Linkage disequilibrium

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.[1]

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).[1] Furthermore, linkage disequilibrium is sometimes referred to as gametic phase disequilibrium;[2] however, the concept also applies to asexual organisms and therefore does not depend on the presence of gametes.

Formal definition edit

Suppose that among the gametes that are formed in a sexually reproducing population, allele A occurs with frequency   at one locus (i.e.   is the proportion of gametes with A at that locus), while at a different locus allele B occurs with frequency  . Similarly, let   be the frequency with which both A and B occur together in the same gamete (i.e.   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   of the probabilities. There is said to be a linkage disequilibrium between the two alleles whenever   differs from   for any reason.

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

 

provided that both   and   are greater than zero. Linkage disequilibrium corresponds to  . In the case   we have   and the alleles A and B are said to be in linkage equilibrium. The subscript "AB" on   emphasizes that linkage disequilibrium is a property of the pair   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,  . Their relationships can be characterized as follows.[3]

 

 

 

 

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.[4] 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.[1]

Measures derived from D edit

The coefficient of linkage disequilibrium   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[5] suggested normalising D by dividing it by the theoretical maximum difference between the observed and expected haplotype frequencies as follows:

 

where

 

An alternative to   is the correlation coefficient between pairs of loci, usually expressed as its square,  [6]

 

Limits for the ranges of linkage disequilibrium measures edit

The measures   and   have limits to their ranges and do not range over all values of zero to one for all pairs of loci. The maximum of   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,   where  , or when the allele frequencies have the relationship   when  .[7] While   can always take a maximum value of 1, its minimum value for two loci is equal to   for those loci.[8]

Example: Two-loci and two-alleles edit

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
   
   
   
   

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

Allele Frequency
   
   
   
   

If the two loci and the alleles are independent from each other, then one can express the observation   as "  is found and   is found". The table above lists the frequencies for  ,  , and for ,  , hence the frequency of   is  , and according to the rules of elementary statistics  .

The deviation of the observed frequency of a haplotype from the expected is a quantity[9] called the linkage disequilibrium[10] and is commonly denoted by a capital D:

 

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

    Total
              
       
Total         

Role of recombination edit

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   converges to zero along the time axis at a rate depending on the magnitude of the recombination rate   between the two loci.

Using the notation above,  , we can demonstrate this convergence to zero as follows. In the next generation,  , the frequency of the haplotype  , becomes

 

This follows because a fraction   of the haplotypes in the offspring have not recombined, and are thus copies of a random haplotype in their parents. A fraction   of those are  . A fraction   have recombined these two loci. If the parents result from random mating, the probability of the copy at locus   having allele   is   and the probability of the copy at locus   having allele   is  , 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

 

so that

 

where   at the  -th generation is designated as  . Thus we have

 

If  , then   so that   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   to zero.

Resources edit

A comparison of different measures of LD is provided by Devlin & Risch[11]

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 edit

  • PLINK – whole genome association analysis toolset, which can calculate LD among other things
  • LDHat
  • Haploview
  • LdCompare[12]— 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 edit

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

See also edit

References edit

  1. ^ a b c Slatkin, Montgomery (June 2008). "Linkage disequilibrium — understanding the evolutionary past and mapping the medical future". Nature Reviews Genetics. 9 (6): 477–485. doi:10.1038/nrg2361. PMC 5124487. PMID 18427557.
  2. ^ Falconer, DS; Mackay, TFC (1996). Introduction to Quantitative Genetics (4th ed.). Harlow, Essex, UK: Addison Wesley Longman. ISBN 978-0-582-24302-6.
  3. ^ Slatkin, Montgomery (June 2008). "Linkage disequilibrium — understanding the evolutionary past and mapping the medical future". Nature Reviews Genetics. 9 (6): 477–485. doi:10.1038/nrg2361. ISSN 1471-0056. PMC 5124487. PMID 18427557.
  4. ^ Calabrese, Barbara (2019-01-01), "Linkage Disequilibrium", in Ranganathan, Shoba; Gribskov, Michael; Nakai, Kenta; Schönbach, Christian (eds.), Encyclopedia of Bioinformatics and Computational Biology, Oxford: Academic Press, pp. 763–765, doi:10.1016/b978-0-12-809633-8.20234-3, ISBN 978-0-12-811432-2, S2CID 226248080, retrieved 2020-10-21
  5. ^ Lewontin, R. C. (1964). "The interaction of selection and linkage. I. General considerations; heterotic models". Genetics. 49 (1): 49–67. doi:10.1093/genetics/49.1.49. PMC 1210557. PMID 17248194.
  6. ^ Hill, W.G. & Robertson, A. (1968). "Linkage disequilibrium in finite populations". Theoretical and Applied Genetics. 38 (6): 226–231. doi:10.1007/BF01245622. PMID 24442307. S2CID 11801197.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  7. ^ VanLiere, J.M. & Rosenberg, N.A. (2008). "Mathematical properties of the   measure of linkage disequilibrium". Theoretical Population Biology. 74 (1): 130–137. doi:10.1016/j.tpb.2008.05.006. PMC 2580747. PMID 18572214.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  8. ^ Smith, R.D. (2020). "The nonlinear structure of linkage disequilibrium". Theoretical Population Biology. 134: 160–170. doi:10.1016/j.tpb.2020.02.005. PMID 32222435. S2CID 214716456.
  9. ^ Robbins, R.B. (1 July 1918). "Some applications of mathematics to breeding problems III". Genetics. 3 (4): 375–389. doi:10.1093/genetics/3.4.375. PMC 1200443. PMID 17245911.
  10. ^ R.C. Lewontin & K. Kojima (1960). "The evolutionary dynamics of complex polymorphisms". Evolution. 14 (4): 458–472. doi:10.2307/2405995. ISSN 0014-3820. JSTOR 2405995.
  11. ^ Devlin B.; Risch N. (1995). "A Comparison of Linkage Disequilibrium Measures for Fine-Scale Mapping" (PDF). Genomics. 29 (2): 311–322. CiteSeerX 10.1.1.319.9349. doi:10.1006/geno.1995.9003. PMID 8666377.
  12. ^ Hao K.; Di X.; Cawley S. (2007). "LdCompare: rapid computation of single – and multiple-marker r2 and genetic coverage". Bioinformatics. 23 (2): 252–254. doi:10.1093/bioinformatics/btl574. PMID 17148510.

Further reading edit