acceleration

Peter Ralph and Graham Coop have an interesting paper in the current Genetics, titled, "Parallel Adaptation: One or Many Waves of Advance of an Advantageous Allele?" [1]

Fisher [2] famously considered the case in which an advantageous allele is dispersing through a spatially dispersed population, showing that the dispersal forms a "wave of advance". This work was the foundation for a lot of progress in understanding spatial dynamics of organisms.

As I discussed in 2008 ("Overstating the obvious"), one of the consequences of the Fisher wave model for human evolution is that advantageous alleles will spread very slowly through the population. During the course of the Holocene, a strongly selected mutation might move only across a radius of a thousand or so kilometers. That provides one explanation for why new advantageous alleles haven't spread very far beyond their points of origin -- they just haven't had time yet.

Another reason why an allele might not have spread widely is interference from other alleles with similar effects. I mentioned this process last year ("Spatial variation and near-fixed selected alleles"):

Greg Cochran and I have been discussing this idea for some time. We call it the "Stooge effect". Think of the Three Stooges all trying to run through a door at the same time and getting stuck in the middle. That's what these genes are doing -- all of them are competing to respond to selection, but each is slowed by the presence of the others.

Ralph and Coop have cleverly combined the "Stooge effect" phenomenon with spatial dispersal. They suppose a case in which two separate advantageous mutations arise in different geographic locations, each affecting the same trait. Each begins to spread independently as a Fisher wave of advance. What happens when they meet?

As they show, the dynamics in this case give rise to a static equilibrium -- once the "waves of advance" meet, they stop moving, forming a stable boundary. A new favorable mutation makes headway only so long as it has no equally favorable mutation to compete against.

I like the way they used both analytical approaches and simulations to come to this outcome. The appearance of stable boundaries in a reaction-diffusion system has long been known (demonstrated first by Alan Turing, actually!). But to my knowledge, no one has considered this specific case from an analytical perspective.

The Fisher equation is not all that simple for most students to work with. If you become familiar with the equation, you will notice the key aspect is that it has two separate components -- a logistic (or reaction) component representing the increase in frequency at a single point in space, and a diffusion component representing the dispersal across space.

The muscle of the dispersal process comes from the logistic component. Without the intrinsic growth of the selected allele, the dispersal of individuals along the boundary would not carry many copies of the selected allele into new geographic areas. If the local selective advantage dies, the wave of advance rapidly stalls. A static equilibrium arises, with the frequency of the selected allele forming a cline that correlates with the local selection pressure.

Ralph and Coop's model approximates this case, in a dynamical sense. Each new selected mutation forms an increasing zone in which the selective advantage of other mutations is zero. When those other mutations encounter this zone, they form a stable cline. The cline is stable in the short term, but the diffusion component still disperses copies of an allele; they just lack the muscle to continue their deterministic expansion.

The most interesting simulations by Ralph and Coop show the two-dimensional case, in which the stable boundaries emerge in a "tesselation" pattern.

Figure 6 from Ralph and Coop (2010), showing "tesselations" in 2-d simulations of waves of advance.

The lower three panes in the figure show the stability of the boundaries between the selected alleles. They proceed to fixation locally, but their dispersal stops where they come into contact with other adaptive alleles. Over the very long term, the population will mix -- the diffusion process will slowly carry all these alleles throughout the species' range. Look at the process after a million generations and the entire zone will be gray. But this dispersal occurs at the neutral rate, where the diffusion term is the only factor driving the dispersal.

What about humans?

My graduate student Zach Throckmorton and I have been working in this area for a while now. One of the things that impresses us is the way that much more interesting dynamics can emerge when you alter the assumptions. I learned some of this stuff by talking to Frank Livingstone, who gave a lot of thought to these issues of spatial dispersal and selection as applied to malaria resistance alleles.

In particular, Frank thought about the case where one allele has a slightly larger advantage than another. In some contexts, this allows the "better" allele to overtake and swamp the expansion of the "weaker" (but nonetheless adaptive) one. In others, the two come to a near standstill, one displacing the other only very gradually. Much depends on the timing of the two mutations and the local conditions controlling their initial dispersal.

