john hawks weblog

paleoanthropology, genetics and evolution

chimpanzees

  • Cheetah the chimpanzee, RIP

    Thu, 2011-12-29 10:41 -- John Hawks

    I've been unusually busy this holiday week, and haven't had much time to sit down and write. A reader sent me this death notice for the longest-lived chimpanzee on record:

    Cheetah the chimp from 1930s Tarzan flicks dies

    The chimp was unusually long-lived, surviving beyond both Weissmuller and Maureen O’Sullivan, who played Tarzan’s mate Jane in many of the early films. Chimpanzees live an average of 35 to 45 years in captivity. Guinness World Records cited Cheetah as the world’s oldest non-human primate.

    There is some confusion over which films this particular chimpanzee acted the part.

    Many chimpanzees have played Tarzan’s simian sidekick over the franchise’s long run in both films and television. The Cheetah who died Dec. 24 is not the one who appeared in the first two Weissmuller films, “Tarzan the Ape Man” (1932) and “Tarzan and His Mate” (1934), but is thought to have played the role in the 1930s and ’40s.

  • Mailbag: Neandertal-human comparisons

    Fri, 2011-12-09 21:38 -- John Hawks

    Re: Neandertal-human comparisons

    Your website states, "of those positions where the human genome differs from chimpanzees, Neandertals have the chimpanzee version around 12.7 percent of the time."

    Since the subject is the comparison with supposed MRCA of humans/chimps, shouldn't the correct statement be, "of those positions where the human genome differs from chimpanzees, Neandertals have the MRCA version around 12.7 percent of the time." ?

    Or therefore, "of those positions where the human genome differs from chimpanzees, Neandertals have the chimpanzee version around 6.35 percent of the time."

    If Neanderthals were something like 2 million base pairs closer to chimpanzee, shouldn't a few thousand of those base pairs be in at least a few modern Eurasians ?

    Hi, thanks for your question!

    Your point is correct that Neandertals do not have chimpanzee ancestors. If we were considering a comparison of all sites in the Neandertal sequence, you would be correct about the proportions. Neandertals would lack some proportion of the mutations that occurred on the modern human's lineage but they would lack every one of the mutations that happened on the chimpanzee lineage -- except for a very small fraction of parallelisms.

    However, the comparison carried out by Green and colleagues was not of the entire genome, but specifically those sites in the genome that underwent mutations on the human lineage. The mutations on the chimpanzee lineage from the MRCA are completely ignored by this comparison.

    The chimpanzee genome therefore stands in for the MRCA in this comparison. Sites at which both chimpanzees and humans have undergone parallel mutations have the potential to confound this comparison, because they are not counted (they are not places where the human and chimpanzee genomes differ). But the proportion of human substitutions that are also chimpanzee substitutions from the MRCA is very small, only around 1 percent of the human sites.

    The fraction of Neandertal ancestry of Eurasians is around 3 percent, this is calculated differently, by examining polymorphisms within human populations today and considering the fraction shared by different humans' genomes with Neandertals. Eurasian people have around 3 percent more similarity with Neandertals than present-day Africans.

  • Chimp brains don't shrink with age

    Mon, 2011-08-22 00:07 -- John Hawks

    The Wall Street Journal reported on Chet Sherwood's work late last month: "Brain Shrinkage: It's Only Human".

    The human brain normally can shrink up to 15% as it ages, a change linked to dementia, poor memory and depression. Until now, researchers had assumed this gradual brain loss in later years was universal among primates.

    But in the first direct comparison of humans to chimpanzees, a brain-scanning team led by George Washington University anthropologist Chet Sherwood found that chimpanzees don't experience such brain loss. From that, researchers concluded that only people are afflicted by this oddity of longevity.

    The paper is in PNAS [1]. The press article doesn't really explain the findings of the paper very well. Sherwood and colleagues found that the age effect in their sample of humans was limited to ages older than any chimpanzee in their samples. So there's no evidence that humans and chimpanzees differ across the same ages. Now, whether we expect chimpanzees to shrink their brains at a younger age (because they develop and senesce faster) is an open question; I can see arguments both ways. Anyway, I think the study goes as far as gross morphological comparisons can take this question, and more detail will have to wait for us to understand the cellular mechanisms that influence brain size senescence.


