1Finding “the gene” for cysticfibrosisFinding “the gene” for cysticfibrosisWhy is this in quotes?A. CF is not caused by a gene, it’s caused bymultiple genes.B. CF is not caused by genetic factors.C. CF is not caused by a gene, it’s caused by amutation.How to find geneticdeterminants of naturallyvarying traits?2Genetic markersFig. 10.3(microsatellite)Genetic markersFig. 10.3(microsatellite)Table 11.1Lots of benign variationbetween us.How do you find polymorphisms?Fig. 11.63How do you find polymorphisms?Fig. 11.6Introduced in lecture 9/15.How do you find polymorphisms?Fig. 11.6How do you find polymorphisms?Fig. 11.6How do you find polymorphisms?Fig. 11.64How do you find polymorphisms?Fig. 11.6How do you find polymorphisms?Fig. 11.6Hybrid mapping: location of probewww3.mdanderson.org/depts/cellab/fish1.htmmouse human/mouse hybridHybrid mapping: location of probeBack then, notechnique to see 6kbat cytologicalresolution.5Who cares about benignpolymorphisms?Remember Sturtevant?Fig. 5.10Who cares about benignpolymorphisms?We are going to do a two-point cross.One of our genetic loci is represented byphenotype; the other is a DNA marker.Mapping a disease locusFig. 1 1.A(Autosomal dom)A1A2Mapping a disease locusFig. 1 1.A(Autosomal dom)phenotype(variation inlocus 1)A1A26Mapping a disease locusFig. 1 1.A(Autosomal dom)phenotype(variation inlocus 1)markergenotype(variation inlocus 2)A1A2Mapping a disease locusFig. 1 1.A(Autosomal dom)phenotype(variation inlocus 1)markergenotype(variation inlocus 2)How close are they in genetic distance?A1A2Mapping a disease locusFig. 1 1.AA1 DA2 d(Autosomal dom)A1A2Mapping a disease locusFig. 1 1.AA1 DA2 d(Autosomal dom)A1A2(assume phase)7Mapping a disease locusFig. 1 1.AA1 DA2 dA1 dA1 dA1A2Mapping a disease locusFig. 1 1.AA1 DA2 dA1 dA1 dA2 dA1A2Mapping a disease locusFig. 1 1.AA1 DA2 dA1 dA1 dA1 DA1A2Mapping a disease locusFig. 1 1.AA1 DA2 dA1 dA1 dA2 dA1A28Mapping a disease locusFig. 1 1.AA1 DA2 dA1 dA1 d?A1A2Mapping a disease locusFig. 1 1.AA1 dA1 d?A1 DA2 d(sperm)A1A2Mapping a disease locusFig. 1 1.AA1 dA1 dA2 DA1 DA2 d(sperm)A1A2Mapping a disease locusFig. 1 1.AA1 dA1 dA1 DA2 dA1A2In total, 7 of the kids arenon-recombinants and 1is a recombinant.9Mapping a disease locusFig. 1 1.AWhat is the apparentRF between the DNAmarker and thedisease mutation?A. 1/10B. 1/8C. 1/20A1A2In total, 7 of the kids arenon-recombinants and 1is a recombinant.Mapping a disease locusFig. 1 1.AWhat is the apparentRF between the DNAmarker and thedisease mutation?1/8 = 12.5 m.u.A1A2A. 1/10B. 1/8C. 1/20In total, 7 of the kids arenon-recombinants and 1is a recombinant.Why do I say “apparent RF?”What if…observed recombinationfraction = 1/8 = 12.5 cMDisease-causingmutationRestrictionfragmentlengthpolymorphismTrue distance 30 cM10What if…observed recombinationfraction = 1/8 = 12.5 cMDisease-causingmutationRestrictionfragmentlengthpolymorphismTrue distance 30 cMYou could say this willnever happen. But…What if…observed recombinationfraction = 1/8 = 12.5 cMDisease-causingmutationRestrictionfragmentlengthpolymorphismTrue distance 30 cMthis is our observationWhat if…observed recombinationfraction = 1/8 = 12.5 cMDisease-causingmutationRestrictionfragmentlengthpolymorphismTrue distance 30 cMThe observed number ofrecombinants is just apoint estimate, with someerror associated.this is our observation12 cM, 18 cM…who cares?Further experiments need to find the causal variant,not just a marker. If distances are wrong, could behunting for years.11Mapping a disease locusFig. 