Guide to Patagonia's Monsters & Mysterious beings

I have written a book on this intriguing subject which has just been published.
In this blog I will post excerpts and other interesting texts on this fascinating subject.

Austin Whittall

Thursday, November 13, 2014

On Mutations, mutation rates and Ust'-Ishim

A week ago I read the Supplementary Information on the 45 ky old Ust'-Ishim gene sequencing and also several posts that dealt with this very interesting paper.

I was intrigued by two points: one was their estimation of human mutation rates and the other was the autosomal "diversity" of modern and ancient humans as shown in SI 12. So I decided to write a post on each of those subjects. Today's post looks into the question of "mutation rates", the diversity issue will be the subject of a future post.

Molecular clocks and mutations

It is no secret that I am very skeptical about molecular clocks which tick with a constant rate and therefore allow us to measure the timing of past events such as splits between species or the dates when a given haplogroup appeared. So please read on with this in mind: I don't trust molecular clocks.

The key issues in today's post are:

  1. Mutations in humans take place at different rates. Yes, mtDNA, Y chromosome and autosomal DNA mutate at different rates when compared to each other, and that is ok, and explainable. What I mean by different rates is that when we compare the same kind of genetic material: mtDNA against mtDNA or autosomal DNA against autosomal DNA, in different human samples, the rates are different.
  2. Genetic mutations grow at different paces in men and women.
  3. The DNA of our closest relative, the chimpanzee mutates at a different rate, when compared to ours.
  4. More genetic diversity may not mean "older" populations but simply quicker mutation rates that accumulate in a population of the same age as a less diverse one.
  5. The concept of a molecular clock is unsustainable.

The "molecular clock" that is used to estimate past events in human evolution is based on the simple assumption that: mutations take place in our DNA at a certain fixed pace and that by comparing the quantity of mutations by which specimen A and specimen B differ, we can calculate the time that has elapsed since they shared a common ancestor.

Neat. But what exactly does it mean? and even more important: is it really a clock?

First of all, lets see what a mutation is:

We are all familiar DNA and its role in inheritance. DNA is a polymer that is found inside each and every one of our cells, inside the cellular nucleus. It is shaped like two intertwining coils (a "double helix") and these spirals are stabilized by molecules known as "nucleobases" (or "bases" for short) which link the coils together.

One base is attached to one of the coils and another base is attached to the other coil; and both bond together to form a "base pair".

Fortunately these bases come in four kinds: adenine (abbreviated A), cytosine (C), guanine (G) and thymine (T) and they link up in a very simple manner:

A only bonds with T and C only links up to G. So the "steps" of the ladder that joins the two spiral strands is made up of base pairs such as:


During replication, the DNA strands within the nucleus of the cell, "unwind", unzipping each strand. The exposed bases attract a new pair and form the other complementary spiral. The "unpaired" Adenine will attract thymine and link to it while the guanine will bond to cytosine and so forth. This bonding takes place on each of the unzipped strands, so from one (1) initial DNA molecule, two (2) "identical" copies are obtained.

Copies and errors, causes

Well, not exactly "identical", there are some sequence errors, and this takes place even though cells have proofreading abilities and mismatch repair mechanisms that compare original and copied DNAs.

These errors in the transcription mean that the "daughter" DNAs are not an exact replica of the "mother" DNA. So maybe an AT is lost or replaced by a GC or a duplicate is inserted so TA becomes TA TA...

In other words these are natural spontaneously occuring mutations.

Other external factors known as "mutagens" can interact with the DNA and alter the nucleotide sequence producing mutations:

  • High Energy Electromagnetic radiation. For instance X-rays or Ultraviolet light (UV).
  • Oxidizing agents (or free-radicals).
  • Chemicals, such as alkylating agents, heavy metals, solvents, monomers, agrochemicals.

These factors can disrupt the sequence of a DNA strand resulting in a "new" (mutated) chunk of genetic information, either due to deletion or addition of base pairs.

