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Linkage Analysis
Chapter · January 2021
DOI: 10.1007/978-3-319-47829-6_494-1
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Kishore Sesham
Hare Krishna
All India Institute of Medical Sciences Mangalagiri
All India Institute of Medical Sciences Jodhpur
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Linkage Analysis
Basic Concepts
Linkage analysis being a statistical method
requires understanding of some basic terms such
as recombination fraction, likelihood functions,
maximum likelihood estimation, and odds ratios.
location thought to be determined by chance.
Thus, each child inherits a unique set of recombinant chromosomes of their grandparents.
Genes located close enough to each other on a
chromosome and whose expected crossover rate
within the genetic material separating them at
meiosis is less than 50% are said to be linked
genes.
The distance between two or more linked loci
can be expressed in two ways, i.e., by genetic
distance or physical distance. Physical distance
is the number of nucleotide base pairs present
between them and is determined by DNA
sequence analysis, whereas genetic distance is
the frequency of recombination between two loci
and is determined by observing recombination in
a set of families. Thus, genetic distance is relative
and is dependent on the distribution of crossingover with recombination along each chromosome.
Genetic distance may not reflect the physical distance because crossing-over is not evenly distributed along all chromosomes resulting in blocks of
nonrecombinant stretches of DNA existence in
between (Nussbaum et al. 2007).
Genetic Recombination, Linked Genes, Genetic
Distance, and Physical Distance
Recombination Frequency as a Consequence of
Genetic Distance Between Two Loci
Genetic recombination is a biological phenomenon occurring in the parental gametes during the
process of meiosis before eggs and sperms are
formed. This phenomenon leads to exchange of
chromosome material between homologous chromosomes via a crossover event with the crossover
Linkage occurs when two gene loci are physically
close enough on the same homologous chromosome that they tend to be transmitted together.
Estimating the genetic distance between any two
gene loci relates to how often the genetic recombination does or does not occur between those
Kishore Sesham1 and Hare Krishna2
1
Department of Anatomy, All India Institute of
Medical Sciences, New Delhi, India
2
Department of Anatomy, All India Institute of
Medical Sciences, Jodhpur, Rajasthan, India
Introduction
Linkage analysis is a well-established statistical
method in the field of reverse genetics, where in
the predisposing gene(s) causing a heritable trait
is/are identified.
Description
© Springer Nature Switzerland AG 2021
J. Vonk, T. K. Shackelford (eds.), Encyclopedia of Animal Cognition and Behavior,
https://doi.org/10.1007/978-3-319-47829-6_494-1
2
loci. The recombination fraction, often
represented as ɵ, is calculated by counting the
number of recombinant offspring for a given pair
of loci divided by the total number of offspring
(recombinants plus nonrecombinants). It measures the proportion of recombinations observed
between two loci in a group of offspring. If ɵ¼0, it
means the two loci are very much close to each
other and have very high chance of getting
inherited together. If ɵ¼0.5, it means that the
two loci are far apart and assort independently.
All the values of linkage lie between 0 and 0.5
indicating the varied degrees of linkage.
A recombination rate of 1 (100%) is considered
to be a Morgan (M) unit. A recombination frequency of 0.01 (1%) corresponds to one centiMorgan (cM). The centiMorgan is used as a
typical unit of genetic linkage. This unit is defined
on the basis of relative chance of separation of
different traits per meiotic division. A distance of
1 cM between the two markers that are coding for
different traits is separated to different chromosomes on average once per 100 meiotic product,
thus once per 50 meioses (Griffith et al. 2000).
Determination of the Relative Distance of Three
Gene Loci Using Recombinant Frequency
The genetic distances and the order of three loci
can be determined by a testcross of parental genotypes. For example, there are three gene loci A, B,
and C of unknown distance from each other, and
their observed recombination frequencies using
test cross of parental genotypes are as follows:
The distance from locus A to locus C is 0.06
(6%); the distance between locus B and locus
C is 0.29 (29%); and the distance between A and
B is 0.31 (31%). Thus, the three genes are located
in the order A–C–B (Vogel et al. 1997).
LOD Scores Method Analysis
This method was designed by Newton Morton in
1955. LOD score represents the logarithm in base
10 of the odds of linkage of a trait at a recombination fraction r with a particular marker locus
compared to a recombination fraction (ɵ) of 0.5
between the marker and the trait. It provides a
different way of assessing the significance of a
linkage signal, other than a p-value. This method
Linkage Analysis
is an efficient and economical method for studying families because once a decision is reached, it
is not necessary to study additional families.
LOD ¼ Z
probability of birth sequence with a given linkage value
¼ log 10
probability of birth sequence with no linkage
¼ log 10
ð1 yÞNR yR
0:5ðNRþRÞ
LOD score greater than 3.0 is an evidence for
linkage, whereas score less than -2.0 is considered
evidence to exclude linkage (Morton et al. 1955).
