natural selection

The International HapMap is a massive project to determine the genotypes for up to 3 million single nucleotide polymorphisms (SNPs) in samples of people from 11 population samples around the world. The current data release (Phase 3 includes genotypes for a subset of over 1.5 million SNPs in 1,115 people. The 11 population samples include people of African ancestry from the US Southwest, Utah residents of Northern and Western European ancestry, Han Chinese from Beijing, people of Chinese ancestry from Denver, people in the Houston Gujarati Indian community, Japanese people from Tokyo, Luhya and Maasai people from Kenya, people of Mexican ancestry from Los Angeles, Italians in Tuscany, and Yoruba from Ibadan, Nigeria.

As impressive as this effort is, we may wonder why exactly SNP genotyping of so many people is a valuable enterprise in itself. The project’s homepage includes this short statement:

There are theoretical and practical objections to this simple explanation (as I discussed here last month). However, what no one involved with the project seems to have expected is the extent to which the data would demonstrate the importance of recent adaptive evolution in human populations.

Here, I am describing some of the ways that we can test hypotheses about natural selection by using the SNP genotypes from the HapMap. This is a theory-centric description, with some digression into practical aspects of handling the genotype data. First, I consider how we might use information theoretic concepts to test the hypothesis of independence between two genetic loci.

Razib points to a new paper by Johansson and Gyllensten, in which they develop a comparison of F_ST and haplotype block length as a test of positive selection. The paper is interesting enough (and open access) -- they give a list of a few variants that are likely selected in different populations.

What I wanted to point to was this figure:

That pretty much encapsulates the problem of detecting recent positive selection, with current methods. The distribution of selected alleles looks significantly different from the distribution of neutral alleles, but there is a tremendous overlap. Particularly when it comes to choosing an arbitrary cutoff between the two distributions.

Imagine if you had a sample of men and women, and you chose an arbitrary cutoff of stature to distinguish them. Say, everyone over 5 foot 7 is a man. Well, that will do better than chance, but you've included a lot of women in your sample of men, and vice versa. Now, suppose you thought that men were inherently rare compared to women. Say, 100 women for every man. A cutoff of 5 foot 7 inches is going to include many more false positives (i.e., tall women) than genuine men. So you choose a very conservative cutoff, one that is not likely to include very many women. Maybe 6 foot 5. The people you see who are over 6 foot 5 are extremely likely to be men -- not certainly, you still will catch some very tall women -- but quite likely men. But you've excluded 95 percent of the men to do this.

That's the situation we are in with respect to detecting selection. There is an enormous set of false negatives -- truly selected alleles that are indistinguishable by means of an arbitrary cutoff from neutral alleles. In the figure above, Johansson and Gyllensten suppose that each ascertained variant (at s=0.01) represents almost 5 in the population. So far, few have made much of the point that a small number of selected alleles under a very stringent cutoff must correspond to a large number that don't make the cutoff. (our 2007 paper being an exception). The issue is not only ascertainment; it is the shape of the non-ascertained distribution.

Still, one may hope to do better at identifying selected alleles. So far, people have been hacking at these statistical distributions with a hatchet. We need a scalpel.

References:

Johansson A, Gyllensten U. 2008. Identification of local selective sweeps in human popluations since the exodus from Africa. Hereditas 145:126-137. doi:10.1111/j.2008.0018-0661.02054.x

Science has a very important paper in the current issue about the evolution of a gene enhancer in hominids, expressed in forelimb development and concentrated toward the first digit. The enhancer is a conserved sequence named HACNS1, it exhibits a stronger signature of recurrent selection on the human lineage than any other conserved enhancer sequence. In transgenic mice, the human version of this enhancer triggers gene expression in the forelimb, concentrated toward the thumb side, and some other parts of the body, notably the pharyngeal arches (which give rise to elements of mouth, throat and larynx), eye and ear. The research is by Shyam Prabhakar and others at Lawrence Berkeley National Lab, and involves Edward Rubin and James Noonan, otherwise prominent in the Neandertal genome sequencing.

I think this is an extraordinarily important result. You don't see me write those words very often. This is a paper that every biological anthropologist should read. It gives an extremely good example of the importance of developmental regulation to human evolution. We will see many more papers like this one in the coming years. This is one of the genes that makes us human.

Ed Yong of Not Exactly Rocket Science has written a nice online review of the research, and Science has accompanied it with a perspective piece by Gregory Wray and Courtney Babbitt. Here's a quote from that article:

To test the function of this region, they genetically engineered mouse embryos to express a construct composed of human HACNS1, the promoter element of a heat shock gene, and a reporter gene. Their results show that human HACNS1 drives expression in the mesenchyme of the early developing forelimb, and later developing hindlimb, in these mouse embryos. A comparison of expression patterns driven by macaque, chimpanzee, and human orthologs of HACNS1 revealed that consistently strong forelimb expression is a unique property of the human version. By testing various combinations of human and chimpanzee HACNS1 sequences, the authors narrowed down the relevant functional mutations to an 81-base pair region containing 13 substitutions that arose during human evolution. This concentration of substitutions is highly unusual relative to the genome as a whole, implying positive selection on this region during human origins.

The press are going with the story that the evolution of this gene may underlie the unique evolution of human manual dexterity. It's a good hypothesis, but I think there is a more accurate way of putting the situation. We see that the enhancer has effects in different areas of the developing embryo. Its action is therefore pleiotropic: changing its function in one area might well screw up its action somewhere else. So at the very least, this is an enhancer that must satisfy multiple constraints. Strong evolutionary change in its sequence may reflect changes in one of those functions, or more than one. But at the very least, it implies that the hominid developmental program not only satisfies different fitness constraints than in the human-chimpanzee common ancestor, but that these changes required repeated changes.

We don't know how long it would have taken all these nucleotide substitutions to happen. But we might find signs in the fossil record of such a sequence of events, if we had enough bones, and if we had more information about the effects of different forms of the gene on the adult phenotype. For example, the relatively long thumbs of the Hadar hominids (compared to chimpanzees and gorillas) suggest that the sequence of changes started early in hominid evolution. There's a hypothesis.

But like I said, I wouldn't rule out other possible functions of the enhancer as targets for selection. It is plausible (as a hypothesis) that the enhancer with the most selected substitutions on the human lineage might be more likely than others to have been selected for multiple functions. And we have plenty of reasons to suspect selection on its other targets, particularly the developing mouth, throat and ear.

It may even be that the evolution of human thumbs was a side effect of evolution in the throat, or vice versa. That's the kind of weird world evo-devo makes for us!

References:

Prabhakar S and 9 others. 2008. Human-specific gain of function in a developmental enhancer. Science 321:1346 - 1350. doi:10.1126/science.1159974

Wray GA, Babbitt CC. 2008. Enhancing gene regulation. Science 321:1300-1301. doi:10.1126/science.1163568

I have an excellent e-mail question about last week’s Neandertal mtDNA paper, which has provoked a lot of commentary.

Krause et al. (2007) list 15 Neandertal partial mtDNA sequences. Ten of these at that time presented relatively long portions, including the central Asian Okladnikov and Teshik Tash specimens, Mezmaiskaya, Feldhofer 1 and 2, Vindija 75 and 80, Scladina, Monte Lessini, and El Sidrón 1252. The same paper lists five additional specimens for which only a very short sequence had been recovered (just enough to diagnose as part of the Neandertal clade), including Vindija 77, El Sidrón 441, Engis 2, Rochers de Villeneuve, and La Chapelle-aux-Saints.

We do not know that every Neandertal belonged to the same mtDNA clade as those 15 sequences. Some of them may have looked different, possibly including the new clade otherwise present in later Upper Paleolithic and living people. But based on the 15 sequences we have, we can say that a large fraction of Neandertals must have carried the “Neandertal haplogroup.” Exactly how large a fraction depends on what we are willing to believe about contamination, preservation, and the randomness of our sample.

Now, let’s consider the question: Can we predict anything about Neandertal evolution and relationships based on this small, possibly unrepresentative sample of mtDNA?

The answer is that it doesn’t matter very much whether we have 5 sequences or 500. If 15 out of 15 specimens from different sites across Europe preserve a single mtDNA haplogroup, we can’t say it was universal, but we can say it was common. If 40 out of 50, or 400 out of 500 specimens had the same haplogroup, that would increase the precision, but not change the basic fact: Neandertals had at least one common haplogroup that is now so rare it has never been found in a sample of 100,000 or more people. We deserve some explanation.

The possible explanations are:

1. Random genetic drift
2. Accelerated genetic drift due to demographic turnover
3. Population extinction and replacement
4. Natural selection

Drift

Random genetic drift is fairly easy to refute, although it might not appear so at first. In favor of drift: There were few Neandertals, and the population size of the succeeding Upper Paleolithic, up through the Last Glacial Maximum, was also small—the best estimates are on the order of 2000 people for Western Europe and 5000 for continental Europe to the Urals (Bocquet-Appel et al., 2005). There would have been perhaps twice or more that number across the entire Neandertal range. The effective population size represented by this population would have been smaller; perhaps 3000–5000 for Neandertals and Aurignacian-era people, only half, or around 2000, females. Genetic drift in this small mtDNA population would have been much stronger than for autosomal genes, and very much stronger than in most recent human populations.