There is also a process known as "Recombination" by which two DNA molecules merge in certain sections and produce a totally new variety of DNA.

Where (and when) do mutations take place?

Those terrible summer sun-burns that I suffered as a child back in the 70s, and the accumulated doses of UV radiation that my skin has received over the years, may result in a mutation that causes skin cancer (I keep my fingers crossed and visit my dermatologist once a year just in case).

The same could be said about the X-rays that have zapped me at my dentist or during my medical check-ups or the cosmic rays that incessantly criss-cross my body. Some pesticides that I ingested via fruits or cereals, those glasses of red malbec (and its metabolized by-products) or the cigarrettes that I used to smoke are also packed with mutagens... which disrupt my DNA here and there.

But all of these mutations which are taking place in some of the 40 trillion cells that make up my body would only affect me and therefore would not be passed on to future generations unless they took place in certain cells and, during a specific time frame which differs for men and women.

The new DNA information created by mutations would pass on to my progeny only if it mutated inside my "germ cells" (sperm in my case since I am a man or, for women: their ova).

Mutations that are inherited: Meiosis

Normally our cells reproduce by a process known as "Mitosis", and its outcome are two cells, each carrying the same genetic information that the mother cell had, as well as the same number of chromosomes.

We humans are dipolid organisms and as such, our cells carry two homologous copies of each chromosome, one inherited from our mother, the other from our father. Our cells therefore have 23 pairs of chromosomes of which 22 pairs are autosomes, one pair are the sex chromosomes (the X and Y chromosomes, paired XX in women and XY in men ). The grand total is 46 chromosomes per normal human cell

But our "germ cells" are different, they can only carry half of the genetic information of each parent so that the combination of the father's sperm and the mother's ovum with their chromosomes add up to exactly the full number of chromosomes.

This process of germ cell formation is known as "Meiosis", and it takes place differently in males and females:

  • Females. Meiosis in females is known as "oogonia", and consists of a series of divisions of the "original" oogonium with the complete set of chromosomes, the outcome is an an ovum with half the quantity of chromosomes.
    Meiosis in females takes place during the formation of the embryo (after the fourth week of pregnancy), as soon as the primordial germ cells migrate to the ovary, and they will lie dormant inside a protective follicle until the woman reaches puberty, when her menstrual cycle begins.
  • Males. The process in males is known as "spermatogenesis", and takes place in a continuous manner, after puberty, until death. Meiosis produces spermatozoa in the seminiferous tubes inside the testicles.


Since male germ cells are produced in a constant manner, the different mutagens that interact with an individual during is whole adult life, (meiosis is a continuous process in men) may cause mutations. Furthermore, males have a very poor DNA repair mechanism, so these mutations are more likely accumulate, without being "fixed", and therefore more likely to get transmitted to their offspring.

The female ova, on the other hand are produced during fetal growth, and are placed in hybernation for many years until the onset of puberty. But despite this long period during which external mutagens could interact with the ova's DNA producing mutations, females have a very efficient repair mechanism for postmeiotic stages which can repair DNA until after fertilization. [3]

This means that sperm accumulate more mutations than ova, and men transmit more mutations to their offspring than women do. This has been corroborated by separate studies both in humans and in chimps:

Chimpanzees, our closest relatives have different mutation rates

Chimps are our closest primate relatives, and a recent paper (Venn et al., 2014) [1] found that "mutation rates and patterns differ between [our] closely related species", Venn reported that male chimpanzees pass on between seven and eight times more mutations to their offspring than do female chimps. This means that roughly 88% of the mutations found in their offspring have a paternal origin and 12% are maternal.

Also, the older the father, the more the mutations in the paternal genes ageing adds "three mutations per year of father's age"[1].

In humans on the other hand "every additional year of father’s age contribut[es] two mutations across the genome and males contribut[e] three to four times as many mutations as females." [1], so males provide between 75 and 80% of the mutations and females 20 - 25%. /p>

This increased mutation contribution by males was reported in a genetic study by Campbell et al., 2012 [7] which found among Hutterite families that 85% of the new mutations were of paternal origin. Which is higher than those mentioned by Venn for humans and very close to those of chimps.

