The “Big Four,” part IV: Migration

This post is the last in a special series about four fundamental forces in evolution: natural selection, mutation, genetic drift, and migration.

Edited 8 April 2011: Following some interesting comments from population geneticist Lou Jost, I’ve edited my characterization of the rule of thumb that one migrant per generation is generally enough to prevent populations from differentiating.

It’s the little differences. I mean, they got the same shit over there that we got here, but it’s just—it’s just there it’s a little different.
— Vincent, Pulp Fiction

ResearchBlogging.orgDifferent places are different from each other. This is a truism bordering on tautology, but it also has real implications for the ways in which life evolves and diversifies. The specific differences between one environment and another shape how well living things can move between those environments, and what happens when they do—the evolutionary consequences of migration.

Canada geese on the wing. Photo by Brian Guest (giant rebus).

Individuals moving between populations can alter the evolution of those populations in a number of ways [$a]. Migration introduces traits from one population into another, making it a source of variation not unlike mutation. Migration can swamp out the effects of local natural selection, if enough migrants come from a population experiencing a different selective regime. Migration from a larger population to a smaller one can offset the loss of variation to genetic drift; but a small group of individuals migrating to an empty habitat can be strongly affected by drift. Depending on what species concept you prefer, migration between two populations is either what prevents them from becoming separate species, or what conclusively proves that they are the same species.

Migration mixes things up

Strictly speaking, I’m not talking simply about the movement of living things from place to place, but about gene flow, which also requires interbreeding between migrants and the populations to which they migrate. Individuals might be able to travel to another environment, and even do so frequently, but fail to survive when they get there [PDF], or fail to find a mate in the local population, or have offspring that are themselves less fit than the offspring of the locals. Because tracking each of these steps directly is daunting at best, most population biology studies estimate the rate of successful migration by proxy, using some measure of the genetic similarity of populations—the more migrants successfully move between populations, the more similar the traits and gene frequencies of those populations will be.

The rate of gene flow between two populations is essentially a measure of how much those populations evolve as a single unit—if there’s no gene flow, selection or drift can eventually make the two populations into completely different things. An effective migration rate of one migrant per generation is has been generally understood to be enough to prevent drift from causing populations to diverge [$a]. (But there are significant objections to the one-migrant-per-generation rule of thumb, including the question of how we determine that populations have differentiated! See the discussion of this in the comments.) Populations linked by migration along several intervening populations may be isolated by distance [PDF] if the line of connecting populations is long enough.

If natural selection is operating in different directions in the two populations, more migration is necessary to prevent them evolving different traits. If individual genes experience different selection in each population, then those genes may still evolve differently even as migration continues to mix in neutral genes [PDF]. This movement of genes across recognized population and species boundaries is called introgression.

Gene flow versus selection

The bird-pollinated Iris fulva (left) can sometimes hybridize with bee-pollinated I. brevicaulis, but pollinators favor hybrids that look more like the parent species. Photos by Matt N Charlotte and Jim Petranka.

One well-documented case of gene flow between apparently “good” species is that of the Louisiana irises Iris fulva and I. brevicaulis. These two species fill fairly distinct ecological niches: red-orange I. fulva is mainly pollinated by hummingbirds, and grows in very wet conditions; blue I. brevicaulis is pollinated by bees, and grows best in drier habitats.

Yet when the two species co-occur, they sometimes do cross-pollinate. What prevents the two species from merging into a single iris? (Perhaps it would have purple flowers.) Natural selection, in this case, overwhelms migration. Experimentally created fulvabrevicaulis hybrids grown in wet conditions are more likely to survive if they carry specific genes from wet-tolerant fulva; and pollinators tend to favor hybrids that look more like their preferred parent species. I. fulva and I. brevicaulis share some genes that don’t affect wet tolerance or pollinator attraction, but generally remain separate evolutionary entities.

