Genetic variance

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Ronald Fisher in 1913 Youngronaldfisher2.JPG
Ronald Fisher in 1913

Genetic variance is a concept outlined by the English biologist and statistician Ronald Fisher in his fundamental theorem of natural selection. In his 1930 book The Genetical Theory of Natural Selection , Fisher postulates that the rate of change of biological fitness can be calculated by the genetic variance of the fitness itself. [1] Fisher tried to give a statistical formula about how the change of fitness in a population can be attributed to changes in the allele frequency. Fisher made no restrictive assumptions in his formula concerning fitness parameters, mate choices or the number of alleles and loci involved. [2]

Contents

Definition

Phenotypic variance, usually combines the genotype variance with the environmental variance. Genetic variance has three major components: the additive genetic variance, dominance variance, and epistatic variance. [3]

Additive genetic variance involves the inheritance of a particular allele from your parent and this allele's independent effect on the specific phenotype, which will cause the phenotype deviation from the mean phenotype. Dominance genetic variance refers to the phenotype deviation caused by the interactions between alternative alleles that control one trait at one specific locus. Epistatic variance involves an interaction between different alleles in different loci. [4]

Heritability

Heritability refers to how much of the phenotypic variance is due to variance in genetic factors. Usually after we know the total amount of genetic variance that is responsible for a trait, we can calculate the trait heritability. Heritability can be used as an important predictor to evaluate if a population can respond to artificial or natural selection. [5]

Broad-sense heritability, H2 = VG/VP, Involves the proportion of phenotypic variation due to the effects of additive, dominance, and epistatic variance. Narrow-sense heritability, h2 = VA/VP, refers to the proportion of phenotypic variation that is due to additive genetic values (VA). [6]

Quantitive formula

The phenotypic variance (VP) in a population is influenced by genetic variance (VG) and environmental sources (VE)

VP = VG + VE [7] [8]

The total amount of genetic variance can be divided into several groups, including additive variance (VA), dominance variance (VD), and epistatic variance (VI).

VG = VA + VD + VI [4]

Measuring method

1. Traditionally, using pedigree data in humans, plants, and livestock species to estimate additive genetic variance.

2. Using a single-nucleotide polymorphisms (SNP) regression method to quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance. [9]

3. Genetic variance–covariance (G) matrices conveniently summarize the genetic relationships among a suite of traits and are a central parameter in the determination of the multivariate response to selection. [10]

Research examples

1. The distribution of genetic variance across phenotypic space and the response to selection. [11]

Understand how empirical spectral distribution of G predicts the response to selection across phenotypic space. In particular, trait combinations that form a nearly null genetic subspace with little genetic variance respond only inconsistently to selection. They set out a framework for understanding how the empirical spectral distribution of G may differ from the random expectations that have been developed under random matrix theory (RMT). Using a data set containing a large number of gene expression traits.

2. Comparing estimates of genetic variance across different relationship models. [12]

In this research, the researchers use the different relationship models to compare estimates of genetic variance components and the heritability. However, different models may give different estimates of genetic variances. They found that expected genetic variances usually equals the estimated variance times a statistic, Dk, and for the most typical models of relationships, Dk is close to 1, which means most of these models can be used to estimate the genetic variance.

3. Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data [13]

The development of single-nucleotide polymorphisms (SNPs) mapping helps to explore the genetic variation of complex traits at individual loci. Researchers can quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance by using a SNP regression method.

Related Research Articles

An allele is a variation of the same sequence of nucleotides at the same place on a long DNA molecule, as described in leading textbooks on genetics and evolution. The word is a short form of "allelomorph".

