genome-wide scans for selection

Genetic signatures of recent human evolution, continued

dgmacarthur — Tue, 24 Mar 2009 17:56:37 +0000

Genetic signatures of recent human evolution, continued

Pickrell, J., Coop, G., Novembre, J., Kudaravalli, S., Li, J., Absher, D., Srinivasan, B., Barsh, G., Myers, R., Feldman, M., & Pritchard, J. (2009). Signals of recent positive selection in a worldwide sample of human populations Genome Research DOI: 10.1101/gr.087577.108

I pointed yesterday to a new paper in Genome Research taking a genome-wide look at the signatures of recent natural selection in a worldwide sample of humans.

I promised a more thorough analysis of this paper today, but I see Razib at Gene Expression has already done a fine job of that. Razib's post covers the bulk of the most important findings of this paper in detail, so you should go read it now; I'll really just be expanding on what I see as some of the most interesting nuggets of data.

I also mentioned the paper's rather indirect critique of John Hawks' "recent acceleration" hypothesis, which proposes that humans have experienced very rapid evolutionary change over the last 40,000 years. John Hawks responded to that critique last night, pointing out that the paper does not explicitly test the acceleration hypothesis and that its major findings are in fact consistent with his theory. The paper's lead author, Joe Pickrell, has a quick comment on my post yesterday clarifying his position.

Now, onto what I see as some of the most interesting results from the paper.

Different populations show different signals of selection
This isn't a new finding, but it's much more striking in this study compared to previous analyses due to the massively increased number of populations studied. Basically, this tells us that different human populations have responded to their local environment in different ways - either because their environments were different, or because they had different genetic variants available to fuel the process of adaptation. In other words, not all humans share the same evolutionary history.

This figure from the paper (which I've reformatted slightly) shows the degree of sharing between the top 10 signals of selection from each of the 8 broad population clusters defined in the paper (from top to bottom: Biaka Pygmies, Bantu speakers, Europe, Middle East, South Asia, East Asia, Oceania and the Americas). The colour of the boxes ranges from red (strong evidence for selection) to white (no evidence). There is considerable sharing between Europe, the Middle East and South Asia, but the top hits in the other populations tend to be largely restricted to that group:

This pattern is even clearer in some of the expanded Supplementary Figures (see the example right at the end of the post).

Some of the population differences make perfect sense. The fact that the genes underlying skin pigmentation have been under different selective pressures in Africans and Europeans, for instance, is readily apparent from the strikingly different skin colours of individuals from these populations. What scans for selection (and other evidence) suggest is that these local adaptive differences go deeper than skin colour, likely affecting many different aspects of human biology. Of course that would come as no surprise to most mainstream biologists.

Despite the broad-scale differences between continental groups, the authors found little evidence for differences in targets of selection between closely-related populations; in other words, populations that live close together and share relatively recent common ancestry tend to have experienced similar selective pressures. However, the team did identify signals of highly local adaptation in a few genes, mostly involved in the immune system - presumably reflecting adaptation to geographically restricted infectious diseases.

Regions associated with type 2 diabetes risk show evidence of positive selection
The study looks at regions associated with a whole range of common diseases and other traits (e.g. height), but doesn't find much of a striking signal for any of them. For type 2 diabetes, however, there is evidence that the regions associated with disease risk are also significantly more differentiated than expected between African and non-African populations - a pattern suggestive of recent adaptive evolution. Several of these regions also show linkage-based signals of selection (see below).

What does this mean? It's hard to say precisely, and the authors avoid speculating too wildly about the implications. Because the precise genetic variants that alter type 2 diabetes risk in these regions are yet to be identified it is difficult to determine if selection is acting on these variants, or on other independent variants in the same gene. Still, this is a tantalising clue to the evolutionary origins of one of the most common modern diseases, which I'm sure we'll hear more about in the near future.

We don't understand the function of most genes under selection
As is the case for recent genome-wide association studies for common diseases, the majority of the signals emerging from this study localise to regions that contain either no genes, genes of unknown function, or genes with no obvious link to recent human adaptation. Although the functional basis for some of the signals is clear (e.g. pigmentation genes), most of them currently defy explanation.