This kind of partial reproductive isolation is most widely documented in plants, but it has been found in all sorts of organisms—even the chipmunks Tamias ruficaudus and T. amoenus [PDF]. In an evolving world, this shouldn’t be surprising—it makes sense to find many cases of partial reproductive isolation as populations evolve toward the point of being separate species. Sometimes, of course, divergent selection weakens, or previous barriers to migration are removed, and populations re-merge into single evolutionary entities. But sometimes, the balance of the selection, mutation, drift, and migration is just right for just long enough to create a new, independently evolving form of life. And thus, as Darwin wrote, “endless forms most beautiful have been, and are being, evolved.”

References

Arnold, M., Hamrick, J., & Bennett, B. (1990). Allozyme variation in Louisiana irises: a test for introgression and hybrid speciation. Heredity, 65 (3), 297-306 DOI: 10.1038/hdy.1990.99

Good J.M., Hird S., Reid N., Demboski J.R., Steppan S.J., Martin-Nims T.R., & Sullivan J. (2008). Ancient hybridization and mitochondrial capture between two species of chipmunks. Molecular ecology, 17 (5), 1313-27 PMID: 18302691

Hedrick, P.W. (2005). Genetics of Populations. Boston: Jones and Bartlett Publishers. Google Books.

Martin, N.H., Bouck, A.C., & Arnold, M.L. (2005). Detecting adaptive trait introgression between Iris fulva and I. brevicaulis in highly selective field conditions. Genetics, 172 (4), 2481-9 DOI: 10.1534/genetics.105.053538

Martin, N., Sapir, Y., & Arnold, M. (2008). The genetic architecture of reproductive isolation in Louisiana irises: Pollination syndromes and pollinator preferences. Evolution, 62 (4), 740-52 DOI: 10.1111/j.1558-5646.2008.00342.x

Nosil, P., Egan, S., & Funk, D. (2008). Heterogeneous genomic differentiation between walking-stick ecotypes: “Isolation by adaptation” and multiple roles for divergent selection. Evolution, 62 (2), 316-36 DOI: 10.1111/j.1558-5646.2007.00299.x

Nosil, P., Vines, T., & Funk, D. (2005). Reproductive isolation caused by natural selection against immigrants from divergent habitats. Evolution, 59 (4), 705-19 DOI: 10.1554/04-428

Slatkin, M. (1987). Gene flow and the geographic structure of natural populations. Science, 236 (4803), 787-92 DOI: 10.1126/science.3576198

Wang, J. (2004). Application of the one-migrant-per-generation rule to conservation and management. Conservation Biology, 18 (2), 332-43 DOI: 10.1111/j.1523-1739.2004.00440.x

Wright, S.J. (1943). Isolation by distance. Genetics, 28, 139-56 PMCID: PMC1209196

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The “Big Four,” part III: Genetic drift

This post is the third in a special series about four fundamental forces in evolution: natural selection, mutation, genetic drift, and migration.

ResearchBlogging.orgHave a coin handy? Flip it.

If your coin is fair, I can guess that it’s come up heads and have a fifty percent chance, or probability equal to 0.5, that I’ve guessed correctly. Now, flip the coin ten times in a row. How many times did heads come up? Again, the best guess is that it came up five times—but it’s not all that unlikely that it came up six times, or four, or even as many as eight.

God may not play dice, but evolution does. Photo by jcotherals.

Now, if you flipped the coin an infinite number of times, then exactly fifty percent of the total flips would be heads. But who has time for that? Similarly, populations of living organisms are not infinite—often far from it—and this means that the frequency of genes in those finite populations can change as a result of the same phenomenon at work on your coin. Biologists call this genetic drift.

Evolution at random

The basic principle behind genetic drift is that each generation is a process of sampling from the parental population to create a population of offspring. As most folks know from discussions of opinion polls, smaller samples tend to be less representative of the pool from which they are drawn. Say a population of annual plants begins with equal numbers of plants bearing blue flowers or white flowers. If only ten seeds survive from that population to form the next generation, you would expect them to be five blue-flowered and five white-flowered seeds. However, it’s just like flipping a coin ten times: the probability of drawing six blue seeds is actually a little less than 21%, or one in five. The probability of drawing nine blue seeds is almost one in one hundred—small, but hardly impossible.

