Genetic drift
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Genetic drift is change in the allele frequencies of a population that comes about by chance. The genes a generation passes on are a sample of those its parents carry. Some plants leave more offspring than others for reasons unrelated to their genes. Each offspring also receives one of the two copies of a gene that each parent holds, drawn at random.[1] Each generation therefore carries only a subset of the variation of the one before. Drift acts without regard to whether an allele helps or harms the plants that carry it. Its effects are strongest in small populations.[2]
Drift has no direction. Averaged over many populations it leaves the frequency of an allele unchanged. Within any one population it carries alleles to fixation or loss.[3] A population that stays small loses heterozygosity and becomes more inbred.[4] The founding of a population by a few individuals and a sharp fall in numbers, a population bottleneck, have the same effects quickly: variation is lost and relatives mate more often.[5][6] The size that sets the rate of drift is the population's effective population size, which is often smaller than the number of individuals counted.[7]
In Cannabis the low diversity of a small, isolated feral population has been put down to its size and isolation. Bottlenecks in breeding may explain the inbreeding of hemp varieties. Seed collections that must be regrown every few years to keep them alive may lose variation by drift at each regrowing.[8][9][10]
Sampling between generations
The simplest model of drift is named after Sewall Wright and R.A. Fisher. A population of N diploid individuals carries 2N copies of each gene. Every copy in the next generation is drawn at random from them, like the outcome of a toss of a coin weighted by the allele's present frequency. The number of copies of an allele among the offspring can come out at any value from none to all. The model has no mutation, so once an allele is lost or fixed the population stays that way. Sooner or later every population in the model fixes one allele.[11]
Because chance favours no allele, the probability that an allele is the one eventually fixed equals its present frequency. Populations of the same size that start from the same frequency keep the same average frequency between them while they drift apart. The variance of their frequencies grows until each is fixed for one allele or the other.[3] Drift in a finite population is the same process as inbreeding. As alleles are lost, more of the copies that remain descend from a single ancestral copy and so are identical by descent.[1]
The Hagedoorns in 1921 and Sergei Chetverikov in 1926 drew attention to the evolutionary importance of drift, without treating it mathematically. Wright worked out its mathematics in 1929 and 1931.[1]
Loss of heterozygosity
In the ideal model a population of N individuals loses 1/(2N) of the heterozygosity it still holds in each generation. Half of it is gone after about 1.39N generations: some 14 generations for a population of 10, 139 for 100 and 1,386 for 1,000. These figures are averages over many populations. In a single population the frequency of an allele can wander up and down, so its loss of variation is not smooth.[4]
As allele frequencies spread apart among populations, the average heterozygosity within them falls.[3] More individuals are homozygous, which can expose harmful recessive alleles that heterozygotes carry unseen.[2] The inbreeding depression that can follow in cannabis is described under outcrossing.
Mutation replaces what drift removes. In a model in which every mutation produces a new allele, a population keeps substantial variation at a locus when more than one new mutation arises there in each generation, that is when 2Nu is well above 1, where u is the mutation rate.[12]
Founder events and bottlenecks
A small group that leaves a larger population to found a new, isolated one carries only part of its variation. Alleles that happened to be common among the founders become common in the new population and others are missing from it altogether. Drift in the small new population can widen the difference over the following generations. This is the founder effect. The new population starts with less variation and with more mating between relatives.[5]
A population bottleneck is a sharp fall in the size of a population that lasts at least one generation. The individuals that survive are a small sample of the population and need not represent it. Some alleles disappear and others rise in frequency by chance. Drift grows stronger and relatives mate more often. The variation lost may not return even when the population grows again.[6] The loss is fast and the recovery slow. In a population cut to ten individuals, the probability that two copies of a gene are identical rises by about 0.05 in each generation. Once the population has grown large again, variation returns only as new mutations arise and drift to high frequency, which can take millions of generations.[12] A few generations at a small size also weigh heavily in a population's effective size over a longer span.[13]
Drift beside selection and migration
Drift is the one force acting on allele frequencies whose direction is random. Natural selection, migration and mutation move frequencies in a set direction or hold them at an equilibrium. How far the random effects of drift override them depends on its strength relative to theirs.[14] In a small population a favourable allele can be lost by chance while a harmful one persists.[2][7] Selection begins to have a marked effect against drift when 4Ns exceeds about 1, where s is the selection coefficient.[15] Migration between populations works against the divergence that drift produces, as described under gene flow.
