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Office hours 304A Stanley Hall next week 3-4pm Monday Nov 24

Office hours 304A Stanley Hall next week 3-4pm Monday Nov 24. Heritability in exptal organisms. Genetically identical. Genetically different. Heritability in exptal organisms.  e .  t . Genetic variance = total var - “environmental var” Heritability H 2 = .  g  =  t  -  e .

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Office hours 304A Stanley Hall next week 3-4pm Monday Nov 24

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  1. Office hours304A Stanley Hallnext week 3-4pm Monday Nov 24

  2. Heritability in exptal organisms Genetically identical Genetically different

  3. Heritability in exptal organisms e t Genetic variance = total var - “environmental var” Heritability H2 = g = t -e g/t

  4. Heritability in humans: MZ twins http://www.sciam.com/media/inline/15DD5B0E-AB41-23B8-2B1E53E8573428C5_1.jpg http://www.twinsinsurance.net/images/twins.jpg http://www.twinsrealm.com/othrpics/twins16.jpg http://www.twinsrealm.com/othrpics/sarahandsandra.jpg Mean each pair = zi Each individual = zij b2 w2 (zij - z)2   h2 = Total mean sq = = t2 t2 T (zij - zi)2   Within pairs mean sq = = w2 N (zi - z)2  = b2 Between pairs mean sq = N-1

  5. Significance of heritability? mRNA expression all progeny P1 P2 progeny, marker genotype P1 progeny, marker genotype P2

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

  7. Thus far, we have only found linkage to a marker. The causal variant is still unknown.

  8. Mapping imprecision wide mapped interval

  9. Mapping imprecision wide mapped interval You should now know from the first problem set why the LOD score is highest for markers close to the causal variant locus…

  10. Mapping imprecision wide mapped interval But why not just look at the single marker with the best LOD score?

  11. Single best locus isn’t the answer 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.

  12. True variant is “under” peak Fig. 11.17

  13. Submergence tolerance in rice

  14. Variation in submergence tolerance http://www.a2mediagroup.com/data/images/news/categories/riceplant.jpg

  15. Linkage mapping intolerant tolerant

  16. Finding the causative variant

  17. Finding the causative variant

  18. Finding the causative variant

  19. Transgenic test http://www.plantsci.cam.ac.uk/Haseloff/SITEGRAPHICS/Agrotrans.GIF

  20. Transgenic test From Prof. Garriga problem set http://www.plantsci.cam.ac.uk/Haseloff/SITEGRAPHICS/Agrotrans.GIF

  21. Transgenic test

  22. Transgenic test

  23. Transgenic test Only expressed upon submergence

  24. Transgenic test Expressed all the time…

  25. Now in a real crop strain Swarna INTOL x IR49830 TOL x Swarna INTOL Check for Sub1A+ F1

  26. Now in a real crop strain Swarna INTOL x IR49830 TOL x Swarna INTOL F1 x Swarna INTOL Check for Sub1A+ B1

  27. Now in a real crop strain Swarna INTOL x IR49830 TOL x Swarna INTOL F1 x Swarna INTOL B1 x Swarna INTOL B2 …

  28. Now in a real crop strain Swarna INTOL x IR49830 TOL x Swarna INTOL F1 x Swarna INTOL B1 x Swarna INTOL B2 … Result: Sub1A in Swarna genome

  29. Common in plant breeding Wild: resistant to fungus Cultivated: bred for yield, etc. http://www.anbg.gov.au/cpbr/program/sc/barl_mole.htm

  30. “Naturally genetically modified”

  31. Every linkage study faces this problem What is the causative variant linked to the marker?

  32. How to formulate a guess?

  33. How to formulate a guess? Here a very obvious hypothesis. Often not such a large gain or loss.

  34. Fine-mapping Fig. 11.17

  35. Fine-mapping: new markers Fig. 11.17

  36. Fine-mapping: new markers Between two humans, 1 polymorphism every 1000 bp; linkage study probably started with a tiny fraction of total.

  37. Fine-mapping: new markers Position of true causal variant A simulation of a qualitative trait in a large mouse cross; sparse marker set Best marker

  38. Fine-mapping: new markers Position of true causal variant Peak looks pretty close—why bother improving resolution? Best marker

  39. Fine-mapping: new markers Position of true causal variant Because you have to hunt through by hand to find the causal gene, and test experimentally. The smaller the region, the better. Best marker

  40. Fine-mapping: new markers Position of true causal variant Increased marker density

  41. Fine-mapping: new markers Position of true causal variant Why did the LOD score go up? More markers increases multiple testing, which boosts LODs in the region. Closer markers have more significant linkage, increasing their LODs. Peak is narrower, so LODs increase in the region. The LOD score scales with the number of markers, so actually it isn’t different if you normalize correctly.

  42. What do functional (e.g. disease-causing) variants look like?

  43. Rearrangements/large gain and loss

  44. Rearrangements/large gain and loss

  45. Coding variants Fig. 7.25

  46. Coding variants http://homepages.strath.ac.uk/~dfs99109/BB310/CFTRgene.jpg Fig. 2B

  47. Coding variants http://homepages.strath.ac.uk/~dfs99109/BB310/CFTRgene.jpg New amino acid Fig. 2B

  48. Coding variants http://homepages.strath.ac.uk/~dfs99109/BB310/CFTRgene.jpg Premature STOP Fig. 2B

  49. Coding variants http://homepages.strath.ac.uk/~dfs99109/BB310/CFTRgene.jpg Regulatory change, not coding! Fig. 2B

  50. Nucleotide repeat diseases http://graphics.jsonline.com/graphics/badger/img/may02/5martin506.jpg Fig. 11.13

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