Consider, too, that once you draw six blue seeds, it becomes slightly more likely that you’ll draw seven in the next generation, which makes it slightly more likely you’ll draw eight in the next. Repeated selection of small samples means that traits can drift to fixation (or loss, depending on your perspective), so that everyone in the population has the same trait. Rare traits are more likely to be lost to drift, and large populations are less prone to its effects. This is nicely illustrated in this online simulation from the University of Connecticut—over time, a focal gene fixes or disappears from the population as a function of the population size and the initial frequency of the gene.

In general, drift interferes with the efficient operation of natural selection. Even in relatively large populations, the probability that a new beneficial mutation will become fixed is approximately twice the selective benefit of that mutation—typically very small. (This is from a 1927 paper by J.B.S. Haldane that doesn’t seem to be online in any form, but which is discussed by Otto and Whitlock in a 1997 paper extending the classic result.) In a small enough population, a trait can become fixed even if it reduces its carriers’ fitness [PDF].

Evolving differences without selection

As I’ve discussed above, the effect of drift in a single population is to reduce variation as rare traits are lost to chance. This means that, when more than one independently-evolving population is considered, drift actually increases variation among them [$a], as different traits fix or are lost in each. That is, drift can make isolated populations evolve into different species even if they experience identical regimes of natural selection.

Woodland salamanders (genus Plethodon: left, P. vehiculum; right, P. yonahlossee) have diversified not by adapting to different environments, but by being homebodies. Photos by squamatologist.

A flagship example of this sort of non-adaptive diversification are the woodland salamanders of eastern North America, genus Plethodon. Woodland salamanders are quite diverse, having accumulated more than 40 species in the last 27 million years, but all of these species live in more or less the same habitat, under the leaf litter in moist Appalachian forests, and many are “cryptic” species distinguishable only by DNA analysis. How, then, did Plethodon become so diverse?

The answer is simply that woodland salamanders don’t travel very well. Salamanders need moist environments–they breathe through their skin, which doesn’t work well if it dries out—and so have difficulty moving from one stream drainage to another. This means that it doesn’t take much distance to isolate one Plethodon population from another, allowing drift to take them in different directions. Salamanders form new species, in other words, by staying at home.

This effect of drift means that biologists must adjust their “null” expectation when they observe differences in natural populations—the mere fact that some Joshua trees look different from other Joshua trees does not necessarily mean that natural selection has created those differences. Furthermore, the degree to which drift or selection can generate differences among populations depends strongly on the fourth force in the Big Four, which I’ll discuss next week: migration.

References

Godsoe, W., Yoder, J., Smith, C., & Pellmyr, O. (2008). Coevolution and divergence in the Joshua tree/yucca moth mutualism. The American Naturalist, 171 (6), 816-23 DOI: 10.1086/587757

Kozak, K., Weisrock, D., & Larson, A. (2006). Rapid lineage accumulation in a non-adaptive radiation: phylogenetic analysis of diversification rates in eastern North American woodland salamanders (Plethodontidae: Plethodon) Proc. Royal Soc. B, 273 (1586), 539-46 DOI: 10.1098/rspb.2005.3326

Lande, R. (1992). Neutral theory of quantitative genetic variance in an island model with local extinction and colonization. Evolution, 46 (2), 381-9 DOI: 10.2307/2409859

Otto S.P., & Whitlock M.C. (1997). The probability of fixation in populations of changing size. Genetics, 146 (2), 723-33 PMID: 9178020

Wright S (1931). Evolution in Mendelian populations. Genetics, 16 (2), 97-159 PMID: 17246615

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The “Big Four,” part II: Mutation

This post is the second in a special series about four fundamental forces in evolution: natural selection, mutation, genetic drift, and migration.

This post was chosen as an Editor's Selection for ResearchBlogging.orgIn order for populations to change over time, to descend with modification, as Darwin originally put it, something has to create the modifications. That something is mutation.

