Genetic equilibrium

Last updated

Genetic equilibrium is the condition of an allele or genotype in a gene pool (such as a population) where the frequency does not change from generation to generation. [1] Genetic equilibrium describes a theoretical state that is the basis for determining whether and in what ways populations may deviate from it. Hardy–Weinberg equilibrium is one theoretical framework for studying genetic equilibrium. It is commonly studied using models that take as their assumptions those of Hardy-Weinberg, meaning:

Contents

It can describe other types of equilibrium as well, especially in modeling contexts. In particular, many models use a variation of the Hardy–Weinberg principle as their basis. Instead of all of the Hardy–Weinberg characters being present, these instead assume a balance between the diversifying effects of genetic drift and the homogenizing effects of migration between populations. [2] A population not at equilibrium suggests that one of the assumptions of the model in question has been violated.

Theoretical models of genetic equilibrium

The Hardy–Weinberg principle provides the mathematical framework for genetic equilibrium. Genetic equilibrium itself, whether Hardy-Weinberg or otherwise, provides the groundwork for a number of applications, in including population genetics, conservation and evolutionary biology. With the rapid increase in whole genome sequences available as well as the proliferation of anonymous markers, models have been used to extend the initial theory to all manner of biological contexts. [3] Using data from genetic markers such as ISSRs and RAPDs as well as the predictive potential of statistics, studies have developed models to infer what processes drove the lack of equilibrium. This includes local adaptation, range contraction and expansion and lack of gene flow due to geographic or behavioral barriers, although equilibrium modeling has been applied to a wide range of topics and questions.

Equilibrium modeling have led to developments in the field. Because allelic dominance can disrupt predictions of equilibrium, [4] some models have moved away from using genetic equilibrium as an assumption. Instead of the traditional F-statistics, they make use of Bayesian estimates. [5] Holsinger et al. developed an analog to FST, called theta. [6] Studies have found Bayesian estimates to be better predictors of the patterns observed. [7] However, genetic equilibrium-based modeling remains a tool in population and conservation genetics-it can provide invaluable information about previous historical processes. [4]

Biological study systems

Genetic equilibrium has been studied in a number of taxa. Some marine species in particular have been used as study systems. The life history of marine organisms like sea urchins appear to fulfill the requirements of genetic equilibrium modeling better than terrestrial species. [8] They exist in large, panmictic populations that don’t appear to be strongly affected by geographic barriers. In spite of this, some studies have found considerable differentiation across the range of a species. Instead, when looking for genetic equilibrium, studies found large, widespread species complexes. [9] This indicates that genetic equilibrium may be rare or difficult to identify in the wild, due to considerable local demographic changes on shorter time scales. [10]

In fact, although a large population size is a required condition for genetic equilibrium according to Hardy–Weinberg, some have argued that a large population size can actually slow the approach to genetic equilibrium. [11] This can have implications for conservation, where genetic equilibrium can be used as a marker of a healthy and sustainable population.

Related Research Articles

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">Hardy–Weinberg principle</span> Principle in genetics

In population genetics, the Hardy–Weinberg principle, also known as the Hardy–Weinberg equilibrium, model, theorem, or law, states that allele and genotype frequencies in a population will remain constant from generation to generation in the absence of other evolutionary influences. These influences include genetic drift, mate choice, assortative mating, natural selection, sexual selection, mutation, gene flow, meiotic drive, genetic hitchhiking, population bottleneck, founder effect,inbreeding and outbreeding depression.

Allele frequency, or gene frequency, is the relative frequency of an allele at a particular locus in a population, expressed as a fraction or percentage. Specifically, it is the fraction of all chromosomes in the population that carry that allele over the total population or sample size. Microevolution is the change in allele frequencies that occurs over time within a population.

Phylogeography is the study of the historical processes that may be responsible for the past to present geographic distributions of genealogical lineages. This is accomplished by considering the geographic distribution of individuals in light of genetics, particularly population genetics.

<span class="mw-page-title-main">Peripatric speciation</span> Speciation in which a new species is formed from an isolated smaller peripheral population

Peripatric speciation is a mode of speciation in which a new species is formed from an isolated peripheral population. Since peripatric speciation resembles allopatric speciation, in that populations are isolated and prevented from exchanging genes, it can often be difficult to distinguish between them. Nevertheless, the primary characteristic of peripatric speciation proposes that one of the populations is much smaller than the other. The terms peripatric and peripatry are often used in biogeography, referring to organisms whose ranges are closely adjacent but do not overlap, being separated where these organisms do not occur—for example on an oceanic island compared to the mainland. Such organisms are usually closely related ; their distribution being the result of peripatric speciation.

<span class="mw-page-title-main">Molecular ecology</span> Field of evolutionary biology

Molecular ecology is a field of evolutionary biology that is concerned with applying molecular population genetics, molecular phylogenetics, and more recently genomics to traditional ecological questions. It is virtually synonymous with the field of "Ecological Genetics" as pioneered by Theodosius Dobzhansky, E. B. Ford, Godfrey M. Hewitt, and others. These fields are united in their attempt to study genetic-based questions "out in the field" as opposed to the laboratory. Molecular ecology is related to the field of conservation genetics.