    References

    1. Sherwood CC, Gordon AD, Allen JS, Phillips KA, Erwin JM, Hof PR, and Hopkins WD. 2011. Aging of the cerebral cortex differs between humans and chimpanzees. Proceedings of the National Academy of Sciences 108:13029 - 13034.
  • Chimp gunplay

    Thu, 2011-07-21 11:46 -- John Hawks

    MSNBC reports on the really important issues, such as, "Will chimpanzees rise against us?"

    Any chimp gunplay would most likely be restricted to mimicry. [Primatologist John] Mitani believes actor chimps would likely learn to operate machine guns to please their trainers and receive rewards, but he doesn't think the apes are capable of using them to purposely do harm. "When shooting the gun, I'd be hard-pressed to think that the chimp can really understand (the consequences of) what he's doing."

    Hmmm...we're talking about creatures that will tear off a man's testicles, here. I have a feeling that chimps manning a submachine gun would cackle with chimpish glee.

  • Chimpanzee yawning

    Sat, 2011-04-16 08:20 -- John Hawks

    Hannah Little describes a recent study of chimpanzees by Matthew Campbell and Frans de Waal [1]: "The path to empathy".

    The study used 23 chimpanzees from two separate groups and they were made to watch videos of familiar and unfamiliar individuals yawning. Videos of the same chimps not yawning were also used for control. The chimpanzees yawned more when watching the familiar yawns than the familiar control or the unfamiliar yawns, demonstrating an ingroup-outgroup bias in contagious yawning.

    In this case, the chimpanzee research leads that in humans; we don't yet know how extensive such biases may be. Campbell and de Waal do not mention the obvious difference between chimpanzee and human yawns as social signals: the canines. It would be very interesting if the yawn contagion is the same despite the obvious salience of canine teeth for chimpanzee yawning.


    References

  • Goodall record digitization

    Mon, 2011-03-28 22:05 -- John Hawks

    Jason Goldman covers the acquisition of Gombe chimpanzee records from the Jane Goodall Institute by Duke University ("Digitizing Jane Goodall's legacy at Duke").

    Now, researchers at Duke University are taking more than twenty file-cabinets full with fifty years of check-sheets, longhand narratives in both English and Swahili, hand-drawn maps, videos, and photos, and carefully digitizing everything. This will allow researchers to construct searchable life-histories of the chimpanzees of Gombe, for the first time. The word "archives" is a bit misleading, though. The new Jane Goodall Institute Research Center at Duke is continuing to receive new data from Gombe, which will all become digitized and included in the collection as well.

    The move toward digitizing and making primate field records available has been a major challenge for primatology. Different research teams have legacies of partially incompatible records, which complicates the process of comparing data from different sites and different species. My UW-Madison colleague Karen Strier together with many of the leading figures in primate field research have been involved for several years in an effort to bring life history records from different primate species together. One of the first tangible results of the collaboration is a paper that appeared earlier this month in Science by Anne Bronikowski and colleagues [1].

    Seems to me that this kind of archiving is absolutely essential to our ability to study primate behavior in the future. Not least, data archives will be necessary to document the effect of range contractions and habitat fragmentation on primate behavior. Openness is difficult to negotiate in these contexts, because of the long-term effort put into data collection. But in thirty years, these archives will not be useful unless they are extended and put into accord with formats that are widely used. Goldman describes the idiosyncrasies of Goodall's data, and many other field projects have similar traditions that differ from each other. Without building a larger community capable of understanding these records, the data may be as useful as WordStar files from 1981.


    References

  • The real "junk" DNA

    Wed, 2011-03-09 22:47 -- John Hawks

    Let me be honest: when I started doing paleoanthropology, I really did not expect I'd be talking about Neandertal penises.

    And yet, here I am. Cory McLean and colleagues [1] combine a straightforward genomic analysis of human-specific deletions with a couple of transgenic mice, and take us straight to penis spines.

    You see, most primates, and indeed many mammals, have at least some spines on their penises. "Spine" means more or less what you would expect: little projections that are covered in hard material, generally keratin, curving toward the base of the penis. These spines are sometimes called "horny papillae."

    No, I cannot make this stuff up.

    The morphology of these spines varies among primates. They overlie sensory receptors, and they intensify or enhance sensations accompanying intromission of the penis. Like a KY commercial, except they don't enhance sensations for the female. The net effect in some species is to reduce how long it takes the male to ejaculate. For example, a 1991 paper [2] by A. F. Dixson...

    No, I cannot make this stuff up.