Drift in cannabis
Cannabis is pollinated by the wind and is dioecious, with male and female flowers on separate plants. Its plants are highly heterozygous.[16] How that variation is divided within and among its populations is described under genetic diversity.
Small and isolated populations
Ademola Aina and colleagues genotyped 346 feral plants from the United States and grouped them into five genetic clusters. The cluster from New York, 14 plants, was the least diverse. Its observed heterozygosity was 0.09, against 0.24 in the clusters from along the Mississippi River and from the West North Central states. The authors suggested that the small size and geographic isolation of the New York population might explain it. The New York and Indiana clusters were the most differentiated pair, with an FST of 0.39. In feral populations close to Hardy–Weinberg equilibrium, the authors suggested that the frequencies of cannabinoid genotypes might be the outcome of local drift, with little selection on cannabinoid content or little immigration of alleles from drug-type plants.[8]
Patrick Woods and colleagues compared whole genomes of Asian, European, feral American and drug-type cannabis. The Asian group had the largest share of segregating sites and the lowest value of Tajima's D. The authors suggested that it had the largest effective population size. The positive values of the other groups, highest in the feral and drug-type plants, suggested to them that those groups had recently contracted and had not had time to expand again.[17]
Breeding lines
In a survey with 13 microsatellite markers, every hemp variety had a positive inbreeding coefficient (FIS = 0.19 ± 0.05), which the authors suggested might reflect bottlenecks linked to current breeding practice. Drug-type cannabis is often propagated as clones. Its breeders discard the male plants, which further reduces its diversity.[9] A field in which most male plants have been culled breeds from few fathers, which shrinks its effective size, as described under mass selection.
Seed-lot regeneration
Seed collections of cannabis have to be regrown before the seed dies. At the Vavilov Institute in Russia, which held 397 cannabis accessions in 1993, hemp seed kept for about five years under normal storage before it lost viability. Each accession therefore had to be grown again at least once in that time.[18] Each regrowing passes an accession through the plants that grow and set seed that year. In many plant species genetic drift has been attributed to regeneration. Alleles have been lost with time spent in collections. Collections of barley, maize and common bean have lost diversity, much of it depending on the number of parents used. Cannabis is wind-pollinated and dioecious, so accessions must be grown outdoors at distances of up to 5 km from one another or indoors in facilities that keep out pollen, whose space limits the number of plants. Matthew Welling and colleagues judged that allelic variation may decline with each cycle of regeneration. They proposed cryopreservation of seed as a way to reduce the drift and hybridisation that regeneration may bring.[10]
In 1993 the Vavilov Institute and the International Hemp Association began a programme to regrow the institute's collection. Of 85 accessions sown that year, 60 produced seed. Only 14 of them grew from more than 1,000 plants, the minimum the project had set. At the Kuban station near Krasnodar, 16 of the 20 accessions grew from fewer than 100 plants and one from 10.[18] Over five years the project regrew 379 of the institute's 496 accessions. Lack of growing space and of viable seed often made 1,000 plants impossible. Several accessions had very few seeds left and had to be multiplied "from a possibly more limited genetic base".[19]
See also
References
- ↑ 1.0 1.1 1.2 Felsenstein, J. (December 2019). Theoretical evolutionary genetics. Seattle: Department of Genome Sciences, University of Washington. pp. 251–252.
- ↑ 2.0 2.1 2.2 Davinack, D. (2024). Molecular Ecology & Evolution: An Introduction. Norton, Massachusetts: Wheaton College. pp. 118–119.
