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The 7th Workshop on QTL Mapping and Breeding Simulation, 20-21 Jan., Mexico

Breeding Simulation: Breeding Simulation: Tools, Principles, and Applications

Jiankang WangCIMMYT Chi d CAASCIMMYT China and CAAS

E-mail: [email protected] or [email protected]

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Outline of the presentationOutline of the presentationAvailable simulation toolsAvailable simulation toolsPrinciples of breeding simulationsStrategic applications

Comparison of two breeding strategies (wheat)Modeling of Single Backcrossing Breeding (wheat)

Tactical applicationsppMAS strategies for pyramiding multiple genes (wheat) Design-led breeding based on known gene information (rice) g g g ( )

2

Breeding methods with self-pollinated cropsg p p

Allard, R.W. 1960. Principles of plant breeding. John p p gWiley & Sons, Inc.

Stoskopf, N.C. 1993. Plant Breeding — Theory and p g yPractice. Westview Press.

Mass and pure-line selectionMass and pure-line selectionThe pedigree systemThe bulk population methodThe bulk population methodThe backcross breeding methodSingle seed descent (SSD), a special case of pedigree systemg ( ) p p g yRecurrent selection breeding methodMutation breeding

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Haploid breeding system (doubled haploid)

Breeding methods in CIMMYT’sBreeding methods in CIMMYT s wheat breeding programwheat breeding program

Pedigree system: before 1984. g y“Pedigree selection” is used from F2 to F6.

Modified pedigree/bulk (MODPED): in 1985-Modified pedigree/bulk (MODPED): in 1985-1989/94.

“Pedigree selection” is used in F2 and F6 and “bulkPedigree selection is used in F2 and F6, and bulk selection” is used in other generations.

Selected bulk (SELBLK): after 1995Selected bulk (SELBLK): after 1995. “Pedigree selection” is used only in F6, and “bulk

l ti ” i d i th ti4

selection” is used in other generations.

Toluca (1000 crosses made from 200 parents) A x B

Cd. Obregon (Each selected F1 harvested in bulk) F1About 20% of the crosses are Toluca (30-80 plants harvested individually for MODPED) F2

(30-80 plants harvested in bulk for SELBLK)

Cd. Obregon (Bulk of 10 spikes for MODPED) F3(B lk f 30 ik f SELBLK)

crosses are discarded or used make backcrosses / top crosses (Bulk of 30 spikes for SELBLK)

Toluca (Bulk of 10 spikes for MODPED) F4(Bulk of 30 spikes for SELBLK)

top crosses About 1 to 3% of crosses will derive lines that can be used

Cd. Obregon (Bulk of 10 spikes for MODPED) F5(Bulk of 30 spikes for SELBLK)

Toluca (10 plants harvested individually for MODPED) F6

as cultivars

Toluca (10 plants harvested individually for MODPED) F6(40 plants harvested individually for SELBLK)

Cd. Obregon (Bulk of whole plot) F7About 40% of crosses retained

Toluca and El Batan (Bulk of whole plot) F8 field tests

Cd. Obregon (Bulk of whole plot) F8 yield trial F8 small plot evaluation

(Reserve seed )crosses retained after F7

About 20% of Toluca and El Batan (Bulk of whole plot) F9 field tests


(Reserve seed )About 20% of crosses retained after two rounds

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Toluca and El Batan (Bulk of whole plot) F10 stripe rust screening F10 leaf rust screening

International screening nursery and yield trial

of yield trials

Why do we need tools in breeding?y gTo improve the efficiency of traditional phenotypic p y p ypselection through exploring various optionsTo better use the large amount of gene informationTo better use the large amount of gene information available from To build a bridge between the biological data andTo build a bridge between the biological data and breeders’ requirements To combine all these sources of data into “knowledge” that breeders can use in their breeding programsTo avoid the simplified assumptions made in classical quantitative genetic theory

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q g y

Questions that can be studied by simulationQuestions that can be studied by simulation1 Comparison of breeding efficiencies from different1. Comparison of breeding efficiencies from different

selection strategies and their modifications. Which breeding method should be adopted?breeding method should be adopted?

2. Balance between the number of crosses and population size of segregating generations What shallpopulation size of segregating generations. What shall the breeder do if the available resources increase or reduce?reduce?

3. Evaluation of marker-assisted selection (MAS). When d h h ld MAS b d?and how should MAS be used?

4. Comparative value of single, top, back, and double crosses in breeding?

Questions that can be studied by simulation

5 The correlation bet een parents and their offspring

Questions that can be studied by simulation

5. The correlation between parents and their offspring. Can F1 or F2 hybrids predict the performance of their advanced lines? For early generation selection howadvanced lines? For early generation selection, how early is too early?

6 When to use DH (doubled haploid)?6. When to use DH (doubled haploid)?Early generation: many individuals need to be testedAdvanced line stage: lines will be good for other g gtraits, but the desired genotype may be lost during selection due to population size, trait associations

d i d ifand genetic drift

A il bl b di i l ti t lAvailable breeding simulation tools

QuLine, a computer software that simulates breeding programs for developing inbred linesbreeding programs for developing inbred linesQuHybrid, a computer software that simulates breeding programs for developing hybridsQuMARS a computer software that simulatesQuMARS, a computer software that simulates marker-assisted recurrent selection and

id l tigenome-wide selection

QuLine: A simulation tool for genetics and breeding

Q G (Q G )QU-GENE (QUantitative GENEtics)A simulation platform for quantitative analysis of genetic models, developed by The University of Queensland AustraliaThe University of Queensland, Australia

QuCim (funded by GRDC 2000-2004)A QU-GENE application breeding simulation module, specifically designed for Q pp g , p y gCIMMYT’s wheat breeding programsSimulate most breeding programs for developing inbred linesV i 1 1 l d J l 2003 (W k h i B i b A t li )Version 1.1 released on July, 2003 (Workshop in Brisbane, Australia)More than 100 global requests for QuCim 1.1

Renamed as QuLine10

Renamed as QuLineVersion 2.0 available from http://www.uq.edu.au/lcafs/qugene/

What can QuLine do?at ca Qu e doComparison of genetic gains from different selection methodsselection methods

Change in population meanChange in gene frequencyChange in gene frequencyChange in Hamming distance (distance of a selected genotype to the target genotype)

C i f fComparison of cross performanceSelection historyRogers’ genetic distanceRogers genetic distanceNumber of lines retained from each cross

Comparison of cost efficiencyComparison of cost efficiencyNumber of familiesIndividual plants per generation

11Validation of theories

In geneticsg(implemented by the QU-GENE engine)

Most genetic phenomena, if not all, can be defined in the QU-GENE engine input file (QUG). Among them are:

Multiple alleles (e.g. Glutenin genes in wheat)Multiple alleles (e.g. Glutenin genes in wheat)Linkage (between gene and marker, between genes, between markers)between markers)Additive, dominance and epistasisPleiotropy (one gene effects multiple traits)Genotype by environment interaction

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yp yMolecular markers (dominant, or co-dominant)

In breeding

M t if t ll b di th d f lf

g(implemented by the QuLine module)

Most, if not all, breeding methods for self-pollinated crops, can be defined and then i l t d i Q Lisimulated in QuLine.

Among them are:gPedigree system (including SSD)Bulk-populationBulk populationDoubled haploidMarker-assisted selection (include marker-basedMarker-assisted selection (include marker-based selection)Recurrent selection within one population

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Recurrent selection within one populationMany modifications and combinations

How does QuLine work?How does QuLine work?Two input files are neededTwo input files are needed

QUG file containing the necessary information for a genotype and environment (GE) system and initialgenotype and environment (GE) system and initial population(s) of genotypes. It is the input for the QU-GENE engine Two kinds of output files will beGENE engine. Two kinds of output files will be generated from the engine.

