Genetic Drift -- the role of finite population size

Transcription

1 Genetic Drift -- the role of finite population size Evolution can be thought of as a change in allele frequency, and finite population size alone insures that evolution will occur through sampling error. For example, suppose a population has a gene pool with two alleles, say H and T, each with a frequency of.5 Suppose N (a finite number) of gametes are drawn from this gene pool to form the next generation. Will the frequency of H and T be.5 in this finite population? If not, evolution will have occurred. You can simulate this situation. E.g., let N=, and place coins in a box, shake the box, and count number of heads (i.e., allele "H"). Do this several times to show that finite population size causes random changes in allele frequency. These random changes in allele frequency due to sampling error in finite populations is known as "genetic drift." Genetic drift is an evolutionary force that can alter populations through time, and shows that the Hardy-Weinberg "equilibrium" does hold exactly for any finite population. Now use coins for the simulation, and repeat several times. Results will show that there are still random deviations from.5, but the proportional deviation from.5 is smaller when N= then when N=. This shows that the amount of evolutionary change associated with random sampling error is inversely related to population size; the larger the population, the less the allele frequency will change. Hence, genetic drift is most effective as an evolutionary force when N is small. The coin box simulation above only simulates one generation of genetic drift starting with an allele frequency of.5. It does not simulate the fact that the evolutionary changes induced by drift tend to accumulate through time. In the coin box experiment, it was equally likely to deviate above and below.5. Hence, on the average (i.e., in a large number of identical populations), the average allele frequency remains.5, although in any individual population, it is quite likely that the allele frequency will change from.5. The fact that deviations are equally likely above and below.5 simply means that there is no direction to pure genetic drift. However, suppose drift causes the allele frequency to change from.5 to. in one particular population. How about the next generation? Is it equally likely to be above or below.5, as was the first generation? The answer is no, drift at one generation is always around the allele frequency of the previous generation only; and allele frequencies in more ancient generations are totally irrelevant. THERE IS NO TENDENCY TO RETURN TO ANCESTRAL ALLELE FREQUENCIES. Hence, drift in the second generation will cause deviations around.. This is turn means that after two generations of drift and given that the first had a deviation above.5, it is no longer true that deviations will be equally likely above and below.5; now, the allele frequencies are more likely to stay above.5. With each passing generation, it becomes more and more likely to deviate from the initial conditions. The action of drift over several generations can be simulated on a computer in which each generation drifts around the allele frequency of the previous generation only. Handouts show the impact of this simulated drift in populations of size and 5. In both cases, one starts out with the initial allele frequency of.5, but with

2 increasing generation number, more and more of the populations deviate from.5, and by larger amounts. HENCE, CHANGES CAUSED BY GENETIC DRIFT ACCUMULATE WITH TIME. As can be seen by contrasting N= with N=5, the smaller N, the more radical these changes will be in a given amount of time, but even with the larger N, substantial changes have occurred by generation. Hence, N determines the rate of change caused by drift, but even very large populations can be effected by drift if given enough time. Also note in these simulations (particularly for N=), that eventually all populations go to allele frequencies of (loss of the allele) or (fixation of the allele). Genetic drift, like any other evolutionary force, can only operate when there is genetic variability. Hence, as long as p is not equal to or, drift will cause changes in allele frequency. However, once an allele is lost or fixed, no more genetic drift is possible, and the allele stays lost or fixed, barring new mutations or reintroduction by gene flow. Hence, drift is like a genetic fly paper. The walls are loss and fixation, and sooner or latter (depending upon population size), the fly (allele frequency) will hit a wall and be "stuck". These properties of genetic drift have been demonstrated empirically by Buri (handout). He initiated 7 populations of males and females of Drosophila melanogaster, all with two eye color alleles (bw and bw75) at equal frequency. The handout shows what happened over 9 generations. Note the following:. When allele frequencies are averaged over all 7 populations, there is almost no change from the initial allele frequencies of.5. DRIFT HAS NO DIRECTION.. The chances of any subpopulation deviating from.5 and the magnitude of that deviation increase with each generation. DRIFT ACCUMULATES WITH TIME.. With increasing time, more and more populations become fixed for one allele. Ultimately, all populations are expected to become fixed. HENCE, DRIFT CAUSES THE LOSS OF GENETIC VARIABILITY WITHIN A POPULATION.. All populations started out with identical gene pools, but with time, the populations deviate not only from the ancestral condition, but from each other as well. E.g., at generation 9, populations are fixed for bw, for bw75. These populations no longer share any alleles at this locus, even though they are derived from genetically identical ancestral populations. HENCE, DRIFT CAUSES AN INCREASE OF GENETIC VARIABILITY BETWEEN POPULATIONS.

