Population size

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In population genetics and population ecology, population size (usually denoted N) is a countable quantity representing the number of individual organisms in a population. Population size is directly associated with amount of genetic drift, and is the underlying cause of effects like population bottlenecks and the founder effect. [1] Genetic drift is the major source of decrease of genetic diversity within populations which drives fixation and can potentially lead to speciation events. [1]

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Genetic drift

Of the five conditions required to maintain Hardy-Weinberg Equilibrium, infinite population size will always be violated; this means that some degree of genetic drift is always occurring. [1] Smaller population size leads to increased genetic drift, it has been hypothesized that this gives these groups an evolutionary advantage for acquisition of genome complexity. [2] An alternate hypothesis posits that while genetic drift plays a larger role in small populations developing complexity, selection is the mechanism by which large populations develop complexity. [3]

Population bottlenecks and founder effect

Population bottlenecks occur when population size reduces for a short period of time, decreasing the genetic diversity in the population.

The founder effect occurs when few individuals from a larger population establish a new population and also decreases the genetic diversity, and was originally outlined by Ernst Mayr. [4] The founder effect is a unique case of genetic drift, as the smaller founding population has decreased genetic diversity that will move alleles within the population more rapidly towards fixation.

Modeling genetic drift

Genetic drift is typically modeled in lab environments using bacterial populations or digital simulation. In digital organisms, a generated population undergoes evolution based on varying parameters, including differential fitness, variation, and heredity set for individual organisms. [3]

Rozen et al. use separate bacterial strains on two different mediums, one with simple nutrient components and one with nutrients noted to help populations of bacteria evolve more heterogeneity. [2] A digital simulation based on the bacterial experiment design was also used, with assorted assignations of fitness and effective population sizes comparable to those of the bacteria used based on both small and large population designations [2] Within both simple and complex environments, smaller populations demonstrated greater population variation than larger populations, which showed no significant fitness diversity. [2] Smaller populations had increased fitness and adapted more rapidly in the complex environment, while large populations adapted faster than small populations in the simple environment. [2] These data demonstrate that the consequences of increased variation within small populations is dependent on the environment: more challenging or complex environments allow variance present within small populations to confer greater advantage. [2] Analysis demonstrates that smaller populations have more significant levels of fitness from heterogeneity within the group regardless of the complexity of the environment; adaptive responses are increased in more complex environments. [2] Adaptations in asexual populations are also not limited by mutations, as genetic variation within these populations can drive adaptation. [5] Although small populations tend to face more challenges because of limited access to widespread beneficial mutation adaptation within these populations is less predictable and allows populations to be more plastic in their environmental responses. [2] Fitness increase over time in small asexual populations is known to be strongly positively correlated with population size and mutation rate, and fixation probability of a beneficial mutation is inversely related to population size and mutation rate. [6]

LaBar and Adami use digital haploid organisms to assess differing strategies for accumulating genomic complexity. This study demonstrated that both drift and selection are effective in small and large populations, respectively, but that this success is dependent on several factors. [3] Data from the observation of insertion mutations in this digital system demonstrate that small populations evolve larger genome sizes from fixation of deleterious mutations and large populations evolve larger genome sizes from fixation of beneficial mutations. [3]  Small populations were noted to have an advantage in attaining full genomic complexity due to drift-driven phenotypic complexity. [3] When deletion mutations were simulated, only the largest populations had any significant fitness advantage. [3] These simulations demonstrate that smaller populations fix deleterious mutations by increased genetic drift. [3] This advantage is likely limited by high rates of extinction. [3] Larger populations evolve complexity through mutations that increase expression of particular genes; removal of deleterious alleles does not limit developing more complex genomes in the larger groups and a large number of insertion mutations that resulted in beneficial or non-functional elements within the genome were not required. [3] When deletion mutations occur more frequently, the largest populations have an advantage that suggests larger populations generally have an evolutionary advantage for development of new traits. [3]

Critical Mutation Rate

Critical mutation rate, or error threshold, limits the number of mutations that can exist within a self-replicating molecule before genetic information is destroyed in later generations. [7]

Contrary to the findings of previous studies, [8] critical mutation rate has been noted to be dependent on population size in both haploid and diploid populations. [9] When populations have fewer than 100 individuals, critical mutation rate can be exceeded, but will lead to loss of genetic material which results in further population decline and likelihood of extinction. [9] This ‘speed limit’ is common within small, adapted asexual populations and is independent of mutation rate. [10]

Effective population size (Ne)