GES fil f d fi i GE t ( i t f Q Li )• GES file for defining a GE system (= input for QuLine)• POP file for defining the initial population (= input for QuLine)

QMP file containing the necessary information for the breeding strategies to be simulated (e.g. pedigree,

14bulk, SSD, DH, etc.) (= input for QuLine)

POP file from the engine or

the previous breeding cycle

Propagation of CB

* * * * * *

General procedure *****

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Propagation of CB General procedure for crossing and selection in F1

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Making crosses selection in F1

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Among-family selection * ** * * *

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Within-family selection * * * ** * * *

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Generation advance

15Popbulk(:) for bulk

Propagation process

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General procedure for propagation

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Among-family selectionand selection in F2 and onwards

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Within-family selection

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* *

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*

Generation advance

16Popbulk(:) for bulk Popbulk(:) for pedigree

Define the QMP file for the selected bulk selection method:selected bulk selection method:

an examplean exampleDefine the breeding method in a way

that the computer can understand

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General simulation parametersGeneral simulation parametersNumber of runs: any integerNumber of runs: any integerNumber of breeding cycles: any integerNumber of crosses in F1 generation: any integerI di t f i bl k d t 0 1Indicator for crossing block update, 0 or 1.

0: All individuals after a breeding cycle are used as the parents for the next cycle;1: The best individuals in the final selected population and the initial crossing block are selected as the parents for next cycle

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p y

General simulation parametersGeneral simulation parametersIndicator for outputting GE system details, 0 for no output, p g y , p ,and 1 for outputIndicator for outputting population details 0 for no outputIndicator for outputting population details, 0 for no output, and 1 for outputIndicator for outputting selection history 0 for no outputIndicator for outputting selection history, 0 for no output, and 1 for outputI di t f t tti R di t f hIndicator for outputting Rogers distance for each cross and the lines retained from each cross, 0 for no output,

d 1 f t tand 1 for outputIndicator for outputting correlation coefficient, 0 for no

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output, and 1 for output

The number of models in the GE system and ythe number of runs for breeding strategy

Four nested loops in QuLineLoop for all modelsLoop for all models

All random effects in the GE system will be assigned valuesDetermine the parents for all crosses for the first cycle

• Loop for all runsLoop for all strategiesLoop for all strategies»Loop for all cycles

All strategies start from the same point (same crossing block and same crosses), so that they

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g ) ycan be properly compared.

Parameters to describe aParameters to describe a set of breeding strategies

Number of strategiesFor each strategy

Strategy name: any characterStrategy name: any characterNumber of generations in the strategy: any integer

th 0more than 0Definition for each generation

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Definition of a generationDefinition of a generationNumber of selection rounds in the generation: anyNumber of selection rounds in the generation: any integer more than 1Seed source indicator

0: Seed for selection round i (i > 1) come from round 10 Seed o se ect o ou d ( ) co e o ou d1: Seed for selection round i (i > 1) come from round i-1

D fi iti f h l ti dDefinition of each selection round

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An example for seed source indicator 0Practical breeding

F6 field test at Toluca

Virtual breeding

F6

Families selected

452 → 408 → 14,7606 e d test at o uca 6 5 08 , 60

F7 field test at Cd. Obregon

F7 Round 1 for F7

14,760 → 3,868

F8 field test at Toluca and El Batan

F8 (T), F8 (B) Rounds 2 and 3

3 868 2 163 1 974

F8 yield trial and F8 F8 (YT)

3,868 → 2,163 → 1,974

Round 4small plot evaluation at

Cd. ObregonF8 small plot

1,974 → 779

779

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F8 small plot 779

An example (LRC, Toowoomba, Australia)f

Pedigree in F2 Families selected

for seed source indicator 1Pedigree in F2 Families selected

Bulk in F3 Round 1 for F3

4000 → 1200

PYEI, F4

4000 → 1200

Round 2

1200 → 600

Round 3

PYEII, F5

P di i F4

600 → 100

100 100024

Pedigree in F4 100 → 1000

Definition of each selection roundTitle for the generationSeed propagation type (within a family)

clone asexual reproductionclone, asexual reproductionDH, doubled haploidself, self-pollinationbackcross, backcrossed to one parent, ptopcross, crossed with a third parent (three-way cross)doublecross crossed with another F1doublecross, crossed with another F1random, random mating

25noself, random mating but self-pollination is eliminated

Definition of each selection roundGeneration advance method (or harvest method): management of the selected individual plants in amanagement of the selected individual plants in a family

pedigree: the selected plants in each family are harvested individually, resulting a few families in the a ested d dua y, esu t g a e a es t enext generationbulk: the selected plants in each family are harvestedbulk: the selected plants in each family are harvested in bulk, resulting one family in the next generation

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Definition of each selection roundField experiment design

Number of replications for each familyNumber of replications for each familyNumber of plants in each replication

fNumber of test locationsEnvironment type for each test location

• defined in the GE system• if 0, randomly determined based on environment y

frequency

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Definition of each selection ro ndDefinition of each selection round

Among family and within family selectionNumber of traits used for selectionDefinition of each trait

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Definition of each trait used in selectionDefinition of each trait used in selectionTrait number, which trait. 0 is used for marker scoreSelection mode

T for top, e.g. yield, tillering, grains per spike and 1000-kernel weightB for bottom e g lodging and rustsB for bottom, e.g. lodging and rustsM for middle, e.g. height and headingR for random, for some special studiesTV for top valueBV for bottom valueTN for a number of individuals with top phenotypic valuesTN for a number of individuals with top phenotypic valuesBN for a number of individuals with bottom phenotypic valuesRN for a number of individuals to be selected randomly

Selected proportion or value: the proportion or value of individual plants in a family (for within family selection) or of families (for among family selection) to be selected

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among family selection) to be selected

A l f ti d fi itiAn example of generation definitionRounds

of selection

Seed source

indicator

Generation title

Seed propagation

type

Generation advance method

Replications

Plot size

Test locations

Environment type

1 0 F6 self pedigree 1 750 1 2, Toluca

4 0 F7 self bulk 1 70 1 1 Obregon4 0 F7 self bulk 1 70 1 1, Obregon

F8(T) self bulk 1 70 1 2, Toluca

F8(B) self bulk 1 70 1 3, El Batan

F8(YT) self bulk 1 100 1 1, Obregon

1 0 F8(SP) self bulk 1 30 1 1 Obregon

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1 0 F8(SP) self bulk 1 30 1 1, Obregon

Traits, their selection modes and selected proportions/values/numbers

Trait Yield Lodg-ing

Stem rust

Leaf rust

Stripe rust Height Tillering Heading

Grains per

spike

1000 kernel weight

Total

S l tiSelection mode T B B B B M T M T T

F6, among 0.99 0.96 0.95 0.90, g

F6, within 0.90 0.70 0.90 0.95 0.98 0.10 0.05

F7 among 0 85 0 70 0 98 0 85 0 96 0 70 0 75 0 25F7, among 0.85 0.70 0.98 0.85 0.96 0.70 0.75 0.25

F8(T), among 0.55 0.70 0.99 0.98 0.99 0.90 0.55

F8(B), among 0.90 0.90

F8(YT), among 0.40 0.40

31F8(SP), among 1.00

Steps to run QuLineInput information about the GxE system and populations

QUGENE

Breeding strategies GE system PopulationBreeding strategies GE system Population

QuLineQuLine

Major outputs from QuLine

* fit * var* fre * ham* cro * his * rog* pou* fix

Major outputs from QuLine

.fit .var.fre .ham.cro .his .rog.pou.fixCrosses after

selectionGenetic advance

Genes fixed

Gene frequency

Selection history

Hamming distance

Population details

Cross details

Variance components

Test cross implemented in QuHybridp yFamily PopBefore(1) PopBefore(2) PopBefore(3) … TestersFamily size 5 3 6 … 3