But when we plug these numbers into a model of random genetic drift, it starts to appear very unlikely that drift alone could explain the observations. Let’s assume (falsely) that our Neandertal genetic samples all dated to 40,000 years ago, and the female effective size was 2000 individuals between then and 15,000 years ago, and that the population of Neandertal country were a random mating pool. Following these assumptions, on averageall the mtDNA genomes at 15,000 years ago would descend from only 4 or 5 ancestral copies in the population 40,000 years ago. If these five ancestral copies were, by chance, a different haplogroup from the 15 copies we’ve already found, then drift could explain the data.

However, this still doesn’t appear very likely. So far, every one of the Neandertals shares a single haplogroup. The frequency of this haplogroup was apparently very high, making it very unlikely that all five ancestral copies would have belonged to some other haplogroups of which we have never found any trace.

Notice that this argument does not depend very much on the number of Neandertal mtDNA sequences that we have found. The fact that there are 15 helps to constrain the frequency of the haplogroup within the population 40,000 years ago, in our model. That frequency is unlikely to be less than around 85%, assuming random sampling. But suppose there were only five. We would still know that the Neandertal haplogroup was very common in its population, even if we thought it was only 50%. It would still be unlikely to draw four or five ancestral copies and have all of them be some other haplogroup that we haven’t found.

This gives us a considerable confidence margin against drift. We need it. After all, the Neandertals were not randomly sampled at a single time, and it is possible that some of them actually carried a human-like mtDNA sequence, which we now falsely interpret as contamination. But even with these shadows hanging over us, it would still be unlikely that none of the ancestors of today’s mtDNA variation were like the Neandertal haplogroup.

Also, the population was not a random-mating pool. When we add geographic structure to the story, which tends to reduce the importance of genetic drift, we find that the possibility that drift alone is almost zero, and it remains very unlikely that a single migration of modern humans interbreeding with Neandertals under random drift could explain the observations, either (Currat and Excoffier, 2004).

Extinction

It is at this point that most geneticists turn to the hypothesis of complete Neandertal extinction. They have a point. Genetic drift apparently cannot explain what we have observed, In their point of view, if genetic drift alone cannot explain the Neandertal mtDNA disappearance, then the only other random process at hand is extinction.

I think that hypothesis is false. It does not account for morphological similarities between Neandertals and later people, genetic evidence that suggests a strong ancient population structure with introgression, or with the apparent behavioral continuity in the Upper Paleolithic.

Happily, I don’t have a commitment to random processes. Instead, I think that the mtDNA evolution of Europe was driven by nonrandom processes of demographic turnover and selection.

Demographic turnover

Here we come to an important point. No one believes that later Europeans evolved from earlier Neandertals by a random process of genetic drift. Yet that is precisely the hypothesis that most studies have set up to refute. Without question it is valuable to set up boundary conditions under the hypothesis of random genetic drift. But the time has come to investigate more interesting models.

Personally, I am surprised that more complicated metapopulation dynamics have not gotten more attention as an explanation for the Neandertal mtDNA results. Population sources and sinks are a hot topic in biology, and you would think that anthropologists would have picked up on this. To my knowledge, the only time anyone has examined a population sink model was in 2001, when Milford Wolpoff and I worked with mathematician Per Enflo on such an idea for Neandertals (Enflo et al., 2001). This idea deserves a fuller treatment (I think I’ll suggest it as a project for one of my classes this year!).

In a nutshell, a population sink is a region where the average rate of reproduction is below replacement levels. This region can remain populated only if individuals migrate in from other places. The places that reproduce above replacement are called population sources. The continual migration from sources to sinks creates a genetic gradient. Individuals sampled at any given time in the population sink are overwhelmingly likely to have ancestors not in the sink but in one or more source populations.

Europe today is a population sink. The population of the continent does not produce enough children to replace itself, and immigration from other parts of the world is high. There are several reasons to suggest that Europe may have been a population sink in prehistory as well. In Neandertal and Upper Paleolithic times, climate fluctuations created unique challenges in Europe, where caloric expenditures were high and food harder to obtain than some other regions.

Continual migration into Europe would provide a simple explanation for why none of today’s mtDNA haplogroups derive from the European Neandertals. The mtDNA population of 15,000 years ago had a few ancestors 40,000 years ago, and none of these ancestors lived in the sink population—all came from the source population in Africa or West Asia. The Neandertal mtDNA variation would have been a short-lived phenomenon, continually being turned over from source populations. Some Neandertal genes would have survived in Europe for hundreds of thousands of years, but some would have come in with more recent migrants from the population source.

There are points that argue against this source-sink hypothesis. The Neandertal-human divergence time for mtDNA is not very different than that estimated for the autosomal genome. If a European population sink had made genetic drift more powerful, that should have affected mtDNA more than the autosomes, so we might expect a more recent mtDNA divergence. Still, there is nor reason why the source-sink dynamic need have been constant over Neandertal evolution, and there may have been multiple sources in the Pleistocene, not only Africa and West Asia. Investigating the boundary conditions of the source-sink model and its correspondence to autosomal genetic results would be helpful.

I should note that mtDNA is not special. Neandertals had lots of traits that are now very rare. The horizontal-oval, or “bridged” mandibular foramen is a prominent example. Out of the relatively small sample of Neandertal mandibles, half have this derived form. Fewer than one percent of recent European mandibles have this form. As for mtDNA, a once-common variant is now very rare. And as for mtDNA, we deserve some explanation. A source-sink model would appear consistent with the continued evolution of such traits during the Upper Paleolithic—a time when the extinction and replacement hypothesis predicts no change in these characters.

Natural selection

The other nonrandom hypothesis is natural selection, which would presumably have favored one or more modern human types while eliminating the original Neandertal haplogroup. I won’t say much about that hypothesis here, since I discussed it in my initial post about the whole-mtDNA-genome sequencing. Selection has a leg up over the other hypotheses now because it seems like there’s good evidence it happened.

Still, selection on mtDNA alone could not explain the total pattern of observations about Neandertals. Physical traits that were once frequent in Neandertals were much less common or absent in later Europeans, and some continued to reduce in frequencies over time. To explain these changes, we must invoke either selection on other traits, or continued demographic turnover in the post-Neandertal population (probably more immigration into Europe) or both.

So selection on mtDNA has never been a sufficient or necessary hypothesis, even if we assume that other genes carried by Neandertals still survive. But given the current evidence that suggests something distinctive about the mtDNA of recent humans, natural selection may receive renewed attention as a factor in the disappearance of the Neandertal mtDNA haplogroup.

References

The keywords to the article include, "carnivorous marsupial" and "precocious breeding." What better teaser could you possibly hope for?

Tasmanian devils are dying because of a transmissible cell line infection, or "cancer," decimating their population. In fact, in some places it's killing 9 out of 10, which is way beyond decimation.

The new paper by Menna Jones and colleagues claims that the population is evolving toward a radical life history solution to the problem: Tasmanian devils are starting to mate and have large litters after a single year, before they have a chance to succumb to the disease:

This change in life history is associated with almost complete mortality of individuals from this infectious cancer past their first year of adult life. Devils have shown their capacity to respond to this disease-induced increased adult mortality with a 16-fold increase in the proportion of individuals exhibiting precocious sexual maturity. These patterns are documented in five populations where there are data from before and after disease arrival and subsequent population impacts. To our knowledge, this is the first known case of infectious disease leading to increased early reproduction in a mammal.

It's a simple response: young breeders used to have lower fitness, because of competition from older adults. Now, the high mortality after the first year has made it a losing strategy to wait to reproduce. When the early breeders are the only ones having many offspring, the population will evolve quickly to early breeding.

References:

Jones ME, Cockburn A, Hamede R, Hawkins C, Hesterman H, Lachish S, Mann D, McCallum H, Pemberton D. 2008. Life-history change in disease-ravaged Tasmanian devil populations. Proc Nat Acad Sci USA (in press) doi:10.1073/pnas.0711236105

This is the first in a series of essays titled, "Practical Evolution." Here are links to the whole series and the series introduction. I've decided to break the articles up into two parts, so that a full essay will appear in two successive weeks. So if you enjoy the current installment, by all means come back on Friday, when I will follow the threads of dispersal by way of an obnoxious animal pest right back to hominids.

Spring has finally come to us here in the North, and it's time to start thinking about planting. So, when I went to a seminar yesterday by John Willis, it was with dual motives.

Naturally, I was interested in hearing about his work relating the evolutionary ecology of Mimulus species to their genomics. As Willis and his many former and current lab members made clear in a recent review article in Heredity, monkeyflowers have become a really interesting model system for studying the dynamics of natural selection on genomes -- particularly, with relation to local ecological adaptation, and also with relation to speciation.

