Poblaciones para mejora vegetal y análisis genético

Poblaciones para mejora vegetal y análisis genético

Antonio J. MonforteIBMCP (UPV-CSIC)

[email protected]

Almería, 28 de Enero de 2019

…more productive plants making healthier food with less

resources

200 employees

42 Staff Researchers

144 Pre- and Post-doctoral researchers

2 main Public Spanish Research Institutions together

with 1 common objective…

Mechanisms of stress response

Development and hormone action

Molecular virology

Breeding and biotechnology

years of Plant Research 25

General Research Lines

Instituto de Biología Molecular y Celular de Plantas

EXCELLENT

BASIC and

TRANSLATIONAL

RESEARCH

54 PhD thesis (5 years)

136 total publications in 2017

(half in top D1 journals)

12 national and international patents

SUCCESS IN

RAISING PUBLIC

FUNDING (active in 2018)

8 EU projects (3 coordinated)

26 National MICINN grants

6 Regional GVA

projects

7 Young research projects

FRUITFUL

PUBLIC-PRIVATE

PARTNERSHIP

Trusted by >25 industrial partners

13 industry-led grants

Studying the secret life of plants

ADVANCED

RESEARCH

SERVICES

Metabolomics, Genomics,

Proteomics, DNA sequencing,

Microscopy and Bioinformatics

QUALITY in EDUCATION

and

ENGAGEMENT with

SOCIETY

PhD program in Graduate School UPV

Quality awarded MsC in Plant Biotech

>250/Y visits from secondary schools

LEADING EDGE

SCIENTIFIC

FACILITIES

7000 m2 labs and core services

4150 m2 greenhouses and

growth chambers

Unveiling the molecules that feed the world

Poblaciones para mejora y análisis genético

From left to right:

• Carlos Romero. Reproductive barriers in Cucumis and Prunus

• Mariemm Himdi, Chaymaa Riahi. Master Students

• Cecilia Martínez Postdoc. . Cloning melon fruit shape QTL

• Soledad Casal. Technician

• Clara Pons. Genomic and metabolomisc characterization of tomato traditional varieties (TRADITOM)

• Maria José Gonzalo. Heat tolerance in tomato (TOMGEN)

• Antonio J. Monforte. PI

Selected publications• Diaz A, Fergany M, Formisano G,..et al . 2011. A consensus linkage map for molecular markers and

Quantitative Trait Loci associated with economically important traits in melon (Cucumis melo L.). BMC Plant Biology 11.

• Diaz A, Martin-Hernandez AM, Dolcet-Sanjuan R, Garces-Claver A, et al. 2017. Quantitative traitloci analysis of melon (Cucumis melo L.) domestication-related traits. Theoretical and AppliedGenetics 130, 1837-1856.

• Monforte AJ, Diaz A, Cano-Delgado A, van der Knaap E. 2014. The genetic basis of fruit morphologyin horticultural crops: lessons from tomato and melon. Journal of Experimental Botany 65, 4625.

• Rambla JL, Medina A, Fernandez-del-Carmen A, Barrantes W, Grandillo S, et al. 2017. Identification, introgression, and validation of fruit volatile QTLs from a red-fruited wild tomato species. Journal of Experimental Botany 68, 429-442.

• Rios P, Argyris J, Vegas J, Leida C, Kenigswald M, Tzuri G, et al 2017. ETHQV6.3 is involved in melonclimacteric fruit ripening and is encoded by a NAC domain transcription factor. Plant Journal 91, 671-683.

• Sato et al 2012 2012. The tomato genome sequence provides insights into fleshy fruit evolution. Nature 485, 635-641.

• Tieman D, Zhu GT, Resende MFR, Lin T, Taylor M, Zhang B, Ikeda H, et al.. 2017. A chemical geneticroadmap to improved tomato flavor. Science 355, 391-394.

• Wu S, Zhang B, Keyhaninejad N, Rodríguez GR, Kim HJ, Chakrabarti M, et al. (2018) A commongenetic mechanism underlies morphological diversity in fruits and other plant organs. NatureCommunications 9:4734


Problems in plant breeding

• Disease resistance. (Virus, bacteria, fungus, insects). Monogenic control in some cases

• Abiotic stress. Drought, salt, cold. Complex, multigenic.

• Quality

– Increase agronomic yield

– Higher quality products.