Campbell reported the following figures:

SNV mutation rate: 1.20 × 10-8, (95% confidence interval 0.89 – 1.43 × 10-8) mutations per basepair per generation. And 0.96×10-8 for the most recent generation.

The lower mutation rate for the latest generation was justified by "the relatively young age of the father of the trios analyzed here (21–30 years old at the time of the child’s birth)" [7], meaning that a younger father had accumulated less mutations than an older one.

Calculating Mutation Rate

The mutation rate can be calculated using the following formula:

Mutation Rate = # of mutations observed ⁄ (# of generations x # of base pairs sequenced) [a]

By comparing the discrepancies in the gene sequences of two related individuals separated by a given time span the mutation rate can be calculated (i.e. father - son pairs or comparisons of the DNA between living individuals and that sequenced from his ⁄ her ancestors).

Roach et al., (2010) [8] analyzed the full genome sequence of a family (two children and their parents) and calculated a mutation rate of 1.1 x 10-8 per position per haploid genome.

But what does this mean? Look at it this way: humans have about 6 x 109 base pairs (six billion), so it is very straightforward to work out the number of mutations that will appear in a child, inherited from its parents. They are (see [a] above) directly proportional to the number of bases, the number of generations - in this case = 1 - and the mutation rate. So, using [a] we can calculate:

# of mutations observed = Mutation Rate x # of generations x # of base pairs

So, replacing the terms with actual numbers:

# of mutations = 1.1 x 10-8 x 1 x 6 x 109

# of mutations = 66 (the new mutations in a child, compared to its parents).


Out of these 66 mutations, roughtly 80% (or 53 are parental, the other 13 maternal). Since paternal mutations grow at a rate of 2 per year [1], we can see that the child of an "old" dad aged 45 would receive 2 x (45-20) = 50 "extra" mutations in its genome in comparison to the child of a "young" 20 year old father.

So the baby of "old" dad would have 66 + 50 = 106 mutations while the baby of the "young" dad would have only 66 mutations.

Looking at a society where older parenting prevails (young males are not successful in mating with the women, or they die off before bearing children, or their children die off before reaching maturity) we would find that mutations would have accumulated at 106 mutations⁄generation. While a society where young males exclude older ones from bearing children, the mutations would accumulate at a rate of 60 mutations⁄generation.

After "n" generations the situation would be:

Old men society: n x 106 mutations. Time span: n x 40.
Mutations per year: n x 106 ⁄ n x 40 = 106⁄40 = 2.65

Young men society: n x 60 mutations. Time span: n x 20.
Mutations per year: n x 60 ⁄ n x 20 = 60⁄20 = 3.00

On a "per generation" basis there are 76.7% more mutations in the "old men" society, but on a "per year" basis, the mutation rate is 13.2% higher in the "young men" society.

This should be a word of caution when using "generations" to gauge ancient events. The conclusions will be very different in one case or the other.

The variability of Mutation Rates

The problem is that the mutaton rates are quite "variable". A paper by Wang, J. et al., (2012) [9], sequenced individual sperm cells in a 40 year-old individual. They obtained mutation rates of 2.0 to 3.8 x 10-8, which, are different from other values measured in other studies:

Hutterites (mentioned above): their "SNV mutation rate [was] 1.20 × 10-8 (95% confidence interval 0.89-1.43 × 10-8) mutations per base pair per generation." [7]

Pedigree. Xue et al., (2009) [6] compared the mutations detected in the Y chromosme of two members of the same family separated by a span of 13 generations. They reported that "The mutation rate is ... 1.0 × 10-9 mutations ⁄ nucleotide ⁄ year (95% CI: 3.0 × 10-10 – 2.5 × 10-9), or 3.0 × 10-8 mutations ⁄ nucleotide ⁄ generation (95% CI: 8.9 × 10-9 – 7.0 × 10-8)" [6] .