Ralph and Coop briefly consider this case in their paper, noting that the difference in fitness advantage of two alleles will allow one to advance into the range of the other, albeit at a slower rate. In humans, we may be seeing a smaller subset of cases, where one or more of the alleles have not yet established a wavefront. In these cases, the arrival of another wave can disrupt the spatial pattern of the rarer allele. The diploid case gives rise to the possibility of more complex epistases. Well-defined boundaries between selected alleles are rare, and where they occur (as may be the case with HbC and HbS in Africa), many have focused on negative epistasis as an explanation.

Also, alleles are unlikely to substitute perfectly for each other. In many cases, they may work synergistically -- individuals carrying two selected alleles that affect the same function may outperform those carrying only one such allele. At some point, new selected mutations may start to have diminishing returns, even on a trait like skin pigmentation where dozens of alleles may have been selected in widespread human populations. So the current distribution may to some extent be "frozen", but by a more complicated dynamic than the simple intersection of waves of advance.

As Coop and colleagues showed last year [3], and we discussed in 2007 [4], there are really only few genes that have approached local fixation in recent human evolution. The current spatial pattern of recently selected alleles doesn't look like a tesselation with many alleles near local fixation. Over most of the Old World, it looks like populations have a very large number of very new alleles, far from fixation, and few up over 70 percent in frequency.

So the specific scenario in this paper by itself probably does not explain the overall empirical pattern in humans. But if we consider the current pattern as a transient, approximating the early stages of dispersal for many selected alleles, we may not be terribly far off the mark.

Mutation-limited evolution

This is a long dense paper and there's a lot in it. One further aspect of the paper that I think is essential is the way that Ralph and Coop reiterate the basic point that more people means more mutations. In their case, they focus on population density over space (population number, when you multiply them) as a constraint on the number of possible adaptive mutations. They apply this idea as a hypothesis to account for parallel adaptations that may have emerged in recent human evolution.

Multiple mutational origins are likely if the characteristic length is shorter than the physical dimensions of the region. Eurasia measures >8000 km across, and so Table 1 suggests that multiple origins at a single base pair are very unlikely at the lower population density. On the other hand, if the mutational target is large, then multiple origins are likely at low densities, while at high densities independent origins are ubiquitous. The complementary cases of (rho = 2, µ = 10^–8) and (rho = 0.002, µ = 10^–5) give identical characteristic lengths of 3000 km, although the timescale on which the mutations spread differs. Thus for these two parameter combinations we can expect a few mutations to dominate within continents and for multiple mutations to be common in a population spread across an area the size of Eurasia. Obviously these calculations are very crude, as population densities vary through space and time, and dispersal across continents is not simply a function of geographic distance and individual dispersal. Nevertheless, these calculations suggest that it is plausible that for adaptive traits with reasonable mutational targets (e.g., a change anywhere within a gene or pathway) even low population densities can lead to parallel adaptation across an area the size of Eurasia, and higher densities almost certainly will.

We note that as human population densities have increased dramatically over time, so too has the probability of parallel adaptation. It is interesting therefore to note that a number of recent human adaptations (e.g., sickle cell alleles) involve repeated changes at very small mutational targets in relatively small geographic areas, while older adaptations from single changes (e.g., skin pigmentation) are more broadly spread.

They are describing a scenario in which small human populations would have been mutation-limited -- that is, the number of new mutations is small, making it unlikely that adaptive mutations will happen in any given generation. In such populations, the rate of adaptation is limited by the availability of new mutations. In an extreme -- in the very small effective sizes of Pleistocene human populations -- the rate of adaptation may be extremely slow and regional populations may come to differ at many weakly selected loci, which spread very slowly.

As the population grows, strongly adaptive mutations become more and more likely to happen somewhere in the species' range. Yet they are still relatively rare -- meaning that they have an opportunity to spread fairly far before encountering another equally strongly selected mutation affecting the same trait.

This process can give rise to very large differences on a continental scale, even when the selection pressures in different regions do not differ. In humans, the dispersal of selected alleles across space may have been significantly accelerated by actual dispersals of populations. It is not a mere coincidence that very widespread alleles in Eurasia also tend to be much older than 20,000 years old -- long-distance dispersals prior to that time had a higher chance of leaving a lasting influence on subsequent populations.

