Background, and why I am here

Insect resistance in Arabidopsis

Epistasis and growth rate

Insect resistance in the field

Approaches to drought tolerance in rice

Thomas Mitchell-OldsInstitute for Genome Sciences & PolicyDepartment of BiologyDuke University

tmo1@duke.edu

Advances in biotic and abiotic stress tolerance

University of Wisconsin: Ph.D. in Botany; Plant Breeding & Plant Genetics Postdoc in Human Genetics

Department of Genetics and Evolution

Max Planck Institute of Chemical Ecology

Duke University

Complex trait variation for

Insect resistance

Flowering time

Drought tolerance

NSF NIH

146

276

150

Undernourished population in millions

Why am I here?

1) Research to benefit human welfare

2) Rice is similar to Arabidopsis

3) Phenotypes in the field

Why are quantitative traits polymorphic?

LOD

sco

reInsect resistance

Position on Chromosome V

Correspondence of QTLs for insect resistance & glucosinolate levels

Position on Chromosome V

GlucosinolatesR

S-Glucose

NOSO3-

Insect Resistance in Arabidopsis

Myrosinase

Otherproducts

Thiocyanates(RSCN)

Nitriles(RCN + S)

Isothiocyanates(RNCS)

RS-H

NOSO3-

Insect resistance and chemical defense

RS-Glucose

NOSO3-

Arabidopsis glucosinolates:

From amino acid precursor

Influence insect resistance

Genetically variable

Evolve non-neutrally

Breakdown ofglucosinolates leads

to toxic products

Cloning QTL for insect resistance and glucosinolatesLO

D s

core

Insect resistance

Position on Chromosome V

Position on Chromosome V

Glucosinolates

Initial QTL mapping

Fine scale mapping of GS QTL

Positional cloning

Verification by transformation

QTL cloning is easier for secondary traits

(like GS) than for insect damage or

yield under drought

glucosinolate concentration

MAM2 gene controls

& resistance to generalist herbivores

but not specialist herbivores,

and does not impact growth rate

Kroymann et al. 2003 PNAS

Why are complex traits polymorphic?

Data come from cloned QTLs

Hence no information on small effect QTL

Growth rate QTL in Arabidopsis thaliana

Kroymann & Mitchell-Olds, Nature, 2005

Juergen Kroymann

Epistasis and growth rate

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position [kb]

Growth rate QTL in the MAM region

MAM2 genedoes not impact

growth rate

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position [kb]

Two Growth rate QTL in the MAM region

Right QTL: grLeft QTL: gl

-0.06

-0.03

00.03

0.06

Mas

s (L

er-C

ol)

[mg

]

-0.06

-0.03

00.03

0.06

Mas

s (L

er-C

ol)

[mg

]

-0.06

-0.03

00.03

0.06

Mas

s (L

er-C

ol)

[mg

]

Tightly linked QTL show opposite effects

Ler > ColCol > Ler

grLC:

grCL:

grLC:

grCL:

Crosses to identify the QTL on the right

at5g23140at5g23180

at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210

LJ47C LJ01C CJ10LCJ45L

CJ36LLJ52C

LJ30C CJ40L CJ26L LJ32C LJ35C

222 236230 234232224 228226218 220212 216214206 210208 [kb]

grLC: 1 2 3 4 5

6 7 8 9grCL:

at5g23140at5g23180

at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210

LJ47C LJ01C CJ10LCJ45L

CJ36LLJ52C

LJ30C CJ40L CJ26L LJ32C LJ35C

222 236230 234232224 228226218 220212 216214206 210208 [kb]222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 [kb]

grLC: 1 2 3 4 5

6 7 8 9grCL:

RecombinationBreakpoints

Right QTL: gr

Segregatingregion

Reciprocalflanking

backgrounds

At5g23140At5g23180

At5g23150 At5g23160 At5g23170 At5g23190 At5g23200 At5g23210

LJ47C LJ01C CJ10LCJ45L

CJ36LLJ52C

LJ30C CJ40L CJ26L LJ32C LJ35C

222 236230 234232224 228226218 220212 216214206 210208 [kb]

grLC1grLC2grLC3grLC4grLC5

grCL6grCL7grCL8grCL9

grCL(6-9)

a

b

c

At5g23140At5g23180

At5g23150 At5g23160 At5g23170 At5g23190 At5g23200 At5g23210At5g23150 At5g23160 At5g23170 At5g23190 At5g23200 At5g23210