Just look at Xue et al.'s enormous Confidence Interval: it is almost one order of magnitude, that is the upper limit is nearly 10 times the value of the lower limit! This is like saying that we estimate the weight of the stone to be 10 pounds, with a CI of 3 lb - 25 lb.

The range between the minimum and maximum values of these studies goes from 0.89 to 7 x 10 -8 mutations ⁄ base pair ⁄ generation. A big window indeed.

Variability between families

Additional proof of the variability of mutation rates comes from a paper (Conrad et al., 2011) [5] which confirms that there is "considerable variation in mutation rates within and between families". The authors compared female and male germline and non-germline de novo mutation rates and found that "in one family [...] 92% of germline DNMs were from the paternal germline, whereas, in contrast, in the other family, 64% of DNMs were from the maternal germline." [5]

Against the constancy of mutation rates

We could imagine that additional research will refine those values and come up with a more reliable rate, but there is another problem: the mutation rate is not constant. It fluctuates accelerating and slowing down over time.

A paper by Amos W., (2013) points out a that "tendency for Africans to have diverged more from chimpanzees than non-Africans is unexpeced under classical theory." [4] Since we all derived from chimps, and have had the same time to accumulate mutations, why do Africans appear more distinct?

Applying the formula [a] it is quite simple to see that if the number of mutations is higher for Africans, then either the number of generations and ⁄ or the mutation rate must be higher for them than among non-Africans. Amos finds no reason to imagine a shorter generation time in Africa (shorter duration means more generations in a given time span). Clearly something is influencing the mutation rates in Africa.

So for Amos, this implies that the anomaly may be due to two reasons "local effects that vary across the genome due, for example, to natural selection, and genome-wide effects arising from a mutator allele impacting mutation rate or demographic influences that alter generation time." [4], the paper suggests that the mechanism that is acting to distort mutation rates is known as the "heterozygote instability" (HI) hypothesis.

Under the HI hypothesis:

mutation rate increases at and near heterozygous sites where the two homologous chromosomes differ in sequence [...] [4]

This means that "gene conversion events focused on heterozygous sites during meiosis locally increase the mutation rate [and] As humans left Africa they lost variability, which, if HI operates, should have reduced the mutation rate in non-Africans. [4]

In other words, the bottle necks that decimated humans (and also their Neanderthal and Denisovan) predecessors as they moved out of Africa and across Eurasia, led to reduced diversity and this in turn decelerated their mutation rate in comparison to those that remained in the African homeland whose diversity remained higher.

"Under the HI hypothesis, this demographically-induced reduction in heterozygosity should create a parallel reduction in mutation rate such that Africans have diverged more than non-Africans from their common ancestor" [4]

I will go over this in detail in my next post on "African diversity vs. non-African lack of diversity", but focusing on this post's subject, how does this impact on mutation rates?

Simple: mutation rate grow with increasing heterozygosity. Also "When population size is constant, smaller populations will experience lower mutation rates than related larger populations" [4].

Summary on mutation rates

DNA mutates at different rates:

  • In male or female germ cells
  • In different families
  • In less diverse populations vs highly heterozygous populations (HI hypothesis)
  • In chimpanzees (vs. humans)
  • In older men's sperm vs. younger men's sperm
  • In large populations vs. small populations

And as we will see below, ancestral DNA (obtained from the remains of ancient humans) show different rates when compared to the pedigree rates calculated by using sequences of recent modern families.

Ust'-Ishim and its estimates on mutation rates

And now, we get to the paper on the Ust'-Ishim remains (Fu, et al., 2014) [2]. Besides a wealth of data on admixture and mtDNA & Y chromosome haplogroups also deals with mutation rates, and reaches some very interesting conclusions (Below I will refer to the Supplementary Information freely available online):

Autosomal Mutation Rates Estimates

The paper measured how many mutations are "missing" in this 45 ky old individual when compared to contemporary humans. The logic behind this calculation is that we kept on evolving during that period of time and accumulated new mutations (see SI 15). Since the bone was carbon dated (41,410 ± 960 BP or 45,000 cal BP) and the substitutions can be measured, the calculation was relatively simple.