    ...removed the penile spines of several male marmosets, finding that they took twice as long to achieve penile intromission after starting pelvic thrusts. Of course, "twice as long" in marmosets only means 15 seconds. The spineless males took 2 seconds to ejaculate, compared to only 1.73 seconds for those who had a "sham surgery" -- that is, they got the same depilatory spine-removal procedure without the active ingredient. That's some evidence in favor of the idea that losing penile spines might be related to longer coital duration.

    But penile spines don't always mean fast sex. Galagos have penises covered in long hook-like spines, which they use in virtual sex marathon sessions lasting two hours or more. Prosimians tend to have much more elaborated spines, in contrast chimpanzees' spicules are comparatively minor -- in a broad comparison across primates, Harcourt and Gardiner [3] rated chimpanzees along with humans as having insignificant penile spinosity.

    Let me just say that the comparative data don't convince me of an adaptive model for loss of penile spines in humans. Evidence from mutilated monkeys is not all that persuasive. I mean, really, how fast do you think you would manage after the "operation"? More important, the differences among hominoids run against the hypothesis -- gibbons have the spiniest penises among the apes, despite their monogamous, pair-bonded social habits.

    And I'll pause to savor the surreality: I'm here making value judgments about genital cacti.

    One thing that is definitely well-known about these penile spines is that their development depends on testosterone. Castrated monkeys do not develop the characteristic spines, and they lose them if already present. The androgen receptor (AR) locus is surrounded by promoter/enhancer sequences that are tissue-specific, capable of being flipped on or off as development proceeds within different parts of the body.

    Within this system, the genetics in humans and chimpanzees are simple: A long (60 kilobase) deletion of DNA in the human lineage has knocked out a 5 kb conserved region that enhances AR. That enhancer is specific to the follicles around the developing facial whiskers (vibrissae) and in the skin layers of the penis. This specificity was discovered in transgenic mice, in which a reporter gene is inserted with the enhancer, and embryos display expression of the reporter wherever the enhancer is active. Very straightforward, very cool science.

    One more thing: The chimpanzee version can drive expression when implanted into transgenic human foreskin fibroblasts. That indicates that the overall genetic system to make penile spines is still there lurking in our genomes. If we could turn on the gene at the right time, replacing the function of the enhancer, we can still grow penile spines.

    Just saying -- there may be a market there. Maybe the "male enhancement" companies will hit that next. I can only imagine what the wrapper on the NASCAR circuit will look like. OK, I know, don't encourage them. It's bad enough that we have labs full of foreskin tissue with chimpanzee genes floating around.

    I couldn't make this stuff up if I tried.

    Finding the deletion was straightforward genomics: They scraped the human genome for parts missing from chimpanzees and macaques, and then extracted from that set all deletions that included sequence conserved in other mammals. Others have done similar comparisons for conservation and human-specific changes; this is a clever twist on the same problem. It does fit an ongoing theme -- many essential aspects of humans may involve the loss of genes or functionality from our ape ancestors.

    Ok, so where do Neandertals fit in? They have the sequence deletion just like the rest of us do. If that deletion rules out chimpanzee-like spiky penises, then Neandertals could glide like the rest of us.

    All in all, it's a nice short paper, and very straightforward. The only questionable part to me is the social model. The genetics and expression data are solid.

    Speaking of Neandertals and the androgen receptor (AR) locus, my genome appears to have a Neandertal-derived haplotype across that gene. I'll expose this fact at greater length later, but I thought it worth sharing that the current paper is not the end of the story. Neandertals may not have had penis spines, but some functional polymorphisms in testosterone response might still have come into our population from them or other ancient people.

    UPDATE (2011-03-11): Eric Michael Johnson gives us the real dirt on this story ("Penis spines, pearly papules and Pope Benedict's balls"). He points out the relatively small extent of these features of the chimpanzee penis compared to other primates, and adds detail about the lack of association between their presence and sexual system in hominoids.

    He also reveals a shocking fact: a fairly large fraction of men still have the chimpanzee-like pearly papules.

    Scicurious also takes on the topic "Friday Weird Science: Penis Spines, what are they REALLY?", reviewing the original Osman Hill study of chimpanzee penis morphology. I think the Nature paper is very misleading in its use of galago illustrations for these spines, the chimpanzee version is comparatively minor.


    References

  • Ham the space chimp

    Sun, 2011-01-30 15:15 -- John Hawks

    Remembering Ham, 50 years later: "The chimp that took America into space."