Breeding process

Problem

Genetic

VaribilityCultivar

AssemblySelection

Breeding

Population


Masal Selection

Acquaah 2012


General considerations

• New variability is not generated

• Maintain the purity of a cultivar

• Rapid, simple, inexpensive

• Based on plant phenotype. High h2 to be

effective


Pure-line selection



• Once fixed, no selection can be done within lines

• It is rapid, inexpensive.

• Selection Based on progeny performance.

Effective for low h2 traits

• New variability is really not generated,

improvement is limited to the isolation of the most

desirable genotype from a mixed population

• Promotes genetic erosion


Pedigree selection



• New variability is created

• The final cultivar has a narrow genetic diversity

with high purity

• Selection is based in phenotypes and genotypes

(progeny rows) being more effective

• Record keeping is slow, expensive


Single Seed Descent

• Modified pedigree method

• One randomly selected seed per plant is used for

next generation

• Fast, small spaces.

• Plants are selected based on individual phenotype


Bulk population breeding



• New variability is created

• Plants will be homozygous during selection

• It is relatively simple to conduct, specially in early

generations

• Due drift and natural selection, superior genotypes

may be lost before artificial selection


Backcross



• Efficient to incroporate one/two traits to a cultivar

• High h2

• Useful for introgressing genes from wide crosses

• Recessive traits are more time consuming


Recurrent selectionCombining crossing and selection

- Simple Recurrent Selection. Based on phenotypic

scores

- Recurrent selection for general combining ability. A

wide genetic-based cultivar is user as tester.

- Recurrent selection for specific combining ability.

An inbred line is used as tester

- Reciprocal recurrent selection. Explore both

general and specific combining ability


Problem: Response to selection

S Diferencial

de selección

ShR N

2=

R

Response

to

selection


PROCESSING TOMATO MID-SEASON

MATURITY VARIETY TRIALShttp://vric.ucdavis.edu/veg_info_crop/tomato.htm

Year Avg. Brix

2001 5

2002 5.2

2003 5.3

2004 5.3

2005 5.5

2006 5.5

2007 5.3

2008 4.98

2009 5.2

2010 5.2

2011 5.2


Why this low Response

• Low genetic variability

• Low h2


Pre-breeding: Gene Pools

GP-2

GP-3


Genetic variability in melon


Pre-breeding populations: Incorporating

new genetic varibility

Local

Varieties

Exotic

germplasm

Adapted/Elite

Genotypes

Breeding

Material

Breeding

Cultivar


Mapping populations

• Pre-breeding populations

• Designed to answer genetic questions

• Little or not conscious selection

• Increasing interest in applied breeding


Mapping populations : F2

P1 P2 F1 F2

- One meiosis.

- Recombination in both mega- and microgametophyte

permit better linkage resolution

- Segregation AA:Aa:aa. Dominant and codominant

markers

X


Mapping populations : BackcrossP1 P2 F1 BC1

- One meiosis.

- Only one of the chromosomes is recombinant

- Individuals are either homozygous for P1 alleles or

heterozygous

X X


Advanced BackcrossP1 P2 F1 BC1 BC2

- Two meiosis.

- Only one of the chromosomes is recombinant

- Individuals are either homozygous for P1 alleles or

heterozygous


Double Haploids LinesP1 P2 F1

X

Gametes

Anther culture

g - Irradiated

pollen

Haploid

tissue

Tissue culture

Diploidization

- One meiosis

- Only one of the chromosomes is

recombinant

- All individuals are homozygous

-Immortal population


Applications of DHL

• Quick generation of fixed genetic

variabilitiy (very common in barley)

• Genetic maps

• QTL mapping

• Difficult or even not possible in some

species (tomato)


Recombinant Inbred Lines


RILs

- All individuals are homozygous

- Immortal population

- Multiple meiosis

- Multiple recombinant chromosomes

-Highest mapping resolution

-Long time required

- Good choice for genetic mapping

RIL population

level of inbreeding

% within-line

homozygosity at each

locus

F3:4 75.0

F4:5 87.5

F5:6 92.3

F6:7 96.9

F7:8 98.4

F8*9 99.2


Outbred crosses or Cross-Pollinator (CP)

P1 P2 F1 “pseudo-testcross”

- One meiosis within each parent

- Phase unknown

- Two linkage maps, one for each parent

- Multiple possible segregations

X


Introgression Lines

P1 P2 F1 BC1 BC2

Marker

Assisted

Backcrossing


“Next-Generation” of mapping

population

Multiple alleles and high mapping resolution


Multi-parent Advanced Generation Inter-Cross (MAGIC)