A mutation of large effect? Photo by Cayusa.

A mutation is any change to an individual’s genetic code, whether caused by an external factor like radiation, or an error in the DNA copying that takes place every time an individual cell divides. However, not all mutations are created equal.

First and foremost, for a mutation to have any future existence beyond the individual in which it occurs, it must be in a cell that will go towards forming the next generation, a germline cell. In sexually reproducing species, this means sperm or egg cells, or the progenitor cells in the testes or ovaries that form them. Second, for a mutation to be “visible” to natural selection, it must have some effect on fitness, the number of offspring an individual carrying the mutation is likely to have. The genetic code determines how and when individual cells make proteins, and proteins determine phenotypes, the visible characteristics of living things. However, many changes to the genetic code don’t affect their carriers’ fitness. Mutations might be more or less neutral because

  • They occur in regions of the genome that don’t code for proteins or control protein production—so-called “junk” DNA.
  • They are synonymous substitutions, which occur in a protein-coding region of DNA, but don’t alter the protein produced.
  • They alter a protein, but not in a way that changes its function [PDF].
  • They alter a protein’s function and an individual’s phenotype, but in a way that doesn’t affect how many offspring that individual has.

Neutral mutations are actually quite important for biological studies—DNA fingerprinting and population genetics studies rely on them. Their frequencies evolve at random, reflecting the history of the populations that carry them rather than the effects of natural selection.

Favorable new mutations sweep the population


TOP: DNA sequences from a population are variable (blue) before a new mutation (red dot) arises; after it “sweeps,” every individual carries the allele as well as identical sequence nearby (red). BOTTOM: a figure from Linnen et al. (2009), demonstrates this pattern in deer mice. Images from Pritchard et al. (2010), fig. 3 and Linnen et al. (2009), fig. 4.

The variation introduced by neutral mutations—or, rather its absence—can help identify regions of the genome where selection is active. When a new gene arises by mutation, and it is strongly favored by selection, it can quickly spread through a population. In species that remix their genomes through sexual selection, the region of the genome containing a useful new gene can recombine into many different genetic backgrounds—but the closer a region of DNA is to the favored mutation, the less likely it is to recombine and separate from it. Thus, a region of the genome rather larger than the gene favored by selection is carried along until everyone in the population has the same DNA sequence.

When a new mutation takes over a population in this manner, it’s called a selective sweep, and the pattern it produces has been used to identify genes recently favored by selection in many different species, including humans. For instance, Linnen et al. documented reduced genetic variation in the neighborhood of gene variant responsible for light-colored fur in deer mice to demonstrate that it spread rapidly through the population after the mice colonized a region with light-colored sand.

Fuel for the engine of natural selection

Selective sweeps highlight how natural selection acts in opposition to mutation: mutation introduces new variation into populations, and natural selection causes the most fit variants to spread—potentially until the whole population carries the same trait. At the same time, selection requires variation in order to operate. If everyone is identical, then everyone has the same expected number of offspring, and the next generation will look just like the current one.

Because of this, natural selection can only operate as rapidly as mutation can introduce new variation from which to select. We know of specific cases in which selection seems to have “stalled” for lack of heritable variation. For instance, the fly Drosophila birchii lives in rainforest habitats along the northeast coast of Australia. Fly populations from the driest locations in this range have greater tolerance for dry conditions, but they also have virtually no heritable variation for drought tolerance [PDF]—and the authors suggest that this could limit the flies’ ability to evolve in response to climate change.

In other cases, though, biologists have found that mutation seems to provide new variation at least as fast as selection can remove it, leading to sustained, long-term evolution of experimental populations [PDF]. One important factor that may determine the outcome of this mutation-selection balancing act is actually the size of the population—more individuals means more opportunities for mutations to occur.