But as the population gets bigger and bigger, parallel mutations are more and more likely to happen. As Ralph and Coop point out, at the extreme of large population size and likely mutations, you shouldn't see any new mutations emerging and spreading over very large areas. Any of these mutations would be very likely to encounter other new mutations that do the same thing.

Is this likely in humans? Clearly some mutations have happened recurrently. Making a broken gene is easy -- there's a large mutational target, since a large fraction of nonsynonymous substitutions might do the job. So if there's a net selective advantage to breaking a gene, we ought to see that happen recurrently in human populations.

In contrast, if the mutational target is very small, then mutations will still be rare even in a very large population. If only one base change can have an adaptive effect, that precise change will happen less than once in 10⁹ births (remember that not just any mutation at a site, but some particular mutation is what we may need). If a rare duplication or gene conversion is the necessary change, then it may be much rarer.

Looking across the last few million years, when human population numbers were much smaller than the Holocene, we can be pretty sure that some aspects of our evolution were mutation-limited. The changes that took hold in our ancestors were the ones that happened, and that survived the winnowing of genetic drift. Many changes that would have been adaptive didn't happen in our ancestors. They just weren't lucky enough.

But some of those changes would still be adaptive now, if we could get them. And we have had much larger numbers in the last 10,000 years. Homo erectus needed these mutations, but we only now are seeing them selected in the human population.

Malaria adaptation

Hemoglobinopathies are among the cases of easy mutations -- where breaking a gene is adaptive. It's not just any broken version of alpha- or beta-globin that does the job, though. The hemoglobin needs to be impaired in certain ways to impede the parasites while maintaining blood function. This provides many of the classic cases of human adaptation, and Ralph and Coop turn to this system for examples of parallel adaptation:

The sickle cell allele HbS at the β-globin gene in humans provides a particularly interesting case of putative parallel adaptation. The HbS allele (β6 Glu-Val) has been driven to intermediate frequencies by selection within the past 10,000 years due to increased resistance to malaria of heterozygotes for the allele (HALDANE 1949; ALLISON 1954; CURRAT et al. 2002; KWIATKOWSKI 2005). The HbS allele is present on at least four major distinct haplotypes in Africa, each at intermediate frequency within a different geographic region; the haplotypes are named after the population sample where they were first discovered (Central African Republic, Senegal, Benin, and Cameroon). This is consistent with multiple origins of this single-base-pair change. Note that a distinct, malaria resistance allele, HbC (β6 Glu-Lys), has also arisen in Africa at the same codon as the HbS allele (TRABUCHET et al. 1991; AGARWAL et al. 2000; WOOD et al. 2005a), increasing our confidence that the mutational input was high enough to allow multiple types to arise. However, FLINT et al. (1998) thought the hypothesis of multiple new mutations arising at a single base pair was extremely unlikely and proposed that it was more likely that gene conversion had spread a single mutation across multiple haplotypes.

The theory we have developed can be used to assess the plausibility of the multiple mutational origins of the sickle cell allele, by exhibiting parameter combinations that yield characteristic lengths consistent with the separation of the sample locations. [Recall that the wave of advance, and thus also our model, works in the case of heterozygote advantage (ARONSON and WEINBERGER 1975).] The different HbS haplotypes co-occur within a few thousand kilometers of each other (see Table 5 of FLINT et al. 1998) (noting that these locations are unlikely to reflect the geographic mutational origins, and mutations will have been spread by large population movements). As the HbS changes occur at a single base pair, the mutation rate would have been 10^–8, and we take an s = 0.05 (as in CURRAT et al. 2002). If human dispersal at that time was well approximated by a Gaussian kernel with sigma = 100 km, then a characteristic length of 1000 km would require an effective density of individuals of rho = 25 km^–2, while if sigma = 10 km, then we would require only rho = 2.5 km^–2. This latter set of parameters does not seem unrealistic, considering our knowledge of population density and dispersal parameters, so our model suggests that the hypothesis of multiple origins is not unreasonable.