Similar properties than RILs plus multiple alleles


Difficulty to obtain the ancestral haplotypes

(mouse)


- No genetic structure in the pop

- Founder alleles assigned in

87% of the genome


Increasing genetic map

MAGICEXPEN

2012

EXPIM

2012

Chr cM cM cM EXPEN2012 EXPIM2012

1 214.45 117.2 127.5 83% 68%

2 200.16 110.2 80.2 82% 150%

3 215.2 105.4 108.2 104% 99%

4 200.06 108.1 93 85% 115%

5 168.18 95.5 88.9 76% 89%

6 140.99 87.7 66.8 61% 111%

7 191 74.8 83.2 155% 130%

8 129.42 76.9 77.4 68% 67%

9 206.07 96.7 72.4 113% 185%

10 120.96 84.5 75.5 43% 60%

11 183.33 98.8 92.1 86% 99%

12 186.18 99.1 84.1 88% 121%

Total 2156 1154.9 1049.3 87% 105%

increase on MAGIC

More map distance->more recombination->more genetic resolution


Assignation of genetic effects


All-in-one

Bandillo et al. 2013

Rice 6:11


Nested Association Mapping (NAM)

N collections of RILs with a common parent (Yu et al. 2008)

Maize NAM: 25 collections of 200 RILs/each: 5000 RILs


Some results from

maize NAM

Flowering time Buckler (2009)

39 QTLs

R2= 89%


Association mapping

Map directly in natural populations or germplasm collections

By linkage disequilibrium analysis


Genotypic composition and power considerations

F2 RIL/LDH BC1 BC2

NAM/MAGIC

AAAAAA 555000 111000000 111000000

AAAaaa 111000000 111000000

aaaaaa 555000 111000000

150

50


Herebitability and Environment

F2 RIL/LDH BC1 BC2

NAM/MAGIC

h2 High Low High High

GxE No Yes No No


Genetic effectsF2 RIL/LDH BC1 BC2

NAM/MAGIC

-AA

-Aa

-aa

2

aaAAa -=

2

)( aaAAAad +-=

-AA

-aa

-Aa

-aaGenotypes

Genetic

Effectsa

da a*=(a+d)= Aa-aa

Overdominant

QTLs are not

detected

Recessive

QTLs are not

detected

-Aa

-aa


Percentage of donor and recurrent genome

F2 RIL/LDH BC1 BC2

NAM

% donor

genome 50 50 25

% recurrent

genome 50 50 75

High proportion of donor genome combined

with high homozygosity may cause partial

sterility when using wide crosses

12.5

87.5


Mapping resolution

F2, RIL, IL MAGIC, NAM Association Mapping


Schematic comparison of various methods for identifying trait

association in terms of resolution, research time and

allele number. (Yu and Buckler 2006)

NAM

MAGIC


What population?

• Additive Trait. Any of them. DHL, RIL, NAM, MAGIC

more efficient but more difficult to obtain

• Dominance. F2 or crosses between DHL, RIL, NAM,

MAGIC, NIL

• Reject recessive QTLs. Backcrosses

• Minimize sterility, linkage drag problems, Breeding

applications. Advanced Backcross, IIL

• Environment effects. DHL, RIL, NIL, MAGIC, NAM or

progeny test with F2 and BC

• Multiple allele testing: MAGIC, NAM

• High-resolution mapping: MAGIC, NAM


F2, BC AB-BC DHL RIL NIL MAGIC NAM

Funder genotypes 2 2 2 2 2 >8 >25

Seed multiplications No No Yes Yes Yes Yes Yes

Investment Very low Low Low Medium High High Very High

Population size and phenotyping

cost Low Medium Low Medium Medium High Very High

Genotyping cost Medium Medium Medium Medium High Very High Very High

Power for QTL detection Low Low Low Medium High High High

Resolution QTL position Low Low Low Medium Low High High

Replicated trials No No Yes Yes Yes Yes Yes

Statistical complexity Medium Medium Medium Medium Low High Very high

Transfer to breeding Low Medium Low Low High Medium Medium

Potential future relevance Low Low Medium High High High High

Comparison between populations


Case study: Introgression Lines


Tomato genus


Wild species as donor

Why wild species?