F11 F12 F13 F14 F15 F21 F22 F23 F31 F32 F33 F34 F35 F36 … T1 T2 T3…

Making testcrosses

Testcross 1 F11×T1 F12×T1 F13×T1 F14×T1 F15×T1 F21×T1 F22×T1 F23×T1 F31×T1 F32×T1 F33×T1 F34×T1 F35×T1 F36×T1



Among family selection




Within family selection

F21×T1 F22×T1 F23×T1 F31×T1 F32×T1 F33×T1 F34×T1 F35×T1 F36×T1



Population after selection, this population will be used as the starting for the next generation

Family PopAfter(1) PopAfter(2) PopAfter(3)Family size 0 2 4

F22 F23 F31 F33 F34 F36

Seed propagation type in QuHybridSeed propagation type in QuHybridclone, asexual reproductionDH, doubled haploidself, self-pollinationself, self pollinationbackcross, backcrossed to one parenttopcross crossed with a third parent (three way cross)topcross, crossed with a third parent (three-way cross)doublecross, crossed with another F1random, random matingnoself, random mating but self-pollination is eliminatedose , a do at g but se po at o s e atedtestcross, crossed with a tester population

A tester population can consist of one inbred line or several

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A tester population can consist of one inbred line, or several inbred lines, or can be a random mated population etc.

Th fl h tP1 × P2

Stage I: Testcrossing: Starting from a single cross, To generate the initialpopulation for recurrent selection; To build the prediction equation of breedingtraits on markers

The flowchart of QuMARS

F1

200 F2 individuals

200 F2:3 families Genotyping each family using bulk DNA of 10 individualsof QuMARS 200 F2:3 families Genotyping each family using bulk DNA of 10 individuals10-20 individuals each family Testcrossing between each F2:3 family and the tester

200 testcross families Phenotyping each testcross family

Selecting using MARS or GWS

30 selected F2:3 families based on testcross performance

Stage II: Recurrent selection: To intermate the selected families (S0); To grow andgenotype randomly mated progenies; To select individuals based on MARS or GWS

Cycle 0 Intermating of the 30 selected F2:3 families

Cycle 1 300 individuals Genotyping each individual


30 selected individuals Intermating of the 30 selected findividuals

Cycle n 300 individuals Genotyping each individual


30 selected individuals End of the recurrent selection

Repeated self-pollination to derive inbred lines

Stage III: Inbred development: To generate inbred lines through pedigree breeding

Repeated self-pollination to derive inbred lines

Inbred lines Note: QuMARS stops here

Repeated testcrossing evaluation to derive hybrids

Hybrids

Before we go for applications, I want to ask…What is the ideal population in breeding ?

0 6

0.8 A. Different means, same variance

0 6

0.8 B. Same mean, different variances

0.4

0.6

bability

0.4

0.6

bability

0.0

0.2

Prob

0.0

0.2

Prob

5 6 7 8 9 10 11 12 13 14 15

Trait value

5 6 7 8 9 10 11 12 13 14 15

Trait value

An ideal population should have high mean and large variation.variation. It is easy to say, but not easy to make such populations 36

Application 1:Application 1: Comparison of two breeding strategies: p g g

modified pedigree (MODPED) and l t d b lk (SELBLK)selected bulk (SELBLK)

Crop Science, 2003, 43: 1764-1773Crop Science, 2004, 44: 2006-2018

37

Breeding methods in CIMMYT’sBreeding methods in CIMMYT s wheat breeding programwheat breeding program

Pedigree system: before 1984. g y“Pedigree selection” is used from F2 to F6.

Modified pedigree/bulk (MODPED): in 1985-Modified pedigree/bulk (MODPED): in 1985-1989/94.

“Pedigree selection” is used in F2 and F6 and “bulkPedigree selection is used in F2 and F6, and bulk selection” is used in other generations.

Selected bulk (SELBLK): after 1995Selected bulk (SELBLK): after 1995. “Pedigree selection” is used only in F6, and “bulk

l ti ” i d i th ti38

selection” is used in other generations.

Germplasm flow f i l

Toluca (1000 crosses made from 200 parents) A x B

Cd. Obregon (Each selected F1 harvested in bulk) F1

for simple crosses made in Toluca and

Toluca (30-80 plants harvested individually for MODPED) F2 (30-80 plants harvested in bulk for SELBLK)

Cd. Obregon (Bulk of 10 spikes for MODPED) F3(B lk f 30 ik f SELBLK)Toluca and

targeted to ME1

MODPED:

(Bulk of 30 spikes for SELBLK)

Toluca (Bulk of 10 spikes for MODPED) F4(Bulk of 30 spikes for SELBLK)

MODPED: modified pedigree/bulk

Cd. Obregon (Bulk of 10 spikes for MODPED) F5(Bulk of 30 spikes for SELBLK)

Toluca (10 plants harvested individually for MODPED) F6p g

SELBLK: selected bulk

Toluca (10 plants harvested individually for MODPED) F6(40 plants harvested individually for SELBLK)

Cd. Obregon (Bulk of whole plot) F7selected bulk methods



(Reserve seed )



(Reserve seed )

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Toluca and El Batan (Bulk of whole plot) F10 stripe rust screening F10 leaf rust screening

International screening nursery and yield trial

Trait, segregating gene number, gene effects and trait heritability

Gene effect h 2Trait Genes Gene effect

type AA Aa aa Trait range hb2

(Indiv. plant)

Yield 20, 40 E0, E1, E2 Random value from UD (0, 1) 0.05, , , ( , )

Lodging 3 additive 0 5 10 0-30 0.10

Stem rust 5 additive 0 0.5 1 0-5 0.30Stem rust 5 additive 0 0.5 1 0 5 0.30

Leaf rust 5 additive 0 5 10 0-50 0.30

Yellow rust 5 additive 0 5 10 0 50 0 30Yellow rust 5 additive 0 5 10 0-50 0.30

Height 3 additive 40 30 20 120-60 0.45

Till / l t 3 dditi 5 3 1 15 3 0 35Tillers/plant 3 additive 5 3 1 15-3 0.35

Heading 5 additive 20 16 12 100-60 0.30

40

Grains/spike 5 additive 14 10 6 70-30 0.35Seed weight 5 additive 12 8.5 5 60-25 0.35

Trait correlation and pleiotropyTrait correlation and pleiotropyTrait Yield Lodging Stem

rustLeaf rust

Yellow rust Height Tillers/

plant Heading Grains/spike

Seed weightrust rust rust plant spike weight

Yield -0.50 -0.20 -0.10 -0.10 -0.50 0.40 0.30 0.50 0.40

Lodging -0 56Lodging -0.56

Stem rust -0.25 Estimated by CIMMYT breedersLeaf rust -0.05

Yellow rust -0.09

CIMMYT breeders

Height -0.62

Tillers/plant -0.08 -0.20 -0.40Estimated from the d fi d ti d l

Heading 0.60

Grains/spike 0.09 -0.17 -0 30

defined genetic model

41

Grains/spike 0.09 0.17 0.30

Seed weight -0.07 -0.30 -0.07

Experimental designExperimental design12 Genotype and environment (GE) systems12 Genotype and environment (GE) systems

Two yield gene numbers: 20 and 40, two alleles for each genePleiotropy (same gene effects various traits): absent and presentPleiotropy (same gene effects various traits): absent and presentEpistasis (multiple gene interaction): no epistasis, digenic-epistasis and tri-genic epistasisepistasis, and tri-genic epistasisLinkage: no linkage (independent gene segregation)

Initial populationInitial population200 parents, gene (allele) frequencies of 0.5 for all genes

1000 d1000 crosses were made258 lines were selected after 10 generations of selection

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Result 1: Genetic gain in yield from SELBLK is 3.3% higher than MODPED SELBLK is slightly more efficienthigher than MODPED. SELBLK is slightly more efficient.