In population genetics an idealised population is one that can be described using a number of simplifying assumptions. Models of idealised populations are either used to make a general point, or they are fit to data on real populations for which the assumptions may not hold true. For example, coalescent theory is used to fit data to models of idealised populations. The most common idealized population in population genetics is described in the Wright-Fisher model after Sewall Wright and Ronald Fisher and (1931). Wright-Fisher populations have constant size, and their members can mate and reproduce with any other member. Another example is a Moran model, which has overlapping generations, rather than the non-overlapping generations of the Fisher-Wright model. The complexities of real populations can cause their behavior to match an idealised population with an effective population size that is very different from the census population size of the real population. For sexual diploids, idealized populations will have genotype frequencies related to the allele frequencies according to Hardy-Weinberg equilibrium.

Inbreeding depression is the reduced biological fitness which has the potential to result from inbreeding. Biological fitness refers to an organism's ability to survive and perpetuate its genetic material. Inbreeding depression is often the result of a population bottleneck. In general, the higher the genetic variation or gene pool within a breeding population, the less likely it is to suffer from inbreeding depression, though inbreeding and outbreeding depression can simultaneously occur.

In population genetics overlapping generations refers to mating systems where more than one breeding generation is present at any one time. In systems where this is not the case there are non-overlapping generations in which every breeding generation lasts just one breeding season. If the adults reproduce over multiple breeding seasons the species is considered to have overlapping generations. Examples of species which have overlapping generations are many mammals, including humans, and many invertebrates in seasonal environments. Examples of species which consist of non-overlapping generations are annual plants and several insect species.

Panmixia means uniform random fertilization. A panmictic population is one where all potential parents may contribute equally to the gamete pool, and that these gametes are uniformally distributed within the gamete population (gamodeme). This assumes that there are no hybridising restrictions within the parental population : neither Genetics, Cytogenetics nor behavioural; and neither spatial nor temporal. Therefore, all gamete recombination (fertilization) is uniformally possible. Both the Wahlund effect and the Hardy Weinberg equilibrium assume that the overall population is panmictic.

Population genomics is the large-scale comparison of DNA sequences of populations. Population genomics is a neologism that is associated with population genetics. Population genomics studies genome-wide effects to improve our understanding of microevolution so that we may learn the phylogenetic history and demography of a population.

Population structure is the presence of a systematic difference in allele frequencies between subpopulations. In a randomly mating population, allele frequencies are expected to be roughly similar between groups. However, mating tends to be non-random to some degree, causing structure to arise. For example, a barrier like a river can separate two groups of the same species and make it difficult for potential mates to cross; if a mutation occurs, over many generations it can spread and become common in one subpopulation while being completely absent in the other.

Genetic monitoring is the use of molecular markers to (i) identify individuals, species or populations, or (ii) to quantify changes in population genetic metrics over time. Genetic monitoring can thus be used to detect changes in species abundance and/or diversity, and has become an important tool in both conservation and livestock management. The types of molecular markers used to monitor populations are most commonly mitochondrial, microsatellites or single-nucleotide polymorphisms (SNPs), while earlier studies also used allozyme data. Species gene diversity is also recognized as an important biodiversity metric for implementation of the Convention on Biological Diversity.

HLA-NET is a network targeted to the study of Human leukocyte antigen (HLA) from a populational point of view. The network was initiated by COST Action BM0803 in January 2009. Currently HLA-NET activities are being coordinated by a subcommittee of the scientific committee of the European Federation for Immunogenetics.

The stepwise mutation model (SMM) is a mathematical theory, developed by Motoo Kimura and Tomoko Ohta, that allows for investigation of the equilibrium distribution of allelic frequencies in a finite population where neutral alleles are produced in step-wise fashion.

<span class="mw-page-title-main">Reinforcement (speciation)</span> Process of increasing reproductive isolation

Reinforcement is a process of speciation where natural selection increases the reproductive isolation between two populations of species. This occurs as a result of selection acting against the production of hybrid individuals of low fitness. The idea was originally developed by Alfred Russel Wallace and is sometimes referred to as the Wallace effect. The modern concept of reinforcement originates from Theodosius Dobzhansky. He envisioned a species separated allopatrically, where during secondary contact the two populations mate, producing hybrids with lower fitness. Natural selection results from the hybrid's inability to produce viable offspring; thus members of one species who do not mate with members of the other have greater reproductive success. This favors the evolution of greater prezygotic isolation. Reinforcement is one of the few cases in which selection can favor an increase in prezygotic isolation, influencing the process of speciation directly. This aspect has been particularly appealing among evolutionary biologists.

<span class="mw-page-title-main">Landscape genetics</span> Combination of population genetics and landscape ecology

Landscape genetics is the scientific discipline that combines population genetics and landscape ecology. It broadly encompasses any study that analyses plant or animal population genetic data in conjunction with data on the landscape features and matrix quality where the sampled population lives. This allows for the analysis of microevolutionary processes affecting the species in light of landscape spatial patterns, providing a more realistic view of how populations interact with their environments. Landscape genetics attempts to determine which landscape features are barriers to dispersal and gene flow, how human-induced landscape changes affect the evolution of populations, the source-sink dynamics of a given population, and how diseases or invasive species spread across landscapes.