    Fifty years ago tomorrow an African-born astronaut made it into space ahead of Soviet pioneer Yuri Gagarin. His name was Ham, a chimpanzee born in July 1957 in the rainforests of what was then the French Cameroons. He was bought by the US Air Force to be used in early space flight experiments for $457 – not a bad investment as it turned out.

  • What is the human mutation rate?

    Thu, 2010-11-04 01:33 -- John Hawks

    Last spring I wrote about a study that used whole-genome comparisons between parents and offspring to estimate the rate of per-genome mutation in humans ("A low human mutation rate may throw everything out of whack").

    The study was by Jared Roach and colleagues [1], and as you might guess from my post title, the result was surprising. Previous work had suggested a human mutation rate around 2.5 x 10-8 per site per generation. The new study found less than half the expected number of mutations between these parents and offspring, an estimated rate of only 1.1 x 10-8 per site.

    If this lower rate of mutation were to hold up, it would affect much of our understanding of the chronology of human evolution. Fossils and archaeological sites would not change in date, but some hypotheses about their relationships would be challenged. For example, the higher rate of 2.5 x 10-8 per site suggests a chimpanzee-human population divergence around 4 million years ago. A new rate of 1.1 x 10-8 would not have a linear effect on this divergence time -- the genes don't have genealogical roots at the same instant as the population divergence. But the human-chimpanzee divergence time would be radically higher than in many recent estimates.

    The same might be true for other primate divergences, and for genealogical relations within human populations today. Basically any times that are estimated from genetic differences may be affected by our knowledge of the per-generation rate of mutations.

    What does this mean? Open below the fold to read more.

    What mutations are we counting?

    Human genomes differ from each other in many ways. There are single base-pair changes in sequences, insertions and deletions, repeat polymorphisms, and larger-scale rearrangements such as inversions and gene duplications. Recent work suggests that some of these larger-scale effects may be very important to phenotypic variation among people. So why should we be talking about only the first of these kinds of variation?

    Single nucleotide mutations have been the focus of most attention about mutation rates because they are relatively easy and quantify. In high-quality sequence data, a single nucleotide change is relatively unambiguous. Reversals are fairly unlikely, although at a small fraction of "hotspot" sites, recurrent mutations can make a big difference.

    It is somewhat misleading to refer to "a" rate of single nucleotide mutations, because some kinds of sites (e.g., CpG nucleotides) have had a much higher probability of mutations than others. This affects the apparent rate of mutations in noncoding versus synonymous sites [2]. Also, the germline in males has been estimated to be as much as 6 times more likely to suffer mutations than the germline in females (discussed by Crow [3]). The idea of a genome-wide rate assumes that when we bin all the single nucleotide mutations together, across large amounts of sequence, we do arrive at a relatively stable rate that can be applied to similarly broad extents of sequence data. Or at least that we can identify sequence regions with compatible rates (e.g., noncoding DNA or synonymous sites).

    At the moment, technical issues make it hard to find and quantify many other kinds of variation. The current generation of sequencing devices tend to generate short reads, which make it difficult to assess the presence of insertions or deletions of more than a few base pairs. Duplications and other rearrangements require special treatment such as higher coverage or longer sequence reads. By contrast, a single nucleotide mutation will typically align in the proper location and be quite evident in a read. In principle, we can just run down the genome and count them.

    Still, finding novel mutations is not without its problems. Recent sequencing projects have yielded a very high rate of false positives. The rate of false negatives is really not yet known. We have a good reason to suspect that the false negative rate will be high. In a low-coverage genome, many short segments of the genome will have very low read numbers, making it likely that the sequence reads represent only one of the two copies of the genome present at that location. Any novel mutations in that area have a 50-50 chance of being missed by our sequencing efforts. This false negative risk can be reduced by adding higher sequence coverage, but we're not yet at the point where we have a lot of genomes sequenced at the 10x or higher coverage that we would really want.

    So while sequencing a parent and offspring genome is the most direct way to estimate the per-generation mutation rate, it is not yet ideal.

    Where did the high rate come from?

    That means we need to look very closely at other sources of data, to see if they may provide some independent confirmation of a lower per-generation mutation rate. In the process, we should ask, why did the higher rate, around 2.5 x 10-8 per generation, become so widely accepted?