57

55

56

type SELBLK

54

55

geno

t

MODPED

53

arge

t

51

52

% o

f t

50

51%

43Initial Final selected

Population

For gains per spike and 1000-kernel weight, SELBLK has a faster genetic gain For tillers/plant MODPED has a faster genetic gaingenetic gain. For tillers/plant, MODPED has a faster genetic gain.

35

SELBLK MODPED25

30

(%)

SELBLK MODPED

15

20

ic g

ain

(

10

15

Gen

eti

0

5

Yield

rs/pla

ntRN/SPK

TKWing to

l.SR re

s.LR re

s.YR re

s.Heig

htea

ding

44Tillers

GRN

Lodgin SR LR Y H Hea

Traits

Result 2: SELBLK retained 25% more crosses in the final selected population (more genetic diversity retained)selected population (more genetic diversity retained)

700

500

600

osse

s SELBLKMODPED

300

400

r of c

ro MODPED

200

300

umbe

r

0

100N

F1 F2 F3 F4 F5 F6 F7F8

(T)

F8(B

)F8

(YT)

F8(S

P)F9

(T)

F9(B

)F9

(YT)

F9(S

P)10

(YR

)10

(LR

)

45

F F F F F1 F1

Generation

Result 3: SELBLK required 1/3 less land from F1 to F8 than MODPED SELBLK is more cost effectiveF8 than MODPED. SELBLK is more cost-effective.

2500000an

ts

2000000

ual p

la

SELBLK1500000

divi

du MODPED

1000000

r of i

nd

0

500000

umbe

r

0

F1 F2 F3 F4 F5 F6 F7F8

(T)

F8(B

)F8

(YT)

8(SP

)F9

(T)

F9(B

)F9

(YT)

9(SP

)0(

YR)

0(LR

)Nu

46

F F8 F F9 F1 F1

Generations

Result 4: SELBLK produced 40% less families (plots) to be planted from F1 to F8 (less labor required)to be planted from F1 to F8 (less labor required)

32000

24000

mili

es SELBLKMODPED

16000of fa

m MODPED

8000umbe

r

0

Nu

0

F1 F2 F3 F4 F5 F6 F7F8

(T)

F8(B

)F8

(YT)

F8(S

P)F9

(T)

F9(B

)F9

(YT)

F9(S

P)10

(YR

)10

(LR

)

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F F F F F1 F1

Generation

Application 2: Modeling of the Single BackcrossingModeling of the Single Backcrossing

Breeding Strategy (SBBS)Breeding Strategy (SBBS)

Theor. Appl. Genet., 2009, 118: 683-694

Estimated percentages of favourable alleles or gene combinations in different parental lines in wheat

breeding at CIMMYTCategory % favorable

genesExample % total

parental lines

g

Elite adapted lines (EAL) 80-85 Major released cultivars in targeted mega-environments (MEs) either developed by CIMMYT or by partners

10

Adapted lines (AL) 75 80 Elite advanced lines from CIMMYT’s 60Adapted lines (AL) 75-80 Elite advanced lines from CIMMYT s International Nursery and Yield Trials

60

Intermediate adapted lines (IAL)

65-75 Advanced lines from CIMMYT’s Yield Trials in Ciudad Obregón and Toluca, Mexico

10

Un-adapted (or non-adapted) lines (UAL)

20-40 Land races 2

Second generation of re 40 60 Deri ed lines bet een the first generation of 10Second generation of re-synthesized wheat (SYNII)

40-60 Derived lines between the first generation of re-synthesized wheat derivatives and adapted lines

10

First generation of re- 20-40 Derived lines between primary re- 5First generation of resynthesized wheat (SYNI)

20 40 Derived lines between primary resynthesized wheat and adapted lines

5

Primary re-synthesized wheat (SYN0)

0-30 Inter-specific crosses between Triticumdurum and Aegilops tauschii

3

Two traits defined in QU-GENETwo traits defined in QU-GENEAdaptation

200 genes on the 21 wheat chromosomesLowest adaptation with no favorable alleles: 0Highest adaptation with all favorable alleles: 100Heritability: 0.5 y

Donor traits (DT) to be transferred10 genes governing the donor traits10 genes governing the donor traitsLowest DT with no favorable alleles: 0Highest DT with all favorable alleles: 10Highest DT with all favorable alleles: 10Heritability: 0.5

“All models are wrong but some are useful!“All models are wrong, but some are useful!

Adapted parental groupsAdapted parental groups in simulationin simulation

Gene frequency of favorable adaptation alleles fixed at 0.8q y p

A0: the frequency of favorable DT alleles is 0A2: the frequency of favorable DT alleles is 0.2A4: the frequency of favorable DT alleles is 0 4A4: the frequency of favorable DT alleles is 0.4A6: the frequency of favorable DT alleles is 0.6A8: the frequency of favorable DT alleles is 0.8

Donor parental groups o o pa e ta g oupsin simulation

Gene frequency of favorable DT alleles fixed at 1.0

D0: the frequency of favorable adaptation alleles is 0D1: the frequency of favorable adaptation alleles is 0 1D1: the frequency of favorable adaptation alleles is 0.1D2: the frequency of favorable adaptation alleles is 0.2D3: the frequency of favorable adaptation alleles is 0 3D3: the frequency of favorable adaptation alleles is 0.3D4: the frequency of favorable adaptation alleles is 0.4D5: the frequency of favorable adaptation alleles is 0 5D5: the frequency of favorable adaptation alleles is 0.5D6: the frequency of favorable adaptation alleles is 0.6D7: the frequency of favorable adaptation alleles is 0 7D7: the frequency of favorable adaptation alleles is 0.7

Crosses made between different parental groups for wheat breeding

t CIMMYTat CIMMYTCategory Percentage Similarity to defined parentalCategory Percentage

of total crosses

Similarity to defined parental groups

(EAL+AL) × (EAL+AL) 65 (A0+A2+A4+A6+A8) ×D7(EAL+AL) × IAL 10 (A0+A2+A4+A6+A8) ×D5+D6)(EAL+AL) × UAL 5 (A0+A2+A4+A6+A8)

×(D2+D3+D4)(EAL AL) × SYNII 10 (A0 A2 A4 A6 A8) ×(D6 D7)(EAL+AL) × SYNII 10 (A0+A2+A4+A6+A8) ×(D6+D7)(EAL+AL) × SYNI 7 (A0+A2+A4+A6+A8) ×(D4+D5)(EAL+AL) × SYN0 3 (A0+A2+A4+A6+A8)(EAL+AL) × SYN0 3 (A0+A2+A4+A6+A8)

×(D0+D1+D2)

The single backcrossing breedingThe single backcrossing breeding strategy (SBBS)

Generation Seed propagation method

No. crosses or families grown

Individuals per cross or family

No. selected crosses or

No. selected individuals in each cross orgrown or family crosses or

familieseach cross or family

F1 Hand pollination between adapted

100 20 100 20between adapted and donor lines

B1F1 Backcrossing to the adapted parents

100 400 100 50adapted parents

B1F2 Selfing 100 1200 100 30

B1F3 Selfing 100 400 100 10

B1F4 Selfing 100 400 100 10

B1F5 Selfing 100 400 100 10

B1F6 Selfing 1000 200 30 200

Final selected advanced lined 10

Four crossing strategiesFour crossing strategies defined in QuLine

No backcross

One time of backcross

Two times of backcross

Three times of backcross

Generation advance methodbackcross backcross backcross backcross

B0 B1 B2 B3F F F F BulkF1 F1 F1 F1 BulkF2 BC1F1 BC1F1 BC1F1 BulkF3 BC1F2 BC2F1 BC2F1 BulkF4 BC1F3 BC2F2 BC3F1 BulkF5 BC1F4 BC2F3 BC3F2 BulkF6 BC1F5 BC2F4 BC3F3 Pedigree6 1 5 2 4 3 3 gF7 BC1F6 BC2F5 BC3F4 Bulk