-Unused genetic variability

-High molecular marker

polymorphism


Segregating populations from interspecific crosses

S. lycopersicon x S. chesmanniaePS x PI161375


Advanced Backcross QTL analysisTanksley and Nelson (1996) Theor Appl Genet 92: 191-203

P1 P2 F1 BC1 BC2

-Similar statistical limitations than other populations

-Only additive or dominant QTLs can be detected

-Evaluation of vegetal material more similar to the final cultivar

-Exotic QTL allele effects are evaluated in a mainly cultivated

genome background.

QTL

analysisx


Favorable allelic effects from wild species


Introduction of exotoic variation by Introgression Lines

BC2

-Construcction of Introgression

Lines (ILs) by MAS.

- Positive selection for target

region

- Negative selection for rest of

the genome

Evaluation in

replicated trials


Advantages of introgression lines (ILs)

Fixation, verification and estimation of QTL effects on the appropiate

genetic background

5.5 5.3 4.5

“Mendelization”

of Quantitaive

Genetics

a= (5.5-4.5)/2= 0.5

d= 5.3 -(5.5+4.5)/2=0.3

d/a= 0.3/0.5= 0.6


Construction of IL collectionP1 P2 F1 BC1 BC2

Marker

Assisted

Backcrossing

PI161375

Piel de Sapo

x P1 x P1

x P1

(x)

Full

Linkage

Map


BC₂plants

GoldeGate

genotyping (712

SNP)

Selected BC₂ PlantsX Moneymaker

BC₃seedlings

Selected BC₃ plantas

BC₃S₁

X Moneymaker

BC₄High Resolution

Melting (HRM)

Veracode

Genotyping

(96 SNP)

Moneymaker x S. pimpinellifolium

F1BC1

Introgression Lines

Application of High-throughput technologies for IL construction


BC2 Graphic genotypeReceptorDonor


pla

nt

SN

P_013a

SN

P_011a

SN

P_030a

SN

P_044a

SN

P_061a

SN

P_076a

SN

P_084a

Gro

up

2

SN

P_090a

SN

P_105a

SN

P_120a

SN

P_138a

SN

P_159a

SN

P_180a

SN

P_199a

Gro

up

3

SN

P_208a

SN

P_222a

SN

P_234a

SN

P_242a

SN

P_258a

SN

P_272a

Gro

up

4

SN

P_276a

SN

P_286a

SN

P_297b

SN

P_317a

SN

P_330a

PC

126

SN

P_336a

Gro

up

5

SN

P_342a

SN

P_373a

SN

P_361a

PC

184a

Gro

up

6

SN

P_067a

SN

P_413a

SN

P_312a

SN

P_419a

SN

P_427a

SN

P_438a

a h #in

trogre

sio

ns

0 15.2 42.5 60.2 81.1 102 115 0 16.7 31 43.9 60.8 75.9 90.9 0 14.5 30 47.3 63.3 78.5 0 13.2 33.7 50.6 66.2 88.1 98.2 0 16.6 31.3 48.4 0 22.2 35.3 60.2 68.7 78.7 a h

68 h h a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a 35 2 1

11 a h a a a a a h a a a a a a a a a a a a a a a a a a a a a a a h a a a a a 34 3 2

25 a a a a a a a a a a a a a a a a a a a a a a a a a h a a a h h a a a a a a 34 3 2

4 a a a a h h h a a a a a a a a a a a a a a a a a a a a a a a a a a a a h a 33 4 2

23 a a a a a a h a a a a a a a h h a a a a a a a a a h a a a a a a a a a a a 33 4 3

26 a a a a a a a a a a a a a a a a a a a a a a a a a a a h a a a a a h h h a 33 4 2

36 a a a a a a a a a a a a a a a h h h a a a a a h a a a a a a a a a a a a a 33 4 2

51 a a a a a h h a a a a a a a a a a a a a a a a a a h a a a a a a a a a h a 33 4 2

28 a a a a h h h a a a a a a a a a a a a a a a a a a h a a a a h a a a a a a 32 5 3

38 a a a a a a a a a a a a a a a a a a a h h a a a a a a a a a a h h h a a a 32 5 3

45 a a a a a a a a a a a a a a h h h a a a h h a a a a a a a a a a a a a a a 32 5 2

55 h h h a a a a a a a h h a a h h a a a a h h h a a a a a a a a h h h a a a 24 13 5