LJ47C LJ01C CJ10LCJ45L

CJ36LLJ52C

LJ30C CJ40L CJ26L LJ32C LJ35C

222 236230 234232224 228226218 220212 216214206 210208 [kb]222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 [kb]

grLC1grLC2grLC3grLC4grLC5

grCL6grCL7grCL8grCL9

grCL(6-9)

a

b

c

RecombinationBreakpoints

N > 7000

Interval1 2 3 4 5 6 7 8 9

P value n.s. P<0.05 n.s. n.s. n.s. n.s. P<0.05 n.s. n.s.

Col 140 199

Ler 161 189

at5g23140at5g23180

at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210

LJ47C LJ01C CJ10LCJ45L

CJ36LLJ52C

LJ30C CJ40L CJ26L LJ32C LJ35C

222 236230 234232224 228226218 220212 216214206 210208 [kb]

grLC: 1 2 3 4 5

6 7 8 9grCL:

at5g23140at5g23180

at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210

LJ47C LJ01C CJ10LCJ45L

CJ36LLJ52C

LJ30C CJ40L CJ26L LJ32C LJ35C

222 236230 234232224 228226218 220212 216214206 210208 [kb]222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 [kb]

grLC: 1 2 3 4 5

6 7 8 9grCL:

Interval 7 is significant in both reciprocal crosses

at5g23140at5g23180

at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210

LJ47C LJ01C CJ10LCJ45L

CJ36LLJ52C

LJ30C CJ40L CJ26L LJ32C LJ35C

222 236230 234232224 228226218 220212 216214206 210208 [kb]

grLC: 1 2 3 4 5

6 7 8 9grCL:

at5g23140at5g23180

at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210

LJ47C LJ01C CJ10LCJ45L

CJ36LLJ52C

LJ30C CJ40L CJ26L LJ32C LJ35C

222 236230 234232224 228226218 220212 216214206 210208 [kb]222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 [kb]

grLC: 1 2 3 4 5

6 7 8 9grCL:

No QTLNo QTL

1 - synonymous SNP1 - intergenic SNP1 - intron indel of 1 bp Epistatic QTL

QTL

serine/threonine protein kinase

Interval1 2 3 4 5 6 7 8 9

P value n.s. P<0.05 n.s. n.s. n.s. n.s. P<0.05 n.s. n.s.

Col 140 199

Ler 161 189

at5g23140at5g23180

at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210

LJ47C LJ01C CJ10LCJ45L

CJ36LLJ52C

LJ30C CJ40L CJ26L LJ32C LJ35C

222 236230 234232224 228226218 220212 216214206 210208 [kb]

grLC: 1 2 3 4 5

6 7 8 9grCL:

at5g23140at5g23180

at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210at5g23150 at5g23160at5g23170 at5g23190at5g23200 at5g23210

LJ47C LJ01C CJ10LCJ45L

CJ36LLJ52C

LJ30C CJ40L CJ26L LJ32C LJ35C

222 236230 234232224 228226218 220212 216214206 210208 [kb]222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 222 236230 234232224 228226218 220212 216214206 210208 [kb]

grLC: 1 2 3 4 5

6 7 8 9grCL:

Allelic effect is reversed depending on genetic background

Epistatic growth rate QTL

Growth rate QTL within 170 kb

Two tightly linked growth rate QTL

Undetectable with standard QTL mapping

Too small

Opposing effects

Epistasis: QTL change sign depending on background

If typical, then:

Complex traits are massively polygenic

Epistasis is fundamental

Epistasis is fundamental for

drought tolerance(e.g., qtl12.1)

This will complicate association studies

Insect resistance in natural environments

Why are quantitative traits polymorphic?

