Finding “the gene” for cystic fibrosis

1. Finding “the gene” for cystic fibrosis

2. Finding “the gene” for cystic fibrosis Why is this in quotes? CF is not caused by a gene, it’s caused by multiple genes. CF is not caused by genetic factors. CF is not caused by a gene, it’s caused by a mutation.

4. How to find genetic determinants of naturally varying traits?

5. Genetic markers (microsatellite) Fig. 10.3

6. Genetic markers (microsatellite) Fig. 10.3 Table 11.1

7. Lots of benign variation between us.

8. How do you find polymorphisms? Fig. 11.6

9. How do you find polymorphisms? Introduced in lecture 9/15. Fig. 11.6

10. How do you find polymorphisms? Fig. 11.6

11. How do you find polymorphisms? Fig. 11.6

12. How do you find polymorphisms? Fig. 11.6

13. How do you find polymorphisms? Fig. 11.6

14. How do you find polymorphisms? Fig. 11.6

15. Hybrid mapping: location of probe mouse human/mouse hybrid www3.mdanderson.org/depts/cellab/fish1.htm

16. Hybrid mapping: location of probe Back then, no technique to see 6kb at cytological resolution.

17. Who cares about benign polymorphisms? Remember Sturtevant? Fig. 5.10

18. Who cares about benign polymorphisms? We are going to do a two-point cross. One of our genetic loci is represented by phenotype; the other is a DNA marker.

19. Mapping a disease locus (Autosomal dom) A1 A2 Fig. 11.A

20. Mapping a disease locus (Autosomal dom) phenotype (variation in locus 1) A1 A2 Fig. 11.A

21. Mapping a disease locus (Autosomal dom) phenotype (variation in locus 1) A1 A2 marker genotype (variation in locus 2) Fig. 11.A

22. Mapping a disease locus (Autosomal dom) phenotype (variation in locus 1) A1 A2 marker genotype (variation in locus 2) How close are they in genetic distance? Fig. 11.A

23. A1 D A2 d Mapping a disease locus (Autosomal dom) A1 A2 Fig. 11.A

24. A1 D A2 d Mapping a disease locus (Autosomal dom) (assume phase) A1 A2 Fig. 11.A

25. A1 d A1 D A1 d A2 d Mapping a disease locus A1 A2 Fig. 11.A

26. A1 d A1 D A1 d A2 A2 d d Mapping a disease locus A1 A2 Fig. 11.A

27. A1 d A1 A1 D D A1 d A2 d Mapping a disease locus A1 A2 Fig. 11.A

28. A1 d A1 D A1 d A2 A2 d d Mapping a disease locus A1 A2 Fig. 11.A

29. A1 d A1 D A1 d A2 d Mapping a disease locus A1 A2 ? Fig. 11.A

30. A1 d A1 D A1 d A2 d Mapping a disease locus (sperm) A1 A2 ? Fig. 11.A

31. A1 d A1 D A1 d A2 A2 D d Mapping a disease locus (sperm) A1 A2 Fig. 11.A

32. A1 d A1 D A1 d A2 d Mapping a disease locus A1 A2 In total, 7 of the kids are non-recombinants and 1 is a recombinant. Fig. 11.A

33. Mapping a disease locus A1 A2 In total, 7 of the kids are non-recombinants and 1 is a recombinant. What is the apparent RF between the DNA marker and the disease mutation? 1/10 1/8 1/20 Fig. 11.A

34. Mapping a disease locus 1/8 = 12.5 m.u. A1 A2 In total, 7 of the kids are non-recombinants and 1 is a recombinant. What is the apparent RF between the DNA marker and the disease mutation? 1/10 1/8 1/20 Fig. 11.A

35. Why do I say “apparent RF?”

36. What if… True distance 30 cM Disease-causing mutation Restriction fragment length polymorphism observed recombination fraction = 1/8 = 12.5 cM

37. What if… True distance 30 cM Disease-causing mutation Restriction fragment length polymorphism observed recombination fraction = 1/8 = 12.5 cM You could say this will never happen. But…

38. What if… True distance 30 cM Disease-causing mutation Restriction fragment length polymorphism observed recombination fraction = 1/8 = 12.5 cM this is our observation

39. What if… True distance 30 cM Disease-causing mutation Restriction fragment length polymorphism observed recombination fraction = 1/8 = 12.5 cM this is our observation The observed number of recombinants is just a point estimate, with some error associated.

40. 12 cM, 18 cM…who cares? Further experiments need to find the causal variant, not just a marker. If distances are wrong, could be hunting for years.

41. Mapping a disease locus 1/8 = 12.5 m.u. A1 A2 We now know the mutation is near (linked to) the marker. Fig. 11.A

42. Mapping a disease locus marker (known) 1/8 = 12.5 m.u. A1 A2 We now know the mutation is near (linked to) the marker.

43. Mapping a disease locus marker (known) 1/8 = 12.5 m.u. window containing causative mutation A1 A2 We now know the mutation is near (linked to) the marker.

44. Mapping a disease locus 1/8 = 12.5 m.u. A1 A2 How significant?

45. Mapping a disease locus 1/8 = 12.5 m.u. A1 A2 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?

46. 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?

47. 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 2 to evaluate significance. Here we can’t.

48. LOD scores r = genetic distance between marker and disease locus 1 recomb, 7 non-recomb. A1 A2

49. LOD scores r = genetic distance between marker and disease locus Odds = P(pedigree | r) P(pedigree | r = 0.5) 1 recomb, 7 non-recomb. A1 A2

50. LOD scores r = genetic distance between marker and disease locus “How likely are the data given our model?” Odds = P(pedigree | r) P(pedigree | r = 0.5) 1 recomb, 7 non-recomb. A1 A2