58 a a a a a a h h h a a a a a a a a a a a a a a a a h a a a a a h a a a a a 32 5 4

64 a a a a a a a a a a a a a a a a a a h h a h h h a a a a a a a a a a a a a 32 5 2

10 a a a a a a a h h h h a a a h a a a a a a a a a a a a a a h a a a a a a a 31 6 3

29 a a a a a h h a a a a a a h a a a a a a a a a h h h a a a a a a a a a a a 31 6 3

43 a a a a h h h a a a a a a a a a a a a a h h a a a a a a a a a h a a a a a 31 6 3

49 a a a a a a a a a a a a a h a a a a a a a a h h h h h a a a a a a a a a a 31 6 2

69 a a a h a a a a a a a a a a a a a a a a a a a a h h a a a a h a h a h a a 31 6 4

83 a a a a a a a a a a a a a a h a a a a h a a a a a h a a h h h a a a a a a 31 6 4

33 a h h a a h h a a a a a a a a a a a a a h h h a a a a a a a a a a a a a a 30 7 3

48 a a a a a a a a a a a a a a a a a h h h a a a h h h h a h h h h h h a a a 24 13 4

55 h h h a a a a a a a h h a a h h a a a a h h h a a a a a a a a h h h a a a 24 13 5

Selection of founder plants

Target


Graphic genotype of BC popualtion wth 712 SNPs Selected 16 BC2 plants with lower number of SP introgressions

PopulationMM genome

(%)

BC2 86.5

Selected BC2 91.4

S. pimpinellifolium

MM


248 BC3 seedlings genotyped with 96 SNPs

76 BC₃ selected plants

Population

MM

Genome

(%)

SP

introgressions

BC3 96 3.7

Selected

BC396.5 2.9


BC

2 p

ed

igre

e

2M

Pla

nt

*CS

GA

057

TJ2

*CM

AC

C146

*CM

AG

59

*CM

AT

141

NR

101

NR

52

*CM

AT

35

*NR

3

*NR

2

TJ15

TJ17

*CM

TA

A166

NR

100

*CM

TC

160

mc264

*CS

WC

T18B

NR

89

*CM

GA

104

1M92-11 114 0 0 1 1 1 1 1 1 0 0 0 1 1 1 1

0 – Homozigous for PS

1 – Heterozigous for PS x PI161375

n N-F2 N-BC

1 10 4

2 46 10

3 190 22

4 765 46

5 3066 94

6 12269 190

Nº plants to screen to obtain at least one plant

with a single introgresion with p=0.95

log 0.05

log 1 − 0.25𝑛

log 0.05

log 1 − 0.5𝑛

F2

BC

n=number of introgressions

Segregation

- BC 1:1 p=0.5

-F2 1:2:1 p=0.25


BC

2 p

ed

igre

e

2M

Pla

nt

*CS

GA

057

TJ2

*CM

AC

C146

*CM

AG

59

*CM

AT

141

NR

101

NR

52

*CM

AT

35

*NR

3

*NR

2

TJ15

TJ17

*CM

TA

A166

NR

100

*CM

TC

160

mc264

*CS

WC

T18B

NR

89

*CM

GA

104

1M92-11 114 0 0 1 1 1 1 1 1 0 0 0 1 1 1 1

1 1 1 1

2 0 1

3 0 0

4 0 0 1 1

5 1 1 1

6 0 1 1 1

7 1 1 1

8 0 0 1 1

9 0 1

10 0 0

11 0 0

12 1 1 1

13 - -

14 0 1 1 1

15 0 1 1 1

16 0 1

17 0 0

18 - 0

19 - 1 1

20 - -

21 0 1 1 1

22 - -

23 - -

24 - -

0 – Homozigous for PS

1 – Heterozigous for PS x PI161375

cmtc160

cmacc146 cmat35

PS PI 4 6 8 14 15 21

PS PI 1 4 5 6 7 8 12 14 15 18 21

PS PI 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24


NIL Fixation

| | | | | | | | | | | |2M94-10 1 1

3M38-1 1 1

3M38-2 1 0

3M38-3 0 0

3M38-4 1 1

3M38-5 1 1

3M38-6 2 2

3M38-7 1 1

3M38-8 0 1

3M38-9 1 0

3M38-10 1 1

3M38-11 2 1

3M38-12 1 1

3M38-13 1 1

3M38-14 1 1


Final IL collection

Poblaciones para mejora vegetal y análisis genético

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