Linkage analysis

Linkage Analysis and genotyping analysis techniques with bioinformatics tools

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

23. SSR(Single Sequencing reactions)

24. Single Stranded Conformations Polymorphism

25. 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 .

26. Thank you