    The source cited by Roach and colleagues for the higher rate, 2.5 x 10-8 per site, is a paper by Michael Nachman and Susan Crowell [4]. Nachman and Crowell examined processed pseudogenes in humans and chimpanzees, under the assumption that mutations in these pseudogenes would be neutral to selection in the human and chimpanzee lineages.

    The average mutation rate was calculated from the average autosomal rate of evolution assuming a generation time of 20 years (Table 3). Recent estimates of the time since humans and chimpanzees diverged (T) include 4.5 mya (TAKAHATA and SATTA 1997 ), 5.5 mya (KUMAR and HEDGES 1998 ), and 6.0 mya (GOODMAN et al. 1998 ). ARNASON et al. 1998 estimated the Homo-Pan divergence at 10–13 mya; however, their estimate is based on a calibration using distant, nonprimate species and is at odds with most other recent estimates. Mutation rates were calculated for a range of different human-chimpanzee divergence times and for two different ancestral population sizes. Mutation rate estimates vary from 1.3 x 10-8 (assuming T = 6 mya and Ne = 105) to 2.7 x 10-8 (assuming T = 4.5 mya and Ne = 104). If the average generation time is assumed to be 25 years (e.g., EYRE-WALKER and KEIGHTLEY 1999 ), then mutation rates are estimated to be between 1.6 x 10-8 and 3.4 x 10-8.

    Wait a minute. There's no independent estimate of mutation rate here at all!

    What they did was to assume values for the human-chimpanzee divergence and ancestral (chuman) effective size, and then provide an estimate of mutation rate consistent with those assumptions. That's perfectly reasonable as a way of quantifying the genetic divergence that they observed. If our goal is to predict the per-generation mutation rate from interspecific divergence, that's more or less the kind of estimate that we want.

    But many, many other studies have instead used a citation to the Nachman and Crowell rate as a justification for their own estimates of the human-chimpanzee divergence time! That's not perfectly reasonable, in fact, it's perfectly circular. It's turtles all the way down!

    Worse, those citations tend to cite the midpoint of Nachman and Crowell's range of estimates (2.5 x 10-8) as if it were a true value measured with little error. Reading the original reference, you can plainly see that Nachman and Crowell reported estimates that varied over a factor of three, corresponding to a wide range of chuman population histories. From their discussion:

    Mutation rates estimated for a range of divergence times and ancestral population sizes fall between 1.3 x 10-8 and 2.7 x 10-8 assuming a generation time of 20 years (Table 3) or between 1.6 x 10-8 and 3.4 x 10-8 assuming a generation time of 25 years. We suggest that 2.5 x 10-8 is a reasonable estimate of the average mutation rate per nucleotide site (but caution that the actual rate may be between 1.3 x 10-8 and 3.4 x 10-8).

    That 2.5 x 10-8 is simply the midpoint of their range of estimates with the 25-year generation time.

    What would be more reasonable? For hominins and chimpanzees, we probably want to apply a shorter generation length, a larger ancestral effective size, and a higher time of divergence. All of these would have yielded a lower rate for the Nachman and Crowell data. But we don't want to just assume these values, we should try to test whether they are valid based on other data.

    Other mutation rates from phylogenetic comparisions

    Nachman and Crowell have not been alone in their ultimate reliance on fossil evidence as an assumption underlying the per-generation mutation rate. But several other studies came to a slower mutation rate. Mostly, these studies have assumed that the human-chimpanzee divergence happened significantly earlier than 5 million years ago. Necessarily, then, the human per-generation mutation rate would have to be lower, as long as the sequence divergence remained the same.

    These estimates are ultimately rooted in the date of one or more fossils, among which the generation time certainly varied. The resulting per-site mutation rates are often reported as per-year instead of per-generation. For example, Yi and colleagues [5] yielded a rate of 0.99 x 10-9 per year for the human-chimpanzee comparison, which would multiply to 1.98 x 10-8 per 20-year generation. They propose this as a maximal rate, assuming that Sahelanthropus at a minimum date of 6 million years ago is a hominin. With an older divergence date, they propose a correspondingly lower rate (e.g., 0.79 x 10-9 per year, not accounting for ancestral population polymorphism).

    Similarly, Steiper and Young [6] considered a long (1.9 Mb) alignment of sequence from 19 primate species. In their model to estimate relative rates on different branches of the primate phylogeny, they incorporated the assumption that Sahelanthropus is on the hominin clade. A divergence date of 6 million years gave rise to a human per-site mutation rate of 0.65 x 10-9 per year (1.3 x 10-8 per 20-year generation). A divergence date of 7 million years lowered the mutation rate to 0.57 x 10-9 per year.