The effective population size (Ne) is defined as "the number of breeding individuals in an idealized population that would show the same amount of dispersion of allele frequencies under random genetic drift or the same amount of inbreeding as the population under consideration." Ne is usually less than N (the absolute population size) and this has important applications in conservation genetics. [11]

Overpopulation may indicate any case in which the population of any species of animal may exceed the carrying capacity of its ecological niche. [12]

See also

Related Research Articles

<span class="mw-page-title-main">Mutation</span> Alteration in the nucleotide sequence of a genome

In biology, a mutation is an alteration in the nucleic acid sequence of the genome of an organism, virus, or extrachromosomal DNA. Viral genomes contain either DNA or RNA. Mutations result from errors during DNA or viral replication, mitosis, or meiosis or other types of damage to DNA, which then may undergo error-prone repair, cause an error during other forms of repair, or cause an error during replication. Mutations may also result from insertion or deletion of segments of DNA due to mobile genetic elements.

Molecular evolution is the process of change in the sequence composition of cellular molecules such as DNA, RNA, and proteins across generations. The field of molecular evolution uses principles of evolutionary biology and population genetics to explain patterns in these changes. Major topics in molecular evolution concern the rates and impacts of single nucleotide changes, neutral evolution vs. natural selection, origins of new genes, the genetic nature of complex traits, the genetic basis of speciation, the evolution of development, and ways that evolutionary forces influence genomic and phenotypic changes.

<span class="mw-page-title-main">Neutral theory of molecular evolution</span>

The neutral theory of molecular evolution holds that most evolutionary changes occur at the molecular level, and most of the variation within and between species are due to random genetic drift of mutant alleles that are selectively neutral. The theory applies only for evolution at the molecular level, and is compatible with phenotypic evolution being shaped by natural selection as postulated by Charles Darwin.

Population genetics is a subfield of genetics that deals with genetic differences within and among populations, and is a part of evolutionary biology. Studies in this branch of biology examine such phenomena as adaptation, speciation, and population structure.

<span class="mw-page-title-main">Muller's ratchet</span> Accumulation of harmful mutations

In evolutionary genetics, Muller's ratchet is a process which, in the absence of recombination, results in an accumulation of irreversible deleterious mutations. This happens because in the absence of recombination, and assuming reverse mutations are rare, offspring bear at least as much mutational load as their parents. Muller proposed this mechanism as one reason why sexual reproduction may be favored over asexual reproduction, as sexual organisms benefit from recombination and consequent elimination of deleterious mutations. The negative effect of accumulating irreversible deleterious mutations may not be prevalent in organisms which, while they reproduce asexually, also undergo other forms of recombination. This effect has also been observed in those regions of the genomes of sexual organisms that do not undergo recombination.

<span class="mw-page-title-main">Genetic diversity</span> Total number of genetic characteristics in a species

Genetic diversity is the total number of genetic characteristics in the genetic makeup of a species, it ranges widely from the number of species to differences within species and can be attributed to the span of survival for a species. It is distinguished from genetic variability, which describes the tendency of genetic characteristics to vary.

In evolutionary genetics, mutational meltdown is a sub class of extinction vortex in which the environment and genetic predisposition mutually reinforce each other. Mutational meltdown is the accumulation of harmful mutations in a small population, which leads to loss of fitness and decline of the population size, which may lead to further accumulation of deleterious mutations due to fixation by genetic drift.

<span class="mw-page-title-main">Evolution of sexual reproduction</span> How sexually reproducing multicellular organisms could have evolved from a common ancestor species

Sexual reproduction is an adaptive feature which is common to almost all multicellular organisms and various unicellular organisms. Currently, the adaptive advantage of sexual reproduction is widely regarded as a major unsolved problem in biology. As discussed below, one prominent theory is that sex evolved as an efficient mechanism for producing variation, and this had the advantage of enabling organisms to adapt to changing environments. Another prominent theory, also discussed below, is that a primary advantage of outcrossing sex is the masking of the expression of deleterious mutations. Additional theories concerning the adaptive advantage of sex are also discussed below. Sex does, however, come with a cost. In reproducing asexually, no time nor energy needs to be expended in choosing a mate and, if the environment has not changed, then there may be little reason for variation, as the organism may already be well-adapted. However, very few environments have not changed over the millions of years that reproduction has existed. Hence it is easy to imagine that being able to adapt to changing environment imparts a benefit. Sex also halves the amount of offspring a given population is able to produce. Sex, however, has evolved as the most prolific means of species branching into the tree of life. Diversification into the phylogenetic tree happens much more rapidly via sexual reproduction than it does by way of asexual reproduction.