So the rate at which new mutations accumulate in a population depends on many factors, not the least of which are how you choose to measure that rate, and the fitness effects of the counted mutations. (Does a mutation “count” as soon as it occurs in a cell’s nucleus, or only when it has passed on to the next generation, or only when it has spread to everyone in a population?) Ultimately, populations evolve through a constant tension between the effects of mutation, natural selection, and the subject of next week’s Big Four force: genetic drift.

References

Barton, N., & Keightley, P. (2002). Understanding quantitative genetic variation. Nature Reviews Genetics, 3 (1), 11-21 DOI: 10.1038/nrg700

Drake J.W., Charlesworth B., Charlesworth D., & Crow J.F. (1998). Rates of spontaneous mutation. Genetics, 148 (4), 1667-86 PMID: 9560386

García-Dorado, A., Ávila, V., Sánchez-Molano, E., Manrique, A., & López-Fanjul, C. (2007). The build up of mutation-selection-drift balance in laboratory Drosophila populations. Evolution, 61 (3), 653-65 DOI: 10.1111/j.1558-5646.2007.00052.x

Hoffmann, A., Hallas R.J., Dean J.A., & Schiffer M. (2003). Low potential for climatic stress adaptation in a rainforest Drosophila species. Science, 301 (5629), 100-2 DOI: 10.1126/science.1084296

Keightly, PD. (2003). Mutational variation and long-term selection response. Pages 227-48 in Plant Breeding Reviews, Volume 24, part I. J. Janick, ed. John Wiley & Sons. Google Books.

Linnen, C., Kingsley, E., Jensen, J., & Hoekstra, H. (2009). On the origin and spread of an adaptive allele in deer mice. Science, 325 (5944), 1095-8 DOI: 10.1126/science.1175826

Pritchard, J., Pickrell, J., & Coop, G. (2010). The genetics of human adaptation: Hard sweeps, soft sweeps, and polygenic adaptation. Current Biology, 20 (4) DOI: 10.1016/j.cub.2009.11.055

Tokuriki, N., & Tawfik, D. (2009). Protein dynamism and evolvability. Science, 324 (5924), 203-7 DOI: 10.1126/science.1169375

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The “Big Four,” part I: Natural selection

This post is the first in a special series about four fundamental forces in evolution: natural selection, mutation, genetic drift, and migration.

This post was chosen as an Editor's Selection for ResearchBlogging.orgAmong non-biologists, the best-known of the Big Four forces of evolution is almost certainly natural selection. We’ve all heard the catchphrase “survival of the fittest,” and that’s a pretty good, if reductive, summing up of the principle. In more precise terms, here’s how natural selection works:

  • Natural populations of living things vary. Deer vary in how fast they can run, plants vary in how much drought they can tolerate, birds vary in their ability to catch prey or collect seeds—no two critters of the same species are exactly alike.
  • Some of those variable traits determine how many offspring living things have. How well you avoid predators, fight off disease, and collect food all determine how many babies you can make.
  • Many of those variable traits are heritable, passed on from parents to offspring. Faster deer usually have faster fauns; drought-tolerant plants make drought-tolerant seeds.

With these three conditions in place, natural selection occurs: heritable traits that help make more babies become more common. That is, if you have a trait that lets you support more offspring than your neighbor, you’ll have more children than your neighbor, and they’ll have more children than your neighbor’s children, and so on.

Fitness-versus-phenotype regressions for directional, stabilizing, and disruptive selection. Graphic by jby.

Measuring selection

Put this way, natural selection is simply a relationship between fitness, the number of offspring an organism can produce (often reported in comparison to the rest of the local population), and phenotype, the value of one or more traits of that organism (wing length, running speed, number of flowers produced, &c). Biologists can measure selection in natural populations by estimating this relationship between fitness (or a proxy for fitness, like growth rate), and phenotypes. Such an analysis should produce something like the regression graphs to the right, in which the relationship might be directional, with greater- (or smaller-) than-average phenotypes having greater fitness; stabilizing, with the average phenotype value having greater fitness; or disruptive, with extreme phenotype values having greater fitness. The slope of the line, or the shape of the curve, is a measure of the strength of natural selection [PDF] on an organism’s phenotype. This approach to measuring selection has been widely applied, and in 2001 a group of biologists led by Joel Kingsolver collected more than 2,500 estimates of the strength of natural selection [PDF].

