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Linkage analysis
- 1. LINKAGE ANALYSIS AND GENOTYPINGANALYSIS REPRESENTED BY – USHA M.SC. BIOINFORMATICS SUBMITTED TO – DR. NISHA SINGH
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- 3. LINKAGE • GENETIC LINKAGEDESCRIBES 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
- 4. TYPES OF LINKAGE ONTHE 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 • GENETICLINKAGE 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 • PROBABILITYOF 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 • STATISTICALMEASURE 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 SCORE • LODCALCULATIONS: • 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
- 10. MAPPING FUNCTIONS • MAPPINGFUNCTIONS 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
- 11. HALDANE’S MAPPING FUNCTIONS ACCORDINGTO 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))
- 12. TOOL FOR LINKAGEANALYSIS • JOINMAP • VITESSE • MAPMAKER • HOMOG • LOT • LINKAGEMAPVIEW
- 13. GENOTYPING • PROCESS OFDETERMINING 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
- 14. GENOTYPING • WHOLE GENOMEGENOTYPING • TARGETED GENOTYPING • CUSTOM GENOTYPING • COPY NUMBER VARIATIONS ANALYSIS
- 15. Genotyping Descriptions Tools Wholegenome genotyping Provides an overview of the entire genome, enabling genome-wide discoveries and associations PLINK SNPTEST Targeted genotyping Allows researchers to focus time and expenses on specific regions of interest GeneChip Custom genotyping Allows researchers to focus on genes, variants, and genomic regions of interest Copy number variations analysis Include analysis of CNVs regions Control-FREEC, CNVnator, mrCaNaVaR, BreakDancer
- 16. APPROACHES TO VISUALIZE GENETICALTERATIONS • ENZYMATIC APPROACHES FOR DISCRIMINATIONS OF ALLELIC VARIANTS • ELECTROPHORETIC DISCRIMINATIONS OF ALLELIC VARIANTS • SOLID-PHASE DETERMINATIONS OF ALLELIC VARIANTS • CHROMATOGRAPHIC METHODS FOR DISCRIMINATIONS OF ALLELIC VARIANTS • PHYSICAL METHODS FOR DISCRIMINATIONS OF ALLELIC VARIANTS • IN-SILICO
- 17. Approaches to visualizegenetic Alterations Methods Included Enzymatic Approaches for Discriminations of Allelic Variants RFLP, AFLP, RAPD Electrophoretic Discriminations of Allelic Variants SSCP, SSR, Fragment Analysis Solid-Phase Determinations of allelic Variants Oligonucleotide arrays Chromatographic methods for discriminations of Allelic Variants DHPLC Physical methods for Discriminations of Allelic Variants Differential sequence with mass spectroscopy, Fluorescence exchange based method In-Silico Analyzing EST Data
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- 22. REFERENCES • PULST SM,GENETICLINKAGE 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.
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