Linkage Analysis
<p><b>Genetic linkage is the tendency of DNA sequences that are close together on a chromosome to be inherited together during the meiosis phase of sexual reproduction</b>. Two genetic markers that are physically near to each other are unlikely to be separated onto different chromatids during chromosomal crossover, and are therefore said to be more linked than markers that are far apart. In other words, the nearer two genes are on a chromosome, the lower the chance of recombination between them, and the more likely they are to be inherited together. Markers on different chromosomes are perfectly unlinked.</p>
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Genetic linkage is the most prominent exception to Gregor Mendel's Law of Independent Assortment. The first experiment to demonstrate linkage was carried out in 1905. At the time, the reason why certain traits tend to be inherited together was unknown. Later work revealed that genes are physical structures related by physical distance.</p>
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The typical unit of genetic linkage is the centimorgan (cM). A distance of 1 cM between two markers means that the markers are separated to different chromosomes on average once per 100 meioses.</p>
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<b>Linkage analysis may be either parametric </b>(if we know the relationship between phenotypic and genetic similarity) or <b>non-parametric</b>. Parametric linkage analysis is the traditional approach, whereby the probability that a gene important for a disease is linked to a genetic marker is studied through the LOD score, (The LOD score (logarithm (base 10) of odds)) which assesses the probability that a given pedigree, where the disease and the marker are cosegregating, is due to the existence of linkage (with a given linkage value) or to chance. Non-parametric linkage analysis, in turn, studies the probability of an allele being identical by descent with itself.</p>
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For many years, linkage analysis was the primary tool used for the genetic mapping of Mendelian and complex traits with familial aggregation. Linkage analysis was largely supplanted by the wide adoption of <b>genome-wide association studies (GWASs)</b>. However, with the recent increased use of whole-genome sequencing (WGS), linkage analysis is again emerging as an important and powerful analysis method for the identification of genes involved in disease aetiology, often in conjunction with WGS filtering approaches.</p>
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Sep 22, 2020 08:28 AM <img src="/1521728c-7964-51f4-ac2d-530b80b055fc.png"/></p>
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Genetic linkage analysis can be used as a tool for estimating the genetic distance between two loci.
In family data, a small recombination fraction between a hypothesized disease locus and a genetic marker is evidence of short distance between the two loci.
Linkage analysis is contrasted with family-based association analysis, in which unaffected family members serve as control individuals (in family-based association tests).
Single-nucleotide variants (SNVs) generated by whole-genome sequencing (WGS) can be used in linkage analysis.
We describe various linkage algorithms and their properties, as well as their implementations.
A detailed enumeration of the pertinent steps in linkage analysis provides a guideline for non-specialists on procedures and pitfall</p>
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<b>What is Linkage Disequilibrium?</b>
Linkage disequilibrium (LD) is the non-random association of alleles of different loci in a population. In other words, linkage disequilibrium refers to the dependence of gene frequencies at two or more loci. Allelic association and gametic disequilibrium are two synonyms of linkage disequilibrium. It is calculated by the difference between the observed frequency of a particular combination of alleles at two loci and the frequency expected for the random association. Therefore, LD measures the deviation from the expectation of non-association along the genome. When there is linkage disequilibrium, the frequency of association of the different alleles is higher or lower than the expected frequency (when they are independent and associated randomly).
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