A good example is the region that emerges as one of the clearest regions of positive selection in non-African populations, which contains one protein-coding gene and three non-protein coding RNA genes. The protein-coding gene, C21orf34, is just one of the thousands of functionally uncharacterised genes in the genome - essentially nothing is known about its biological role. There are no known genetic variants in any of these genes that could explain the striking evidence for recent selection.

That's the beauty of unbiased genome-wide scans: you don't need to have a hypothesis to find something interesting. The data from this study will serve to guide further downstream analyses exploring the function of the genes in human biology and recent adaptive change.

Power to detect recent selection is still far from complete
Most genome scans for positive natural selection work by looking for unusually strong patterns of association between genetic variants stretching over a long region of the genome. These patterns of association (called linkage disequilibrium) tend to decay over time through the process of recombination. That means that you can use the length of the region of strong association as an indirect measure of how old a variant is; if you find something at high frequency that looks very young, it must have increased in frequency very rapidly and recently.

There are two possible explanations for a variant increasing in frequency very rapidly. The boring explanation is pure chance: random genetic drift, facilitated by demographic changes like population bottlenecks. The more interesting explanation is that the variant increased the reproductive fitness of the individuals that carried it, and thus increased in frequency through positive natural selection.

One of the nice things about this study is that the authors have explicitly examined the power of their algorithms to discriminate selection from the random noise of genetic drift. Here's a figure from the Supplementary Data based on some complex simulations to estimate the power of their two linkage-based methods to detect positive selection:

These two methods are the integrated haplotype score (iHS; top) and cross-population extended haplotype homozygosity (XP-EHH) tests. The authors have simulated the power of these tests to detect positive selection on a variant with a selective advantage of 1% in three populations: East Africans (YRI), Europeans (CEU) and East Asians (ASN), for genetic variants at various frequencies in these populations (frequency is the horizontal axis).

There's a lot that could be said about these graphs, but I'll just make two points: (1) the tests are nicely complementary, with iHS having maximum power for variants at around 70% frequency whereas XP-EHH is well-powered for very high-frequency variants; and (2) even so, there are a lot of positively selected variants that these tests would miss. In East Asia and Europe, for instance, both tests would miss a large majority of selected variants with a current frequency below 50%. That means that extremely recently selected variants in these populations (which are still at a low frequency) would be essentially invisible to these tests.

This problem is especially acute for populations that have been subject to very strong recent bottlenecks (e.g. Native Americans), where the noise arising from the bottleneck can largely confound signals of selection.

All this means that there are a lot of signals of selection out there yet to be found. Increasing sample sizes and exploring more varied populations will help a little, but will bring diminishing returns; for low-frequency selected variants there may well be no feasible way to distinguish them from background noise.

Possibly the most successful strategy will be combining signals from these types of scans with functional information to detect clustering of weak signals in particular biological pathways; this study uses this type of approach to find a compelling signature of selection acting on the NRG-ERBB4 pathway in non-African populations.

Anyway, I gather that a second paper on the same data-set is also awaiting publication, which will have more juicy data to explore. I'll also be following the dialogue between John Hawks and the authors of this paper with some interest.

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As promised above, here's the expanded signal-sharing chart for Bantu-speaking Africans from the paper's supplementary data; the extraordinarily low degree of sharing (even with the other African cluster, Biaka Pygmies) is readily apparent:

dgmacarthur Tue, 03/24/2009 - 13:56

Signals of selection in the human genome: important new paper

dgmacarthur — Mon, 23 Mar 2009 20:10:20 +0000

Signals of selection in the human genome: important new paper

I'll hopefully have more time to write about this tomorrow, but for now I'll simply suggest that you go and readÂ the free full text PDF of this advance online manuscript in Genome Research.

This is the most important recent paper in the field of human evolutionary genetics - a thorough and careful analysis of the signatures of positive natural selection left in our genome by the last 10-40,000 years of adaptation, using a population sample that is far broader than those used in previous studies (53 populations rather than 4). I covered some of the approaches used in the paper in this post on the HGDP Selection Bowser, which is a graphical window into the same data used in this study.