As expected, the DNA of Ust'-Ishim is around 0.6% shorter than the A-Panel (a low-coverage of 24 - 32%) modern humans and 0.35% for B-Panel samples (with a higher coverage of 35 -42%). So the autosomal mutation rates are: "0.80-0.91 × 10-9 ⁄ bp ⁄year for panel-A and 0.44-0.63 × 10-9 ⁄ bp ⁄ year for the B-panel." [2]

The authors therefore "estimate a nuclear mutation rate of 0.44 -0.63 × 10-9 ⁄ site ⁄ year, which is lower than the value that has been widely used in the past (1 × 10-9)." they do point out that the "lower quality A-panel individuals give significantly different results, indicating that this measure is sensitive to quality differences between the compared genomes" [2]

Indeed "different", the values differ by a factor of 2! Notice that they are also giving their figures in mutations per site per Year, further up, the figures we mentioned were "per Generation". Conversion from one to other depends on the time span assigned to a Generation which can range from 19 to 40 years!

Comparing Ust'-Ishim (ancestral) and Xue's pedigree values [4] there is a two-fold spread between the minimum and maximum values.

  • 0.44 - 0.63 x 10-9 ⁄ bp ⁄ year (Ust'-Ishim)
  • 0.30 - 2.50 x 10-9 ⁄ bp ⁄ year (Xue's data)

Mitochondrial DMA mutation rates

Using the mtDNA (SI 8), Fu et al., (which by the way, the mtDNA "appears to be most closely related to the direct R sub-clades R* (P, B, F, T, J)" [2]), they also estimate a mutation rate of "2.53 × 10-8 substitutions per site per year (95% HPD: 1.76 -3.23 × 10-8) for the complete mtDNA" [2]. Notice that it differs from the autosomal mutation rate calculated above by a factor of about 50 corroborating that mtDNA mutates rapidly.

Y-chromosome mutation rate

The team also sequenced Ust'-Ishim's Y chromosome and found that it "clusters with the K(xLT) haplogroup." [2], they estimated its mutation rate as "0.76 × 10-9 substitutions per site per year (95% HPD: 0.67-0.86 × 10-9)". Which was higher than the rate reported in the controversial paper by Mendez et al. (2013) which discovered a new Y chromosome lineage (A00) with a Most Recent Common Ancestor (TMRCA) of 338 ky, far older than the oldest anatomically modern human fossils.

Table S9.1, shows that the (TMRCA) for all Y-Chromosomes as 153 ky old (range: 132-175 ky).[2], since the mutation rate used is higher, the TMRCA is much more recent than the figure calculated by Mendez (153 ky vs. 338 ky).

A novel calculation of the mutation rate

Fu et al., devised a new method of calculating the mutation rate "assuming the population size history of the ancient sample is identical to that of present humans prior to the death of the archaic individual" [2] , and estimated a muation rate of 0.43×10-9 per site per year, with a 95% CI (0.38×10-9 - 0.49×10-9).

This value coincides with their estimate based on another method and is much lower than other previous values. The fact that the mutation rate is lower and therefore slower means that more time is necessary to accumulate the mutations that we carry, in other words it suggests an older date for the split between modern and ancient humans.

Another recent paper on Mutation Rates

A few days after Fu's paper, another one (Rieux et al., 2014) [10] was published, it reported an improved calibration of the mtDNA clock, and calculated a TMRC for modern humans as 143 ky (95% CI 112 - 180 ky), which agrees pretty well with Fu's estimate.

They ratified the "acceleration of substitution rates in recent times" (for mtDNA mutation rates) which is explained by the " 'time-dependency of molecular rates' hypothesis, which postulates an acceleration over recent times in coding sequences due to the time needed for selection to purge slightly deleterious mutations" [10].

