Genetic Drift

Concept and origins

Genetic drift is a form of sampling error. Even in a population where two alleles are equally common, the gametes that form the next generation are a random sample of the whole, so frequencies do not stay exactly at one half. As such chance changes accumulate, one allele eventually reaches 100 percent (fixation) or 0 percent (loss). Fisher (1930) and Wright (1931) analyzed this process mathematically in what became the Wright–Fisher model. The strength of drift is inversely proportional to population size, so small populations lose genetic diversity quickly. What matters is not the census count but the effective population size, which reflects the number of breeders, the sex ratio and fluctuations in size across generations. Wright (1932) also proposed the shifting balance theory, in which drift and selection act together among small subpopulations.

Experiments and special forms

Buri (1956) maintained 107 populations of fruit flies at 16 individuals each for 19 generations. All started with an allele frequency of 0.5, but frequencies spread out across populations over time, and by the end many had reached fixation or loss. Special forms of drift include the bottleneck effect, when a population temporarily shrinks sharply, and the founder effect, when a few individuals colonize a new area and carry a genetic makeup different from the source population. Mayr (1954) argued that founder effects could contribute to speciation, and Nei, Maruyama and Chakraborty (1975) quantified how the loss of genetic diversity after a bottleneck depends on its severity and the speed of recovery.

Molecular evolution and modern significance

Kimura (1955) approximated drift with diffusion equations to calculate fixation probabilities and times. Building on this, Kimura (1968) proposed the neutral theory of molecular evolution, holding that most molecular variants are fixed by drift rather than selection, and Ohta (1973) extended it in the nearly neutral theory, showing that slightly deleterious mutations can be fixed by drift in small populations. Kingman's (1982) coalescent models drift by tracing the genealogy of sampled genes backward in time and became the foundation of modern population genomic analysis. Lynch (2007) argued that organisms with small effective population sizes experience strong drift that allows nonadaptive complexity to accumulate in their genomes, and Charlesworth (2009) reviewed how effective population size shapes patterns of molecular variation. Genetic drift is understood as a basic force driving evolution alongside natural selection (Masel, 2011).

FAQ

What is genetic drift in simple terms?

In small populations, which individuals happen to leave offspring is partly luck, so gene frequencies change at random regardless of whether genes are helpful or harmful.

How do bottleneck and founder effects differ?

A bottleneck is a sudden sharp reduction in an existing population, while a founder effect occurs when a few individuals start a new population elsewhere. Both are special forms of drift that reduce genetic diversity.

Sources reviewed: 2026-10-26

References

1. Wright, S. (1931). Evolution in Mendelian populations. Genetics, 16(2), 97–159.
2. Fisher, R. A. (1930). The Genetical Theory of Natural Selection. Oxford: Clarendon Press.
3. Wright, S. (1932). The roles of mutation, inbreeding, crossbreeding and selection in evolution. Proceedings of the Sixth International Congress of Genetics, 1, 356–366.
4. Buri, P. (1956). Gene frequency in small populations of mutant Drosophila. Evolution, 10(4), 367–402.
5. Kimura, M. (1955). Solution of a process of random genetic drift with a continuous model. Proceedings of the National Academy of Sciences, 41(3), 144–150.
6. Mayr, E. (1954). Change of genetic environment and evolution. In J. Huxley, A. C. Hardy & E. B. Ford (Eds.), Evolution as a Process (pp. 157–180). London: Allen & Unwin.
7. Kimura, M. (1968). Evolutionary rate at the molecular level. Nature, 217(5129), 624–626.
8. Ohta, T. (1973). Slightly deleterious mutant substitutions in evolution. Nature, 246(5428), 96–98.
9. Kingman, J. F. C. (1982). The coalescent. Stochastic Processes and their Applications, 13(3), 235–248.
10. Nei, M., Maruyama, T., & Chakraborty, R. (1975). The bottleneck effect and genetic variability in populations. Evolution, 29(1), 1–10.
11. Lynch, M. (2007). The Origins of Genome Architecture. Sunderland, MA: Sinauer.
12. Charlesworth, B. (2009). Effective population size and patterns of molecular evolution and variation. Nature Reviews Genetics, 10(3), 195–205.
13. Masel, J. (2011). Genetic drift. Current Biology, 21(20), R837–R838.