1 1.AWe now know the mutation is near (linkedto) the marker.1/8 = 12.5 m.u.A1A2Mapping a disease locusWe now know the mutation is near (linkedto) the marker.marker (known)1/8 = 12.5 m.u.A1A2Mapping a disease locusWe now know the mutation is near (linkedto) the marker.windowcontainingcausativemutation1/8 = 12.5 m.u.marker (known)A1A2Mapping a disease locus1/8 = 12.5 m.u.How significant?A1A212Mapping a disease locus1/8 = 12.5 m.u.How significant?If RF = 0.5 (unlinked), would be like flipping a coin 8 times.How likely would you be to get 7 heads and 1 tail?A1A2If RF = 0.5 (unlinked), would be like flipping a coin 8 times.How likely would you be to get 7 heads and 1 tail?How much MORE likely is a model of RF < 0.5?If RF = 0.5 (unlinked), would be like flipping a coin 8 times.How likely would you be to get 7 heads and 1 tail?How much MORE likely is a model of RF < 0.5?For large cross between known parents,would use χ2 to evaluate significance.Here we can’t.LOD scores1 recomb, 7 non-recomb.r = genetic distance between marker and disease locusA1A213LOD scores1 recomb, 7 non-recomb.Odds = P(pedigree | r)P(pedigree | r = 0.5)r = genetic distance between marker and disease locusA1A2LOD scores1 recomb, 7 non-recomb.Odds = P(pedigree | r)P(pedigree | r = 0.5)r = genetic distance between marker and disease locus“How likely are thedata given ourmodel?”A1A2LOD scoresk = 1 recomb, n = 7 non-recomb.Odds = P(pedigree | r)P(pedigree | r = 0.5)r = genetic distance between marker and disease locusOdds = (1-r)n • rk 0.5n • 0.5kA1A2LOD scoresOdds = P(pedigree | r)P(pedigree | r = 0.5)r = genetic distance between marker and disease locusOdds = (1-r)n • rk 0.5(total # meioses)A1A2k = 1 recomb, n = 7 non-recomb.14LOD scoresOdds = P(pedigree | r)P(pedigree | r = 0.5)r = genetic distance between marker and disease locusOdds = (1-r)n • rk 0.5(total # meioses)We have an idea of true r,but it is imprecise.k = 1 recomb, n = 7 non-recomb.A1A2Remember?observed recombinationfraction = 1/8 = 12.5 cMDisease-causingmutationRestrictionfragmentlengthpolymorphismTrue distance 30 cMThe observed number ofrecombinants is just apoint estimate, with someerror associated.this is our observationLOD scoresOdds = P(pedigree | r)P(pedigree | r = 0.5)r = genetic distance between marker and disease locusOdds = (1-r)n • rk 0.5(total # meioses)k = 1 recomb, n = 7 non-recomb.A1A2This formalism allowsany r value. Let’sguess r = 0.3.LOD scoresOdds = P(pedigree | r)P(pedigree | r = 0.5)r = genetic distance between marker and disease locusOdds = (1-r)n • rk 0.5(total # meioses)Odds = 0.77 • 0.31 0.58k = 1 recomb, n = 7 non-recomb.A1A2This formalism allowsany r value. Let’sguess r = 0.3.15LOD scoresOdds = P(pedigree | r)P(pedigree | r = 0.5)r = genetic distance between marker and disease
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