How strong is selection?

Kingsolver et al. found that selection was usually surprisingly weak. Studies with the largest sample sizes, and the most statistical power to detect selection, mostly found directional selection strength (that is, the slope of the fitness-phenotype regression) less than 0.1, and the strength of stabilizing or disruptive selection was similarly low. Does this mean selection doesn’t matter in the short-term evolution of natural populations?

Probably not. The average selection strength estimates from the Kingsolver et al. dataset are actually stronger than selection strength assumed in most mathematical models of evolution. Furthermore, the collected estimates of selection had “long tailed” distributions—a small number of studies found quite strong selection, up to ten times as strong as the average. So maybe rare but strong bouts of selection have disproportionate impact over the long term.

Peter and Rosemary Grant have documented decades of shifting natural selection on Darwin’s finches (Geospiza spp.). Photo by Igooch.

Taking the finch by the beak

Part of the problem with assessing selection in nature is that most datasets measure selection over just one or a few years. One exception is the case of Darwin’s finches in the Galapagos Islands. The Galapagos offers a wide variety of habitat types, and experiences substantial year-to-year environmental variation—a landscape that should exert all sorts of natural selection on its occupants. Peter and Rosemary Grant have studied Galapagos finches for decades now, and found that selection is continuously at work on these unassuming birds. (The Grants’ book How and Why Species Multiply sums up their research program for a lay audience.)

Much of the Grants’ work has focused on the finches’ beaks, which largely determine what food the birds can eat. The distribution of seed sizes available on different Galapagos islands strongly predicts [PDF] the size of finches’ beaks on those islands. In 1989, the Grants published estimates of selection on beak size in the finch species Geospiza conirostris following a drastic wet-to-dry climactic shift that radically changed what foods were available to the finches. They found strong selection [$a], with fitness-phenotype regression slopes as high as 0.37. What’s more, the direction of selection changed dramatically from a very wet year to the dry year immediately afterward, as the finches were forced to move from feeding on small seeds and arthropods—which gave the advantage to shorter beaks—to hard-to-crack seeds, which required deep beaks.

The Grants’ longer-term study of selection on Galapagos finches confirms this image of selection swinging back and forth unpredictably [PDF]. From 1972 to 2001, they tracked populations of the finch species G. scandens and G. fortis, and saw both more gradual long-term changes in the finches’ body size and beak measurements as well as sudden sharp shifts. These changes continually altered the ability of the two species to hybridize, so that some years they were more reproductively isolated than others—and conditions in any one year were poor indicators of what would be going on five, ten, or twenty years later.

So when does selection matter?

The Grants’ study makes natural selection look as shifting and impermanent as the wind. How can it shape patterns of evolution over millions of years, then? One possibility is that trends may emerge over longer periods of time, as wobbly selection moves species in new directions in a drunkard’s walk, with two steps forward, then one step back, then four steps forward. Another is that lasting trends only occur when speciation intervenes to lock in fleeting changes due to variable natural selection [$a]. Much also depends on how selection interacts with mutation, genetic drift, and migration, as I’ll discuss in the rest of this series.

And here’s a shameless plug for a t-shirt. Photo by jby.

References

Futuyma, D. (1987). On the role of species in anagenesis. The American Naturalist, 130 (3), 465-73 DOI: 10.1086/284724

Grant, B.R., & Grant, P.R. (1989). Natural selection in a population of Darwin’s finches. The American Naturalist, 133 (3), 377-93 DOI: 10.1086/284924

Grant, P.R., & Grant, B.R. (2002). Unpredictable evolution in a 30-Year study of Darwin’s finches. Science, 296 (5568), 707-11 DOI: 10.1126/science.1070315

Grant, P.R. and B.R. Grant. (2008) How and Why Species Mutliply: The Radiation of Darwin’s Finches. Princeton University Press. Google Books.