I think they've got the basic idea correct here, but there are some additional details to consider. The distribution of HbE is not quite so easy to understand if parallel mutations are really so likely, and of course there is the negative epistasis of different alleles (and the thalassemias) which impacts their dispersal ability when they become moderately common. The dynamic may be of similar form to the one described here, but boundaries between alleles may be reinforced by the fitness costs of carrying multiple ones.

This situation raises the issue of path dependence. Some mutations have "first mover" advantages. Once they are common, other adaptive mutations may still occur -- even mutations that are better from the standpoint of fitness -- but be lost or grow very slowly because their net fitness advantage over the common mutant is slight. Where HbE is common, new HbS alleles are unlikely to invade quickly. Where HbS is common, new HbE mutants are similarly unlikely to invade -- even though HbE has a higher fitness.

Network effects among genes may also dominate the spatial dynamics. HbS spread most widely in the context of populations that were already Duffy null, and in which G6PD deficiency was rapidly increasing. The first conditioned the parasite environment -- P. vivax had a strong disadvantage in Duffy null populations, P. falciparum made up most of the parasite load. G6PD deficiency should have impacted the relative advantage of HbS, more and more as it became more common. Those are two loci among many that alter malaria dynamics in Africa compared to South and Southeast Asia.

Conclusions

There is much more to say about this paper -- it's 22 journal pages. But I think I've given an impression of what's there and how the ideas may impact our interpretation of recent human evolution. Many of the central concepts were presaged by earlier work in 2007 and 2008, as reviewed here on the blog. The new analytical and simulation work, I really like.

Hopefully we can get out some shorter papers that will focus on aspects of these problems as applied to humans. A message that comes across very clearly in our work and this new paper is that different time periods in our evolutionary history must have had very different selection dynamics. Pleistocene humans were not only in a different ecology than us, they experienced a radically lower potential for adaptation.

References

Before the Neandertal genome release last week, I was reading (thanks to a correspondent) an essay that James Noonan wrote for the current Genome Research. The piece, titled, "Neanderthal genomics and the evolution of modern humans" is well worth reading. It's a snapshot of what we might reasonably have anticipated would come out of the efforts to sequence Neandertal genomes, without the punchline -- no recognition that we would ultimately turn out to have Neandertal genes.

It will take a while for paleoanthropologists to come to any kind of informed opinion about the importance of the current genome results. The quotes I've gathered from various newspaper sources include a pretty wide range of silly ideas. Maybe some of mine fall in that category. But generally I try to be informed by both archaeology and genetics, and I find that tends to avoid some of the silliest statements.

Note however, there is really no excuse at all for archaeologists saying silly things about the archaeological record.

Noonan's point of view is that of a mainstream geneticists, and is clearly stated. It represents a widespread school of thought about Neandertal genetics, but (understandably) is mostly uninformed by the archaeological record. For example,

The primary motivation behind generating a Neanderthal reference genome is to determine how distinct modern humans really are from all earlier versions of humanity. We are the only remaining human species, and thus we do not know if Neanderthals or our other extinct relatives shared our capacity for invention, abstract reasoning, or language. We have had to speculate on these matters based on the bones, the settlements, and the artifacts Neanderthals left behind. The question of modern human and Neanderthal biological similarity is particularly compelling given the recent common ancestry of both species: Based on both genomic and mitochondrial sequence comparisons, the lineages leading to modern humans and Neanderthals likely diverged in Africa ∼300,000–700,000 yr ago (Krings et al. 1997; Serre et al. 2004; Green et al. 2006, 2008; Noonan et al. 2006). This genetic evidence has become folded into a narrative of modern human and Neanderthal evolutionary history that continues to frame comparative studies of both species. In its simplest form, the modern human and Neanderthal lineages continued on parallel evolutionary tracks subsequent to their divergence, with the descendants of one branch migrating to Europe and giving rise to Neanderthals, and the other branch remaining in Africa and eventually producing us (White et al. 2003; Mellars 2004; Hublin 2009; Tattersall 2009). The modern human colonization of Europe ∼40,000 yr ago potentially brought both lineages back into widespread contact (Mellars 2004).

Given their very recent common ancestry, how much did the species have in common at this point? Were modern humans and Neanderthals capable of interbreeding, and, if so, did it happen to any appreciable extent? Or were the species so different that no meaningful exchange of information could occur?