Evolvability is defined as the capacity of a system for adaptive evolution. Evolvability is the ability of a population of organisms to not merely generate genetic diversity, but to generate adaptive genetic diversity, and thereby evolve through natural selection.

Genetic load is the difference between the fitness of an average genotype in a population and the fitness of some reference genotype, which may be either the best present in a population, or may be the theoretically optimal genotype. The average individual taken from a population with a low genetic load will generally, when grown in the same conditions, have more surviving offspring than the average individual from a population with a high genetic load. Genetic load can also be seen as reduced fitness at the population level compared to what the population would have if all individuals had the reference high-fitness genotype. High genetic load may put a population in danger of extinction.

Genetic hitchhiking, also called genetic draft or the hitchhiking effect, is when an allele changes frequency not because it itself is under natural selection, but because it is near another gene that is undergoing a selective sweep and that is on the same DNA chain. When one gene goes through a selective sweep, any other nearby polymorphisms that are in linkage disequilibrium will tend to change their allele frequencies too. Selective sweeps happen when newly appeared mutations are advantageous and increase in frequency. Neutral or even slightly deleterious alleles that happen to be close by on the chromosome 'hitchhike' along with the sweep. In contrast, effects on a neutral locus due to linkage disequilibrium with newly appeared deleterious mutations are called background selection. Both genetic hitchhiking and background selection are stochastic (random) evolutionary forces, like genetic drift.

Neutral mutations are changes in DNA sequence that are neither beneficial nor detrimental to the ability of an organism to survive and reproduce. In population genetics, mutations in which natural selection does not affect the spread of the mutation in a species are termed neutral mutations. Neutral mutations that are inheritable and not linked to any genes under selection will be lost or will replace all other alleles of the gene. That loss or fixation of the gene proceeds based on random sampling known as genetic drift. A neutral mutation that is in linkage disequilibrium with other alleles that are under selection may proceed to loss or fixation via genetic hitchhiking and/or background selection.

In population genetics, fixation is the change in a gene pool from a situation where there exists at least two variants of a particular gene (allele) in a given population to a situation where only one of the alleles remains. That is, the allele becomes fixed. In the absence of mutation or heterozygote advantage, any allele must eventually be lost completely from the population or fixed. Whether a gene will ultimately be lost or fixed is dependent on selection coefficients and chance fluctuations in allelic proportions. Fixation can refer to a gene in general or particular nucleotide position in the DNA chain (locus).

The nearly neutral theory of molecular evolution is a modification of the neutral theory of molecular evolution that accounts for the fact that not all mutations are either so deleterious such that they can be ignored, or else neutral. Slightly deleterious mutations are reliably purged only when their selection coefficient are greater than one divided by the effective population size. In larger populations, a higher proportion of mutations exceed this threshold for which genetic drift cannot overpower selection, leading to fewer fixation events and so slower molecular evolution.

The evolution of biological complexity is one important outcome of the process of evolution. Evolution has produced some remarkably complex organisms – although the actual level of complexity is very hard to define or measure accurately in biology, with properties such as gene content, the number of cell types or morphology all proposed as possible metrics.

<span class="mw-page-title-main">Clonal interference</span> Phenomenon in evolutionary biology

Clonal interference is a phenomenon in evolutionary biology, related to the population genetics of organisms with significant linkage disequilibrium, especially asexually reproducing organisms. The idea of clonal interference was introduced by American geneticist Hermann Joseph Muller in 1932. It explains why beneficial mutations can take a long time to get fixated or even disappear in asexually reproducing populations. As the name suggests, clonal interference occurs in an asexual lineage ("clone") with a beneficial mutation. This mutation would be likely to get fixed if it occurred alone, but it may fail to be fixed, or even be lost, if another beneficial-mutation lineage arises in the same population; the multiple clones interfere with each other.

Host–parasite coevolution is a special case of coevolution, where a host and a parasite continually adapt to each other. This can create an evolutionary arms race between them. A more benign possibility is of an evolutionary trade-off between transmission and virulence in the parasite, as if it kills its host too quickly, the parasite will not be able to reproduce either. Another theory, the Red Queen hypothesis, proposes that since both host and parasite have to keep on evolving to keep up with each other, and since sexual reproduction continually creates new combinations of genes, parasitism favours sexual reproduction in the host.

Fisher's geometric model (FGM) is an evolutionary model of the effect sizes and effect on fitness of spontaneous mutations proposed by Ronald Fisher to explain the distribution of effects of mutations that could contribute to adaptative evolution.