But I was also thinking about whether I could find a nice flower variety for my garden. I'm not particularly excited about peas, and I tolerate Arabidopsis when it comes up, but let's face it, it's not exactly a show flower. I'd love to get one of the prettier hawkweeds going (these have eponymical appeal as well as botanical interest) but the common ones are pretty boring.

Well, Willis's lab has been a center of development for Mimulus genetics. They have developed a store of SNPs and other markers (available at the Mimulus evolution website) for QTL mapping, and are using them to find genes responsible for ecological adaptations in different wild Mimulus populations. In the talk, Willis featured some of his collaborators' work finding genes involved in wet versus dry habitat adaptations and in early versus late flowering. These traits are connected to each other, as well as to other life history, plant size and flower size.

I left having my prior belief abundantly confirmed: botany is awesome. I mean, think about it. You can go outside, in your own neighborhood, and study biology. You can uproot your subjects and transplant them somewhere else, to watch how well they do. If they die, well, that's a data point, not an ethical emergency! Worried about gene-environment interactions? No problem, just put samples of all your subjects in the same greenhouse and wait. Need to isolate a QTL against a uniform genetic background? Cool, just repeatedly backcross it into an inbred line for a few generations, selecting for the trait each time. Want to study genetic correlations? Well, you can breed a thousand plants and select for any trait you want!

Oh, and if you want to, you can clone them.

Let's look at an example, from the Heredity review:

Recent work on floral evolution demonstrates that fundamental evolutionary questions can be addressed in Mimulus through the combination of field experiments and modern genomic approaches. Bradshaw et al. (1995, 1998) pioneered the application of genome mapping to study of ecologically important traits in Mimulus using RAPD and allozyme markers to map floral QTLs underlying the divergence between red-flowered, hummingbird-pollinated M. cardinalis and pink-flowered, bee-pollinated M. lewisii. The initial mapping experiments, with hybrid phenotypes measured in controlled greenhouse environments, revealed QTLs with major effects on virtually every floral character studied, from coloration and morphology to nectar production. To determine the effect of these QTLs on pollinator visitation and discrimination, Schemske and Bradshaw (1999) moved the genotyped hybrids to a field site near one of the few regions where the species coexist, and observed bee and hummingbird visitation behavior. Amazingly, the M. cardinalis allele at a single QTL, YELLOW UPPER (YUP), was responsible for an 80% loss of visitation by bee pollinators, and the M. cardinalis allele at a QTL responsible for variation in nectar production doubled hummingbird visitation (Schemske and Bradshaw, 1999). Bradshaw and Schemske (2003) subsequently created near-isogenic lines (NILs), where heterospecific alleles at YUP were reciprocally introgressed into the parental genetic backgrounds, and evaluated the response of pollinators to the NILs in the field. They observed an even clearer pattern of pollinator discrimination due to this locus, with a 74-fold increase in bee visitation in M. cardinalis NILs that carried the M. lewisii YUP allele, and a 68-fold increase in hummingbird visitation in M. lewisii NILs with the M. cardinalis YUP allele. Although the ecological context, in this case the community of potential pollinators, is certainly important to the evolution of new pollinator associations, these results also demonstrate that single genomic regions can have a large effect on major evolutionary transitions (Wu et al. 2008: 224-225).

The talk was mostly focused on the Mimulus guttatus complex, where some of the most pressing issues are life history, drought tolerance, and tolerance of high mineral concentrations, such as salt or copper. They were able to trace many QTL's of small effect with relation to the major differences in life history and moisture requirements in ecogeographic races of M. guttatus, to show that the within-population variation for these traits is caused by high-frequency (likely balanced) alleles rather than mutation-selection balance or rare alleles, and to find the correlated responses to selection of different plant traits based on different QTL's.

With respect to the genetics of speciation and ecogeographic race formation, they are helped by a long history of research on Mimulus. For example:

Macnair and Christie (1983) performed the first direct genetic analysis of hybrid incompatibilities in Mimulus. While studying the genetic basis of copper tolerance in California populations of M. guttatus, they noticed that some crosses between plants from the copper mines and certain other populations resulted in F1s that died as young seedlings. Further crossing studies revealed that the F1 lethality was caused by a deleterious epistatic interaction between the copper tolerance allele from the mine populations (or a gene tightly linked to it) and alleles at an unknown number of different loci from the other populations. Such deleterious interlocus interactions, usually referred to as Dobzhansky–Muller (D-M) incompatibilities, are thought to be the major cause of low hybrid fitness in plants and animals (reviewed in Coyne and Orr, 2004). Remarkably, it appeared that natural selection for copper tolerance had indirectly resulted in the evolutionary origin of the hybrid incompatibility (Wu et al. 2008:226).

So yes, say what you want, botany is awesome. Plus, there's one more thing: I sat through an entire lecture about natural selection and ecological differentiation of species and races, and never once heard the word, "bottleneck." It was like traveling to some kind of bizarro world where biologists still read Darwin!

So we come down to the really difficult question: which variety am I going to plant? Mimulus glabratus is native here in Wisconsin, including Dane County, but it is not very showy, and prefers wet habitat. That makes it a poor fit for my native plant patch, which is dry/mesic, and which I never water unless the black-eyed Susans and bee balms start to wilt. Mimulus ringens is prettier, with bigger, lavender flowers, but also likes it wet.

I guess I'll have to keep looking. M. lewisii is a pretty variant, if I can find a good source for it, and I can keep it in one of the wetter corners of the yard. I would try for M. cardinalis, since we have hummingbirds sometimes, but I'd like to get Lobelia cardinalis going also, and it's a lot easier to find. Besides, it hardly looks like a monkey!

References:

Wu CA, Lowry DB, Cooley AM, Wright KM, Lee YW, Willis JH. 2008. Mimulus is an emerging model system for the integration of ecological and genomic studies. Heredity 100:220-230. doi:10.1038/sj.hdy.6801018

That's the thrust of a technical comment by Graham Coop and colleagues, now online in Molecular Biology and Evolution. The letter refers to the extraction of FOXP2 from two Neandertal specimens from El Sidrón, by Johannes Krause and colleagues, reported last year (I wrote about the paper here).

First, the bad news. The current letter raises the prospect of contamination. Notably, the controls applied by Krause et al. (2007) may be relatively weak evidence against contamination, because of polymorphism within large human comparative samples. The tests rely on the assumption that there is little DNA from living humans in the samples. But if we cannot distinguish Neandertal from human DNA with great accuracy, then we will be mistaken some proportion of the time. Krause et al.'s test, based on derived human alleles absent from the Neandertal genome draft, can still go wrong if the human contaminants happen to have all the ancestral (non-derived) human alleles.

Well, that seems to be the story these days with Neandertal DNA extraction. No test of contamination is good enough. (And remember, that every "test" of contamination is really a procedure for excluding the hypothesis that ancient sequences are identical to recent ones.)

Now, the more interesting news. Coop and colleagues verify that the selective sweep affecting human FOXP2 was indeed recent -- they estimate 42,000 years ago:

To demonstrate this, we estimated the time of the most recent common ancestor (tMRCA) of the selected haplotype (see Figure 1), using an approach sometimes called phylogenetic dating (Thomson et al. 2000; Hudson 2007). This method does not make assumptions about demography and selection, but only requires that the mutations in the intron be neutral or nearly neutral. Taking this approach, we obtained a mean tMRCA of 42 Kya (see SOM for details). While there is considerable uncertainty associated with this estimate, it is surprisingly recent if selection took place over 300 Kya (see SOM). In other words, the selective scenario proposed by the authors cannot account readily for patterns of variation in modern humans. Given that we have no power to detect a beneficial substitution that occurred over 250 Kya, (cf. Sabeti et al. 2006) yet we see a footprint of positive selection at FOXP2, the conclusion of a recent selective sweep at FOXP2 is not surprising (Coop et al. 2008:3-4).

FOXP2 is in one of the ENCODE regions, so its variation is pretty well known. This is not a problematic case: it has a very limited amount of variation around it, and has a strong excess of rare alleles, both signs of a recent sweep.

Coop and colleagues suggest that the beneficial human allele spread into Neandertals (or vice versa) by low levels of gene flow coupled with its selective advantage -- in other words, introgression.

They do allow for an alternative -- perhaps the two amino-acid-coding mutations were not the target of selection, but instead some linked locus. This would not erase the necessity of gene flow from Neandertals, but would question whether this gene flow had involved the FOXP2-language scenario, since it might be some linked gene unrelated to language.

(CORRECTION (2008/04/18): If selection were on a linked site, then Neandertals might share the human-derived amino acids as a result of ancient shared ancestry with humans, while the linked selected sweep might be absent in Neandertals, not necessitating any gene flow.)

I doubt this hypothesis of a linked sweep, since the two sites with human-derived substitutions are otherwise very strongly conserved among mammals. This looks like a credible target for recent selection. But the hypothesis of selection on a linked site cannot presently be tested.

