Genetic linkage analysis and genotyping techniques are used to map disease genes to their chromosome locations. Linkage describes how closely linked genes are inherited together on a chromosome. Complete linkage means genes do not cross over, while incomplete linkage means genes can separate during crossing over. Linkage analysis uses techniques like recombination fraction, LOD scores, and Haldane mapping functions to statistically map traits to chromosomes. Genotyping determines genetic differences by examining DNA sequences, and can analyze whole genomes, targeted regions, or custom panels of variants. It enables studying SNPs, CNVs, and structural variants.

1. Linkage Analysis and Genotyping
Analysis
Represented By – Usha
M.Sc. Bioinformatics
Submitted to – Dr. Nisha Singh

2. Linkage
• Genetic linkage describes the way in which
two genes that are located close to each other
on a chromosome are often inherited
together
• Genes on the same chromosome are said to
be exhibit linkage and are called linked genes
• Linkage is based on crossing over frequency

3. Linked genes

4. Types of linkage
On the basis of Crossing over
• Complete Linkage - The genes located on the
same chromosome do not separate and are
inherited together over the generations due to
the absence of crossing over
• Incomplete Linkage - Genes present in the same
chromosome have a tendency to separate due to
crossing over and hence produce recombinant
progeny besides the parental type

5. Linkage Analysis
• Genetic Linkage Analysis is a power tool to
detect the chromosomal locations of diseases
genes
• Statistical method for mapping heritable trait
genes to their chromosome locations

6. Linkage Analysis Techniques
• Recombination Fraction
• LOD score
• Haldane mapping function

7. Recombination Fraction
• Probability of a marker and a susceptibility
locus segregating independently(may be
represented as θ)
• Ratio of the number of recombined gametes
to the total number of gametes produced
• If θ = 0.5 No linkage
• If θ < 0.5 Linkage

8. LOD scores
• Statistical measure of the likelihood of genetic
linkage between two loci
• Test to compare the likelihood that two loci
are linked, vs. the likelihood that the two loci
are unlinked
• LOD – logarithm of the odd

9. LOD scores

10. LOD score
• LOD calculations:
• LOD(Z) = log10 = probability of birth
sequences with a given linkage/probability of
birth sequences with no linkage
• A LOD score, higher than 3.0 is generally
accepted as evidence for linkage
• A LOD score lower than -2.0 is accepted as
evidence against linkage

11. Mapping functions
• Mapping functions are used to translate
recombination fractions into genetic distances
• A genetic map function M gives a relations i.e.
r = M(d), connecting recombination fraction r
and genetic map

12. Haldane’s Mapping functions
According to Haldane’s
dM = -1/2ln(1-2r) where
• dM is the distance between marker loci,
• r is the recombination frequency,
• dM is expressed in Morgan, so
• r = ½(1-exp (-2dM))

13. Tool for Linkage Analysis
• JoinMap
• Vitesse
• MAPMAKER
• HOMOG
• LOT
• LInkageMapView

14. Genotyping
• Process of determining differences between
genotype of individuals by examining DNA
sequences
• Genotyping enables researchers to explore
genetic variants such as single nucleotide
polymorphisms (SNPs) and large structural
changes in DNA

15. Genotyping
• Whole genome genotyping
• Targeted genotyping
• Custom genotyping
• Copy number variations analysis

16. Whole genome Genotyping
• Whole-genome genotyping provides an
overview of the entire genome, enabling
genome-wide discoveries and associations
• Include high-throughput next-generation
sequencing (NGS) and microarray
technologies

17. Targeted Genotyping
• Allows researchers to focus time and expenses
on specific regions of interest
• Generates a smaller, more manageable data
set, thereby reducing data analysis burdens
• Offers a cost-effective solution with reduced
turnaround time compared to broader
approaches

18. Custom genotyping
• Allows researchers to focus on genes, variants,
and/or genomic regions of interest relevant to
certain diseases or traits of interest, but not
covered in pre-designed products
• Conserves resources by avoiding irrelevant
regions of the genome

19. CNV Analysis
• Copy number variations (CNVs) are genomic
alterations that result in an abnormal number
of copies of one or more genes

20. Tool for CNV analysis
• Control-FREEC
• CNVnator
• mrCaNaVaR
• BreakDancer
• CNVrd
• CNVer

21. Approaches to visualize genetic
Alterations
• Enzymatic Approaches for Discriminations of
Allelic Variants
RFLP
AFLP
• Electrophoretic Discriminations of Allelic Variants
SSCP
High performance DNA sequencing
• Solid-Phase Determinations of allelic Variants
Oligonucleotide arrays

22. Approaches to visualize genetic
Alterations
• Chromatographic methods for discriminations of
Allelic Variants
DHPLC(Denaturing high performance liquid
chromatography)
• Physical methods for Discriminations of Allelic
Variants
Differential sequencing with mass spectrometry
Fluorescence exchange based methods
• In-Silico – Analyzing EST Data

24. SSR(Single Sequencing reactions)

25. Single Stranded Conformations
Polymorphism

26. References
• Pulst SM,Genetic linkage analysis.Arch Neurol.
1999 Jun;56(6):667-72.
• Kristensen VN, Kelefiotis D, Kristensen T,
Børresen-Dale AL.High-throughput methods
for detection of genetic
variation.Biotechniques. 2001 Feb;30(2):318-
22, 324, 326 passim.

27. Thank you