteroplasmy.
To create his mutation rate, Jeanson only considered the line showing homoplasmies. This line showed that there were:
- 7273 homoplasmic variants in the 333 children
- 7266 homoplasmic variants in the 333 mothers
- 7238 variants common to both mother and child
Jeanson concluded from this that there were 35 variants found in children but not found in mothers and 28 variants in mothers not found in children (together these add to 63). At first this seems reasonable until you consider the fact that this line was specifically excluding heteroplasmies.
It is possible that those 35 homoplasmic variants in children already existed as mutations in mothers but in mothers they were heteroplasmic variants. Jeanson would have counted these as germline line mutations when the reality is that they weren’t. This can happen through mitochondrial bottlenecking (Figure 2) or it could happen through a later mutation in the somatic cells of the mothers (Figure 1).
It is also possible that the 28 homoplasmic variants found in mothers had become heteroplasmic in their children because of later mutations that had happened in the child’s somatic cells, giving rise to heteroplasmies in their lymphocytes even though they didn’t inherit these from their mother and wouldn’t pass these on to offspring (Figure 1). As above, Jeanson would have counted these as genuine germline mutations.
Note that for the sake of molecular clocks which work based on generational changes, we are only interested in mutations that happen in the germline.
Jeanson failed to account for all 3 of these possibilities and instead assumed that if a homoplasmic variant exists in the lymphocyte of a mother then it must also exist in the lymphocyte of her child unless a mutation has occurred in the germline – this couldn’t be more wrong. Mutations can happen in somatic cells and heteroplasmic states can be lost due to bottlenecks. If he wanted to know the generational mutation rate then he should only have been looking at germline mutations.
Given known mutation rates and the fact that they looked at 333 pedigrees, I would expect to find about 2 new mutations in germline cells as opposed to 63. The remaining 61 differences would have either happened outside the germline or they would have been the case of heteroplasmic loss due to a bottleneck.
What if Jeanson had used the correct mutation rate?
So what if, instead of making up his own mutation rate based on cherry picking studies and flawed assumptions, he had consulted the peer reviewed literature for a mutation rate instead? What would that tell us about how distantly related these two individuals are?
The published mutation rate is 1.665 × 10−8 substitutions per nucleotide per year
These individuals of African descent had 123 mutations separating them
Therefore on average each individual had changed by 61.5 mutations since their most recent common matrilineal ancestor
There are 16,569 nucleotides in the mitochondrial genome
So there are 2.76 × 10−4 substitutions per complete mitochondrial sequence per year
So 61.5 mutations will take 223,000 years
Mitochondrial eve was estimated to live between 99,000 – 234,000 years ago so this mutation count (123) and mutation rate (1.665 × 10−8 substitutions per nucleotide per year) fit with existing data.
I’ve recreated Jeanson’s graph based on the published, peer reviewed mutation rate. In order to do so, I’ve made two assumptions: mitochondrial eve lived 230,000 years ago and the biblical eve supposedly lived 6000 years ago.
In summary, Jeanson was looking for a mutation rate which needed to be about 35x greater than what has been measured in order to fit his narrative (a story about a global flood wiping out humanity 4000 years ago). He created this mutation rate by cherry picking data from one study and then combining this with null results from two other studies in order to reduce it. The study he took data from was not suited to providing a mutation rate and this is not what the authors of that study were even looking at. Finally he made a number of fatal assumptions with the data from that study which don’t stand up to scrutiny and he accidentally ended up with a mutation rate which just so happened to perfectly match the rate required to prove that humanity was 6000 years old.