Alan R. Templeton explains concepts of genetic drift, genetic bottleneck, and founder effect.

Alan R. Templeton

Alan R. Templeton, Population Genetics and Micoevolution, 2nd ed. (Hoboken, NJ: John Wiley & Sons, 2021), 77–87

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Alan R. Templeton
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Genetic drift is the random change in allele frequency due to sampling error in a finite population. Genetic drift is an evolutionary force that can alter the genetic make-up of a population’s gene pool through time and shows that the Hardy–Weinberg “equilibrium” and its predicted stability of allele frequencies do not hold exactly for any finite population. The purpose of this chapter is to investigate the evolutionary properties and significance of genetic drift.

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Founder and Bottleneck Effects

As shown in the previous section, genetic drift causes its most dramatic and rapid changes in small populations. However, even a population that is large most of the time but has an occasional generation of very small size can experience pronounced evolutionary changes due to drift in the generation(s) of small size. If the population size grows rapidly after a generation of small size, the increased population size tends to decrease the force of subsequent drift, thereby freezing in the drift effects that occurred when the population was small. These features are illustrated via computer simulation in Figure 4.5. Figure 4.5a shows four replicate simulations of genetic drift in populations of size 1000, over 100 generations, with an initial allele frequency of 0.5. Figure 4.5b shows parallel simulations, but with just one difference: at generation 20, the population size was reduced to 4 individuals and then immediately restored to 1000 at generation 21. In contrasting Figure 4.5a with 4.5b, the striking difference is the radical change in allele frequency that occurs in each population during the transition from generation 20 to 21, reflecting drift during the generation of small size. However, there is relatively little subsequent change from the allele frequencies that existed at generation 21. Thus, the pronounced evolutionary changes induced by the single generation of small population size are “frozen in” by subsequent population growth and have a profound and continuing impact on the gene pool long after the population has grown large. These computer simulations show that genetic drift can cause major evolutionary change in a population that normally has a large population size as long as either:

the population was derived from a small number of founding individuals drawn from a large ancestral population (founder effect), or

the population went through one or more generations of small size followed by subsequent population growth (bottleneck effect).

We will now consider some examples of founder and bottleneck effects.

There are many biological contexts in which a founder event can arise. For example, there is much evidence that individuals of Hawaiian Drosophila (fruit flies) are on rare occasions blown to a new island on which the species was previously absent (Carson and Templeton 1984). Because this is such a rare event, it would usually involve only a single female. Most Drosophila females typically have had multiple matings and can store sperm for long periods of time. A single female being blown from one island to another would often therefore carry over the genetic material from two or three males. Hence, a founder size of four or less is realistic in such cases. (Single males could also be blown to a new island, but no population could be established in such circumstances.) If the inseminated female found herself on an island for which the ecological niche to which she was adapted was unoccupied, the population size could easily rebound by one or two orders of magnitude in a single generation, resulting in a situation not unlike that shown in Figure 4.5b.

Founder events are also common in humans. One example of both a founder effect and a bottleneck effect is given by Roberts (1967, 1968). Tristan da Cunha is an isolated island in the Atlantic Ocean. With the exile of Napoleon on the remote island of St. Helena, the British decided to establish a military garrison in 1816 on the neighboring though still distant island of Tristan da Cunha. In 1817, the British Admiralty decided that Tristan da Cunha was of no importance to Napoleon’s security, so the garrison was withdrawn. A Scots corporal, William Glass, asked and received permission to remain on the island with his wife, infant son, and newborn daughter. A few others decided to remain and were joined later by additional men and women, some by choice and some due to shipwrecks. Altogether, there were 20 initial founders. The population size grew to 270 by 1961, mostly due to reproduction but with a few additional immigrants. The growth of this population from 1816 to 1960 is shown in Figure 4.6.

Because there is complete pedigree information over the entire colony history, the gene pool can be reconstructed at any time as the percentage of genes in the total population derived from a particular founding individual (Figure 4.7). This method of portraying the gene pool can be related to our standard method of characterizing the gene pool through allele frequencies by regarding each founder as homozygous for a unique allele at a hypothetical locus. Then, the proportion of the genes derived from a particular founder represents the allele frequency at the hypothetical locus of that founder’s unique allele in the total gene pool.

The top histogram in Figure 4.7 shows the gene pool composition in 1855 and 1857. Note from the population size graph in Figure 4.6 that a large drop in population size occurred between those years. This was caused by the death in 1853 of William Glass, the original founder. Following his death, 25 of his descendants left for America in 1856. This bottleneck was also accentuated by the arrival of a missionary minister in 1851. This minister soon disliked the island, preaching that its only fit inhabitants were “the wild birds of the ocean.” Under his influence, 45 other islanders left with him, thereby reducing the population size from 103 at the end of 1855 to 33 in March 1857. Note that in going from 1855 to 1857, the gene pool composition changes substantially; the relative contributions of some individuals show sharp decreases (founders 1 and 2) whereas others show sharp increases (founders 3, 4, 9, 10, 11, and 17). Moreover, the genetic contributions of many individuals are completely lost during this bottleneck (founders 6, 7, 12, 13, 14, 15, 16, 19, and 20). Thus, the gene pool is quite different and less diverse after the first bottleneck.

Figure 4.6 reveals that the population grew steadily between 1857 and 1884. With the exception of a few new immigrant individuals (founders 21–26), the basic shape of the gene pool histograms changes very little in those 27 years (the second histogram from the top in Figure 4.7). In particular, note that there is much less change in these 27 years than in the 2 years between 1855 and 1857. Hence, the changes induced by the first bottleneck were “frozen in” by subsequent population growth.

Figure 4.6 shows that a second, less drastic bottleneck occurred between 1884 and 1891. The island has no natural harbor, so the islanders had to row out in small boats to trade with passing vessels. In 1884, a boat manned by 15 adult males sank beneath the waves with the resulting death of everyone on board, making Tristan da Cunha the “Island of Widows.” Only four adult men were left on the island, two very aged, leading many of the widows and their offspring to leave the island. This reduced the population size from 106 in 1884 to 59 in 1891. The third histogram in Figure 4.7 shows the impact of this second bottleneck on the island’s gene pool. As with the first bottleneck, some individual contributions went up substantially (founders 3, 4, and 22), others went down (founders 9 and 10), and many were lost altogether (founders 21, 24, 25, and 26).

After this second bottleneck, there was another phase of steady population growth (Figure 4.6). The shapes of the gene pool histograms change little from 1891 to 1961 during this phase of increased population growth (the bottom histogram in Figure 4.7, which excludes the impact of a few additional immigrants). Once again, this shows how subsequent population growth freezes in the changes induced by drift during the bottleneck.

As discussed in Chapter 3, the founder and bottleneck effects on Tristan da Cunha also led to pedigree inbreeding, despite a system of mating of avoidance of inbreeding (see Figure 3.5). This is yet another effect of genetic drift: finite population size leads to an increase in the mean inbreeding coefficient (the average probability of uniting gametes bearing alleles identical-by-descent) with time. Each bottleneck accentuates this accumulation of F because the number of founders contributing to the gene pool goes down after each bottleneck event, making it more likely that the surviving individuals must share a common ancestor. Thus, founder and bottleneck effects usually increase pedigree inbreeding.

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