Biology:Linkage disequilibrium

Short description: Allele association in population genetics

In population genetics, linkage disequilibrium (LD) is the non-random association of alleles at different loci in a given population. Loci are said to be in linkage disequilibrium when the frequency of association of their different alleles is higher or lower than expected if the loci were independent and associated randomly.

Linkage disequilibrium is influenced by many factors, including selection, the rate of genetic recombination, mutation rate, genetic drift, the system of mating, population structure, and genetic linkage. As a result, the pattern of linkage disequilibrium in a genome is a powerful signal of the population genetic processes that are structuring it.

In spite of its name, linkage disequilibrium may exist between alleles at different loci without any genetic linkage between them and independently of whether or not allele frequencies are in equilibrium (not changing with time). Furthermore, linkage disequilibrium is sometimes referred to as gametic phase disequilibrium; however, the concept also applies to asexual organisms and therefore does not depend on the presence of gametes.

Formal definition

Suppose that among the gametes that are formed in a sexually reproducing population, allele A occurs with frequency $p_A$ at one locus (i.e. $p_A$ is the proportion of gametes with A at that locus), while at a different locus allele B occurs with frequency $p_B$. Similarly, let $p_{AB}$ be the frequency with which both A and B occur together in the same gamete (i.e. $p_{AB}$ is the frequency of the AB haplotype).

The association between the alleles A and B can be regarded as completely random—which is known in statistics as independence—when the occurrence of one does not affect the occurrence of the other, in which case the probability that both A and B occur together is given by the product $p_A{p}_B$ of the probabilities. There is said to be a linkage disequilibrium between the two alleles whenever $p_{AB}$ differs from $p_A{p}_B$ for any reason.

The level of linkage disequilibrium between A and B can be quantified by the coefficient of linkage disequilibrium $D_{AB}$, which is defined as

$D_{AB}=p_{AB}-p_A{p}_B,$

provided that both $p_A$ and $p_B$ are greater than zero. Linkage disequilibrium corresponds to $D_{AB}\ne 0$. In the case $D_{AB}=0$ we have $p_{AB}=p_A{p}_B$ and the alleles A and B are said to be in linkage equilibrium. The subscript "AB" on $D_{AB}$ emphasizes that linkage disequilibrium is a property of the pair $\{A,B\}$ of alleles and not of their respective loci. Other pairs of alleles at those same two loci may have different coefficients of linkage disequilibrium.

For two biallelic loci, where a and b are the other alleles at these two loci, the restrictions are so strong that only one value of D is sufficient to represent all linkage disequilibrium relationships between these alleles. In this case, $D_{AB}=-D_{Ab}=-D_{aB}=D_{ab}$. Their relationships can be characterized as follows.

$D=P_{AB}-P_A{P}_B$

$-D=P_{Ab}-P_A{P}_b$

$-D=P_{aB}-P_a{P}_B$

$D=P_{ab}-P_a{P}_b$

The sign of D in this case is chosen arbitrarily. The magnitude of D is more important than the sign of D because the magnitude of D is representative of the degree of linkage disequilibrium. However, positive D value means that the gamete is more frequent than expected while negative means that the combination of these two alleles are less frequent than expected.

Linkage disequilibrium in asexual populations can be defined in a similar way in terms of population allele frequencies. Furthermore, it is also possible to define linkage disequilibrium among three or more alleles, however these higher-order associations are not commonly used in practice.

Measures derived from D

The coefficient of linkage disequilibrium $D$ is not always a convenient measure of linkage disequilibrium because its range of possible values depends on the frequencies of the alleles it refers to. This makes it difficult to compare the level of linkage disequilibrium between different pairs of alleles.

Lewontin suggested normalising D by dividing it by the theoretical maximum difference between the observed and expected haplotype frequencies as follows:

$D^{\prime }=\frac{D}{D_{\max }}$

where

$D_{\max }=\{\begin{array}{ll}\max \{-p_A{p}_B,-(1-p_A)(1-p_B)\}& \text{when }D<0\\ \min \{p_A(1-p_B),(1-p_A)p_B\}& \text{when }D>0\end{array}$

An alternative to $D^{\prime }$ is the correlation coefficient between pairs of loci, usually expressed as its square, $r^2$

$r^2=\frac{D^2}{p_A(1-p_A)p_B(1-p_B)}.$

Limits for the ranges of linkage disequilibrium measures

The measures $r^2$ and $D^{\prime }$ have limits to their ranges and do not range over all values of zero to one for all pairs of loci. The maximum of $r^2$ depends on the allele frequencies at the two loci being compared and can only range fully from zero to one where either the allele frequencies at both loci are equal, $P_A=P_B$ where $D>0$, or when the allele frequencies have the relationship $P_A=1-P_B$ when $D<0$. While $D^{\prime }$ can always take a maximum value of 1, its minimum value for two loci is equal to $|r|$ for those loci.