Genomic control (GC) is a statistical method that is used to control for the confounding effects of population stratification in genetic association studies. The method was originally outlined by Bernie Devlin and Kathryn Roeder in a 1999 paper. It involves using a set of anonymous genetic markers to estimate the effect of population structure on the distribution of the chi-square statistic. The distribution of the chi-square statistics for a given allele that is suspected to be associated with a given trait can then be compared to the distribution of the same statistics for an allele that is expected not to be related to the trait. The method is supposed to involve the use of markers that are not linked to the marker being tested for a possible association. In theory, it takes advantage of the tendency of population structure to cause overdispersion of test statistics in association analyses. The genomic control method is as robust as family-based designs, despite being applied to population-based data. It has the potential to lead to a decrease in statistical power to detect a true association, and it may also fail to eliminate the biasing effects of population stratification. A more robust form of the genomic control method can be performed by expressing the association being studied as two Cochran–Armitage trend tests, and then applying the method to each test separately.

In quantitative genetics, QST is a statistic intended to measure the degree of genetic differentiation among populations with regard to a quantitative trait. It was developed by Ken Spitze in 1993. Its name reflects that QST was intended to be analogous to the fixation index for a single genetic locus (FST). QST is often compared with FST of neutral loci to test if variation in a quantitative trait is a result of divergent selection or genetic drift, an analysis known as QST–FST comparisons.

Allochronic speciation is a form of speciation arising from reproductive isolation that occurs due to a change in breeding time that reduces or eliminates gene flow between two populations of a species. The term allochrony is used to describe the general ecological phenomenon of the differences in phenology that arise between two or more species—speciation caused by allochrony is effectively allochronic speciation.

References

  1. ↑ "Genetic equilibrium".
  2. ↑ Duvernell, D. D.; Lindmeier, J. B.; Faust, K. E.; Whitehead, A. (2008). "Relative influences of historical and contemporary forces shaping the distribution of genetic variation in the Atlantic killifish, Fundulus heteroclitus". Molecular Ecology. 17 (5): 1344–60. doi:10.1111/j.1365-294X.2007.03648.x. PMID   18302693. S2CID   27306569.
  3. ↑ Shriner, D. (2011). "Approximate and exact tests of Hardy-Weinberg equilibrium using uncertain genotypes". Genetic Epidemiology. 35 (7): 632–7. doi:10.1002/gepi.20612. PMC   4141651 . PMID   21922537.
  4. 1 2 Kramer, Koen; van der Werf, D. C. (2010). "Equilibrium and non-equilibrium concepts in forest genetic modeling: population- and individually-based approaches," Forest Systems , 19(SI): 100–112.
  5. ↑ Wilson, G. A.; Rannala, B. (2003). "Bayesian inference of recent migration rates using multilocus genotypes" (PDF). Genetics. 163 (3): 1177–91. doi:10.1093/genetics/163.3.1177. PMC   1462502 . PMID   12663554.
  6. ↑ Holsinger, K. E.; Lewis, P. O.; Dey, D. K. (2002). "A Bayesian approach to inferring population structure from dominant markers". Molecular Ecology (Submitted manuscript). 11 (7): 1157–64. doi:10.1046/j.1365-294X.2002.01512.x. PMID   12074723. S2CID   11461448.
  7. ↑ Ramp Neale, Jennifer M.; Ranker, TOM A.; Collinge, Sharon K. (2008). "Conservation of rare species with island-like distributions: A case study of Lasthenia conjugens(Asteraceae) using population genetic structure and the distribution of rare markers". Plant Species Biology. 23 (2): 97–110. doi: 10.1111/j.1442-1984.2008.00211.x .
  8. ↑ Palumbi, Stephen R.; Grabowsky, Gail; Duda, Thomas; Geyer, Laura; Tachino, Nicholas (1997). "Speciation and Population Genetic Structure in Tropical Pacific Sea Urchins". Evolution. 51 (5): 1506–1517. doi: 10.1111/j.1558-5646.1997.tb01474.x . PMID   28568622..
  9. ↑ Knowlton, Nancy (1993). "Sibling Species in the Sea". Annual Review of Ecology and Systematics. 24: 189–216. doi:10.1146/annurev.es.24.110193.001201..
  10. ↑ Whitlock, M. C. (1992). "Temporal Fluctuations in Demographic Parameters and the Genetic Variance Among Populations". Evolution; International Journal of Organic Evolution. 46 (3): 608–615. doi:10.1111/j.1558-5646.1992.tb02069.x. PMID   28568658. S2CID   20983027.
  11. ↑ Birky Jr, C. W.; Maruyama, T.; Fuerst, P. (1983). "An approach to population and evolutionary genetic theory for genes in mitochondria and chloroplasts, and some results" (PDF). Genetics. 103 (3): 513–27. doi:10.1093/genetics/103.3.513. PMC   1202037 . PMID   6840539.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.