So that's the story. It seems very likely that Neandertals got the language gene from us, or us from them, long after many other genes in the two populations diverged. I write "many" rather than "most" because we haven't really been able to assess the proportion of derived alleles shared by humans and Neandertals. The completion of the draft sequence may help, but I'm afraid that the specter of contamination is going to keep on being raised whenever a part of the Neandertal draft genome looks humanlike.

(via Dienekes)

References:

Coop G, Bullaughey K, Luca F, Przeworski M. 2008. The timing of selection at the human FOXP2 gene. Mol Biol Evol (in press) doi:10.1093/molbev/msn091

A complicated story is tangled through this paper by Augustine Kong and colleagues, and I don't see where it may end. But here's the abstract:

The genome-wide recombination rate varies between individuals, but the mechanism controlling this variation in humans has remained elusive. A genome-wide search identified sequence variants in the 4p16.3 region correlated with recombination rate in both males and females. These variants are located in the RNF212 gene, a putative ortholog of the ZHP-3 gene that is essential for recombinations and chiasma formation in Caenorhabditis elegans. It is noteworthy that the haplotype formed by two single-nucleotide polymorphisms (SNPs) associated with the highest recombination rate in males is associated with a low recombination rate in females. Consequently, if the frequency of the haplotype changes, the average recombination rate will increase for one sex and decrease for the other, but the sex-averaged recombination rate of the population can stay relatively constant.

Perhaps it's not so curious that alleles of this gene have opposite effects on recombination in males and females. The mechanisms of gamete production are obviously different in the two sexes, and we might expect some kind of frequency-dependent mechanism to regulate recombination. At least, it's a hypothesis.

What I find mysterious is this:

A phylogenetic analysis of a 55-kb region containing rs3796619 and rs1670533 in the HapMap data (24) revealed three well-differentiated clusters of haplotypes showing notable differences in frequency between the Yoruban Nigerians (YRI) and CEU and East Asians (CHB and JPT) (fig. S6). The [C,T] and [T,C] haplotypes that associate most strongly with recombination rate have a combined frequency of only 17% in the YRI sample, but reach a frequency of 91% and 98% in the CEU and East Asian samples, respectively. Several SNPs in this region show an unusual degree of divergence among the HapMap groups, on the basis of the rank percentile of their FST values (Wright's coefficient, a measure of variance in allele frequencies among populations) among all autosomal SNPs with the same overall frequency in the HapMap. Specifically, we identified eight SNPs whose FST values are in the top 0.5% for differences between the YRI and East Asian HapMap samples and also in the top 5% of differences between the YRI and CEU samples. Each of these SNPs differentiated a subset of [T,T] haplotypes from the rest, perhaps indicating an episode of positive selection (or a severe founder effect) that increased the frequency of [C,T] and [T,C] haplotypes in the ancestors of European and East Asian populations.

The [C,T] and [T,C] haplotypes are the ones associated with increased recombination rate in males and females, respectively. The markers are in strong disequilibrium (no [C,C] haplotypes were observed), and seem to have been selected outside of Africa.

I have no idea why.

The recombination rates were all inferred from a large Icelandic sample, so maybe the rates don't really characterize the haplotypes in other populations. Maybe recombination rate is incidental to the real reason for the selection. Or maybe in populations roaring with positive selection on many genes at once, it is a good thing to break them apart more often.

References:

Kong A and 16 others. 2008. Sequence variants in the RNF212 gene associate with genome-wide recombination rate. Science 319:1398-1401. doi:10.1126/science.1152422

The PNAS Early Edition this week includes a paper by bee genome researchers Amro Zayed and Charles Whitfield. After a short review of honeybee phylogeny, they demonstrate two things:

1. An ancient dispersal of honeybees from Africa into Europe was accompanied by a pulse of positive selection on coding genes, amounting to selection on approximately 10 percent of bee genes.

2. As Africanized bees have spread across South and into North America, adaptive genes from the existing populations of European bees have introgressed into the Africanized population, increasing under positive selection.

These are remarkable parallels to the worldwide evolution of humans. In bees, the geographic pattern is not the same, and the timescale is different, but the overall genetic impact is quite similar.

Here's the bee history:

In its native range, A. mellifera is classified into approximately two dozen subspecies, which are further organized into four major geographically and genetically distinct groups: African, Western and Central Asian (hereafter referred to as Asian), Eastern European, and Western and Northern European (hereafter referred to as West European) (9-11). European honey bees were introduced by humans to the New World by European settlers as early as the 1600s. In Brazil in 1956, an intentional introduction of African honey bees (A. mellifera scutellata), which hybridized with previously introduced European bees, led to the establishment and spread of the highly invasive and economically devastating Africanized honey bees in North America and South America (12). Subsequent studies have shown that Africanized bees are predominantly African in ancestry with minor but consistent contribution from European genotypes (11, 12). Using recently developed SNP panels, Whitfield et al . (11) demonstrated that the honey bee originated in Africa and subsequently expanded into Eurasia in two or more independent ancient expansions. One expansion gave rise to Western European honey bees, and at least one other independent expansion gave rise to Asian and Eastern European honey bees. Honey bee subspecies vary in a host of phenotypic traits, such as morphology, behavior, physiology, and gene expression (9-11, 13, 14) (Zayed and Whitfield 2008:3421).

I was not aware of the initial dispersals of bees into Europe and Asia. The genetic data show that the Western European strains are the ones with the most adaptive evolution since their dispersal from Africa. The separate ancient bee dispersals were documented by Whitfield et al. (2006), but they were not able to provide date estimates for the ancient dispersals, and none are attempted in this study.

This is the kind of test that ought to fail in most wild populations. Without a shift in the adaptive landscape, the fraction of new mutations with potential adaptive value is bound to be small -- because species are optimized to the environments that they have occupied for a long time. But European bees have a number of recent environmental changes, ranging from the simple effect of moving from a tropical to a temperate environment, the need to use new and different flora, and the effects of domestication. In a very numerous, rapidly dispersing species, these effects led to a rapid adaptive response in a large proportion of genes. These are the basic principles underlying the recent acceleration of positive selection in our lineage also.

The introgression of European genes into the dispersing Africanized bees in the Americas is interesting, because it seems counter-intuitive. The main differences between Africanized bees and European bees involve adaptations to climate. European bees put up lots of honey for the winter, and swarm less frequently, in addition to being more sedate. African bees don't bother with as much honey, which together with their more frequent swarming would seem to be a good fit for the tropical pattern of seasonality. These African traits explain why the African bees have spread at the expense of the European bees across the tropical New World. But Africanized bees have picked up a lot of genes from the European bees in the New World.

The authors propose some possible explanations:

The adaptive value of functional (coding) portions of Western European genomes could be related to positive selection on novel variation in West European bees, to positive selection on novel hybrid gene combinations, and/or to selection for heterozygous genotypes. Our study thus provides direct evidence that invasive populations can exploit hybridization in an adaptive fashion -- a finding of immense relevance to understanding the dynamics of biological invasions (Zayed and Whitfield 2008:3424).

In other words, behavioral correlates of climate may be a target of selection and introgression -- I would speculate because of the intrinsic rarity of adaptive mutations in these functions.

This is a relatively course-grained analysis of positive selection, since the study basically averages within SNP categories, determining F_ST between pairs of populations. For non-coding SNPs, the Africanized bees are very similar to African bees (F_ST = 0.05), while for coding SNPs they are twice as divergent (F_ST = 0.10). That's a lot of difference in allele frequencies over a short time; it must have been caused by strong positive selection across a broad sample of loci. They do not attempt the same kind of "10% of genes" estimate for the introgression, but their figures show that it is quite significant across their data.

I don't know but it may be a while before this initial study can be followed up with recombination based selection tests, because of this little known fact: bees have a recombination rate of 19 cM/Mb -- roughly 15 times higher than humans. Still, Whitfield et al. (2006) found an excess of linkage disequilibrium in the West European subspecies of bees. It now seems likely that some of this LD is explained by the widespread selection documented in the current study.

In other words, the genetic structure of global bee populations provides another strong example of the importance of rapid evolution in abundant species, coupled with ecological changes. Bees also now provide a strong example of adaptive introgression -- in this case, within a very tightly timed dispersal with known climatic conditions.

References:

Zayed A, Whitfield CW. 2008. A genome-wide signature of positive selection in ancient and recent invasive expansions of the honey bee Apis mellifera. Proc Nat Acad Sci USA 105:3421-3426. doi:10.1073/pnas.0800107105

Whitfield CW and 9 others. 2006. Thrice out of Africa: Ancient and recent expansions of the honey bee, Apis mellifera. Science 314:642-645. doi:10.1126/science.1132772

RPM at Evolgen has a post raising a concern I've been seeing a lot the last week or two:

If you add up all three classes of mutations -- deleterious, neutral, and beneficial -- and figure out how many have fixed over the time scale you're looking at, you get the amount of evolutionary change along the lineage in question. So, to say that there was increased evolution along the human lineage in recent history implies that there was an increase in the total number of genetic changes. However, an increase in the amount of adaptive evolution (or an increase in the number of mutations fixed by positive selection), means there was an increase in the number of beneficial changes along the human lineage in recent history.