Ecological model systems

Clone QTLs

Measure fitnessof allelesin natural populations

Genus Boechera (formerly Arabis)

Close relative of Arabidopsis

Genome ~ 250 Mb

Positional cloning

Transformation

Undisturbed natural populations

Diploid apomixis

0 20 40 60 80 100

Percent Leaf Damage

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req

ue

ncy

Resistance variation in Boechera stricta

Trichoplusia ni

Glucosinolate quantity in Boechera stricta

6 7 8 9 10 11 12 13

Log Total Glucosinolate

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Fre

qu

enc

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About 30% of variation is under genetic control

BCAA: branched chain amino acids: Val, Leu, Ile

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Proportion of GS from BCAA

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requ

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Glucosinolate type in Boechera stricta

Met-GS BC-GS

BCMA locus:Branched Chain

Methionine Allocation

T. ni: generalist herbivore BCMA controlsresistance togeneralist herbivore

Met allele is more resistant

40N

120W 110W

Montana

Colorado

40N

120W 110W

Montana

Colorado

Near Isogenic lines for BCMA:

2304 plants into original populations

Measure herbivore damage & fitness

Today: phenotypic selection

(Still scoring BCMA genotypes)

Fitness of alleles in their ancestral environments

MontanaColorado

CO MT0

5

10

15

Per

cen

t L

eaf

Dam

age

Susceptible BC allele

Resistant Met allele

High herbivore pressure

Lower herbivore pressure

N = 2,032 plants; 47,109 leaves

0 10 20 30 40 50 60Percent Leaf Damage

0.0

0.5

1.0

1.5

Via

bilit

y C

o mpo

n en t

of

Fi tn

ess

ANOVA: significantnatural selectionin the wild, P < 10-9

Colorado: Herbivory reduces survival

Montana: No natural selection on herbivore resistance

Su

rviv

al

993 plants in ColoradoSelection gradient:1% of leaf area removedreduces fitness by 1.1%

How does insect resistance influence

fitness?

How does insect resistance influence

fitness?

How do secondary traits influence yield

under drought?

CO MT0

5

10

15

Per

cen

t L

eaf

Dam

age

Susceptible BC allele

Resistant Met allele

High herbivore pressure

Lower herbivore pressure

Strong selection for resistance

No selection for resistance

BCMA summary

Positional cloning of BCMA

Influence of trait on fitness in field environment

Approaches to drought tolerance in rice

1) Yield in managed stress environments

2) Trait dissection into component traits

360 degrees using computer controlled motorized turntable

Benfey labDuke Univ

Nondestructive, automated analysis of root architecture

Indicas

Teqing

93-11

IR64Caipo

Jefferson

JaponicasBenfey Lab

Topology-based image analysis

High throughput phenotyping

enables cloning of QTLsBenfey Lab

Photo by J. Lamo & O. Michael

Approaches to drought tolerance in rice

1) Yield in managed stress environments

2) Trait dissection into component traits

3) Dissecting drought environments

Develop laboratory models of drought environments

Understand their effects on drought tolerance

Quantify axes of environmental variation

Ruiz Corral, et al. 2008, Crop Sci 48:1502

Environmental Conditions PC1

Env

ironm

enta

l Con

ditio

ns P

C2

Shapes indicategenetic groups

Different maize races are grown in different environments

Quantify axes of

environmental

variation

Hypothetical example: environmental dependence of drought tolerance

0 1 2 3 4 5 6 7Environment PC1

1

2

3

4

5

6

Env

iron m

ent

PC

2

Grow NILs in multiple environments

Plot nurseries based on environments

Measure yield advantage at each site

3D plot: yield advantage vs. environment

Hypothetical example: environmental dependence of drought tolerance

What aspects of the

environment control

the yield advantage?

Develop laboratory

models of drought

environments

Approaches to drought tolerance in rice

1) Yield in managed stress environments

2) Trait dissection into component traits

3) Dissecting drought environments

4) Integrated pedigrees for QTL & association analysis

- Cannot use association approach for traits that

differ between indica, japonica, or other groups

- Epistasis is a major problem for association studies

Bao-Hua SongKasavajhala PrasadAntonio ManzanedaCarrie Olson-Manning

Philip Benfey

Eric SchranzAaron WindsorJuergen Kroymann Maria ClaussKarl SchmidDan KliebensteinJonathan Gershenzon

NSF NIH Duke MPG

Kathy SpringerToyin Aremu-ColeMolly Mitchell-OldsSara Mitchell-OldsJanoo NaqviSlater HurstMichael CameronJ. LutkenhausLaura SaucierElizabeth BallwegCheng-Ruei Lee

Antje Figuth Susi Donnerhacke Kerstin WenigerSylke DietelMarion Kupper Sylke DietelGrit SchubertKatja SchwarzerNancy RichterD. SchnabelrauchTabea BirkKerstin Weniger