Well, you know my answer to those questions.

I quoted this part because I think the earlier part of the passage deserves comment. Will the genetics tell us more about the cognitive relations of Neandertals and their contemporaries? Maybe eventually, but for the time being there is a tremendous void in our understanding of functional genetics. We really know nothing about the relationship of genetic variants to the "capacity for invention, abstract reasoning or language."

Compare the situation to "personalized genomics." If we sequence somebody's genome and find new variants, for the most part we have no way of predicting what they do. And even the genes have functionally apparent properties -- for example, a stop codon -- there still may be no practical way to test the hypothesis that it influences a given phenotype.

The archaeological record is actually pertinent to cognition in a way that the genetic evidence isn't yet. That doesn't mean we have many answers -- we're still groping the dark. But if I want to know about the evolution of human cognition, the archaeology is a much better place to start.

What we know about the archaeology seems very clear: Most of the things that later MSA Africans did, Neandertals also did. There were differences, which may have been important -- but those differences don't exceed the variation of material culture in later human populations.

That doesn't rule out that Neandertals may have been cognitively different from us in some important ways. But when we look at the complexity of the material record within Africa, I think it is fair to say that Neandertal behavior fits comforably within the continuum represented by MSA people. "Behavioral modernity" is broadly shared, and doesn't clearly track lines of biological differences. Rachel Caspari and Sang-Hee Lee's work on mortality differences are another concrete illustration of the ways that material culture and behavior do not track with anatomy in these populations.

In the short term, the most important influence of understanding the Neandertal genome will be what it tells us about phylogenetics and demographic history. That is what got all the attention last week, and will continue to occupy many of us in the next few months.

Even though the news of interbreeding is fascinating, working out the phylogenetic relationships of Pleistocene humans is only a first step towards understanding their evolutionary history. Noonan focuses on strategies for uncovering which genetic changes were important to recent human and Neandertal phenotypic evolution. In this respect, the essay could serve as an introduction to the two papers released in Science last week. It explains a bit about why the Neandertal genome is useful for uncovering functional changes in the human genome, and what may prove useful to drive this inquiry further. For example, from near the end of the essay:

These studies illustrate a general strategy toward an understanding of biological differences between modern humans and Neanderthals, in which the first step is the reverse genetic analysis of genes and gene regulatory elements showing human-specific or Neanderthal-specific sequence changes. In this approach, changes in basic molecular functions, such as enhancer activity, protein-DNA interactions, or receptor-ligand binding affinity are identified in synthetic assays. The phenotypic consequences of these molecular changes can then be assessed in mouse models: A recent study describing the introduction of a "humanized" version of FOXP2 into the mouse genome by gene targeting is one early example (Enard et al. 2009). The data from such studies, combined with a growing body of information on human gene function, the effects of genetic variation on human phenotypes, and comprehensive efforts to functionally annotate the human genome, would provide the foundation for more sophisticated hypotheses concerning the biological similarity of modern humans and Neanderthals than can be generated from the paleoanthropological record alone.

Now, in light of last week's data release, we know some things about these general topics. The evolution of human-specific changes in conserved regions, for example, apparently mostly preceded the human-Neandertal common ancestor. There are few amino acid changes in recent (post-Neandertal) evolution that have become fixed worldwide -- the new studies counted only 88. There are only 212 estimated selective sweeps not present in the Neandertal genome.

Those are manageable numbers.

Of course, we shouldn't underestimate how hard it will be to untangle the interactions among these human-specific changes. It may require testing not each change one by one, but many possible combinations of the changes, since we don't necessarily know their order. And it is not only the fixed changes that are important to morphological and behavioral evolution, polymorphisms will also be important. Among those polymorphisms will be later, strongly selected changes that may substantially modify the "fixed" substitutions -- in a few cases, may even reverse them.

But this isn't a hopeless prospect anymore, it's a practical research program. The genetic changes that are nearly fixed in living people but absent in Neandertals represent one of the earliest -- possibly the first -- instances of geographic isolation and selection in Homo sapiens. They are one aspect of a pattern that has become increasingly important in later human populations, as the pace of adaptation has accelerated beyond the ability of gene flow to disperse adaptive alleles. Reconstructing this history will tell us about the shared evolutionary dynamics of humans and Neandertals, and the ecological particularities that may have made both populations phenotypically different.