Here's the point in a nutshell:

1. Our recent acceleration paper suggests that the rate of adaptive human evolution has vastly increased during the past 40,000 years.

2. Some people confuse the idea of adaptive evolution with the idea of neutral evolution.

3. We can't let this happen, because, well, choose one: (a) we're good acolytes of Stephen Jay Gould; (b) people might start suggesting that all the human phylogeography based on "neutral" loci is irrelevant or worse; (c) we have a deep concern with the pattern of evolution of gene variants that don't actually do anything interesting.

I tend to notice that the various critiques of acceleration don't include any mathematics. I don't really understand this, since the math is simple. It is a whole lot easier to look at this algebra than to write a four or five-paragraph blog post!

So, let's consider some of the mathematical relations describing neutral evolution and how they apply to the recent increase in human population numbers.

1. The expected change in frequency of a neutral allele each generation is zero. That is, after all, why we call them neutral.

2. But the variance in the change in frequency of a neutral allele is related to population size -- in fact it is p(1 - p)/2N_e, where N_e is the effective population size (actually the variance effective size).

3. Because of this relation, neutral alleles in large populations change more slowly in frequency than those in small populations. Once human populations reached an effective size on the order of 100,000 -- certainly by 40,000 years ago -- the change in allele frequency due to drift alone became extremely small (on the order of 10^-6 or less per generation).

4. So neutral evolution in the past 40,000 years should have vastly slowed compared to earlier phases of human evolution.

Except...

5. Changes in population size make absolutely no difference to the neutral substitution rate. The rate of generation of new neutral mutations is directly proportional to population size (2N_eu for an autosomal locus). But the rate of fixation is inversely proportional to population size (1/2N_e). So the neutral substitution rate is simply u: the neutral mutation rate, irrespective of population size. That's part of what makes the neutral substitution rate cool -- and of course, what underlies the molecular clock assumption.

6. From this, we might conclude that the rate of neutral evolution was absolutely unchanged in the last 40,000 years. Of course, now it is obvious that the problem is what we mean by "rate" -- do we mean the substitution rate or the per-generation rate of change in allele frequency?

Except...

7. It should be obvious that we don't mean "neutral substitution rate" because this is irrelevant to recent human evolution. The fixation time of a new neutral mutation is directly proportional to the effective size of the population (4N_e generations for an autosomal locus). It doesn't take much figuring to show that is a long, long time from now with today's population size. There is no chance that a new neutral mutation within the last 40,000 years could be near fixation today -- in fact, every neutral segregating allele 40,000 years ago ought to still be segregating today!

8. From that perspective, we might well conclude there has been no neutral evolution in the last 40,000 years -- because it is vanishingly unlikely that any neutral variation has been lost during that time.

Except...

9. Our study actually did find a large number of neutral areas of the genome that had recently approached fixation, and a much larger number of initially rare neutral variants that have reached substantial frequencies during the last 40,000 years. Empirically, neutral evolution has been very rapid during recent human history. This is entirely the result of ...

10. Hitchhiking. The fast rate of generation of new adaptive mutations means that the rate of neutral evolution by hitchhiking has vastly accelerated in the recent past. This is, after all, how we manage to find evidence of selection in the first place -- the hitchhiking effect on neutral markers!

Therefore, the rate of neutral evolution in humans really has accelerated, as a function of hitchhiking on new adaptive mutations. For every selected mutation, we are talking about hundreds of kilobases' worth of linked neutral variants that have been experiencing rapid changes in frequency due to hitchhiking. In the long run, this will have not a jot of effect on the neutral substitution rate, but it accounts for most of the neutral evolution of allele frequencies in human populations.

I expect that there will be people who don't like this idea. I expect many of them have been counting on various neutral markers being informative about population movements. I'm not saying that neutral markers aren't informative, but we really need to consider the effects of selection on these distributions of markers.

Another class of people who don't like this idea are those who propagate one of my pet peeves -- the idea that we need to "invoke" selection as some kind of extraordinary event. The use of this term is very clear: Its only purpose is to vilify folks who want to explain evolution in terms of Darwin's mechanism. It's precisely the same way that we vilify creationists -- they want to "invoke" supernatural forces to explain evolutionary changes.

It's time to get the message -- natural selection has been the major force driving recent human evolution. Humans are no exception to the natural order -- any species that has increased in numbers and changed in ecology to the extent of ours should undergo a rapid pulse of selection resulting in the appearance and proliferation of many more new adaptive mutations. In fact, it looks like domesticated species like maize have undergone a similar effect. There's no "invoking" here, and neutrality is not a hypothesis that can explain these observations.

The foregoing should make one thing very clear -- I have nothing against neutral evolution. I am not an "adaptationist", and have no stakes whatsoever in the "adaptationist-neutralist controversy". This is not a matter of preferences or verbal arguments -- it is simple algebra!

What's more, its pretty obvious that this account of recent neutral evolutionis an evolutionary scenario of which Stephen Jay Gould would have been proud: the most widespread source of change in human genes is chance linkage to a relatively small number of selected sites.

It's just that there are quite a few more of these selected sites than anybody probably expected to find.

I've had a very busy couple of days, and haven't been maintaining my reading-and-linking as much as I had hoped. So I wanted to take a few minutes to do a quick tour of the blogosphere to see what people are saying about the idea of acceleration.

I'm linking to posts I have read, and in some cases commented on. They are a mix of explanation of the concepts, applauding the ideas and analysis, and criticism of the methods. What I most want to point out is that the discussion on blogs is at a very high level -- people are reading the paper with much more precision than I have ever experienced in the peer review process. This is really the best that today's science community has to offer.

One of the best posts is over at LiveJournal, where shoshin works through the theoretical part of the paper. Naturally, this is my favorite part -- and shoshin describes things exceptionally well. The beginning is great:

The case for a recent acceleration of human evolution in the last 40K years (and especially the last 10K) follows pretty straightforwardly from evolutionary first principles combined with elementary facts about human history since the late Pleistocene. So straightforwardly, in fact, that you have to wonder why nobody thought of it sooner. It's one of those rare cases where the theoretical argument is so strong that you can pretty much use accordance with it as a test of experimental methods at least as much as the other way around.

---

Razib works through the paper at Gene Expression, in a long, detailed post. I like this part:

We are now the most numerous large mammal on the face of this planet. Using the data above the authors imply that our species has been subject to somewhat more that 1/2 a substitution per year. Remember, a substitution is a replacement of one allele for another at a locus on a population wide scale. If this is correct that means right now every few years alleles driven by selection are being fixed within our species.

---

At the old-school Gene Expression, p-ter posts some analysis and critiques. A great comments section has arisen on this post, including comments from some of the principals, and general comments about the quality of the discussion on blogs compared to the journal process. I've answered some of the points in my rarely asked questions post, but the most powerful part bears repeating:

Every distribution has a tail, so if they were to move their threshold a bit further to the right, surely they'd be able to narrow down the number of regions to something consistent with a constant rate. That is, the entire argument is predicated on perfectly identifying selection in the regions of the parameter space they search. This is a major assumption, and not one I'm willing to make without strong evidence. They provide none.

Actually, with an acceleration of around two orders of magnitude, we can tolerate a lot of slop in the estimates. We don't need to perfectly identify selection -- in fact, we'd still have strong support for rapid acceleration if we threw away 95 percent of our data! Naturally, we don't have to do that -- our methods are based on a threshold that eliminates nearly all false positives, and we are missing the vast majority of events. For one thing, the LDD test doesn't find selection on multiple alleles at the same locus. I am working on new methods that will find some of these kinds of events, but for the time being we continue to interpret all things conservatively.

---

Andrew Sullivan posts approvingly:

I posted on this potentially world-changing research this afternoon. Here's a helpful, chatty, specialist blog with lots of extra links if you're scientifically literate and curious.

What I want to know is, sure, Razib is helpful and chatty, but what am I, chopped liver?

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Larry Moran has added several posts on the research, starting with this one:

In addition to the major flaw in logic, there are many other things wrong with the claim that modern humans have stopped evolving. The claim carries with it a very loaded assumption that is never explicitly stated. The assumption is that humans have pretty much reached their optimal level of fitness for all other characteristics. For example, we are no longer selecting for higher intelligence, or a better immune system, or more efficient energy production, or stronger muscles, or any of a host of other things that might make us better adapted to all environments.

Why is this assumption necessary? Because nobody could possibly suggest that we have stopped evolving without assuming that we have reached optimal fitness for all those things in our present environment.

Larry follows with several other posts, some critical, focused in part on the problem of how much evolution is explained by positive selection as opposed to other forces.

---

Nature's blog, "The Great Beyond" notes the paper and the resulting discussion.

