Editing Genetic variation (section)

=== Post-Darwinian concepts of heritable variation ===
In the 20th century, a field that came to be known as [[population genetics]] developed. This field seeks to understand and quantify genetic variation.<ref name=":4" /> The section below  consists of a timeline of selected developments in population genetics, with a focus on methods for quantifying genetic variation.

* '''1866''' - '''Heterozygosity''': Gregor Mendel's hybridization experiments introduced the concept that in the 1950s came to be recognized as [[Zygosity#Heterozygous|heterozygosity]].<ref name=":3" /> In a [[diploid]] species, one that contains two copies of DNA within each cell (one from each parent), an individual is said to be a heterozygote at a particular location in the genome if its two copies of DNA differ at that site. Heterozygosity, the average frequency of heterozygotes in a population, became a fundamental measure of the genetic variation in a population by the mid-20th century.<ref>{{Cite web|title=Heterozygosity|url=https://www.oxfordbibliographies.com/view/document/obo-9780199941728/obo-9780199941728-0039.xml|access-date=2021-12-11|website=Oxford Bibliographies |language=en}}</ref> If the heterozygosity of a population is zero, every individual is homozygous; that is, every individual has two copies of the same allele at the locus of interest and no genetic variation exists. 
* '''1918''' -  '''Variance''': In a seminal paper entitled "The correlation between relatives on the supposition of Mendelian inheritance", [[Ronald Fisher|R.A. Fisher]] introduced the statistical concept of [[variance]]; the average of squared deviations of a collection of observations from their mean (<math display="inline">\sigma^2=\frac{1}{I}\sum_{i=1}^I(x_i-\mu)^2</math>), where <math>\sigma^2</math> is the variance and <math>\mu</math> is the mean of the population from which the observations <math>x_i</math> are drawn).<ref name=":5">{{Cite journal|last1=Charlesworth|first1=Brian|last2=Edwards|first2=Anthony W. F.|date=2018-07-26|title=A century of variance |journal=Significance|volume=15|issue=4|pages=20–25|doi=10.1111/j.1740-9713.2018.01170.x |doi-access=free|issn=1740-9705}}</ref> R.A. Fisher's work in population genetics was not just important to population genetics; these ideas would also form the foundations of modern statistics.
* '''1918, 1921''' - '''Additive and dominant genetic variance''': R.A. Fisher subsequently subdivided his general definition of variance into two components relevant to population genetics: additive and dominant genetic variance.<ref>{{Cite journal|last=Dietrich|first=Michael|date=2013-01-01|title=R.A. Fisher and the Foundations of Statistical Biology|url=https://digitalcommons.dartmouth.edu/facoa/33|journal=Outsider Scientists: Routes to Innovation in Biology}}</ref> An additive genetic model assumes that genes do not interact if the number of the genes affecting the phenotype is small and that a trait value can be estimated simply by summing the effect of each gene on the trait. Under Fisher's model, the total genetic variance is the sum of the additive genetic variance (the variance in a trait due to these additive effects) and the dominant genetic variance (which accounts for interactions between genes).<ref name=":5" />
* '''1948''' - '''Entropy''': Unlike variance, which was developed with the purpose of quantifying genetic variance, [[Claude Shannon|Claude Shannon's]] measure of diversity, now known as [[Shannon entropy]], was developed as part of his work in communication theory as a way to quantify the amount of information contained in a message. However, the method quickly found use in population genetics, and was the central method used to quantify genetic diversity in a seminal paper by Richard Lewontin, "The Apportionment of Human Genetic Diversity".<ref>{{cite book |last=Rosenberg|first=Noah A.|chapter=Variance-Partitioning and Classification in Human Population Genetics|doi=10.1017/9781316276259.040 |editor=Rasmus Grønfeldt Winther |title=Phylogenetic Inference, Selection Theory, and History of Science|year=2018|pages=399–404|publisher=Cambridge University Press|isbn=9781316276259}}</ref>
* '''1951'' - ''F-statistics''': [[F-statistics]], also known as fixation indices, were developed by population geneticist [[Sewall Wright]] to quantify differences in genetic variation within and between populations. The most common of these statistics, F<sub>ST</sub>, considers in its simplest definition two different versions of a gene, or alleles, and two populations that contain one or both of these two alleles. F<sub>ST</sub> quantifies the genetic variability among these two populations by computing the average frequency of heterozygotes across the two populations relative to the frequency of heterozygotes if the two populations were pooled.<ref>{{Cite journal|last1=Alcala|first1=Nicolas|last2=Rosenberg|first2=Noah A|date=2017-07-01|title=Mathematical Constraints on FST: Biallelic Markers in Arbitrarily Many Populations|journal=Genetics|volume=206|issue=3|pages=1581–1600|doi=10.1534/genetics.116.199141 |pmid=28476869|pmc=5500152|doi-access=free|issn=1943-2631}}</ref> F-statistics introduced the idea of quantifying hierarchical concepts of variance and would become the foundation of many important population genetic methods, including a set of methods that tests for evidence of natural selection in the genome.<ref>{{Cite journal|last1=Excoffier|first1=L.|last2=Hofer|first2=T.|last3=Foll|first3=M.|date=October 2009 |title=Detecting loci under selection in a hierarchically structured population|journal=Heredity|language=en|volume=103|issue=4|pages=285–298|doi=10.1038/hdy.2009.74 |pmid=19623208|doi-access=free |issn=1365-2540}}</ref>