Example: Two-loci and two-alleles

Consider the haplotypes for two loci A and B with two alleles each—a two-loci, two-allele model. Then the following table defines the frequencies of each combination:

Haplotype	Frequency
$A_1{B}_1$	$x_{11}$
$A_1{B}_2$	$x_{12}$
$A_2{B}_1$	$x_{21}$
$A_2{B}_2$	$x_{22}$

Note that these are relative frequencies. One can use the above frequencies to determine the frequency of each of the alleles:

Allele	Frequency
$A_1$	$p_1=x_{11}+x_{12}$
$A_2$	$p_2=x_{21}+x_{22}$
$B_1$	$q_1=x_{11}+x_{21}$
$B_2$	$q_2=x_{12}+x_{22}$

If the two loci and the alleles are independent from each other, then one can express the observation $A_1{B}_1$ as "$A_1$ is found and $B_1$ is found". The table above lists the frequencies for $A_1$, $p_1$, and for$B_1$, $q_1$, hence the frequency of $A_1{B}_1$ is $x_{11}$, and according to the rules of elementary statistics $x_{11}=p_1{q}_1$.

The deviation of the observed frequency of a haplotype from the expected is a quantity called the linkage disequilibrium and is commonly denoted by a capital D:

$D=x_{11}-p_1{q}_1$

The following table illustrates the relationship between the haplotype frequencies and allele frequencies and D.

	$A_1$	$A_2$	Total
$B_1$	$x_{11}=p_1{q}_1+D$	$x_{21}=p_2{q}_1-D$	$q_1$
$B_2$	$x_{12}=p_1{q}_2-D$	$x_{22}=p_2{q}_2+D$	$q_2$
Total	$p_1$	$p_2$	$1$

Role of recombination

In the absence of evolutionary forces other than random mating, Mendelian segregation, random chromosomal assortment, and chromosomal crossover (i.e. in the absence of natural selection, inbreeding, and genetic drift), the linkage disequilibrium measure $D$ converges to zero along the time axis at a rate depending on the magnitude of the recombination rate $c$ between the two loci.

Using the notation above, $D=x_{11}-p_1{q}_1$, we can demonstrate this convergence to zero as follows. In the next generation, $x_{1^{\prime }1}$, the frequency of the haplotype $A_1{B}_1$, becomes

$x_{1^{\prime }1}=(1-c)x_{11}+c{p}_1{q}_1$

This follows because a fraction $(1-c)$ of the haplotypes in the offspring have not recombined, and are thus copies of a random haplotype in their parents. A fraction $x_{11}$ of those are $A_1{B}_1$. A fraction $c$ have recombined these two loci. If the parents result from random mating, the probability of the copy at locus $A$ having allele $A_1$ is $p_1$ and the probability of the copy at locus $B$ having allele $B_1$ is $q_1$, and as these copies are initially in the two different gametes that formed the diploid genotype, these are independent events so that the probabilities can be multiplied.

This formula can be rewritten as

$x_{1^{\prime }1}-p_1{q}_1=(1-c)(x_{11}-p_1{q}_1)$

so that

$D_1=(1-c)D_0$

where $D$ at the $n$-th generation is designated as $D_n$. Thus we have

$D_n=(1-c{)}^n{D}_0.$

If $n\to \mathrm{\infty }$, then $(1-c{)}^n\to 0$ so that $D_n$ converges to zero.

If at some time we observe linkage disequilibrium, it will disappear in the future due to recombination. However, the smaller the distance between the two loci, the smaller will be the rate of convergence of $D$ to zero.

Resources

A comparison of different measures of LD is provided by Devlin & Risch

The International HapMap Project enables the study of LD in human populations online. The Ensembl project integrates HapMap data with other genetic information from dbSNP.

Analysis software

• PLINK – whole genome association analysis toolset, which can calculate LD among other things
• LDHat
• Haploview
• LdCompare— open-source software for calculating LD.
• SNP and Variation Suite – commercial software with interactive LD plot.
• GOLD – Graphical Overview of Linkage Disequilibrium
• TASSEL – software to evaluate linkage disequilibrium, traits associations, and evolutionary patterns
• rAggr – finds proxy markers (SNPs and indels) that are in linkage disequilibrium with a set of queried markers, using the 1000 Genomes Project and HapMap genotype databases.
• SNeP – Fast computation of LD and Ne for large genotype datasets in PLINK format.
• LDlink – A suite of web-based applications to easily and efficiently explore linkage disequilibrium in population subgroups. All population genotype data originates from Phase 3 of the 1000 Genomes Project and variant RS numbers are indexed based on dbSNP build 151.
• Bcftools – utilities for variant calling and manipulating VCFs and BCFs.

Simulation software

• Haploid — a C library for population genetic simulation (GPL)

See also

• Haploview
• Hardy–Weinberg principle
• Genetic hitchhiking
• Genetic linkage
• Co-adaptation
• Genealogical DNA test
• Tag SNP
• Association mapping
• Family based QTL mapping

Further reading

• Hedrick, Philip W. (2005). Genetics of Populations (3rd ed.). Sudbury, Boston, Toronto, London, Singapore: Jones and Bartlett Publishers. ISBN 978-0-7637-4772-5. 
• Bibliography: Linkage Disequilibrium Analysis : a bibliography of more than one thousand articles on Linkage disequilibrium published since 1918.