    Low mutation rates do not always result from these studies. Several have arrived at either a high human mutation rate or a recent human-chimpanzee divergence time. Sometimes a recent human-chimpanzee divergence emerges simply by assuming the rate given by Nachman and Crowell. Yang [7] provides an example of this -- a paper that very thoroughly explores the relationship of divergence time and ancestral effective population size, but ultimately roots the estimates on a single value for mutation rate. This rate we have already seen was itself based on an assumption about divergence time.

    Kumar and colleagues [8] came to a much lower estimate for the human-chimpanzee divergence time, based on an Old World monkey-hominoid divergence at 23.8 million years ago. This estimate did not consider the effect of ancestral polymorphism on the mean genetic divergence time, and so should -- in the language of computer software -- be deprecated.

    I should reiterate that none of these estimates are suitable for testing the times of phylogenetic divergences, because they all assume that the date of some particular fossil (or set of fossils, by fitting a model) is the minimum divergence time for a clade.

    So much of the literature in this area is ultimately circular, I'm pulling out my sparse hair reading through it. By the time we get back to the mid-1990's, the sequence data are even sparser than my hair by today's standards -- only a few hundred base pairs, or a sampling of restriction sites. But the divergence time estimates have propagated forward from that time to today, recycled through the assumptions of papers in the intervening time. It's like the genetic equivalent of money laundering!

    Evidence from parent-offspring sequence differences

    There is another way besides phylogenetic comparison: Simply look at living people and see how many new mutations they have.

    But this is tricky because we are rarely in a position to know which mutations are new. Most variations that we see between two people have persisted in the population for hundreds of generations or more. It takes a special kind of mutation to make its newness evident.

    Up until the advent of large-scale sequencing, the most important source of information about the mutation rate came from the rates of spontaneous Mendelian diseases. When a person has a dominant genetic disorder not carried by either of his parents, you know that the mutation must be new. Disease rates have long been tracked as standard public health data.

    However, the per-genome or per-locus rate of Mendelian disorders can estimate the per-site rate of mutations only by adding well-resolved information about the target size of functional genes. For example, if we know the average gene length and the proportion of different amino acids in functional proteins we can make some estimate of the ratio of synonymous to nonsynonymous sites. But we would still lack information about the fraction of nonsynonymous mutations that cause deleterious effects on protein function. For this reason, it was possible for very early workers (e.g., Haldane) to come within the ballpark of per-locus mutation rates even before the genetic code was available. Yet such estimates are not strictly useful for understanding per-site rates of mutation.

    By 2000, widespread sequencing had begun to identify disease-causing mutations at the sequence level. When exons are known, it is possible to determine the "target size" -- the number of sites at which loss-of-function mutations may occur. These two values provide the numerator and denominator for an estimate of the per-site mutation rate.

    Kondrashov [9] applied this method to estimate the per-site mutation rate across 20 human genes. He surveyed the literature for genes where more than 100 patients had been sequenced completely for the causative locus, finding the causal mutations. Using this value and the disease incidence allowed an estimate of the per-site rate of mutation for different categories of transitions and transversions. There was some variation among loci, with an average rate of per-site mutation equal to 1.8 x 10-8 per generation.

    Kondrashov observed a few hotspots in these genes, with substitution or deletion rates as much as a hundred times the average site. He also observed that the per-gene rate of mutation varies according to the number of CpG sites. The rate of short deletions was on the order of 5 x 10-10, insertions were even less frequent.

    The rate estimate by Kondrashov is within the range considered by Nachman and Crowell, but only 3/4 of the value 2.4 x 10-8 widely cited as the long-term estimate. If this rate were applied to Nachman and Crowell's pseudogene data, it would predict a human-chimpanzee divergence time around 6 million years.

    This year, Lynch [10] performed a more extensive comparison using similar methods as Kondrashov. Including more genes, and considering a broader range of mutational effects (including missense as well as nonsense coding mutations), Lynch found an even lower estimate of mutation rate per generation -- only 1.28 x 10-8 per site.

    These estimates are not precisely the same as comparing parent-offspring pairs, but they are exceedingly powerful because the data on disease rates encompass very large populations of people.