Six selection schemesSix selection schemes• AD: Adaptation is selected first, followed by the

selection for DTselection for DT• DA: DT is selected first, followed by the selection for

Adaptation• ADA: Adaptation is selected first, followed by the

selection for DT, and adaptation is selected again• DAD: DT is selected first, followed by the selection forDAD: DT is selected first, followed by the selection for

Adaptation, and DT is selected again• ADAD: Adaptation and DT are selected two times in• ADAD: Adaptation and DT are selected two times in

each generation, and adaptation is selected firstDADA: Adaptation and DT are selected two times in• DADA: Adaptation and DT are selected two times in each generation, and DT is selected first

Genetic advance of selection scheme AD

A

8590

on

B0 B1 B2 B3

6065707580

hest ada

ptatio

B

505560

D0D1D2D3D4D5D6D7 D0D1D2D3D4D5D6D7 D0D1D2D3D4D5D6D7 D0D1D2D3D4D5D6D7 D0D1D2D3D4D5D6D7

% hig

60708090

100

st don

or trait

20304050

% highe

s

Donor and adapted parental groups

D0D1D2D3D4D5D6D7 D0D1D2D3D4D5D6D7 D0D1D2D3D4D5D6D7 D0D1D2D3D4D5D6D7 D0D1D2D3D4D5D6D7

A0 A2 A4 A6 A8

C l iConclusions• We recommend the use of SBBS based on three

assumptions:assumptions:– multiple genes governing the phenotypic traits to be

transferred from donor parents to adapted parentstransferred from donor parents to adapted parents– donor parents still have some favorable genes that

may contribute to the improvement of adaptation inmay contribute to the improvement of adaptation in the recipient parents even under low adaptation

– the conventional phenotypic selection is applied or thethe conventional phenotypic selection is applied or the individual genotypes cannot be precisely indentified

Application 3: Efficient selection of multiple

genes/QTL via marker-assistedgenes/QTL via marker-assisted selection, an example in wheat

Crop Science, 2007, 47: 580-588. Theor Appl Genet 2009 119: 65 74Theor. Appl. Genet., 2009, 119: 65-74.

59

Ni j t b id d i h tNine major genes to be pyramided in wheatGene Rht B1 Rht D1 Rht8 Sr2 Cre1 VPM Glu B1 Glu A3 tinGene Rht-B1 Rht-D1 Rht8 Sr2 Cre1 VPM Glu-B1 Glu-A3 tin

Chr. 4BS 4DS 2DL 3BS 2BL 7DL 1BL 1AS 1AS

Marker Codom Codom Codom Codom Dom Dom Codom Codom Codom

MK-gene distance

0 0 0.6 1.1 0 0 0 0 0.8

HM14BS Rht B1a Rht D1a Rht8 sr2 cre1 vpm Glu B1a Glu A3e TinHM14BS Rht-B1a Rht-D1a Rht8 sr2 cre1 vpm Glu-B1a Glu-A3e Tin

Sunstate Rht-B1a Rht-D1b rht8 Sr2 cre1 VPM Glu-B1i Glu-A3b Tin

Silverstar+ Rht-B1b Rht-D1a rht8 sr2 Cre1 vpm Glu-B1i Glu-A3c tintin

p

Target Rht-B1a Rht-D1a Rht8 Sr2 Cre1 VPM Glu-B1i Glu-A3b tin

One strategy identified by QuLineOne strategy identified by QuLineto combine the nine genes from topcross

Selection of Sunstate as the final parent (having largest number of favorable alleles) in the topcrosslargest number of favorable alleles) in the topcross

Stage I: Selection for Rht-B1a and Glu-B1i homozygotes, and enrichment of rht8, Cre1, and tin in TCF1Stage II: Selection of homozygotes for one target allele, g yg g ,e.g. Rht8, and enrich remaining target alleles in TCF2Stage III: Selection of the target genotype in DHs/RILsStage III: Selection of the target genotype in DHs/RILs

Comparison with other strategiesComparison with other strategiesFor this strategy one target genotype can beFor this strategy, one target genotype can be selected by screening < 600 individuals/lines

For one-stage selection in advanced generations,For one stage selection in advanced generations, one target genotype can be selected be screening > 3500 linesscreening > 3500 linesFor one-stage selection in early generations, say TCF2, one target genotype can be selected be screening millions of individualsscreening millions of individuals

Phenotypic selection for coleoptile length (h2

entry-mean = 0.80)

From Dr. David Bonnett, CIMMYT

CL (coleoptile length) is a typical quantitative trait 159 DH lines derived from two Australian wheat cultivars Cranbrookand Halbert (provided by Greg Rebetzke, CSIRO, Canberra, Australia) using Inclusive Composite Interval Mapping (ICIM)

10 QTL mapping of coleoptile length (mm) in wheat

468

LOD score

02

1A 1A 1A 1B 1B 1D 1D 1D 2A 2A 2B 2B 2B 2D 2D 2D 2D 2D 3A 3A 3A 3B 3B 3B 3B 3D 3D 4A 4A 4A 4A 4B 4B 5A 5A 5A 5A 5B 5B 5B 5B 5D 5D 5D 5D 6A 6A 6A 6B 6D 6D 6D 7A 7A 7A 7B 7B 7B 7B 7D 7D 7D 7D

L

1D i f dditi QTL l th h t1D‐scanning for additive QTL along the wheat genome

46

mm)

‐202

1A 1A 1A 1B 1B 1D 1D 1D 2A 2A 2B 2B 2B 2D 2D 2D 2D 2D 3A 3A 3A 3B 3B 3B 3B 3D 3D 4A 4A 4A 4A 4B 4B 5A 5A 5A 5A 5B 5B 5B 5B 5D 5D 5D 5D 6A 6A 6A 6B 6D 6D 6D 7A 7A 7A 7B 7B 7B 7B 7D 7D 7D 7Dve effect (m

64‐8‐6‐4

Add

iti

1D‐scanning for additive QTL along the wheat genome

Six major genes in two parental linesSix major genes in two parental lines

Gene Rht-D1 Rht8 Sr2 VPM Glu-B1 Glu-A3Chr. 4DS 2DL 3BS 7DL 1BL 1AS

Marker Codom Codom Codom Dom Codom Codom

MK-gene 0 0.6 1.1 0 0 0MK gene distance

0 0.6 1.1 0 0 0

HM14BS Rht-D1a Rht8 sr2 vpm Glu-B1a Glu-A3eS t t Rht D1b ht8 S 2 VPM Gl B1i Gl A3bSunstate Rht-D1b rht8 Sr2 VPM Glu-B1i Glu-A3b

Additive genetic effects of CL genes, genotypes of HM14BS, Sunstate and the genotype with the longest CL

Locus Chrom Distance to the nearest marker

Additive effect (mm)

Additive variance

HM14BS Sunstate Genotype with all increased CLnearest marker

(cM)(mm) variance

explained (%)increased CL alleles

Rht-D1 4DS 0.0 9.5 42.63 Rht-D1a Rht-D1b Rht-D1aqCL1 1AS 8.1 2.9 3.97 + - +

C SqCL2 2BS 0.7 2.5 2.95 + - +qCL3 2DS 1.1 4.1 7.94 + - +qCL4 3BS 0.9 2.0 1.89 + - +qCL5 5AL 6.2 4.9 11.34 + - +q 11.34qCL6 5DS 13.0 3.6 6.12 + - +qCL7 Unidentified 4.0 7.56 - + +qCL8 Unidentified 3.0 4.25 + - +qCL9 Unidentified 3 0 4 25 + +qCL9 Unidentified 3.0 4.25 - + +qCL10 Unidentified 2.0 1.89 + - +qCL11 Unidentified 2.0 1.89 + - +qCL12 Unidentified 2.0 1.89 - + +qCL13 Unidentified 1.0 0.47 + - +qCL14 Unidentified 1.0 0.47 + - +qCL15 Unidentified 1.0 0.47 + - +qCL16 Unidentified 1 0 0 47 + - +

66

qCL16 Unidentified 1.0 0.47 + +qCL17 Unidentified 1.0 0.47 - + +

Coleoptile length (mm) 158 97 178

Breeding target …Breeding target …For the six major genesGene Rht-D1 Rht8 Sr2 VPM Glu-B1 Glu-A3

For the six major genes

Target Rht-D1a Rht8 Sr2 VPM Glu-B1i Glu-A3b

F l il l h (CL) CL 130 hi h iFor coleoptile length (CL), CL > 130 mm, which is 30% longer than Sunstate’sg

Target: to select as many as possible inbred lines bi i th i d i d ll l d h i CLcombining the six desired alleles and having CL >

130 mm, so as to have chances to select for other

67traits, i.e., yield and adaptation.