---

More will follow...

n. b. This is a story about my work on recent human evolution, describing some of the main results and how the work came about. The story refers to my paper (with Gregory Cochran, Eric Wang, Henry Harpending, and Robert Moyzis), "Recent acceleration of human adaptive evolution," which came out in December, 2007.

Like most good stories in biology, this one begins with Darwin. Darwin was always very interested in animal breeding, which he considered the best analogy for the process of natural selection. Of course, if you're breeding livestock and want to select for some characteristics, it is important to select from as large a herd as possible, because large populations have more variation in them. Darwin recognized this as an important condition for natural selection, which relies on sufficient variation in natural populations.

[A]s variations manifestly useful or pleasing to man appear only occasionally, the chance of their appearance will be much increased by a large number of individuals being kept.... Hence, number is of the highest importance for success.

These words from the Origin, "number is of the highest importance for success" were influential.

This is a quick review of the research, based on a presentation I gave earlier this year. It is not complete, and glosses a number of very important details. A close reader looking for how to do genomics would be better served reading the actual research paper. Here, I'm trying to express the science for everyone else.

By 1930, R. A. Fisher picked up Darwin's idea about numbers, predicting that evolution in large populations could be faster than in small populations. However, this is not in all circumstances, but only where the number of new adaptive mutations is quite small -- in other words, where evolution is "mutation-limited":

The great contrast between abundant and rare species lies in the number of individuals available in each generation as possible mutants.... The importance of the contrast lies with the extremely rare mutations, in which the number of new mutations occurring must increase proportionately to the number of individuals available.

A long history of research in plant genetics (corn breeding), microbial chemostat experiments, and the examination of pesticide resistance in insects support Fisher's concept. For example, flies subjected to low doses of pesticide in the laboratory tend to acquire very complicated patterns of resistance -- involving slight changes in many different genes. These usually aren't transmitted perfectly and often have fitness costs; it's a very imperfect adaptation. But if pesticide is sprayed over a large area, flies sometimes appear very quickly with a single mutation that confers very complete resistance. Here, the very advantageous resistance mutation is incredibly rare -- it only occurs in maybe one in a billion flies. It would never occur in the small laboratory population.

Our growing population

Human populations have been growing rapidly during the last 50,000 years or so. That increase began around the time of the Upper Paleolithic -- that's documented by archaeological evidence. There was a later massive increase during the Neolithic. This agricultural transition actually was quite heterogeneous: earlier in West Asia and China, later in Europe, and then later still in subsaharan Africa. Last, we have within the last few hundred years seen a massive increase in numbers associated with industrialization and globalization of technology.

One day a couple of years ago, Greg Cochran and I were talking about brain evolution. You have to understand, this is long before we knew about any of these genome scans -- they hadn't come out yet. One of the main mysteries of human brain evolution is why it happened apparently gradually for such a long period of time. It is one of the best cases of evolutionary gradualism. But this is a problem, because directional selection would have too be too weak to take such a long time. Now, we know that brain size is constrained in two directions -- larger brains cost more energy to maintain, but smaller brains come with some functional disadvantages. So this creates a situation where new variants that satisfy both constraints -- costing little energy, or making great improvements in brain function -- must be very rare. It should be mutation-limited.

I remember very well, that at precisely the same moment, we both realized -- "Hey, maybe this great increase in human population size made a difference!" Because as we'll see later, the pattern of change in brain size really changed when populations started to get really big.

You see, this is one of those very rare cases where the theory preceded the data! It is quite simple; the rate of mutations in a population is a linear product of the rate per genome and the population size.

Not all mutations are advantageous, and not all advantageous mutations will be fixed. The vast majority are lost. If a mutation has a selective advantage, then the chance that it will proceed toward fixation (and attain high frequency) is 2s -- "s" here is the fitness advantage. That means that 90 percent of new mutations with a 5 percent fitness advantage are simply lost.

The most beneficial mutations are very rare; it is much more likely that a new mutation will be weakly selected. This is another aspect of selection that has been well-known since Fisher. So the chance of fixation increases with s, but the likelihood of the mutation decreases with s -- in fact, the number decreases exponentially as selection is stronger and stronger.

If you put all these together, you can predict how many selected changes you should see in a population that has been growing in size. This tells us the number of new adaptive mutations that should come into the population each generation. It is still linear with population size -- a larger population should have more mutations in precise proportion to its size.

Still, a very small fraction of the mutations in any given population will be advantageous. And the longer a population has existed, the more likely it will be close to its adaptive optimum -- the point at which positively selected mutations don't happen because there is no possible improvement. This is the most likely explanation for why very large species in nature don't always evolve rapidly.

Instead, it is when a new environment is imposed that natural populations respond. And when the environment changes, larger populations have an intrinsic advantage, as Fisher showed, because they have a faster potential response by new mutations.

From that standpoint, the ecological changes documented in human history and the archaeological record create an exceptional situation. Humans faced new selective pressures during the last 40,000 years, related to disease, agricultural diets, sedentism, city life, greater lifespan, and many other ecological changes. This created a need for selection.

Larger population sizes allowed the rapid response to selection -- more new adaptive mutations. Together, the the two patterns of historical change have placed humans far from an equilibrium. In that case, we expect that the pace of genetic change due to positive selection should recently have been radically higher than at other times in human evolution.

Finding selection in the genome

Now, it comes to a problem of how we can see recent mutations that have been selected. A genome scan is based on things that vary, not things that are fixed. So we are looking at some window of frequencies. In our study, that was a window from around 22 to 78 percent.

Before we go too far, it is important to point out that an adaptive gene will be in a window where we can detect it for only a short time -- it spends a long time getting up to an appreciable frequency (here 22 percent, which is our lower ascertainment bound) and a long time going from a high frequency (here 78 percent) to fixation -- this is for a dominant. But it spends only a very short time in the window where we can see it.

And strongly selected genes go through this window quite a lot faster than weakly selected ones.

The importance of this is that we will see genes with different strengths of selection at different ages. Our constraint is that right now all the things we can see are variable -- but some are variable because they originated a short time ago and were very strongly selected, and others are variable because they originated a long time ago, but were very weakly selected.

You can guess, that we expect to see more of the weak ones than the strong ones, because there should be more of them! So the window should give us a view of the strength of selection as well as the number of mutations. If we can estimate the ages of our mutations, then we can predict how many there should be at different strengths of selection, and try to quantify the effect of population size.

Here, we've drawn a graph showing the number of genes in the window, compared with the number that are still variable in the population -- they are on their way to fixation -- but they are outside the window. This is for a growing population, so you see that the number of these genes increases as you get closer to the present.

There are many more that we can't see than the ones we can see -- this is like the tip of the iceberg. That is one aspect of recent selection; these genes are in this intermediate frequency range for a short time, and there will be many more genes that are too rare for us to see with our current methods, but might be very important regionally or locally in some populations.

Based on a model of population growth, we expect to see a big peak corresponding to the period when humans were growing rapidly during the Neolithic. The distribution should plunge down toward the present, because selection would have to be so strong on such a recent mutation for us to see it -- we're talking about 20 percent or more. Those just almost never happen. The true number, remember, is the iceberg under the water -- but we must make predictions about the part we can see.

Linkage disequilibrium and selection

Now, I need to say a few words about how we find these genes when we scan the genome. The International HapMap consists of a list of over 3 million genetic polymorphisms -- SNPs -- taken from a sample of people with ancestry in Northern Europe, West Africa, and East Asia. When we look at a sample of a long stretch of DNA from several people, we will be considering the frequency of many different polymorphisms.

But more important, we have studied whether each polymorphism is linked to the others. As a new positively selected allele increases in frequency in a population, it is initially linked to a wide region including many nearby polymorphisms. This induces a long-distance association among SNPs, which is called linkage disequilibrium.

When we are looking at a stretch of chromosome, what we can observe is that there are areas where recombination seems to be very rare around one SNP -- an in particular where one of the two SNP alleles has almost no recombinant chromosomes, but the other allele appears to have been recombining normally. That kind of mismatch is a strong indication of selection.

I'm not going into the details of that process right now; I'll be posting some real examples of such LD decay analyses later in the week. After applying the analysis, we found more than 3000 in the Yoruba sample, more than 2800 in Europeans, and more than 2300 in Asians.

These numbers are very large -- they make it look like this aspect of evolution, positive selection on new adaptive alleles, has been going very fast. But how long a time period are we looking at? Based on the local rate of crossing-over, we can say how quickly LD ought to be broken by new recombinations, and that allows us to derive age estimates. The ages represent the time that has elapsed since the initial mutation that established each adaptive allele.

Here is a comparison between the ages of selected variants in the African HapMap and in the European HapMap. Let's look at this graph a little bit.

Each of these dots represents a number of different genes -- the y-axis is number; this is a histogram. The x-axis is the age. So you see, there are many of these selected genes that started around 10,000 years ago; there are many fewer that started around 40,000 years ago, and even fewer starting 80,000 years ago.

These fitted lines are what you get if you fit a one-parameter model with very strong selection to these curves. You can fit these without considering the effects of population growth.