<span class="mw-page-title-main">Dominance (genetics)</span> One gene variant masking the effect of another in the other copy of the gene

In genetics, dominance is the phenomenon of one variant (allele) of a gene on a chromosome masking or overriding the effect of a different variant of the same gene on the other copy of the chromosome. The first variant is termed dominant and the second is called recessive. This state of having two different variants of the same gene on each chromosome is originally caused by a mutation in one of the genes, either new or inherited. The terms autosomal dominant or autosomal recessive are used to describe gene variants on non-sex chromosomes (autosomes) and their associated traits, while those on sex chromosomes (allosomes) are termed X-linked dominant, X-linked recessive or Y-linked; these have an inheritance and presentation pattern that depends on the sex of both the parent and the child. Since there is only one copy of the Y chromosome, Y-linked traits cannot be dominant or recessive. Additionally, there are other forms of dominance, such as incomplete dominance, in which a gene variant has a partial effect compared to when it is present on both chromosomes, and co-dominance, in which different variants on each chromosome both show their associated traits.

<span class="mw-page-title-main">Heritability</span> Estimation of effect of genetic variation on phenotypic variation of a trait

Heritability is a statistic used in the fields of breeding and genetics that estimates the degree of variation in a phenotypic trait in a population that is due to genetic variation between individuals in that population. The concept of heritability can be expressed in the form of the following question: "What is the proportion of the variation in a given trait within a population that is not explained by the environment or random chance?"

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">Quantitative genetics</span> Study of the inheritance of continuously variable traits

Quantitative genetics deals with quantitative traits, which are phenotypes that vary continuously —as opposed to discretely identifiable phenotypes and gene-products.

<span class="mw-page-title-main">Human variability</span> Range of possible values for any characteristic of human beings

Human variability, or human variation, is the range of possible values for any characteristic, physical or mental, of human beings.

<span class="mw-page-title-main">Genetic variation</span> Difference in DNA among individuals or populations

Genetic variation is the difference in DNA among individuals or the differences between populations among the same species. The multiple sources of genetic variation include mutation and genetic recombination. Mutations are the ultimate sources of genetic variation, but other mechanisms, such as genetic drift, contribute to it, as well.

<span class="mw-page-title-main">Polymorphism (biology)</span> Occurrence of two or more clearly different morphs or forms in the population of a species

In biology, polymorphism is the occurrence of two or more clearly different morphs or forms, also referred to as alternative phenotypes, in the population of a species. To be classified as such, morphs must occupy the same habitat at the same time and belong to a panmictic population.

A quantitative trait locus (QTL) is a locus that correlates with variation of a quantitative trait in the phenotype of a population of organisms. QTLs are mapped by identifying which molecular markers correlate with an observed trait. This is often an early step in identifying the actual genes that cause the trait variation.

Genetic architecture is the underlying genetic basis of a phenotypic trait and its variational properties. Phenotypic variation for quantitative traits is, at the most basic level, the result of the segregation of alleles at quantitative trait loci (QTL). Environmental factors and other external influences can also play a role in phenotypic variation. Genetic architecture is a broad term that can be described for any given individual based on information regarding gene and allele number, the distribution of allelic and mutational effects, and patterns of pleiotropy, dominance, and epistasis.

A polygene is a member of a group of non-epistatic genes that interact additively to influence a phenotypic trait, thus contributing to multiple-gene inheritance, a type of non-Mendelian inheritance, as opposed to single-gene inheritance, which is the core notion of Mendelian inheritance. The term "monozygous" is usually used to refer to a hypothetical gene as it is often difficult to distinguish the effect of an individual gene from the effects of other genes and the environment on a particular phenotype. Advances in statistical methodology and high throughput sequencing are, however, allowing researchers to locate candidate genes for the trait. In the case that such a gene is identified, it is referred to as a quantitative trait locus (QTL). These genes are generally pleiotropic as well. The genes that contribute to type 2 diabetes are thought to be mostly polygenes. In July 2016, scientists reported identifying a set of 355 genes from the last universal common ancestor (LUCA) of all organisms living on Earth.