V lid ti th ti d lValidating the genetic model

45

50 A. Observation45

50 B. Simulation

30

35

40

y (%

)

Sunstate F5 lines HM14BS

30

35

40

y (%

)

Sunstate F5 lines HM14BS

15

20

25

Frqu

ency

15

20

25

Frqu

ency

0

5

10

0

5

10

80 90 100 110 120 130 140 150 160 170 180 190

Coleoptile length (mm)

80 90 100 110 120 130 140 150 160 170 180 190

Coleoptile length (mm)

68

Do we need backcrossing?g70

80 A. Distribution of inbred linescombining the six major genes 70

80 B. Distribution of inbred lineswith CL > 130 mm

30

40

50

60

eque

ncy (%

)

F1

P1BC130

40

50

60

eque

ncy (%

)

F1 P1BC1 P2BC1

0

10

20

30

Fre P2BC1

0

10

20

30

Fre

0 5 10 15 20 25 30 35 40 45 50 55Number of inbred lines combining

the six major genes Number of inbred lines CL > 130 mm

30 C. Distribution of inbred lines combining

15

20

25

ency (%

)

the six major genes and CL > 130 mm

F1

P1BC1

P2BC1

5

10

15

Freq

ue P2BC1

69

0

0 1 2 3 4 5 6 7 8 9 1011121314151617181920Number of inbred lines combining

the six major genes and CL > 130 mm

Comparison of various MAS strategiesComparison of various MAS strategies in selecting the six major genes (1000 F2 individuals and 200 RILs)

50

60 A. Distribution of selected F2 individuals

Hom0Het6 20

25 B. Distribution of target lines

Hom0Het6

30

40

uenc

y (%

)

Hom1Het5

Hom2Het4 15

20

uenc

y (%

)

Hom1Het5

Hom2Het4

20

30

Freq Hom3Het3

5

10Freq Hom3Het3

0

10

0 10 20 30 40 50 60 70 80 90 00 10 20 30 40 50 60 70 80 90 00 10

0

5

0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80

70

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Number of F2 individuals after selection1 1 2 2 2 3 3 4 4 4 5 5 6 6 6 7 7 8

Number of target inbred lines

Comparison of MAS and phenotypic p p ypselection (PS) for coleoptile length

7

8 MAS (mean: 23.9)

PS (mean: 25.1)

5

6

(%)

MAS+PS (mean: 25.1)

Th h

3

4

quen

cy ( The chance or

number game of l t b di

1

2

3

Fre plant breeding

0

1

0 2 4 6 8 0 2 4 6 8 0 2 4 6 8 0 2 4 6 8 0 2 4 6 8 071

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50

Number of target inbred line

ConclusionsConclusionsAn average of 2.4 individuals with the target genotype were present i l t d F d i d d bl d h l id (DH) bi tin unselected F1-derived doubled haploid (DH) or recombinant inbred line (RIL) populations of size 200.A selection scheme for the six major genes in F2 increased theA selection scheme for the six major genes in F2 increased the number of target individuals to 19.1, and additional marker-assisted selection (MAS) for CL increased the number to 23.9. ( )Phenotypic selection (PS) of CL outperformed MAS in this study due to the high heritability of CL, incompletely linked markers for known QTL d th i t f id tifi d QTLQTL, and the existence of unidentified QTL. However, a selection scheme combining MAS and PS was equally as efficient as PS (25 1 target genotypes selected) and would resultas efficient as PS (25.1 target genotypes selected) and would result in net savings in production and time to delivery of long coleoptilewheats containing the six favorable alleles.

72

Application 4:Application 4: Design-led breeding based on g gknown gene information, an

l i iexample in rice

Genetical Research 2006 88: 93-104Genetical Research, 2006, 88: 93 104 Theor. Appl. Genet., 2007, 115: 87-100

73

Steps in the design-led breedingp g gTo generate genetic populations, to identify genes / gene interactions, to identify allele distribution in parental lines

Linkage mapping, association mapping To determine the target genotype based on theTo determine the target genotype based on the breeding objectives

Need simulation tools to assistNeed simulation tools to assist To identify the suitable breeding strategy (including

i d l ti ) i t f il blcrossing and selecting), i.e. a route from available genetic materials to the target genotype

Need simulation tools to assist 74

A CSSL population consisting of 65 non-idealized lines

ParentsBackground (recurrent): japonica rice variety AsominoriDonor: indica rice variety IR24For details, see Tsunematsu et al. 1996; Kubo et al. 2002; Wan et al. 2004

82 RFLP markers8 a e sTwo selected quality traits

A f h lk d (ACE)Area of chalky endosperm (ACE) Amylose content (AC)

8 environments (4 locations × 2 years)75

Genotyping of the CSSL populationyp g p pChromosome 1 Chromosome 2 Chromosome 3 Chromosome 4 Chromosome 5 Chromosome 6 Chromosome 7 Chromosome 8 Chromosome 9 Chromosome 10 Chromosome 11 Chromosome 12

Marker 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82Asominori -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1CSSL1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1CSSL2 -1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 -1 -1 -1 -1 -1 -1CSSL3 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1CSSL4 -1 1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 1 -1 -1 -1 -1 -1 -1 -1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 -1 -1 -1CSSL5 -1 -1 -1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 -1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1CSSL6 -1 -1 -1 -1 -1 -1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 -1 -1CSSL7 -1 -1 -1 -1 -1 -1 1 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-1 -1 -1 -1 -1 -1 -1 -1CSSL55 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1CSSL56 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1CSSL56 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1CSSL57 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1CSSL58 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1CSSL59 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1CSSL60 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 -1 -1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 -1 -1 -1 -1 1 1 -1 -1 -1 -1CSSL61 -1 -1 -1 -1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 1 1 -1 -1 -1 -1 -1 -1CSSL62 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 1 1 -1 -1 -1 -1 -1 -1CSSL63 -1 -1 -1 -1 -1 -1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 -1 -1 -1 -1 -1 -1CSSL64 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 -1 -1 -1CSSL65 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 -1 1 1 1

Chromosome segments showing

Chromosome 1 2 3 3 5 5 7 7 7 8 8 8 9 10 12 12

QTL for ACEChromosome 1 2 3 3 5 5 7 7 7 8 8 8 9 10 12 12Segment M4 M18 M21 M23 M35 M39 M49 M50 M51 M54 M56 M57 M59 M69 M77 M79LOD E1 0.00 0.26 0.01 0.00 1.87 0.00 0.12 0.03 0.03 0.01 0.02 6.06 0.47 0.01 0.17 0.61