    We should keep in mind the result of Subramanian and Kumar [2], which showed that exons have a higher effective rate of substitution than do noncoding regions. That result implies that the genome-wide rate of change should be lower than estimated by Lynch, because his estimate encompasses only coding mutations. Also, any effect of purifying selection on these mutations will tend to decrease the long-term rate of substitutions per site to a lower value than the rate of mutations. The rate estimated by Lynch should then be an overestimate of the substitution rate that would be applicable to hominoid phylogenetic relationships.

    A slower rate

    These estimates of the per-generation mutation rate are all low compared to the commonly-cited 2.5 x 10-8. They are not quite as low as the rate estimated by Roach and colleagues [1], but the Lynch estimate is very close: 1.28 x 10-8 compared to 1.1 x 10-8 per site.

    The lower estimate from Roach and colleagues is a direct comparison of parent and offspring. In my earlier discussion of that rate, I suggested that false negatives in the sequence comparisons might have lowered the apparent rate of mutations. I still think we can't rule out that possibility. But the rate is not alone, and so it is less surprising than it may have seemed.

    My post last week on the 1000 Genomes Project results ("Now for anthropological genomics") mentioned that the 1000 Genomes comparisions have arrived at essentially the same rate as Roach and colleagues. Comparison of one family trio led to a rate of 1.0 x 10-8 per site per generation; the other family trio gave rise to an estimate of 1.2 x 10-8 per site per generation. These bracket the estimate given by Roach and colleagues.

    My basic observation about the human-chimpanzee divergence time is still sound:

    If this mutation rate is accurate, then the average human-chimpanzee gene divergence has to be up around 11 million years ago. That can be accommodated with a 7-million-year-old species divergence only if we assume a very large ancestral population -- on the order of 50,000 or higher. Or, the ancestral effective size could be lower -- but that would make the species divergence substantially older -- 9 million years or more.

    As we go further back in time, this lower human mutation rate may be less and less relevant, because different primate lineages may have higher (or lower) rates. When some of the kinks have been worked out of whole-genome sequencing, it would be tremendously useful to sequence parent-offspring pairs in other primate species. With those data, rate heterogeneity could be tested directly.

    For events within the hominins, the parent-offspring rate of mutations ought to be better than a rate estimated from phylogenetic distance. Phylogenetic distances are estimated with even more error than mutations, increasingly so as our methods for comparing genomes improve. But some fraction of new mutations will ultimately be lost to purifying selection. That implies, again, that the longer term rate of substitutions will be lower than the rate of mutations measured from parent-offspring comparisons.

    A rate of 1.1 x 10-8 would have no effect on the number of genetic differences observed between people, because these differences are just counted, not estimated by genealogical relationships that are known. It is the unknown genealogical relationships, which are estimated from genetic differences, that may change substantially.

    Let's consider an example. Harris and Hey [11] sequenced 4200 bp of the gene PDHA1, an X-linked gene whose product is part of a mitochondrial enzyme complex. At the time of their study (1999), their result was one of the oldest coalescence times estimated for non-African populations based on sequence data; they estimated the root of the PDHA1 genealogy was 1.8 million years old. This estimate was based on the assumption that human and chimpanzee copies, which differed by an average of 40.42 substitutions, had diverged at 5 million years ago. That would imply that the average genetic difference between humans across the deepest root of the genealogy, 15.05 mutational differences, corresponds to 1.86 million years of time. If we instead assert a per-generation rate of 1.1 x 10-8 per site, these data would generate an estimate of 163,000 generations for the root of the genealogy, roughly 3.3 million years.

    In other words, a coalescence that appeared to have happened in early Homo now looks rooted at the age of A. afarensis. The chimpanzee-human genetic root would be around 8.7 million years for these data.

    These estimates would likely be biased too low, because the X chromosome has a lower rate of mutation than the autosomes by some extent. That issue was addressed by Lynch [10], due to the fact that X chromosomes are in males (with their higher rate of mutations) only 1/3 of the time compared to 1/2 the time for autosomes. Any purifying selection would also bias the estimate too low. If these 4200 bp have a higher-than-average CpG content, that is one factor that might require a higher per-generation rate.

    Is any of this a problem? I don't think we know yet. A lower rate must readjust the apparent correspondence of some molecular time estimates with the archaeological record. But to be honest, most of the apparent correspondences of such dates have been illusory, because genealogical relationships among genes have such large expected variance under any realistic human population model. It is really the availability of whole-genome comparisons that has a chance of improving these population models.