But you notice some differences here between the African and European distributions. Africa has a few more total variants, but it especially has more older variants, before 10,000 years ago. You can see that during that time period, Europe has very few. And Europe has this later peak, where we see an earlier peak in Africa.

These details are a very good match to demographic growth -- Africa had much larger population size during the Late Pleistocene than Europe, but West Asia, and then Europe had earlier Neolithic expansion than Africa -- so we see these early times have a lot more selected variants within Africa, and later on there is a pulse of adaptive variants in Europe.

Testing acceleration

At this point, we have a theory that predicts acceleration of new adaptive variants, and we have data that appear to show a very fast recent rate. But we haven't yet directly tested the hypothesis of acceleration.

We chose a null hypothesis approach. After all, the rate of change looks like it has been very high recently, but what it if were always very high. A constant rate of change is a null hypothesis -- the hypothesis of no change, or in our case, no acceleration. So we worked out the predictions of this hypothesis: a constant, high rate of selection. If we could show that those predictions aren't true, then we could disprove the null hypothesis and show that adaptive human evolution accelerated.

We took several different approaches, testing predictions on different kinds of data. For one thing, if the null hypothesis were true, then there should be a whole lot more selected mutations that have already reached or approached fixation, than the relatively small number that we see still varying in human populations. So to test the null hypothesis, we should look for evidence of these fixed selected substitutions.

That's exactly what we did -- we looked at other means of assessing the number of recently fixed and near-fixed variants.

On the bottom of this graph, we have the European age distribution of variants in our window. This should represent a small fraction of the total number that have happened across this time period. But you can see from this graph, that if the rate was constant, the total number should be very, very large -- since we are looking at 10-generation bins, here we have around 150 predicted substitutions every 10 generations, or around 1/2 per year. Most of these should be way above our window, in fact, as we go back toward 40,000 years ago, almost all should be close to or at fixation.

This large number of completed sweeps should have vastly reduced human genetic variation, because polymorphisms tend to hitchhike along with nearby selected alleles. Hitchhiking up to fixation tends to eliminate variation. When we look at the effect of hitchhiking under this constant selection hypothesis, the genome-wide average diversity should be less than a tenth of what we actually observe. So that also disproves the null hypothesis.

How much acceleration?

Down at the bottom of the graph, you see the predicted number of selected variants over our window, under the hypothesis of population growth -- exactly the demographic growth that really happened to humans. And here you see, that there are many, many fewer of these predicted, and in fact over the long course of human evolution, the rate would have been very low.

We can put a number on just how low, and when we do that, we can see how much human evolution has sped up. For example, if we have 1/2 of a substitution per year, well, there are around 12,000,000 years separating humans and chimpanzees (6 million since the common ancestor, in both these lineages). So if adaptive substitutions had happened at a constant rate as high as the last few thousand years, we should be looking at around 6 million fixed adaptive substitutions between humans and chimpanzees.

But in reality there have been nowhere near that number. There are only 40,000 total amino acid substitutions between humans and chimps. Not all those were selected -- maybe only a third. We can add in some additional selected sites outside of coding regions, but still we are looking at an increase in the rate of new adaptive mutations in humans that is 100 times faster than could possibly have been true during most of human evolution.

Our evolution has recently accelerated by around 100-fold. And that's exactly what we would expect from the enormous growth of our population.

What is all this selection for?

We know something about the functional categories of genes inferred to be under selection; we are studying this now. We expect it will keep us busy for some time.

In a general view, they illustrate the idea that changing cultures and ecologies have been important in changing the pattern of selection. For example, many of the selected genes are involved with pathogen defense -- for new pathogens that didn't always exist. Some are apparently related to metabolism or even directly to diet, in terms of processing new food sources. Of course, lactase is an excellent example in this category.

These are not the kinds of phenotypes that have a lot of visibility in skeletal remains. But we have a skeletal record of these populations during the last 40,000 years. We know a lot about what they looked like and how they changed. So we may try to relate the pattern of genetic, skeletal, archaeological, and other kinds of changes over time.

One obvious way to test hypotheses about these changes would be to sample ancient DNA from skeletons. In this way, we could see if the new selected alleles are in them or not. This spring, a paper by Burger and colleagues (PNAS) sampled ancient European skeletons, Neolithic skeletons, for the lactase persistence allele. They didn't find any who had that allele -- not a single one, and this is in Neolithic populations where today the allele is up over 90 percent in frequency. What is going on there?

In this case, it is quite obvious by considering population genetics. We have a very good date for this lactase persistence allele, from many sources -- it is around 6000-10,000 years old. And you can see in the figure, a new selected allele will remain at a very low frequency for a long, long time after its origin. Here, these skeletons were sampled at a time when the selection pressure favoring the allele was present, but the allele had not yet increased to a substantial frequency. In fact, this allele would have been rapidly increasing through these intermediate frequencies much more recently -- we're talking here about Roman times. And today it is over 90 percent in Scandinavia, but considerably lower in Italy and Southern Europe.

In the future, we will be able to sample for genes more widely in ancient skeletons. At the same time, we will be able to sample skeletal changes to try to correlate them with allele origins. That is some research that I have applied for a number grants to support, and I think it will be very promising.

Conclusion

I hope that this essay gives an introduction to the work we have done. This was based on a presentation about the research I gave earlier this year. There are many missing ends, and I'll be adding more information over the next several days about ways of testing for selection, as well as some of the more surprising implications of our research. I've written it without a bibliography, which I can direct you to the paper for a full set of references.

Usually an FAQ starts with the easiest-to-answer questions. Those are, after all, the ones that are asked frequently!

But today I wanted to handle some of the hardest-to-answer questions: questions about the paper coming from people who are extremely knowledgeable about selection in the genome. We are working on three years of papers describing local and genome-wide scans of positive selection. At this point, the "best" methods each have weaknesses, and our method (the LDD, or "linkage disequilibrium decay" test) is no exception. People who know the weaknesses should be wondering, how have we taken them into account?

In a tight six-page limit, it is impossible to answer every valid question. We accentuated the most obvious ones, but we considered a wide array of others (and dealt with many during peer review). Still, it would be good to have a resource where these issues are hashed out for anyone to read them.

To that end, I've compiled a list of "rarely asked questions": what I see as some of the most critical problems with a study of recent selection like ours, and how we've addressed these in a way that makes our study conservative.

I will be adding to this list as I come across new critiques. And for those who aren't quite conversant with genomic techniques, I will be putting up a frequently asked question list tomorrow!

Methods to detect recent selection all have biases of one kind or another. How can we be sure that one or more of these biases haven't really exaggerated the number of alleles in your dataset?

We are working with a tremendous advantage that previous studies of recent selection have lacked: Mathematics. Unquestionably, there are biases in the data, and as described below we have minimized these to the extent possible. But unlike every other study, we actually describe the theoretical reasons why selection should have accelerated in the human genome.

Personally, I can't believe that nobody noticed how extreme these estimates of recent selection really are. I guess that folks doing genomics just weren't as primed in evolutionary theory to perceive how weird the human estimates looked compared to what is measured in the wild on other species, or even over the span of human evolution!

In the earliest studies, when people were finding that 3 or 4 percent of a sample of genes had signs of recent selection, those numbers were already extremely high. They got even higher, as more and more powerful methods of detecting selection came online. Our current estimate is the highest yet, but even this very high number is perfectly consistent with theoretical predictions coming from human population numbers.

At one level, the mathematical answer is as simple as "more people means more mutations." But more deeply, we can predict a linear response of new selected alleles to population size, and we can model this response with respect to a particular frequency range. The genome is a complicated place -- with different mutations originating at different times, selected at different strengths, consequently with different fixation probabilities and different current frequencies. For some reason, nobody really tried to describe this mathematically before.

Now, our model is extremely simple -- it can be challenged on several specific bases. For instance, population increase was not a simple exponential -- it grew in fits and starts, with some significant crashes. The average strength of selected mutations probably changed over time, and the distribution of the strength of selection may have departed from our assumptions. Even the adaptive mutation rate may have changed over time.

Still, the general prediction is quite clear: the population has grown, its conditions of existence have changed, and as a result selection on new mutations should have accelerated. And the observed data fit our theoretical prediction exceptionally well. Certainly we could do better if we made a more detailed model, and we will be doing some of that in future papers. But mathematical simplicity has a great virtue: we can see precisely why human historical changes should have accelerated this aspect of our evolution, and we can see the magnitude of the response. That magnitude greatly outweighs all potential biases.

I read on Gene Expression that the statistical power to detect selection varies based on allele age. You have the greatest power to detect things in the last 20,000 years. So it's no surprise that you find the most variants in that time period. How can you claim this is evidence of acceleration?

P-ter's post on this problem is well-detailed. This is quite an obvious issue -- if we are trying to detect alleles between 20 and 80 percent frequency, it is clear that we are going to be detecting recent things -- many old things would already have been fixed.