In genetics, transgressive segregation is the formation of extreme phenotypes, or transgressive phenotypes, observed in segregated hybrid populations compared to phenotypes observed in the parental lines. The appearance of these transgressive (extreme) phenotypes can be either positive or negative in terms of fitness. If both parents' favorable alleles come together, it will result in a hybrid having a higher fitness than the two parents. The hybrid species will show more genetic variation and variation in gene expression than their parents. As a result, the hybrid species will have some traits that are transgressive (extreme) in nature. Transgressive segregation can allow a hybrid species to populate different environments/niches in which the parent species do not reside, or compete in the existing environment with the parental species.

In multivariate quantitative genetics, a genetic correlation is the proportion of variance that two traits share due to genetic causes, the correlation between the genetic influences on a trait and the genetic influences on a different trait estimating the degree of pleiotropy or causal overlap. A genetic correlation of 0 implies that the genetic effects on one trait are independent of the other, while a correlation of 1 implies that all of the genetic influences on the two traits are identical. The bivariate genetic correlation can be generalized to inferring genetic latent variable factors across > 2 traits using factor analysis. Genetic correlation models were introduced into behavioral genetics in the 1970s–1980s.

<span class="mw-page-title-main">Behavioural genetics</span> Study of genetic-environment interactions influencing behaviour

Behavioural genetics, also referred to as behaviour genetics, is a field of scientific research that uses genetic methods to investigate the nature and origins of individual differences in behaviour. While the name "behavioural genetics" connotes a focus on genetic influences, the field broadly investigates the extent to which genetic and environmental factors influence individual differences, and the development of research designs that can remove the confounding of genes and environment. Behavioural genetics was founded as a scientific discipline by Francis Galton in the late 19th century, only to be discredited through association with eugenics movements before and during World War II. In the latter half of the 20th century, the field saw renewed prominence with research on inheritance of behaviour and mental illness in humans, as well as research on genetically informative model organisms through selective breeding and crosses. In the late 20th and early 21st centuries, technological advances in molecular genetics made it possible to measure and modify the genome directly. This led to major advances in model organism research and in human studies, leading to new scientific discoveries.

In statistical genetics, inclusive composite interval mapping (ICIM) has been proposed as an approach to QTL mapping for populations derived from bi-parental crosses. QTL mapping is based on genetic linkage map and phenotypic data to attempt to locate individual genetic factors on chromosomes and to estimate their genetic effects.

Quantitative trait loci mapping or QTL mapping is the process of identifying genomic regions that potentially contain genes responsible for important economic, health or environmental characters. Mapping QTLs is an important activity that plant breeders and geneticists routinely use to associate potential causal genes with phenotypes of interest. Family-based QTL mapping is a variant of QTL mapping where multiple-families are used.

Genome-wide complex trait analysis (GCTA) Genome-based restricted maximum likelihood (GREML) is a statistical method for heritability estimation in genetics, which quantifies the total additive contribution of a set of genetic variants to a trait. GCTA is typically applied to common single nucleotide polymorphisms (SNPs) on a genotyping array and thus termed "chip" or "SNP" heritability.

A human disease modifier gene is a modifier gene that alters expression of a human gene at another locus that in turn causes a genetic disease. Whereas medical genetics has tended to distinguish between monogenic traits, governed by simple, Mendelian inheritance, and quantitative traits, with cumulative, multifactorial causes, increasing evidence suggests that human diseases exist on a continuous spectrum between the two.

<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 a different gene.

The infinitesimal model, also known as the polygenic model, is a widely used statistical model in quantitative genetics and in genome-wide association studies. Originally developed in 1918 by Ronald Fisher, it is based on the idea that variation in a quantitative trait is influenced by an infinitely large number of genes, each of which makes an infinitely small (infinitesimal) contribution to the phenotype, as well as by environmental factors. In "The Correlation between Relatives on the Supposition of Mendelian Inheritance", the original 1918 paper introducing the model, Fisher showed that if a trait is polygenic, "then the random sampling of alleles at each gene produces a continuous, normally distributed phenotype in the population". However, the model does not necessarily imply that the trait must be normally distributed, only that its genetic component will be so around the average of that of the individual's parents. The model served to reconcile Mendelian genetics with the continuous distribution of quantitative traits documented by Francis Galton.

References

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