They used two types of estimations, one based on the dates of the fossil remains of ancient humans (tip-based-estimates) and another calibrated on nodes, which mark peopling events such as the peopling of America, New Zealand, Madagascar, etc. They noticed that:

tip-based rate estimates are slower (by a factor of 0.63-fold) than the ones obtained using internal node calibration by Endicott and Ho (2008) but are faster (by a factor of ~1.5-fold) than previous fossil-calibrated rates
the variance over individually calibrated substitution rates is 11 times smaller for tips than internal nodes. Moreover, all of the 21 substitution rates estimated from aAMH sequences had overlapping 95% HPD (fig. 3). The situation is strikingly different for node-based calibrations, where substitution rate estimates strongly depended on the demographic episode used for dating, with only four out of ten individually calibrated rates having overlapping HPDs.
These results strongly suggest that tip calibration estimates are far more consistent than internal node-based ones. However, tip-based calibration also point to slower mean substitution rates than those based on internal nodes. Thus, one important question we need to answer is whether tipbased calibrations are affected by some systematic bias that might lead to slow (and homogeneous) substitution rates. [10]

In other words, the "nodes" or estimated dates of demographic events have a larger variance than those of the "tips" (reliably dated fossil remains). The 95% HPD interval obtained for each independent ancient sequence overlapped the others while the "nodes" only overlapped in 40% of the cases. (See their Fig. 3). The ancient remains are therefore more reliable than the estimated dates for peopling events! (something I have written about several times suggesting an ancient peopling of America). Additionally the fossils indicate a slower mutation rate meaning a more ancient date for all events (African - non-African split, Sapiens - Neanderthal split, etc.).

Rieux et al. recognize that carbon dated remains are much more reliable than the estimations of dates regarding peopling events (allow me to quote them extensively) :

the uncertainty around dated nodes is far more complex and multifactorial and is likely to lead to different degrees of reliability associated to each node. First, there is generally considerable uncertainty associated with the age of the colonization⁄migration event including error in the dating of the archaeological, anthropological, and historical evidence. The age of the oldest evidence for human presence is unlikely to coincide exactly with the demographic expansion. Very generally, we would predict to see a delay in the appearance of traces of human presence after the expansion of AMHs into any new area (Signor and Lipps 1982).
Second, even if a demographic event had been accurately dated, the age of the node in the phylogenetic tree might not coincide with it for a number of reasons (Edwards and Beerli 2000; Ho and Phillips 2009; Balloux 2010; Firth et al. 2010; Crandall et al. 2012). For instance, the phylogenetic node of interest may correspond to the most recent common ancestor (MRCA) of the sampled sequences rather than the split of the population of interest.
the population might have experienced a reduction in size later on, so that the TMRCA could coincide with this subsequent population bottleneck. We could think of additional scenarios and the situation would become even more complex if we considered a possible effect of natural selection. To summarize, node calibration can be affected bymany sources of error, and it is thus nearly impossible to model the age uncertainty around nodes satisfyingly. [10]

In other words, the nodes will give "later" dates for cases like America, subjected to a drastic bottleneck. Even so, I am quite happy to see the dates that they estimated using ancient genomes gave a much older date for the peopling of America than the usual "orthodox" 13 - 17 ky:

time peopling America
Table 2 in [10]. Coalescence Times for Major Haplogroups Involved in the Colonization/Migration Events Considered.

Yet the authors are aware of their "early" dating and try to explain the "discrepancy" to conform to orthodoxy: "However, in the case of the Canary Islands, Remote Oceania, New Zealand, and the Americas, the estimated coalescence times were systematically older than the archaeological evidence. Potential explanations for such discrepancies include ancestral polymorphism in the founding population or complex demographic histories involving multiples wavesof colonists" [10].