There are plenty of interesting factual nuggets in there for anyone interested in recent human evolution (e.g. evidence for positive selection on type 2 diabetes susceptibility genes); but for those who follow human genetics online the most intriguing paragraph is this one:

Further exploration of the geographic patterns in these data and their implications is warranted, but from the point of view of identifying candidate loci for functional verification, the fact that putatively selected loci often conform to the geographic patterns characteristic of neutral loci is somewhat worrying. This suggests that distinguishing true cases of selection from the tails of the neutral distribution may be more difficult than sometimes assumed, and raises the possibility that many loci identified as being under selection in genome scans of this kind may be false positives. Reports of ubiquitous strong (s = 1-5%) positive selection in the human genome (Hawks et al. 2007) may be considerably overstated. [my emphasis]

Hawks et al. 2007 refers to this paper on the "recent acceleration" hypothesis of human evolution, championed by anthropologist blogger John Hawks and expanded on by Gregory Cochran and Henry Harpending in their recent book The 10000 Year Explosion. To my knowledge this is the first direct challenge to Hawks' hypothesis in the peer-reviewed literature; it will be interesting to see how this discussion develops.

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dgmacarthur Mon, 03/23/2009 - 16:10

Do It Yourself: searching for evolution's signature in 53 human populations

dgmacarthur — Mon, 10 Nov 2008 07:18:16 +0000

Do It Yourself: searching for evolution's signature in 53 human populations

Note: I'm introducing Do It Yourself as a new and hopefully semi-regular section on Genetic Future. The aim is to provide readers with instructions on how to access online resources for sequence analysis - an activity traditionally restricted to researchers, but one that will no doubt become more common as more and more people begin to access and interpret their own genetic data.

In this post I'll introduce the brand new HGDP Selection Browser, a tool for exploring traces of recent positive selection in the human genome produced by researchers at the University of Chicago.

Introduction: the traces of positive selection in the human genome
Over the last 50-100,000 years the human species has successfully spread from its African homeland to colonise nearly every corner of the globe, including environments ranging from desert to tundra. Adaptation to these diverse environments, along with major dietary changes, rapid population growth and exposure to a range of novel infectious diseases, has left its mark on the human genome. Essentially, all of us carry a molecular record of our ancestors' adaptation - and with the recent growth of databases of human genetic variation, we can actually determine (albeit imperfectly) which genes played a role in this process.

Genetic variants that offer a benefit to the individuals who carry them - such that they have, on average, more surviving offspring than non-carriers - will tend to increase in frequency in a population through positive natural selection. This relatively rapid increase in frequency has a substantial impact on the region of the genome immediately around the selected variant, resulting in what's known as a "selective sweep": a local reduction in genetic diversity, and an elevation of long-range linkage disequilibrium.

(You can think of these signatures as being a consequence of a selected variant being younger (on average) than a neutral region at the same frequency, due to its rapid increase in frequency. The low genetic diversity and high linkage disequilibrium result from the fact that there hasn't been much time for mutation and recombination, respectively, to act on the section of the genome closely linked to the selected variant.)

If the selection is restricted to just one or a few populations (due to a specific environmental pressure, or simply a lack of the beneficial variant in other populations) there will also be an increase in population differentiation in the region; in other words, in this portion of the genome, human populations will tend to look more different to one another than they do in other areas.

These classic signatures of a selective sweep have been used to hunt for genes subject to recent positive selection in humans by many groups, taking advantage of genetic variation data from the HapMap project and various other sources. The results of these analyses have been used to argue that recent human evolution has been characterised by pervasive, often population-specific positive selection, presumably resulting from the adaptation of modern humans to diverse, novel environments outside of Africa.

What's been lacking in most of these studies is analysis of a broad range of human populations - most attempts, by necessity, have been restricted to the European, East Asian and West African populations samples by the HapMap project. That's changed now with the arrival earlier in the year of data on 650,000 genetic markers (SNPs) in 938 individuals from over 50 populations, using DNA samples from the Human Genome Diversity Panel.

These genome-wide data have now been analysed for various signatures of recent selection by a team at the University of Chicago - and while the publication isn't out yet, the team has generously made their data available through a nifty online browser. It's worth noting that the same group previously produced the Haplotter browser, which allows you to examine signatures of selection in the four HapMap populations (for an introduction to Haplotter and other online resources, see the So you want to be a population geneticist? post on GNXP).