But we won't detect just any recent things -- in fact, we will not be able to detect recent things that are weakly selected. By contrast, we should detect older things that are weakly selected, but we will never detect older things that were strongly selected -- they're the ones that are fixed now.

We find a peak in the number of selected variants around 5500 years ago in Europeans, around 8000 years ago in Africans. That corresponds to a strength of selection around 3 percent or more. We find relatively fewer variants -- in fact, many times fewer, with a strength of selection of 1 percent or less.

In theory, strongly selected mutations ought to be vanishingly rare. In fact, they ought to be exponentially rarer than weakly selected mutations. That doesn't mean the theory has to be right, but it does mean we need some kind of explanation if we find that weakly selected things are rare, and strongly selected ones are common -- I mean, R. A. Fisher was wrong sometimes, but I'm not going out on a limb on this one.

Acceleration can explain this reversal -- there simply weren't as many weakly selected mutations 15,000 years ago, because there weren't as many people. The more strongly selected mutations in the last 8000 years actually were very rare per individual, but there were many, many more people to generate them.

But maybe ascertainment bias for recent alleles might explain this reversal of theoretical expectations?

Here's the problem: Suppose we are missing lots of selected alleles older than 10,000 years ago. That means there has been even more selection than we now think in the last 40,000 years.

We were very careful in the paper not to tie the test of acceleration to the age distribution of selection. The age distribution fits the acceleration theory beautifully, but this fit is not enough -- if we are willing to believe that selection was always intensely powerful and rapid in humans, then finding that it has recently powerful and rapid would be no surprise!

For this reason, we tested the theory of a constant rate of selection against other kinds of data -- data that aren't drawn from the LDD test. We showed that a constant rate makes many false predictions -- it predicts a tenfold lower heterozygosity than we see genome-wide, it predicts a very powerful association of heterozygosity with recombination rate, it predicts an extremely large number of recently fixed alleles, and it predicts 6 million adaptive substitutions between humans and chimpanzees. None of these predictions are close to reality. The rate couldn't always have been as high as it is now.

Now, suppose we missed a large fraction of old events with the LDD test. That means that the total number of recent events would be much larger than we have estimated. Which means that the recent rate of selection would have been much higher. Which means that a constant rate at that much higher level is even further from reality.

The LDD test is better at detecting selection in areas with low recombination rates. Isn't this is an obvious bias on the analysis?

Possibly. But it is a conservative bias. Consider: if we have a higher power in some regions of the genome, then we are actually missing events in others. That makes our assessments into underestimates of recent selection.

We have made this even more conservative by simply eliminating areas of the genome with very low recombination rates. We didn't include such areas at all, even though other studies have found selected variants in them.

But more important, the denser dataset has allowed us greater power in finding selection in areas of higher recombination. This has resulted in a broad addition of new variants to our list of selected alleles, particularly in the Yoruba sample were background LD is lower than the European or Asian samples.

One recent review (Nielsen et al. 2007) showed that a high proportion of alleles found by the LDD test were in areas of low recombination. But this comparison is very misleading -- that review limited itself to selected alleles shared in all sampled populations -- a tiny subset of 90 genes out of the total 1800 listed by Wang et al. (2006). These are predominantly the oldest alleles -- for which the age-related ascertainment bias is the greatest, and the power is strongest in low recombination regions.

Strikingly, we found that increasing the SNP density in the new HapMap made very little difference to the number of selected variants estimated for the CEU sample -- we believe this is because we are finding basically everything there for the method to find. This leaves significant limits -- for instance, the limited frequency window we used. But we don't think we are missing lots of selection in high-recombination regions.

But wait a minute. What if you are finding more variants in areas of low recombination because they are false positives -- in other words, because you are finding alleles that actually weren't selected?

Ah, the opposite ascertainment bias. This is what we have worked the hardest to avoid -- false positives. We have deliberately excluded areas of the genome to avoid them, and we have used very conservative threshold values for our tests to minimize them.

There are several strong reasons to believe that we are not looking at neutral alleles. Here's what we wrote in the paper:

Recent genetic drift including founder effects would affect all genomic regions equally, but the candidate selected genes occur predominantly in genic regions, and preferentially include genes in functional classes that are plausible targets for recent adaptive changes. Selection is the only explanation consistent with all these features.

Almost certainly, we have some false positives. But they cannot be very common, or they would distort these clear alternative signs of selection.

And more important, we are talking about a number of selected variants 100 times greater than we would expect under a constant rate. If we overestimated by a third (that would be a high error rate, which I think is very improbable), the rate has accelerated by 70 times. If we threw 90 percent of our list away, we would still be looking at an acceleration of 10 times faster! The numbers coming out of every other group looking at selection are within the ballpark of ours, so this is no surprise.

In other words, our tests of acceleration do not depend very finely on the ascertainment of these alleles. I believe our assessments are correct and conservative -- if we made errors, they were by underestimating selection rather than overestimating it.

But every distribution has a tail. If you use any kind of threshold, even a 99.5% threshold, you are going to have false positives, aren't you? And across the whole genome, doesn't that add up to a large number?

Our assessment counts the most extreme 0.5 percent of LD clusters as positively selected. Since the entire genome includes all the selected sites, this is conservative. Simulations showed that this value produced very few false positives. And we have a check against false positives -- if there were many neutral clusters in the data, they would not be associated in genic regions, sorted into certain functional categories, found across the entire range of frequencies, etc.

Also, false positives are very likely to be placed in the oldest time range where LD decay has proceeded to the greatest extent. If false positives were very common, we would see an elevation in this time range, which we don't see.

Why didn't you just used the phased data?

Well, the HapMap phased data are freely downloadable now and I've been working with them. The advantage of working with phased data is that we can look for lower-frequency variants. I'll be giving an example of that next week.

But the phased data weren't available when we did the analysis. And the LDD test really is an elegant way of dealing with unphased genotypes.

Don't we expect evolution to be faster on shorter time scales? The "acceleration" you are finding could just be the fact you are looking at a short window of time.

Geneticists may not have seen this question, but paleontologists will be intimately familiar with it. When we look at evolutionary changes over very long time scales, there is an averaging effect. Fluctuations over time tend to average out, so that the long-term change is relatively slight when measured per year.

In contrast, when we look at evolutionary changes over a short time, any immediate fluctuation will tend to add to the rate of change. So measuring change per year yields a relatively high rate.

It is quite obvious that a very high rate of change in phenotypes per generation cannot be maintained indefinitely. For instance, a reduction of 0.01 percent per generation shrinks a trait to only 1 percent of its initial size in only 40000 generations. Most organisms can't seamlessly shrink down to one percent of their size -- selection ultimately constrains their size. So even very low rates of change cannot be maintained over evolutionary time scales.

From that perspective, we may view it is basically unsurprising that human skeletal features have been rapidly evolving over the last 10,000 years. Sure, this is a higher measured rate than ever before -- even over equivalent time spans like the Neandertal-modern transition in Europe. But it cannot be sustained indefinitely, and may just be an artifact of looking at a sharp fluctuation in a narrow window of time.

I don't think that argument applies cleanly to the last 10,000 years. For one thing, the measured rate of skeletal change actually is surprisingly high, not only compared to longer timespans in the past, but also compared to equivalent timespans. But more to the point, the direction of change has been consistent across populations even as they grew in size. This is not some momentary fluctuation in our evolution, it is an exceptional transient from one state to another.

But even more important, the distinction between short-term and long-term changes in phenotype are simply not relevant to allele frequencies. Positive selection is always relatively rapid on a geological time scale. Some alleles can reverse themselves over long periods of time -- increasing and then later decreasing in frequency, or even holding themselves in long-term stasis. But when we count an exceptionally large number of recent alleles, we are not looking at a normal situation. Most fluctuations do not involve complete reversal -- it is unlikely for a fixed substitution to subsequently be erased completely from our species. So comparing short and long-term changes to gene sequences is comparing like with like to a much greater extent than is true of phenotypes.

How can you say anything at all about the rate of adaptive mutations? Everybody knows that adaptive mutations (choose one) occur rarely if ever...happen almost as common as deleterious ones...depend on the environment, which was constantly changing!

Believe it or not, we actually had a reviewer tell us that positive selection "rarely if ever" happens. Rarely if ever! This was a geneticist!

I think it must have been a slip of the keyboard. In any event, the intrinsic rate of new adaptive mutations per genome (as opposed to per population) is incredibly important in determining how fast selection should have happened in recent populations.

The beauty is that we don't have to know what this rate is. We don't have to make any assumption about this rate. In fact, we have structured our analysis so that this unknown rate is what we estimate using the data from the LDD test.

The incredible strength of our analysis is that we can assess the predictions based on this rate against other sources of data. That is, the LDD test generates a hypothesis about the rate of recent change, and we can show that observed rate is absolutely impossible as a long-term rate of change. Hence, evolution accelerated.

The obvious weakness is that for simplicity we assume the rate is constant, but it almost certainly changed over time. However, we have structured the analysis to be conservative with respect to