Kingsolver, J., Hoekstra, H., Hoekstra, J., Berrigan, D., Vignieri, S., Hill, C., Hoang, A., Gibert, P., & Beerli, P. (2001). The Strength of phenotypic selection in natural populations. The American Naturalist, 157 (3), 245-261 DOI: 10.1086/319193

Lande, R. (1976). Natural selection and random genetic drift in phenotypic evolution. Evolution, 30 (2), 314-34 DOI: 10.2307/2407703

Johnson, T., & Barton, N. (2005). Theoretical models of selection and mutation on quantitative traits. Phil. Trans. R. Soc. B, 360 (1459), 1411-25 DOI: 10.1098/rstb.2005.1667

Schluter, D., & Grant, P. (1984). Determinants of morphological patterns in communities of Darwin’s finches. The American Naturalist, 123 (2), 175-96 DOI: 10.1086/284196

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Back to basics: The “Big Four”

ResearchBlogging.orgThe nice thing about a field season away from all regular internet access is that it gives you a real sabbatical of a sort—a chance to reassess plans and set new goals. One of the new goals I set myself this last field season was to introduce a new kind of topic here at Denim and Tweed.

Most of my writing about science at D&T focuses on recently published discoveries in evolution and ecology. It’s fun writing, and it coincides neatly with my regular journal reading, and I intend to keep doing it. But I’ve discovered that when I want to put new work in context, I often need to discuss fundamental concepts of evolutionary biology that aren’t necessarily common knowledge, such as genetic drift or sexual selection. However, I rarely have room to explain these concepts in depth within a blog post devoted to something else.

So maybe the solution is to devote some posts to explaining these “basics.” I’m going to start with a series of posts on the “Big Four” processes of population genetics. These are the four processes that account, in one way or another, for every change in the frequency of genes within natural populations. In other words, the Big Four account for much of evolution itself. They are:

  • Natural selection, changes in gene frequencies due to fitness advantages, or disadvantages, associated with different genes.
  • Mutation, the source of new forms of genes;
  • Genetic drift, or changes in gene frequencies that arise from the way probability works in finite populations; and
  • Migration, or changes in gene frequencies due to the movement of organisms from site to site.

Lay readers may be surprised both by what we know, and what we don’t, about how these four processes operate in nature. Natural selection is relatively easy to measure, and apparently ubiquitous [PDF] in natural populations—but we don’t know how often the resulting short-term changes impact evolution over millions of years. Mutation, the source of variation on which natural selection acts, seems to vary widely among living things. Genetic drift means that a trait can come to dominate a population even if it has no fitness effect—or sometimes a deleterious one. Finally, migration across variable landscapes can interact with selection, drift, and mutation [$a] to completely alter their effects.

I’ll devote one post each to selection, mutation, drift, and migration, discussing classic findings as well as more recent scientific discoveries about each. They’ll arrive as my usual mid-week science posts for the next four weeks, and I’ll update this post with links to the others as they go online—so if this looks worth following, you can either bookmark this post, or subscribe to D&T’s RSS Feed.

Natural selection, mutation, genetic drift, and migration act together to shape the evolution of natural populations. Photo by jby.

References

Drake JW, Charlesworth B, Charlesworth D, & Crow JF (1998). Rates of spontaneous mutation. Genetics, 148 (4), 1667-86 PMID: 9560386

Kingsolver, J., Hoekstra, H., Hoekstra, J., Berrigan, D., Vignieri, S., Hill, C., Hoang, A., Gibert, P., & Beerli, P. (2001). The strength of phenotypic selection in natural populations. The American Naturalist, 157 (3), 245-61 DOI: 10.1086/319193

Slatkin, M. (1987). Gene flow and the geographic structure of natural populations. Science, 236 (4803), 787-92 DOI: 10.1126/science.3576198

Wright S (1931). Evolution in Mendelian populations. Genetics, 16 (2), 97-159 PMID: 17246615

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