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)

• QTL mapping software

Distribution of Phenotypic Values

• Continuous• Catagorical• Binary

0

20

40

60

80

100

120

140

160

-13.6-9.6 -5.6-1.7 2.3 6.310.314.318.322.326.230.234.238.242.246.2More

PREDICTED LESION LENGTH

FREQUENCY

Pitch Canker Phenotypes

Fusiform Rust Phenotypes

Susceptible Resistant

Small Rough Large

0

10

20

30

40

50

60

70

80

-9.0 -6.6 -4.2 -1.8 0.6 3.0 5.4 7.8 10.2 12.6

PREDICTED GALL LENGTH

Frequency

QTL Mapping - Basic Approaches

• Single-factor mapping• Interval mapping

X

A1

Q1

B1

A1

Q1

B1

A2

Q2

B2

A2

Q2

B2Genotypic value= 20 Genotypic value= 4

A1

Q1

B1

A2

Q2

B2

A2

Q2

B2

A2

Q2

B2

X

A1

Q1

B1

A2

Q2

B2

A2

Q2

B2

A2

Q2

B2

A1

Q1

B2

A2

Q2

B2

A2

Q2

B1

A2

Q2

B2

Genotypic value= 12 Genotypic value= 4

12 412 4

A1-A2 = (12+12) -(4+4) = 16

B1-B2 = (12+4) -(12+4) = 0

Genotypic Value

Q1= 10

Q2 =2

Q = additive

Edwards et al. 1987, Genetics, 113-125

Single factor QTL mapping

Advantages of Single Factor QTL Mapping

• No map needed• Standard stat packages, SAS

Disdvantages of Single Factor QTL Mapping

• Map position not precisely determined

• Biased estimates of a and d• Phenotypic effect overestimated

• Multiple testing

Interval Mapping Fig 21.1 from Falconer and Mackay. Pg 364

Recombination frequencies between two marker loci, M and N, and a QTL, A

M1 N1A1

M2 N2A2

c2c1

c

Table 21. 3. Falconer and Mackay

Advantages of Interval QTL Mapping

• More precise location of QTL• Better estimates of %PVE

Disdvantages of Interval QTL Mapping

• Computationally demanding• Custom software

ewsglwsgvol%emfalmfaecwclcwc

DETECTION

VERIFICATION

RELATED

UNRELATED

Aco_10.0

PtIFG_3012_4312.715.0

PtIFG_2150_A19.619.9 PtIFG_2885_B20.1

estPtIFG_8569_a29.5PtIFG_2538_B30.2

PtIFG_2564_A40.3PtIFG_1A7_A42.6estPtIFG_9022_a43.1PtIFG_2536_146.5PtIFG_1A7_D46.8

estPtIFG_48_a58.3estPaINRA_PAXY13_a59.5estPtIFG_464_a62.2

PtIFG_1633_a66.0

PtIFG_48_178.4estPtIFG_8939_aPtIFG_3006_183.4

PtIFG_1918_h83.886.186.3

PtIFG_1623_A90.9

estPtIFG_66_a92.894.6

PtIFG_1626_a95.4

PtIFG_2986_A102.7PtIFG_1D11_A104.0

PtIFG_1165_a121.1

6Pgd_11140.7

estPpaINRA_AS01C10-1_a154.6

LG 2

PtIFG_2006_C0.0estPtIFG_1934_a0.3PtIFG_2145_13.4

PtIFG_2068_A7.8PtIFG_2897_d10.4PtIFG_975_312.2

estPtIFG_8500_a18.8

PtIFG_138_B24.1

estPtNCS_22C5_a30.1PtIFG_2588_132.5estPtNCS_C612F_a33.8

PtIFG_2718_344.8

PtIFG_2745_154.2PtIFG_1918_357.4

59.5

estPtIFG_8612_a64.2PtIFG_2090_267.6

69.4

PtIFG_1636_370.1

78.2

PtIFG_2988_2183.6

PtIFG_2718_186.8

estPtIFG_2889_a95.7

PtIFG_2889_2198.9

estPtIFG_8781_a104.1

PtIFG_2145_76107.4PtIFG_2145_5109.0

113.4 PtIFG_1D9_2113.6116.2

LG 3

C4H-1

Pta14A9

SAMS-1

DETECTION

VERIFICATION

RELATED

UNRELATED

DETECTION

VERIFICATION

RELATED

UNRELATED

PtIFG_2819_12PtIFG_653_dPtIFG_2086_13PtIFG_1626_c

PtIFG_2697_A

PtIFG_2006_A

estPtINCS_20G2_aestPtIFG_9053_aestPtIFG_8843_aPtUME_Ps3_A

estPtIFG_8537_a

estPtIFG_2253_aestPpINR_AS01G01_aestPtIFG_1576_aPtIFG_2253_A

PtIFG_2782_31

PtIFG_1457_b

estPtIFG_9198_aestPtIFG_8496_a

PtIFG_2146_31

PtIFG_2441_1estPtIFG_107_aPtIFG_2931_bestPtNCS_6N3E_aPtIFG_2393_1PtIFG_2931_A

PtIFG_851_1

LG 1

LAC

GlyHMT

PtNCS_CAD-08_b

SCALE

0 cM

10 cM

Brown et al. 2003 Genetics164:1537-46

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