    References

    1. Roach JC, Glusman G, Smit AFA, Huff CD, Hubley R, Shannon PT, Rowen L, Pant KP, Goodman N, Bamshad M, et al. 2010. Analysis of Genetic Inheritance in a Family Quartet by Whole-Genome Sequencing. Science [Internet] 328:636–639. Available from: http://dx.doi.org/10.1126/science.1186802
    2. Subramanian S, and Kumar S. 2003. Neutral Substitutions Occur at a Faster Rate in Exons Than in Noncoding DNA in Primate Genomes. Genome Research [Internet] 13:838–844. Available from: http://dx.doi.org/10.1101/gr.1152803
    3. Crow JF. 2000. The origins, patterns and implications of human spontaneous mutation. Nature Reviews Genetics [Internet] 1:40–47. Available from: http://dx.doi.org/10.1038/35049558
    4. Nachman MW, and Crowell SL. 2000. Estimate of the Mutation Rate per Nucleotide in Humans. Genetics [Internet] 156:297–304. Available from: http://www.genetics.org/cgi/content/abstract/156/1/297
    5. Yi S, Ellsworth DL, and wen-Hsiung Li. 2002. Slow Molecular Clocks in {Old World} Monkeys, Apes, and Humans. Molecular Biology and Evolution 19:2191–2198.
    6. Steiper ME, and Young NM. 2006. Primate molecular divergence dates. Molecular Phylogenetics and Evolution [Internet] 41:384–394. Available from: http://dx.doi.org/10.1016/j.ympev.2006.05.021
    7. Yang Z. 2002. Likelihood and Bayes Estimation of Ancestral Population Sizes in Hominoids Using Data From Multiple Loci. Genetics [Internet] 162:1811–1823. Available from: http://www.genetics.org/cgi/content/abstract/162/4/1811
    8. Kumar S, Filipski A, Swarna V, Walker A, and Hedges BS. 2005. Placing Confidence Limits on the Molecular Age of the Human-Chimpanzee Divergence. Proceedings of the National Academy of Sciences, U. S. A. [Internet] 102:18842–18847. Available from: http://dx.doi.org/10.1073/pnas.0509585102
    9. Kondrashov AS. 2003. Direct estimates of human per nucleotide mutation rates at 20 loci causing mendelian diseases. Hum. Mutat. [Internet] 21:12–27. Available from: http://dx.doi.org/10.1002/humu.10147
    10. Lynch M. 2010. Rate, molecular spectrum, and consequences of human mutation. Proceedings of the National Academy of Sciences [Internet] 107:961–968. Available from: http://dx.doi.org/10.1073/pnas.0912629107
    11. Harris EE, and Hey J. 1999. X chromosome evidence for ancient human histories. Proceedings of the National Academy of Sciences, U. S. A. 96:3320–3324.
    Synopsis: 
    The 1000 Genomes Project is finding that the mutation rate is half the value usually assumed.
  • Mitochondrial catchphrases

    Wed, 2010-11-03 10:28 -- John Hawks

    I love the first day of the month, because my web stats update at 3:00 am, giving me a more or less random midnight slice of my visitors. Over a longer time, the pages and search terms sort themselves into a predictable pecking-order of traffic. But in those three early morning hours, quirky cool readers rise to the top.

    Monday morning, someone found me by searching for "john hawks chimpanzee driver".

    That is beyond awesome. "Get along, little chimpies!" I'm driving them to the rail spur at Abilene, and I'll slake my thirst with rotgut whisky.

    It's actually quite sensible, as several stories about chimpanzee attacks involve taxi drivers. Go figure.

    Now, as to the reader trying to find some "mitochondrial catchphrases"....well, I have only one thing to say:

    "Free the ATP 38!"

Pages

Subscribe to chimpanzees

Neandertals

For years, I've worked on their bones. Now I'm working on their genes. Read more about the science studying these ancient people.

Denisova

From a finger bone of an ancient human came the record of a completely unexpected population. My lab is working on the science of the Denisova genome.

Acceleration

The advent of agriculture caused natural selection to speed up greatly in humans. We're uncovering some of the ways that populations have rapidly changed during the last 10,000 years.

Malapa

Just outside Johannesburg, the Malapa site is producing some of the most exciting finds in human evolution. This site is the headquarters of the Malapa Soft Tissue Project.