E2 0.00 1.05 2.88 4.66 0.95 0.14 0.35 0.30 0.11 0.13 5.84 3.92 2.89 0.22 0.12 0.05E3 2 06 4 03 0 00 0 20 0 84 2 60 0 05 9 61 4 64 0 04 0 04 3 98 3 36 4 35 0 89 2 17E3 2.06 4.03 0.00 0.20 0.84 2.60 0.05 9.61 4.64 0.04 0.04 3.98 3.36 4.35 0.89 2.17E4 0.04 0.04 0.00 4.03 0.05 0.32 0.04 0.02 0.49 0.70 0.05 15.89 6.26 2.57 0.10 0.24E5 0.35 0.66 0.41 3.13 0.40 0.00 4.09 12.51 16.53 2.04 3.18 5.56 9.04 0.31 0.42 0.15E6 0.13 0.38 1.06 1.35 0.30 0.22 0.32 0.02 0.18 0.00 0.16 1.84 4.15 0.90 0.29 0.05E7 0.08 5.07 0.22 0.21 0.04 0.26 1.47 0.33 0.07 0.03 5.52 6.33 4.07 1.66 4.04 0.01E8 0 01 0 00 0 02 0 45 2 16 1 54 0 01 0 02 0 01 0 67 0 17 16 89 10 01 0 01 0 00 0 00E8 0.01 0.00 0.02 0.45 2.16 1.54 0.01 0.02 0.01 0.67 0.17 16.89 10.01 0.01 0.00 0.00

ADD E1 -0.11 -0.72 -0.12 -0.08 -2.13 0.06 -0.36 -0.19 0.25 -0.13 0.17 4.13 1.27 0.08 -0.35 -1.99E2 -0.07 2.21 -2.98 4.35 -2.11 0.78 -0.88 -0.89 -0.72 0.54 4.43 4.51 4.62 -0.72 -0.43 -0.78E3 3.89 4.69 0.11 -0.84 -2.03 -3.66 0.32 -6.12 5.11 -0.32 0.35 4.62 5.16 3.57 -1.21 5.68E4 0 24 0 23 0 04 2 05 0 25 0 61 0 16 0 12 0 76 0 67 0 18 5 84 3 71 1 32 0 20 0 91E4 -0.24 -0.23 -0.04 2.05 -0.25 -0.61 -0.16 0.12 0.76 -0.67 -0.18 5.84 3.71 1.32 -0.20 -0.91E5 1.06 1.22 -0.75 2.42 -0.94 0.07 2.30 -5.19 8.28 -1.59 2.20 3.86 6.40 0.60 -0.55 0.98E6 -1.22 1.73 -2.29 2.88 -1.53 -1.30 -1.11 -0.30 -1.14 0.13 0.86 3.79 7.38 -1.87 -0.85 1.04E7 -0.52 3.74 -0.56 0.61 -0.31 -0.78 -1.37 -0.69 -0.41 -0.19 3.11 4.29 4.01 1.44 -1.91 -0.21E8 -0.09 0.05 -0.11 0.63 -1.63 -1.31 -0.09 -0.12 0.09 -0.62 -0.33 5.94 4.95 -0.09 0.03 0.090.09 0.05 0.11 0.63 1.63 1.31 0.09 0.12 0.09 0.62 0.33 5.94 4.95 0.09 0.03 0.09

PVE E1 0.01 0.48 0.02 0.01 4.15 0.00 0.23 0.06 0.06 0.03 0.04 15.60 1.00 0.01 0.34 1.24E2 0.00 2.24 6.60 11.44 2.04 0.28 0.69 0.59 0.24 0.26 14.54 9.36 6.66 0.46 0.25 0.10E3 3.61 7.76 0.01 0.33 1.45 4.73 0.07 21.28 9.19 0.07 0.07 7.54 6.35 8.53 1.53 3.91E4 0.04 0.05 0.00 5.62 0.06 0.38 0.05 0.03 0.59 0.86 0.05 34.66 9.49 3.35 0.11 0.29E5 0 35 0 68 0 41 3 51 0 41 0 00 4 61 19 86 31 26 2 18 3 57 6 79 12 65 0 31 0 41 0 15

77

E5 0.35 0.68 0.41 3.51 0.41 0.00 4.61 19.86 31.26 2.18 3.57 6.79 12.65 0.31 0.41 0.15E6 0.46 1.37 3.88 4.99 1.07 0.78 1.07 0.07 0.60 0.02 0.55 6.60 16.93 3.06 0.98 0.17E7 0.11 8.28 0.29 0.29 0.06 0.36 2.13 0.46 0.10 0.04 9.25 10.89 6.44 2.33 6.37 0.01E8 0.01 0.00 0.02 0.52 2.66 1.70 0.02 0.02 0.01 0.73 0.17 35.08 16.53 0.01 0.00 0.00

Chromosome segments showing QTL for AC

Chromosome 1 1 1 1 2 3 3 6 8 9 9 10 10 11 12Chromosome 1 1 1 1 2 3 3 6 8 9 9 10 10 11 12Segment M3 M4 M6 M9 M14 M19 M23 M41 M57 M59 M60 M63 M64 M73 M79LOD E1 0.00 2.63 0.05 2.23 4.89 0.07 0.22 1.50 6.30 4.91 2.16 0.02 4.06 0.19 0.26

E2 0.94 3.73 0.00 0.12 0.22 0.10 3.68 2.20 12.59 5.32 0.02 0.10 0.00 0.74 0.01E3 3.98 0.67 2.43 0.03 1.65 1.47 0.23 0.21 8.95 4.44 5.43 0.05 0.04 0.00 0.48E3 3.98 0.67 2.43 0.03 1.65 1.47 0.23 0.21 8.95 4.44 5.43 0.05 0.04 0.00 0.48E4 0.47 2.65 0.18 0.17 0.17 0.00 0.02 0.03 7.70 1.28 1.33 3.57 0.54 2.08 0.85E5 0.94 0.33 0.01 1.00 2.13 0.36 0.21 0.20 4.48 3.44 0.38 0.00 0.02 0.02 3.63E6 3.08 0.67 0.01 4.19 1.78 3.10 0.00 0.06 6.60 0.13 0.23 0.03 0.23 0.52 1.59E7 0.53 0.10 0.05 0.01 2.22 0.01 3.09 0.01 4.94 5.14 2.65 0.03 0.04 0.00 0.02E8 0 04 0 25 1 08 0 23 2 60 0 03 0 01 0 05 7 25 4 65 4 34 1 49 0 06 0 11 0 00E8 0.04 0.25 1.08 0.23 2.60 0.03 0.01 0.05 7.25 4.65 4.34 1.49 0.06 0.11 0.00

ADD E1 0.00 0.80 -0.10 -0.60 -0.93 -0.17 0.16 -0.49 1.09 1.13 0.52 -0.05 0.84 0.21 0.33E2 0.33 0.85 -0.02 0.12 -0.16 0.18 0.61 -0.52 1.52 1.04 0.05 0.11 -0.02 -0.36 -0.05E3 0.62 0.29 0.57 0.05 -0.38 -0.61 0.12 -0.13 1.02 0.80 0.65 -0.06 -0.06 -0.01 0.35E4 0.25 0.76 0.19 -0.15 -0.15 0.01 0.04 -0.06 1.18 0.52 0.38 0.74 0.27 0.67 -0.58E4 0.25 0.76 0.19 0.15 0.15 0.01 0.04 0.06 1.18 0.52 0.38 0.74 0.27 0.67 0.58E5 0.32 0.23 0.04 -0.33 -0.50 -0.34 0.13 -0.15 0.75 0.79 0.18 -0.02 -0.04 0.06 1.14E6 0.74 0.39 -0.04 -0.87 -0.55 -1.25 -0.01 0.09 1.15 0.18 0.17 -0.07 -0.19 0.35 0.88E7 0.27 0.14 0.10 0.04 -0.57 0.06 0.60 -0.04 0.90 1.12 0.56 0.07 -0.08 -0.03 0.09E8 -0.07 -0.22 0.47 -0.17 -0.61 0.10 0.02 -0.08 1.12 1.03 0.71 0.45 -0.09 0.15 0.00