References:

Noonan JP. 2010. Neanderthal genomics and the evolution of modern humans. Genome Res 20:547-553. doi:10.1101/gr.076000.108

Current Biology has released a special issue titled "Global genetic history of Homo sapiens". There is much of interest in this issue, with seven papers, mostly regionally focused in different parts of the world, but one paper by Jonathan Pritchard and colleagues discussing recent adaptive evolution.

The geneticists to varying extents in this volume depend on archaeological observations, but in many cases read the archaeology very selectively. Speaking as someone who takes archaeology seriously, I find this very frustrating. With more genetic data, we need to demand

An editorial by archaeologist Colin Renfrew leads off the special issue ("Archaeogenetics -- towards a 'new synthesis'?").

Today, we have an abundance of data about the genetic variation of living people that we did not have ten years ago. In addition to our samples from living populations, we are beginning to find a trove of information about ancient people, from DNA extracted directly from skeletal material. But despite the attempts of geneticists and (rather pitifully few) archaeologists, I don't see a "new synthesis" emerging.

Reading the first paragraph of his editorial, it seems to me that Colin Renfrew agrees:

It seems a timely moment to review human population history of the five continents as it emerges from recent archaeogenetic studies, as summarised in the reviews of this special issue of Current Biology. Has the ‘new synthesis’ — between genetics, archaeology and linguistics — arrived which I, perhaps incautiously, heralded a few years ago [1]? These highly informative reviews document, it seems to me, both achievement and uncertainty: the achievement relates to the remarkably consistent picture which has now emerged about the out-of-Africa emergence of our own species Homo sapiens and the initial peopling of the Earth. The uncertainty involves the application of archaeogenetics to the more recent, Holocene period, when most of the planet was already peopled — except much of Oceania — and sedentary, farming-based communities emerged. Here, it appears that much of our current understanding still depends on archaeological or, sometimes, linguistic evidence. And, with a few exceptions, the archaeogenetic evidence has not yet been assimilated into a genuine synthesis; but, let us begin with the good news.

I find it a markedly bad sign that Renfrew thinks the best of "archaeogenetics" is the part with the least archaeological evidence. If the genetics doesn't seem to work where there is abundant archaeology, why should we believe the genetics in cases where the archaeology is poor?

I write that quite seriously, as someone engaged directly with the genetics. It's too easy to make stuff up. How can you test a hypothesis that seems consistent with genetic data? The obvious approach is to try to falsify the hypothesis with archaeological observations -- but sadly, archaeology is often pitifully silent on the subject of demography and gene flow, or there are many scenarios equally consistent with the same archaeological record.

In the Holocene, archaeology has a lot of power to rule out hypotheses about demography and population movement. So this is where I want to see serious attempts to falsify archaeological models using genetics. And that's what we're starting to get! The finding from ancient DNA that early European farmers were neither closely related to earlier hunter-gatherers nor to later agriculturalists has been very surprising. It seems to reject the hypothesis that today's gene distributions come from an initial dispersal of farmers with their Indo-European languages -- the European component of the so-called "language-farming hypothesis".

Why? Well, because a later massive genetic change suggests that the language transition may well have happened a lot later (as suggested by much of the linguistic evidence itself), and the mtDNA haplotypes carried by the early European farmers have no clear relationship to Near Eastern or central Asian populations.

It's no surprise that Colin Renfrew would find disagreements with this genetic work; he's the biggest supporter of the "language-farming hypothesis".

But I think that the current situation is very healthy. Geneticists are testing hypotheses and showing them to be false. At the same time, they're proposing models that archaeology can easily show to be false. For example, many recent evaluations of adaptive evolution have looked for genetic outliers against a "neutral" population model that involves very small Holocene population size. From the genetic perspective, this small population size assumption is conservative -- it means that some genuine cases of adaptive evolution will look less statistically significant. But archaeology can actually inform us about these cases. Any scenario in which the Holocene population was smaller than millions of individuals must be false. In many cases, a less conservative model is in order.