Finally their dating of the Divergence between Humans and Chimpanzees was 4.14 Ma (95% HPD 2.991 - 5.448). Which they admit "... may appear too young when compared with the dates that are generally derived from the fossil record." [10] . The authors attempt to explain this "recent" date as due to (i.e. "...more complex speciation scenarios where an initial split was followed by an extended period of gene flow before the final separation..."). But I do not think that it is due to a flaw in their method, but to the dissimilar mutation rates of humans and chimps, as pointed out by Venn et al., in June 2014, [1]:

Under a model in which the mutation rate increases linearly with parental age, the rate of neutral substitution is the ratio of the average number of mutations inherited per generation to the average parental age. We predict the neutral substitution rate to be ~0.46 × 10-9 per base pair (bp) per year in chimpanzees, compared to estimates in humans of ~0.51 × 10-9 bp-1 year-1 (9). These results are consistent with near-identical levels of lineage-specific sequence divergence (12) but surprising given the differences in paternal age effect. In the intersection of the autosomal genome accessible in this study and regions where human and chimpanzee genomes can be aligned with high confidence, the rate is slightly lower (0.45 × 10-9 bp-1 year-1) and the level of divergence is 1.2% (13), implying an average time to the most common ancestor of 13 million years, assuming uniformity of the mutation rate over this time (95% ETPI 11 to 17 million years; table S11). [1]

This is in agreement with the estimate of Langergraber et al., (2012) who dated the Pan-Homo divergence to between 6.78 and 13.45 Ma.

An earlier human-chimp split renders useless the calculations that calibrate molecular clocks based on that event. If it took place 13 Ma instead of 6, the clock's ticking rate has to be adjusted and all events derived from such a clock would actually be much older than currently accepted. Including the peopling of America.

More to follow, on the differing diversity of humans Africans and non-Africans

[1] Oliver Venn, et al., (2014). Strong male bias drives germline mutation in chimpanzees. Science 13 June 2014: Vol. 344 no. 6189 pp. 1272-1275 DOI: 10.1126/science.344.6189.1272
[2] Fu, Q. and many others. (2014). Genome sequence of a 45,000-year-old modern human from western Siberia. Nature, 514, 445-450. doi:10.1038/nature13810
[3] Andrew J. Wyrobek et al., (2007) Assessing Human Germ-Cell Mutagenesis in the Postgenome Era: A Celebration of the Legacy of William Lawson (Bill) Russell. Environ Mol Mutagen. Mar 2007; 48(2): 71–95. doi: 10.1002/em.20284
[4] William Amos, (2013) Variation in Heterozygosity Predicts Variation in Human Substitution Rates between Populations, Individuals and Genomic Regions. April 30, 2013DOI: 10.1371/journal.pone.0063048
[5] Donald F Conrad, et al., (2011). Variation in genome-wide mutation rates within and between human families. Nature Genetics 43, 712–714 (2011) doi:10.1038/ng.862. Published online 12 June 2011
[6] Yali Xue et al., (2009). Human Y Chromosome Base-Substitution Mutation Rate Measured by Direct Sequencing in a Deep-Rooting Pedigree. Curr Biol. Sep 15, 2009; 19(17): 1453–1457. doi: 10.1016/j.cub.2009.07.032
[7] Catarina D Campbell, et al., (2012). Estimating the human mutation rate using autozygosity in a founder population. Nature Genetics 44, 1277–1281 (2012) doi:10.1038/ng.2418
[8] Roach JC, (2010). Analysis of genetic inheritance in a family quartet by whole-genome sequencing. Science. 2010 Apr 30;328(5978):636-9. doi: 10.1126/science.1186802. Epub 2010 Mar 10
[9] Wang J, Fan HC, Behr B, Quake SR, (2012). Genome-wide single-cell analysis of recombination activity and de novo mutation rates in human sperm. Cell. 2012 Jul 20;150(2):402-12. doi: 10.1016/j.cell.2012.06.030
[10] Adrien Rieux, et al., (2014). Improved Calibration of the Human Mitochondrial Clock Using Ancient Genomes. Molecular Biology and Evolution, 2014, 2780-2792, DOI: 10.1093/molbev/msu222

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