PVE E1 0.00 5.60 0.09 4.68 11.31 0.14 0.44 3.08 15.42 11.34 4.54 0.04 9.16 0.38 0.50E2 1.53 6.69 0.00 0.19 0.34 0.16 6.61 3.74 31.54 10.01 0.04 0.16 0.00 1.21 0.01E3 6.35 0.95 3.60 0.04 2.42 2.12 0.33 0.29 17.22 7.14 9.01 0.06 0.06 0.00 0.68E4 1.16 7.16 0.45 0.42 0.41 0.00 0.04 0.07 25.12 3.30 3.38 9.90 1.35 5.47 2.10E5 1 74 0 60 0 02 1 81 4 10 0 66 0 38 0 36 9 39 6 96 0 67 0 01 0 03 0 03 7 42

78

E5 1.74 0.60 0.02 1.81 4.10 0.66 0.38 0.36 9.39 6.96 0.67 0.01 0.03 0.03 7.42E6 6.27 1.20 0.01 8.74 3.45 6.23 0.00 0.10 15.32 0.24 0.42 0.05 0.42 0.96 3.08E7 1.36 0.25 0.12 0.03 6.14 0.02 8.87 0.04 15.25 16.02 7.58 0.08 0.11 0.01 0.06E8 0.07 0.42 1.89 0.38 4.82 0.04 0.01 0.08 15.99 9.25 8.59 2.60 0.10 0.18 0.00

Average additive effects on ACE and gAC of eight chromosome segments

Marker M4 M14 M23 M35 M56 M57 M59 M60 Observation PredictionEffect on ACE 1.50 -1.37 1.33 4.62 4.69 ACE

(%)AC(%)

ACE(%)

AC(%)Effect on AC 0.41 -0.48 1.09 0.83 0.40

Asominori 0 0 0 0 0 0 0 0 4.76 15.12 6.05 15.58DG1 2 0 0 2 0 0 0 2 3.32 17.19DG2 2 0 0 2 0 2 0 2 12 56 19 37DG2 2 0 0 2 0 2 0 2 12.56 19.37DG3 2 0 0 2 0 0 2 2 12.69 18.85DG4 2 0 0 2 0 2 2 2 21.94 21.03CSSL4 2 0 0 0 0 0 0 0 7.32 16.47 6.05 16.40CSSL28 0 0 0 2 0 0 0 0 2.11 15.21 3.32 15.58CSSL49 0 0 0 0 2 2 0 2 19.30 17.76 17.95 18.5619.30 17.76 17.95 18.56CSSL52 0 0 0 0 0 0 2 0 15.70 17.19 15.42 17.24

Linkage: 23.9 cM between M56 and M57 on chr. 8

Diagram of the crossing and selection f tprocess of a top cross

Parent 1 × Parent 2

F1 × Parent 3

200 TCF1

individualsindividuals

1000 DH 800 DH 200 TCF21000 DHlines

800 DHlines

200 TCF2

individuals

600 DHlines

Scheme 1 Scheme 2 Scheme 3Selection among

DH linesSelection in TCF1 and

among DH linesSelection in TCF1,TCF2,

and among DH lines

Comparison of crossing strategies usingComparison of crossing strategies using percentage of the designed genotype

Top cross (TC) DG1 DG2

TC1 (CSSL4 CSSL28) CSSL49 1 272 (0 196) 0 298 (0 064)TC1: (CSSL4 × CSSL28) × CSSL49 1.272 (0.196) 0.298 (0.064)

TC2: (CSSL4 × CSSL49) × CSSL28 2.066 (0.307) 0.269 (0.089)

TC3: (CSSL28 × CSSL49) × CSSL4 2.084 (0.313) 0.267 (0.084)

Double cross (DC) DG3 DG4

DC1: (CSSL4 × CSSL28) × (CSSL49 × CSSL52) 0.207 (0.097) 0.027 (0.025)( ) ( )

DC2: (CSSL4 × CSSL49) × (CSSL28 × CSSL52) 0.145 (0.057) 0.019 (0.017)

DC3: (CSSL4 × CSSL52) × (CSSL28 × CSSL49) 0.144 (0.058) 0.019 (0.017)

Comparison of selection strategies usingComparison of selection strategies using number of the designed genotypeg g yp

Designed genotype

Selection scheme

TC1: (CSSL4 ×CSSL28) ×

TC2: (CSSL4 ×CSSL49) ×

TC3: (CSSL28 ×CSSL49) × CSSL4genotype scheme CSSL28) ×

CSSL49CSSL49) ×CSSL28

CSSL49) × CSSL4

DG1 Scheme 1 12.72 (3.86) 20.77 (5.30) 20.71 (5.31)( ) ( ) ( )

Scheme 2 40.48 (6.17) 66.40 (8.84) 66.48 (8.79)

S h 3 100 41 (14 61) 141 75 (17 63) 141 95 (17 63)Scheme 3 100.41 (14.61) 141.75 (17.63) 141.95 (17.63)

DG2 Scheme 1 2.95 (1.73) 2.70 (1.80) 2.69 (1.77)

Scheme 2 9.50 (3.05) 17.21 (5.24) 17.24 (5.26)

Scheme 3 43.63 (10.44) 62.47 (14.86) 62.33 (14.74)

82

( ) ( ) ( )

Frequency distribution of the number of DG1 from 1000 simulations (Breeding is science, art and chance!)

A. TC1: CSSL4/CSSL28//CSSL4950

20

30

40

requ

ency

(%)

Scheme 1 Scheme 2 Scheme 3

0

10F

B. TC2: CSSL4/CSSL49//CSSL2850

20

30

40

Freq

uenc

y (%

)

0

10F

C. TC3: CSSL28/CSSL49//CSSL450

10

20

30

40

Freq

uenc

y (%

)

0

10

0 2 6 10 14 18 22 26 30 34 38 42 46 50 54 58 62 66 70 74 78 82 86 90 94 98 102

106

110

114

118

122

126

130

134

138

142

146

150

154

158

162

166

170

174

178

182

186

190

Number of target genotypes selected

Thanks to people contributing to Development of simulation tools

Maarten van Ginkel, CIMMYT and ICRISATGuoyou Ye, UQ and IRRIIan DeLacy, Mark Dieters, UQScott Chapman, CSIROScott Chapman, CSIRODean Podlich, Mark Cooper, UQ and Pioneer …

Application of simulation tools CIMMYT’s wheat breeders / scientists : Maarten van Ginkel, Richard Trethowan, Wolfgang Pfeiffer, Ravi Singh, Hans Braun, Sanjaya Rajaram, David Bonnett … CIMMYT’s maize breeders / scientists: Gary Atlin Kevin Pixley Jill Cairns JoseCIMMYT s maize breeders / scientists: Gary Atlin, Kevin Pixley, Jill Cairns, Jose Luis Araus, Jose Crossa, Jianbing Yan … Guoyou Ye, Parminder Virk, IRRIHoward Eagles, Adelaide University Scott Chapman, Greg Rebetzke, CSIROCAAS Scientists: Jianmin Wan Xianchun XiaCAAS Scientists: Jianmin Wan, Xianchun Xia …

The Quantitative Genetics Group, CAAS and CIMMYT

AcknowledgementsAcknowledgementsGrain Research and Development Corporation (GRDC), Australia (1999 – 2004) The Generation Challenge Program (GCP) of CGIAR (2005 – 2014)HarvestPlus Challenge Program of CGIAR (2006 –g g (2014) National 973 Programs of China for Key BasicNational 973 Programs of China for Key Basic Scientific Research (2006 – 2010)National 863 Programs of China for HighNational 863 Programs of China for High Technological Research (2006 – 2010) N t l S i F d ti f Chi (2008 2010)Natural Science Foundation of China (2008 – 2010)

Thank you and have fun withThank you, and have fun with Breeding Simulation!g

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