I think there are tremendous opportunities for integrating adaptive evolution remains to be integrated with our understanding of demography. I don't put a lot of faith in the current storyline about genetics and the earlier part of prehistory. That story will continue to develop as we deepen our understanding of the demographic and adaptive factors that have shaped human genetic variation within the last 50,000 years.

References:

Renfrew C. 2010. Archaeogenetics -- towards a 'New Synthesis'? Curr Biol 20:R162-R165. doi:10.1016/j.cub.2009.11.056

I couple of people have asked me about a new paper in PLoS Genetics by Graham Coop and colleagues, titled, "The role of geography in human adaptation." The paper is open access, and while the details of genetic measures and simulations can be hard to follow, I think it's a great example of the way recent work on selection and human diversity has been structured.

I'll just expand on a few of the topics in the paper, and discuss how they relate to the previous findings about the number and age of selected variants in human populations.

Here's the paper's abstract:

Various observations argue for a role of adaptation in recent human evolution, including results from genome-wide studies and analyses of selection signals at candidate genes. Here, we use genome-wide SNP data from the HapMap and CEPH-Human Genome Diversity Panel samples to study the geographic distributions of putatively selected alleles at a range of geographic scales. We find that the average allele frequency divergence is highly predictive of the most extreme F_ST values across the whole genome. On a broad scale, the geographic distribution of putatively selected alleles almost invariably conforms to population clusters identified using randomly chosen genetic markers. Given this structure, there are surprisingly few fixed or nearly fixed differences between human populations. Among the nearly fixed differences that do exist, nearly all are due to fixation events that occurred outside of Africa, and most appear in East Asia. These patterns suggest that selection is often weak enough that neutral processes—especially population history, migration, and drift—exert powerful influences over the fate and geographic distribution of selected alleles.

The paper looks for "nearly fixed" genetic differences between populations, and finds relatively few of them. That's relatively well-known; the F_ST-based test has been done on fewer populations with similar results (e.g., Williamson et al. 2007; Barreiro et al. 2008). This paper has the HGDP panel, which includes many more populations, and therefore is able to add geographic resolution to these older results. They find that the geographic distribution of near-fixed alleles is clinal; there aren't strong boundaries delimiting the geographic distributions of most apparently selected alleles. That means that the same demographic forces affecting neutral genetic variation have also affected recently selected alleles.

Is that surprising? As we pointed out in our 2007 paper, the recent demographic history of human populations has included a lot of population growth. This means that the number of adaptive mutations should have increased during the last 10,000--20,000 years. High-F_ST selected alleles can only reflect selected mutations that are older than this (old enough to reach near fixation in one population), or are extraordinarily strong. A few mutations are exceptionally strong in their selective advantages -- SLC24A5 and lactase persistence seem to be examples. But as long as adaptive mutations are intrinsically rare, very few of them could have occurred in the small populations of 20,000 years ago or earlier, even if many happened in the large populations of the Holocene. So I think the new paper actually reinforces the interpretation of acceleration. The pattern we're seeing today with new mutations just can't be a feature of human evolution before around 20,000 years ago.

If selection is affected by demographic processes, does that mean that it is "weak"? Clearly, "weak" is a matter of scale. Adaptive genes disperse through a spatially structured population very slowly, even if they confer very large fitness advantages. That means that their dispersal is highly dependent upon demographic conditions, such as the disproportionate growth of some populations or occasional long-distance gene flow. Locally, an allele may rapidly increase under selection, but that effect may have little influence on the evolution of distant populations.

We see that pattern with genes known to be under strong selection in humans, like the ones that help some people resist malaria. Sickle cell, hemoglobin C and E, alpha- and beta-thalassemia, ovalocytosis, G6PD deficiency all have restricted geographic ranges that parallel the clinal pattern of neutral genes. There is an important difference: the patterns of these genes diverge in areas where malaria risk changes rapidly with geography (like coastal versus inland areas of Mediterranean Europe), and some of them have wide geographic distributions compared to their young haplotype ages (like sickle cell). But even in the latter cases, most are too rare to elevate the F_ST of surrounding SNP markers. Malaria adaptations are a tremendous example of the way that demographic conditions limit strong selection.