Linkage Analysis Testing Procedures and
Software Programs
Linkage analysis utilizes data on family structures, trait values, and genome-wide markers and
involves tagging segments of a person’s genome
with markers that allow identification of segments
that have been inherited through the family along
with disease and detects the degree of recombination between those genetic markers and traits in
that particular family pedigrees. The genetic
markers used in this method are typically microsatellites or SNPs that are genotyped and tested in
a study sample of pedigrees, and those showing
the strongest statistical evidence of linkage
exceeding a predetermined threshold localize the
trait gene to the chromosome segment where the
markers reside. Parametric linkage (model based)
analysis is used for Mendelian traits that follow a
specific pattern of inheritance consistent with a
single gene, i.e., X-linked, autosomal recessive,
or autosomal dominant. For genetically complex
traits (due to incomplete penetrance and/or
genetic heterogeneity), nonparametric linkage
analysis is used where the initial approach is similar to the one used for Mendelian traits, but the
mode of inheritance is not known and not specified. Various computer programs have been
included to make linkage analyses more precise
and powerful which are briefly listed in the following table.
The following are the web pages for various
linkage analysis software listed above:
Linkage Analysis
3
Linkage Analysis, Table 1 showing the list of various softwares for linkage analysis that can be used for binary traits
and quantitative traits in large pedigree families and nuclear families (Cantor et al. 2013)
Linkage analysis software
Large pedigrees
Binary traits
Program
name
LINKAGE
MENDEL
Option 2
SAGE/
LODLINK
SAGE/LOD
SIMWALK
Quantitative
Program
traits
name
LOKI
SOLAR
Model
Nuclear families
Program name
Model
Par
Par
GENEHUNTER/ESTIMATE
SAGE/LODPAL
NP
NP
Par
SAGE/SIBPAL
NP
Par
Par / NP
Model
MERLIN
Par
Program name
Model
MCMC
algorithm
Variance
components
GENEHUNTER / MAPMAKERSIBS, NPL,
HASEMAN ELSTON
MERLIN/REGRESS
Par /
NP
NP
SAGE/ SIGPAL
NP
Par ¼ Parametric model; NP ¼ Nonparametric model; Both ¼ parametric and/or nonparametric
1. GENEHUNTER. http://www.broad.mit.edu/
ftp/distribution/software/genehunter/
2. LINKAGE. ftp://linkage.rockefeller.edu/soft
ware/linkage
3. LOKI. http://www.stat.washington.edu/thomp
son/Genepi/Loki.shtml
4. MENDEL. http://www.genetics.ucla.edu/
software/
5. MERLIN. http://www.sph.umich.edu/csg/
abecasis/Merlin
6. OSA. http://wwwchg.duhs.duke.edu/research/
aplosa.html
7. SAGE. http://darwin.cwru.edu/sage/
8. SIMWALK. http://www.genetics.ucla.edu/soft
ware/simwalk
9. SOLAR. http://www.sfbr.org/Departments/
genetics_detail.aspx?p¼37
Advantages and Drawbacks
Linkage methods are particularly useful for the
detection of rare variants with a large effect size
in the population. These methods, however, have
shown inconsistent results for common diseases.
Factors such as heterogeneity, pleiotropy, reduced
penetrance, and variable expressivity, in addition
to variability in environmental exposures, weaken
the power of linkage studies in complex traits.
Although, linkage methods are able to identify
candidate regions, the identified regions are
much larger, sometimes spanning up to 40 Mb.
Due to the availability of “next-generation” DNA
sequencing and its promise to allow identification
of the rare variants, interest in linkage analysis
methods is undergoing a renaissance.
Applications
Linkage analysis studies have been used in routine
OPDs to do positional cloning of genes in disorders such as cystic fibrosis (autosomal recessive),
neurofibromatosis type-1 (autosomal dominant)
using parametric models as well as for complex
disease gene position cloning such as Crohn’s
disease using nonparametric models.
Conclusion
Since the time it is developed, several methods
and computer programs have been included to
make linkage analyses more precise and powerful.
Linkage studies were used in the past only to
isolate genes that cause rare genetic syndromes.
Coupled with whole genome sequencing, this
4
method has been successfully used to identify the
association of rare variants to phenotypic traits
such as hearing impairment, familial goiters, and
familial hypertension. Thus, linkage analysis is
again emerging as an extremely useful method in
genomic analysis.
Cross-References
▶ Candidate Gene
▶ CentiMorgan
▶ Cross Over
▶ Gene Map
▶ LOD Score
▶ Mendel’s Laws
▶ Microsatellite Marker
▶ QTL Linkage Analysis
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Linkage Analysis
References
Cantor, R. M. (2013). Analysis of Genetic Linkage. In D L
Rimoin, R E Pyeritz, B R. Korf (Eds.), Emery and
Rimoin’s Principles and Practice of Medical Genetics
(pp. 1–8). Academic Press, Elsevier Ltd. https://doi.
org/10.1016/B978-0-12-801238-3.05482-9
Griffiths, A. J. F., et al. (2000). An introduction to genetic
analysis (7th ed.). New York: WH Freeman & Co.
Morton, N. E. (1955). Sequential tests for the detection of
linkage. Am. J. Hum. Genet., 7, 277–318.
Nussbaum, R. L., McInnes, R. R., & Willard, H. F. (2007).
Human gene mapping and disease gene identification.
In Thompson and Thompson Genetics in Medicine 7th
edition. (pp. 207–321). Saunders Elsevier Ltd., Philadelphia. ISBN: 9781416030805.
Vogel, F., & Motulsky, A. G. (1997). Human genetics.
Problems and approaches (3rd ed.). Heidelberg–
New York: Springer Verlag.