3 Generation Number of Populations Fixed for bw Number of Populations Fixed for bw Number of bw 75 genes Allele Frequency distributions in 7 populations of Drosophila melanogaster each, discrete generations

4 Founder and Bottleneck Effects As shown previously, genetic drift can cause its most radical and rapid changes in small populations. However, because there is no tendency to return to the initial state, even one generation of very small size can induce radical evolutionary changes that will tend to persist. Indeed, if the population size grows large after a generation of small size, the increased population size tends to decrease the impact of subsequent drift, so that the drift effects that occurred in the generation of small size tend to be "frozen in" the population for many future generations. Hence, genetic drift can cause radical changes in a population that is normally large as long as either ) the population was derived from a small number of founding individuals (founder effect), or the population went through one or more generations of very small size (bottleneck effect). Examples of founder effects.. 5-alpha-steroid reductase deficiency. All cases derived from Alta-Gracia. It is in high frequency in the village of Salinas, Santa Domingo, because Alta-Gracia was one of just a few founders 7 generations ago.. Amish colonies. Founded in Penn. in 7-77, usually by less than people. Only married within religion, and few converts after -- hence have socially defined founder event, but genetic and evolutionary consequences are very real. E.g., currently about, Amish in Lanchaster, Co., but derived from only about founders. A genetic disease known as Ellis-van Creveld syndrome (dwarfism, heart trouble, extra digits) is very rare in general population -- only 5 cases in the world during this century. However, in the Lancaster Amish, p=., and of the 5 cases were found in the Lancaster Amish. All the Amish cases trace back to Mr. and Mrs. Samuel King, who joined group in 7. Hence, a gene very rare in humanity in general, through the founder effect, became very common in this one reproductively isolated subpopulation. Amish show other genes in high frequency that are rare elsewhere. E.g., the genetic disease pyruvate kinase deficiency found only in the Amish -- all cases trace back to Strong Jacob Yoder, 7. The Amish in Ohio have a high incidence of hemophilia -- all cases trace back to sisters who converted in. Example of the Bottleneck Effect: Tristan da Cunha is an example of both founder and bottleneck effects. It was founded as a religous colony about with only initial founders by. The figure below shows the changes in population size on the island from to 9. Because we have complete pedigree information over the entire colony history, we can reconstruct the gene pool at any time as the percentage of genes in the total population derived from a particular individual (see histograms). The first histogram shows the gene pool composition in 55 & 57. Note from the size graph that a radical drop in population size occurred between This was

5 caused by a boat capsizing that drowned most of the adult males of the colony. After their death, many of their wives and children left as well. There was another Population Size Population Size of Tristan da Cunha on Dec. of each year from to DATE bottleneck around 9 when a popular minister died; many people didn't like his replacement and left. Note that in going from 55 to 57, the gene pool composition changes quite a bit; relative contributions of some individuals shift radically (eg. -), and many individuals just drop out entirely (loss due to drift). However, the population grew steadily between 57-. With the exception of a few new immigrant individuals (-), the basic shape of histogram changed very little in those 7 years (the second histogram); much less change than in the years between Hence, changes induced by the first bottleneck were "frozen in" by subsequent population growth. Once again, many changes occurred between -9 (the second bottleneck) (third histogram), but the shape of the histogram changes very little from 9-9 (fourth histogram, with the exception of additional immigrants) during the phase of increased population growth.

6 Tristan da Cunha Before & After the First Bottleneck % Contribution to Gene Pool Founder

7 Tristan da Cunha During Growth After First Bottleneck % Contribution to Gene Pool Founder

8 Tristan da Cunha Before & After nd Bottleneck % Contribution to Gene Pool Founder

9 Tristan da Cunha During Recovery From nd Bottleneck % Contribution to Gene Pool 9 9 (minus immigrants) Founder Founder effects and pedigree inbreeding Decade of Birth On Tristan da Cunha figures, note the increase in mean inbreeding coefficient (pedigree definition -- prob. of uniting gametes bearing alleles identical by descent)

10 with time. This occurred despite the fact that the people avoided incest as much as possible. The reason is straightforward. Because of the founder effect and the closed population, everybody quickly became related to everyone else. By 7 all females on the island were related to all potential male mates; hence, pedigree inbreeding became unavoidable. A second example is Speke's gazelle. The entire North American herd was derived from male and females. Obviously, from very first generation, all individuals breed in captivity were related (all had to have single male founder as a common ancestor). Hence, pedigree inbreeding unavoidable. Thus, founder and bottleneck effects promote rapid increases in pedigree inbreeding. Founder effects and disequilibrium Just as drift causes changes in allele frequencies, it also changes multi-locus gamete frequencies. Tends to destroy linkage equilibrium and creates many associations. If the loci are closely linked, the particular associations will persist for many generations, causing extensive disequilibrium. Eg., G--PD deficiency and color blindness in Sardinia. The disequilibrium induced by founder and bottleneck effects can interact strongly with system of mating. Eg., Drosophila melanogaster has a pheromone system leading to strong disassortative mating. Genetically controlled by a handfull of loci scattered over the genome. Dissassortative mating maintains heterozygosity at these loci. However, D. mel. has only a few chromosomes ( X, major autosome, and a very small autosome), and little recombination among these chromsoomes. Hence, with a severe bottleneck effect, virtually the entire genome will be in linkage disequilibrium with the pheromone loci. Hence, disassortative mating at the pheromone loci will also effectively cause dissassortative mating at all loci for a few generations after the bottleneck effect. Hence, if the small population size does not persist long enough for the disequilibrium to break down, disassortative mating and disquilibrium insure that very little genetic variation will be lost due to drift during a temporary bottleneck or founder event. Other Drosophila (e.g., D. pseudoobscura) do not have this pheromone mating system. Hence, different species show different genetic and evolutionary responses to founder and bottleneck effects as a function of the recombinational properties of their genomes and their system of mating.