Africa versus other populations

Derived alleles are expected to have lower frequencies on average than ancestral alleles. So if a population has a bias toward higher-frequency derived alleles, that may be evidence against neutral evolution. The paper finds that this bias is greater in non-African populations than within Africa:

The overall genic enrichment is present in all three population comparisons, and each tail seems to be similarly enriched for high- F_ST genic SNPs. However, the number of derived alleles in each tail does differ substantially and is biased towards derived alleles outside Africa and especially in east Asia. Thus, the statistical evidence for enrichment of events inside Africa is weaker than for the other two populations (we return to this point later).

In general, populations outside Africa have a genome-wide bias toward higher frequencies of derived alleles. The causes of that bias aren't clear -- ascertainment may account for some of the bias but cannot account for all of it; it's possible that early demographic events may explain some of the bias but the pattern isn't obvious.

The F_ST-based tests of neutrality are most powerful when a new allele has swept several rare mutations with it to near-fixation. Rare mutations tend to be derived ones. So the power of the test depends on how many rare mutations there are to start with, and what their frequencies are in other populations that didn't have the same selected allele.

It's one of many issues that make finding selection in African populations slightly different from elsewhere. I think that Africans have undergone as much, and very possibly more, selection by new adaptive mutations as other populations. But our 2007 work suggested that the modal age of the selection we ascertain in Africa may be older than in other regions. That would be consistent with demographic history, since Late Pleistocene African populations were larger than others. But it's possible that genome-wide features like faster LD decay, higher heterozygosity, and more ancestral versus derived variants may also influence our estimates of the timing and number of selected alleles in Africa.

Polygenic adaptation

Toward the end of the paper, the authors discuss the pattern of local adaptation in a more general sense. Why should there be relatively few near-fixed genetic differences between populations, if human ecological changes suggest that local adaptation should have been a powerful force in our recent evolution? One possibility is acceleration -- most of the variants are too recent to have reached near-fixation in any single population.

But the authors mention another possible influence that we've also been thinking about: epistatic interactions among new variants. For example, lots of skin pigmentation loci are known to have been under recent selection, but only a couple of them have reached near-fixation in any population. The rest are at lower frequencies. Since these alleles all affect the same phenotype, they're subject to diminishing returns. As one lighter-pigment allele becomes common, it reduces the strength of selection on the others. The population doesn't have to fix for any of them; in fact, selection probably cannot drive more than one or two up to fixation since the rest of them compete with each other.

Over the very long term, this situation would be sorted out. A handful of loci that optimize skin pigmentation might ultimately go to high frequencies or fixation, for some alleles the costs may exceed the benefits and they will disappear. Others, relatively neutral to each other, may fix by drift. But the "very long term" is a span of hundreds of thousands of generations. Here we're talking about a few hundred generations at most. So human populations aren't anywhere near an optimum, they're in a transient where epistatic interactions may be quite important.

Greg Cochran and I have been discussing this idea for some time. We call it the "Stooge effect". Think of the Three Stooges all trying to run through a door at the same time and getting stuck in the middle. That's what these genes are doing -- all of them are competing to respond to selection, but each is slowed by the presence of the others.

It's not a new idea -- Frank Livingstone used to talk about this general concept with different malaria adaptations. What's new is the increasing evidence that humans are really in a transient with a lot of genes out of equilibrium. It's very possible that for some phenotypes, standing variation has been an epistatic block on the selection of new mutations. For others, the emergence of some new mutations has limited the trajectory of selection on others.

Conclusion

All in all, I think this paper is a nice contribution to our understanding of the pattern and rate of recent positive selection in human populations. Certainly, the HGDP sample will continue to be a very informative addition to our understanding of spatial dynamics in ancient humans. The addition of the new HapMap v.3 samples may be even more important, because these represent further regions with roughly the same discovery power as the initial three HapMap samples. And of course, we have the 1000 Genomes sample coming up, adding significant potential for discovering rarer selected variants.

References:

Coop G, Pickrell JK, Novembre J, Kudaravalli S, Li J, et al. 2009. The Role of Geography in Human Adaptation. PLoS Genet 5(6): e1000500. doi:10.1371/journal.pgen.1000500