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Lecture 14 - Complex Traits and QTL Maping

Lecture 14 - Complex Traits and QTL Maping. Doerge (2001) Nature Genetics Reviews 3:43-52 Neale, chapter 18 Liu, chapters 13-14. Figures from Lander and Schork , Science, 265-September 1994-pp2037. QTL Mapping. Mapping population Markers and a map Phenotypes (trait measurements)

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Lecture 14 - Complex Traits and QTL Maping

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  1. Lecture 14 - Complex Traits and QTL Maping • Doerge (2001) Nature Genetics Reviews 3:43-52 • Neale, chapter 18 • Liu, chapters 13-14

  2. Figures from Lander and Schork , Science, 265-September 1994-pp2037

  3. QTL Mapping • Mapping population • Markers and a map • Phenotypes (trait measurements) • QTL mapping software

  4. Distribution of Phenotypic Values • Continuous • Catagorical • Binary

  5. Small Rough Large Susceptible Resistant Pitch Canker Phenotypes Fusiform Rust Phenotypes

  6. QTL Mapping - Basic Approaches • Single-factor mapping • Interval mapping

  7. 4 4 12 12 A1 A2 A2 A1 X Q1 Q2 Q2 Q1 B1 B2 B2 B1 Genotypic value= 4 Genotypic value= 20 A1 A2 A2 A2 Q1 Q2 Q2 Q2 X Genotypic value= 4 Genotypic value= 12 B1 B2 B2 B2 A1 A1 A2 A2 A2 A2 A2 A2 Q1 Q1 Q2 Q2 Q2 Q2 Q2 Q2 B1 B2 B2 B2 B2 B2 B2 B1 Genotypic Value Q1= 10 Q2 =2 Q = additive A1-A2 = (12+12) -(4+4) = 16 B1-B2 = (12+4) -(12+4) = 0

  8. Single factor QTL mapping Edwards et al. 1987, Genetics, 113-125

  9. Advantages of Single Factor QTL Mapping • No map needed • Standard stat packages, SAS

  10. Disdvantages of Single Factor QTL Mapping • Map position not precisely determined • Biased estimates of a and d • Phenotypic effect overestimated • Multiple testing

  11. Interval Mapping Fig 21.1 from Falconer and Mackay. Pg 364Recombination frequencies between two marker loci, M and N, and a QTL, A A1 N1 M1 A2 N2 M2 c1 c2 c

  12. Table 21. 3. Falconer and Mackay

  13. Advantages of Interval QTL Mapping • More precise location of QTL • Better estimates of %PVE

  14. Disdvantages of Interval QTL Mapping • Computationally demanding • Custom software

  15. VERIFICATION VERIFICATION VERIFICATION UNRELATED DETECTION UNRELATED UNRELATED DETECTION DETECTION RELATED RELATED RELATED emfa ecwc ewsg lmfa vol% lcwc lwsg SCALE LG 2 0 cM Aco_1 0.0 10 cM PtNCS_CAD-08_b PtIFG_3012_43 12.7 LG 3 15.0 LG 1 PtIFG_2150_A 19.6 19.9 PtIFG_2885_B 20.1 PtIFG_2006_C 0.0 estPtIFG_1934_a 0.3 PtIFG_2819_12 PtIFG_2145_1 3.4 PtIFG_653_d estPtIFG_8569_a 29.5 PtIFG_2086_13 PtIFG_2538_B 30.2 PtIFG_2068_A 7.8 PtIFG_1626_c PtIFG_2897_d 10.4 PtIFG_975_3 12.2 PtIFG_2564_A 40.3 PtIFG_2697_A PtIFG_1A7_A 42.6 estPtIFG_8500_a 18.8 estPtIFG_9022_a 43.1 PtIFG_2536_1 46.5 PtIFG_138_B 24.1 PtIFG_1A7_D 46.8 PtIFG_2006_A estPtNCS_22C5_a 30.1 estPtINCS_20G2_a PtIFG_2588_1 32.5 estPtIFG_9053_a estPtNCS_C612F_a 33.8 estPtIFG_48_a 58.3 estPtIFG_8843_a estPaINRA_PAXY13_a 59.5 PtUME_Ps3_A estPtIFG_464_a 62.2 estPtIFG_8537_a PtIFG_1633_a 66.0 PtIFG_2718_3 44.8 estPtIFG_2253_a estPpINR_AS01G01_a PtIFG_48_1 78.4 PtIFG_2745_1 54.2 estPtIFG_1576_a estPtIFG_8939_a 83.4 PtIFG_1918_3 PtIFG_2253_A 57.4 PtIFG_3006_1 GlyHMT PtIFG_1918_h 59.5 83.8 86.1 86.3 estPtIFG_8612_a 64.2 PtIFG_2090_2 PtIFG_1623_A C4H-1 90.9 67.6 PtIFG_2782_31 69.4 estPtIFG_66_a 92.8 70.1 PtIFG_1636_3 94.6 PtIFG_1626_a PtIFG_1457_b 95.4 Pta14A9 estPtIFG_9198_a 78.2 estPtIFG_8496_a PtIFG_2986_A 102.7 PtIFG_1D11_A 104.0 PtIFG_2146_31 LAC PtIFG_2988_21 83.6 PtIFG_2718_1 86.8 estPtIFG_2889_a 95.7 PtIFG_1165_a 121.1 PtIFG_2889_21 98.9 PtIFG_2441_1 estPtIFG_8781_a 104.1 estPtIFG_107_a PtIFG_2145_76 107.4 PtIFG_2931_b PtIFG_2145_5 109.0 estPtNCS_6N3E_a PtIFG_2393_1 PtIFG_1D9_2 113.4 PtIFG_2931_A 113.6 SAMS-1 116.2 6Pgd_11 140.7 PtIFG_851_1 Brown et al. 2003 Genetics164:1537-46 154.6 estPpaINRA_AS01C10-1_a

  16. What can be learned from a QTL mapping experiment • Estimate of number of genes controlling complex trait • Location of genes in the genome • Estimates of a and d • Estimate of %PVE

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