- ↑ 3.0 3.1 3.2 Felsenstein, J. (December 2019). Theoretical evolutionary genetics. Seattle: Department of Genome Sciences, University of Washington. pp. 261–263.
- ↑ 4.0 4.1 Felsenstein, J. (December 2019). Theoretical evolutionary genetics. Seattle: Department of Genome Sciences, University of Washington. pp. 254–256.
- ↑ 5.0 5.1 Davinack, D. (2024). Molecular Ecology & Evolution: An Introduction. Norton, Massachusetts: Wheaton College. pp. 121–122.
- ↑ 6.0 6.1 Davinack, D. (2024). Molecular Ecology & Evolution: An Introduction. Norton, Massachusetts: Wheaton College. pp. 113–115.
- ↑ 7.0 7.1 Davinack, D. (2024). Molecular Ecology & Evolution: An Introduction. Norton, Massachusetts: Wheaton College. pp. 110–112.
- ↑ 8.0 8.1 Aina, Ademola; Wenger, Jonathan P.; Stanton, Eliot; Majumdar, Chandrani Gon; ElSohly, Mahmoud; Weiblen, George D.; Ellison, Shelby (1 July 2025). "Genetic diversity, population structure, and cannabinoid variation in feral Cannabis sativa germplasm from the United States". Scientific Reports. 15 (1) 20423. doi:10.1038/s41598-025-07912-8. PMC 12215616.
- ↑ 9.0 9.1 Dufresnes, C.; Jan, C.; Bienert, F.; Goudet, J.; Fumagalli, L. (2017). "Broad-scale genetic diversity of Cannabis for forensic applications". PLoS ONE. 12 (1) e0170522. doi:10.1371/journal.pone.0170522.
- ↑ 10.0 10.1 Welling, M.T.; Shapter, T.; Rose, T.J.; Liu, L.; Stanger, R.; King, G.J. (2016). "A belated green revolution for Cannabis: virtual genetic resources to fast-track cultivar development". Frontiers in Plant Science. 7 1113. doi:10.3389/fpls.2016.01113.
- ↑ Felsenstein, J. (December 2019). Theoretical evolutionary genetics. Seattle: Department of Genome Sciences, University of Washington. pp. 256–258.
- ↑ 12.0 12.1 Felsenstein, J. (December 2019). Theoretical evolutionary genetics. Seattle: Department of Genome Sciences, University of Washington. pp. 289–290.
- ↑ Felsenstein, J. (December 2019). Theoretical evolutionary genetics. Seattle: Department of Genome Sciences, University of Washington. pp. 269–270.
- ↑ Felsenstein, J. (December 2019). Theoretical evolutionary genetics. Seattle: Department of Genome Sciences, University of Washington. p. 283.
- ↑ Felsenstein, J. (December 2019). Theoretical evolutionary genetics. Seattle: Department of Genome Sciences, University of Washington. pp. 326–328.
- ↑ Sawler, Jason; Stout, Jake M.; Gardner, Kyle M.; Hudson, Darryl; Vidmar, John; Butler, Laura; Page, Jonathan E.; Myles, Sean (2015). "The genetic structure of marijuana and hemp". PLOS ONE. 10 (8) e0133292. doi:10.1371/journal.pone.0133292.
- ↑ Woods, P.; Price, N.; Matthews, P.; McKay, J.K. (2023). "Genome-wide polymorphism and genic selection in feral and domesticated lineages of Cannabis sativa". G3. 13 (2) jkac209. doi:10.1093/g3journal/jkac209.
- ↑ 18.0 18.1 Lemeshev, N.; Rumyantseva, L.; Clarke, R.C. (1994). "Maintenance of Cannabis germplasm in the Vavilov Research Institute Gene Bank – 1993". Journal of the International Hemp Association. 1 (1): 3–5.
- ↑ Clarke, R.C. (1998). "Maintenance of Cannabis germplasm in the Vavilov Research Institute Gene Bank: five year report". Journal of the International Hemp Association. 5 (2): 75–79.