Using the HGDP Selection Browser
If you want to see if your favourite gene shows a signature of population-specific positive selection, here's how the browser works:

Enter the name of a gene or a SNP into the window at the top left of the browser and it will take you to that region of the genome. You can then use the "Scroll/Zoom" function to move around or view a specific window size ranging from 100,000 to 5 million bases. Here I've taken a snapshot of a 1 Mb (1 million base) region around the EDAR gene - I find that a 1 Mb window size is a pretty good default for getting an idea of how the region looks:

EDAR is a classic example of recent population-specific selection in humans, emerging as a major East Asian-specific outlier in several large-scale studies of the human genome. (The reason for the selection is still unclear, but a common protein-altering variant in EDAR is associated with variation in hair morphology and affects cellular signalling).

The picture from the browser is thoroughly consistent with a selective sweep restricted largely to East Asia: many of the markers within or close to the EDAR gene show unusually high F_st (a measure of population differentiation), and the region as a whole displays elevated iHS and XP-EHH scores (both measures of extended linkage disequilibrium, with XP-EHH being particularly powerful for detecting population-specific selection) that are most dramatic in the East Asian population (green). (For all three measures the value plotted is the -log10 of the empirical P value for each SNP - so the higher the score, the more extreme an outlier that region is relative to the rest of the genome.)

By clicking on individual SNPs in the "Genotyped SNPs" row of the browser you can generate a map of the distribution of frequencies in the various surveyed populations - here's the map for one of the more interesting-looking variants in EDAR:

You can see immediately that the more evolutionarily recent or "derived" version of this SNP is restricted mainly to East Asia and the Americas (where the native populations are relatively recent migrants from East Asia). That makes sense for a region where selection appears to have been almost entirely restricted to East Asian populations.

To drill down a bit further, click on the buttons next to "Haplotype plots" (towards the bottom of the page, just above the display settings) - you can either look at populations individually, or grouped together into 7 continental clusters. After some calculations (based on an algorithm from this paper) you end up with some rather complicated plots that look like this:

These plots take a bit of getting used to, but here's the gist: each row in the plot represents an individual chromosome in the sample (for most genes that means two rows per individual), and sections of the row are coloured depending on whether they share the same combination of variants (also known as a haplotype). A variant that has been a target of recent positive selection should show a long, largely uninterrupted haplotype at high frequency in the population - and that is precisely what you see for the green haplotype in East Asians (the top panel). In the Middle East and South Asia (bottom two panels), where there has been no selection on the EDAR variant, there is a chaotic arrangement with no sign of a dominant, long-range haplotype - in other words, the sort of pattern you would expect under neutral evolution.

I've included massively expanded versions of the East Asian and Middle Eastern haplotype plots at the end of this post - you can obtain these expanded plots simply by clicking on the relevant graph.

Has your favourite gene been recently selected?
I asked a member of the team who put the browser together what he saw as the basic rules of thumb for deciding whether or not a region was a target of recent selection. He noted that the process is still more of an art than a science (which is understandable given the limitations and complexities of the data, and the fact that weakly selected variants will look essentially identical to unselected regions). However, he has this advice:

I'm most convinced if there's a strong (ie. empirical p in the top 1%, which is a 2 on the scales used in the browser) iHS or XP-EHH score and the haplotype plots look "good"--there's a long haplotype at high frequency in the populations with the significant score and not elsewhere. A big Fst also contributes to making the evidence stronger.

There are no absolute criteria distinguishing selected from neutral sites with perfect accuracy, so interpret with caution - but if you already have reason to suspect that a genetic variant might have been a recent target of selection (e.g. that most nebulous form of evidence, "biological plausibility"), this browser can give you a quick sense of whether this might be a possibility worth pursuing further.

A manuscript based on the data presented in this browser is currently in the works, with findings that I think will present a challenge to many in the human evolutionary genetics community - more on that later.

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Here's those expanded haplotype plots for EDAR, showing strong evidence for selection on the green haplotype in East Asians, while individuals from the Middle East show no trace of recent selection:

East Asia (green haplotype under selection)

Middle East (no strong recent selection)

Face images modified from thumbnails at Face Research.

dgmacarthur Mon, 11/10/2008 - 02:18