<span class="mw-page-title-main">Epistasis</span> Dependence of a gene mutations phenotype on mutations in other genes

Epistasis is a phenomenon in genetics in which the effect of a gene mutation is dependent on the presence or absence of mutations in one or more other genes, respectively termed modifier genes. In other words, the effect of the mutation is dependent on the genetic background in which it appears. Epistatic mutations therefore have different effects on their own than when they occur together. Originally, the term epistasis specifically meant that the effect of a gene variant is masked by that of different gene.

<span class="mw-page-title-main">Drift-barrier hypothesis</span>

The drift-barrier hypothesis is an evolutionary hypothesis formulated by Michael Lynch in 2010. It suggests that the perfection of the performance of a trait, in a specific environment, by natural selection will hit a hypothetical barrier. The closer a trait comes to perfection, the smaller the fitness advantages become. Once this barrier is reached, the effects of further beneficial mutations are unlikely to be large enough to overcome the power of random genetic drift. Selection generally favors lower mutation rates due to the associated load of deleterious mutations that come with a high mutation rate.

References

  1. 1 2 3 Wright S (November 1929). "The Evolution of Dominance". The American Naturalist. 63 (689): 556–561. doi:10.1086/280290. S2CID   85301374.
  2. 1 2 3 4 5 6 7 8 Rozen DE, Habets MG, Handel A, de Visser JA (March 2008). "Heterogeneous adaptive trajectories of small populations on complex fitness landscapes". PLOS ONE. 3 (3): e1715. Bibcode:2008PLoSO...3.1715R. doi: 10.1371/journal.pone.0001715 . PMC   2248617 . PMID   18320036.
  3. 1 2 3 4 5 6 7 8 9 10 LaBar T, Adami C (December 2016). "Different Evolutionary Paths to Complexity for Small and Large Populations of Digital Organisms". PLOS Computational Biology. 12 (12): e1005066. arXiv: 1604.06299 . Bibcode:2016PLSCB..12E5066L. doi: 10.1371/journal.pcbi.1005066 . PMC   5140054 . PMID   27923053.
  4. ↑ Provine WB (July 2004). "Ernst Mayr: Genetics and speciation". Genetics. 167 (3): 1041–6. doi:10.1093/genetics/167.3.1041. PMC   1470966 . PMID   15280221.
  5. ↑ Lang GI, Botstein D, Desai MM (July 2011). "Genetic variation and the fate of beneficial mutations in asexual populations". Genetics. 188 (3): 647–61. doi:10.1534/genetics.111.128942. PMC   3176544 . PMID   21546542.
  6. ↑ Gerrish PJ, Lenski RE (1998). "The fate of competing beneficial mutations in an asexual population". Genetica. 102–103 (1–6): 127–44. doi:10.1023/a:1017067816551. PMID   9720276. S2CID   15148583.
  7. ↑ Eigen M (October 1971). "Selforganization of matter and the evolution of biological macromolecules". Die Naturwissenschaften. 58 (10): 465–523. Bibcode:1971NW.....58..465E. doi:10.1007/bf00623322. PMID   4942363. S2CID   38296619.
  8. ↑ Gillespie JH (November 2001). "Is the population size of a species relevant to its evolution?". Evolution; International Journal of Organic Evolution. 55 (11): 2161–9. doi: 10.1111/j.0014-3820.2001.tb00732.x . JSTOR   2680348. PMID   11794777.
  9. 1 2 Aston E, Channon A, Day C, Knight CG (2013-12-27). "Critical mutation rate has an exponential dependence on population size in haploid and diploid populations". PLOS ONE. 8 (12): e83438. Bibcode:2013PLoSO...883438A. doi: 10.1371/journal.pone.0083438 . PMC   3873944 . PMID   24386200.
  10. ↑ Arjan JA, Visser M, Zeyl CW, Gerrish PJ, Blanchard JL, Lenski RE (January 1999). "Diminishing returns from mutation supply rate in asexual populations". Science. 283 (5400): 404–6. Bibcode:1999Sci...283..404A. doi:10.1126/science.283.5400.404. JSTOR   2896813. PMID   9888858.
  11. ↑ Husemann M, Zachos FE, Paxton RJ, Habel JC (October 2016). "Effective population size in ecology and evolution". Heredity. 117 (4): 191–2. doi:10.1038/hdy.2016.75. PMC   5026761 . PMID   27553454.
  12. ↑ Population Reference Bureau PRB (December 1988). "What is overpopulation?". Population Education Interchange. 17 (4): 1–2. PMID   12281798.
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